content
string | pred_label
string | pred_score
float64 |
|---|---|---|
Is sorting on Text/String field no longer available in 5.x?
(Jack Vinijtrongjit) #1
I understand that this is a new change, but I can't see what's wrong with this mapping. This is taken from the mapping of the field registered in ElasticSearch through _mapping call:
"key": {
"type": "text",
"fields": {
"keyword": {
"type": "keyword",
"ignore_above": 256
}
}
}
When I sort using the "key" field, I get this exception. I have also tried adding fieldData=true, but that also didn't work.
Caused by: RemoteTransportException[[_6qwpaI][127.0.0.1:9300][indices:data/read/search[phase/query]]]; nested: IllegalArgumentException[Fielddata is disabled on text fields by default. Set fielddata=true on [key] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory.];
Caused by: java.lang.IllegalArgumentException: Fielddata is disabled on text fields by default. Set fielddata=true on [key] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory.
at org.elasticsearch.index.mapper.TextFieldMapper$TextFieldType.fielddataBuilder(TextFieldMapper.java:335)
at org.elasticsearch.index.fielddata.IndexFieldDataService.getForField(IndexFieldDataService.java:111)
at org.elasticsearch.index.query.QueryShardContext.getForField(QueryShardContext.java:167)
at org.elasticsearch.search.sort.FieldSortBuilder.build(FieldSortBuilder.java:281)
at org.elasticsearch.search.sort.SortBuilder.buildSort(SortBuilder.java:151)
at org.elasticsearch.search.SearchService.parseSource(SearchService.java:678)
at org.elasticsearch.search.SearchService.createContext(SearchService.java:536)
at org.elasticsearch.search.SearchService.createAndPutContext(SearchService.java:502)
at org.elasticsearch.search.SearchService.executeQueryPhase(SearchService.java:243)
at org.elasticsearch.action.search.SearchTransportService.lambda$registerRequestHandler$6(SearchTransportService.java:276)
at org.elasticsearch.transport.TransportRequestHandler.messageReceived(TransportRequestHandler.java:33)
at org.elasticsearch.transport.RequestHandlerRegistry.processMessageReceived(RequestHandlerRegistry.java:69)
at org.elasticsearch.transport.TransportService$6.doRun(TransportService.java:550)
at org.elasticsearch.common.util.concurrent.ThreadContext$ContextPreservingAbstractRunnable.doRun(ThreadContext.java:527)
at org.elasticsearch.common.util.concurrent.AbstractRunnable.run(AbstractRunnable.java:37)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
At first I thought this might be related to the use of a field (e.g. key.keyword), but since I'm not doing that, then I don't see any reason why this is not working.
I'm pretty new to ElasticSearch 5.x and the document is contradicting itself so I hope someone can point me to the right direction. This is what I referring to:
https://www.elastic.co/guide/en/elasticsearch/reference/current/fielddata.html
I'm essentially trying to achieve the same as this original mapping that was working until 5.x:
"mapping": {
"type": "string",
"fields": {
"raw": {
"type": "string",
"ignore_above": 256
},
"english": {
"type": "string",
"analyzer": "english"
}
}
}
(Lee Hinman) #2
This is what you need to do though, instead of sorting on key, sort on key.keyword, which will use the non-analyzed version (that has doc_values) for sorting.
(Jack Vinijtrongjit) #3
I switched to sort by keyword and that sorted out the issue. Is this field now autogenerated? It got created without me specifying anything with field name "keyword". As for the fields I specified, they just don't get added in the mapping. This is my mapping:
{
"strings": {
"match_mapping_type": "text",
"mapping": {
"type": "text",
"fields": {
"raw": {
"type": "keyword",
"ignore_above": 256
},
"english": {
"type": "text",
"analyzer": "english"
}
}
}
}
}
(Lee Hinman) #4
If you index a string with no mapping, ES in 5.0+ now automatically creates a text version and a keyword version (under .keyword) of the field.
(Jack Vinijtrongjit) #5
But I have mapping as default template, but it's not honoring the mapping in the template. I guess that's another breaking change between 2.x to 5.x? This is a major issue.
(Lee Hinman) #6
This is because you have a typo in your dynamic mapping configuration, you are trying to match fields of type "text", but it should be "string" instead. For example, this works:
PUT /test?pretty
{
"mappings": {
"doc": {
"dynamic_templates": [
{
"strings": {
"match_mapping_type": "string",
"mapping": {
"type": "text",
"fields": {
"raw": {
"type": "keyword",
"ignore_above": 42
},
"english": {
"type": "text",
"analyzer": "english"
}
}
}
}
}
]
}
}
}
POST /test/doc/1
{"body": "foo"}
GET /test/doc/_mapping?pretty
(Jack Vinijtrongjit) #7
I thought there is no longer type "string" in 5.x? That's why I changed it to "text". So to make it work, I need to continue using string? That doesn't sound right.
How sort by date/time on Kibana Discover
(Lee Hinman) #8
There's a disconnect for this, the "dynamic" type used for match_mapping_type is the type of the field, not necessarily the ES type. For instance, match_mapping_type only supports "long", not "integer" because it maps to the data type rather than an ES type. So even though ES itself uses "text" and "keyword", the data type is still a "string".
I agree this is confusing, there was a PR here: https://github.com/elastic/elasticsearch/pull/17285 for 5.0+ that adds deprecation logging for this, and I opened https://github.com/elastic/elasticsearch/pull/22090 so 6.0 will throw an exception when an unrecognized type is used.
(system) #9
This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.
|
__label__pos
| 0.980176 |
牙齒矯正
什麼樣的人需要牙齒矯正呢？
1. 前牙移位
2. 咬合不正
3. 牙齒缺失、毫無秩序
4. 齒列稀疏
5. 牙齦萎縮：貼近牙齦的縫隙，沒有牙齦，而形成三角形的間隙
6. 多生牙：智齒影響齒列排列
7. 爆牙：頜骨下頜較短小，導致上排牙齒比下排牙齒凸出。
矯正的過程
醫師諮詢consultation
討論適合的矯正方式矯正前有些患者會希望保留自己的小虎牙、大門牙等等個人特色，或是對於牙齦特別在乎，這些在醫師替各位規劃個人矯正計畫時都是很重要的部分唷！
矯正事前資料蒐集collection
了解牙齒及骨骼條件，制定矯正計畫
製模modle impression
備用，與用於矯正後的牙齒比對
拍照片photo shoting
拍射5個角度照片，用於日後比對
拔牙tooth extraction
除了拔除智齒外，根據牙齒排列的擁擠程度，會需要拔牙，拔牙的牙縫，會等到中期再利用橡皮筋拉緊，調整牙縫，而有些人不需要拔牙，僅需磨牙將牙齒稍微騰出一些空間即可。
分牙tooth separators
分牙是為了移動出空間裝上牙套，分牙的階段大約需要一週，醫師會將分牙圈套在上下的大牙中。
上牙套on braces
剛上牙套要注意的除了適應牙套避免磨嘴，此時的牙齒清潔更需仔細注意，餐後需搭配特殊牙線、牙間刷、牙刷等徹底清潔
固定複診recall
在復安我們採用滑蓋式矯正器
提高矯正效率，大約1個月回診一次。
定型（上橡皮筋）
矯正後約1~3個月就可以看到變化，待6個月基本上就排齊了，此時需要上橡皮筋收緊牙縫
摘下牙套braces move
摘下牙套後，仍需要配戴牙齒維持器約半年，半年後可於睡覺時配戴即可。
牙齦治療
笑齦（Gummy smile）是許多人困擾的問題，非骨性暴牙的笑齦問題是可以
搭配骨釘將牙弓的部分往上移動，若依然還有牙肉過多的部分可再利用電燒的部分將牙齦多餘的牙肉去除，而牙齦過度覆蓋，醫師也會在矯正時讓門牙壓入(intrusion)來改善牙齦外露的問題。
嚴重的『骨性暴牙』，表面的骨性暴牙可利用水雷射來削去多的骨頭，而上顎骨頭垂直方向過長，導致嘴唇緊繃、上翻，還是需要靠正顎手術來改善。
固定式矯正
固定式牙齒矯正有傳統金屬矯正器、透明陶瓷矯正器，配合所需力量的矯正線來移動牙齒，需長期配戴且定期複診調整。不過治療效果良好，可以做大範圍的牙齒移動、改善傾斜、旋轉、調整牙根位置。
活動式矯正
活動式的矯正，可做到小範圍的牙齒移動，可由患者可以自行拿下、裝上矯正器，主要是用來矯正顎骨形狀、上下顎、局部咬合不正、骨性暴牙的問題。
隱適美隱形牙套矯正
隱適美是透明的牙套，戴上隱適美在外觀上不易察覺，患者可以自行拿取與裝上隱適美。醫師會透過3D掃描完整的牙齒骨骼形狀位置，再由電腦計算，替患者設計一整套的矯正過程，並且預估牙套付數與矯正的結果。
侵入式矯正
大暴牙、戽斗的患者若想要達到較大的改善效果，則需在整形外科進行正顎手術後，再進行牙齒矯正。
侵入式矯正須將顎骨事先局部斷折，然後再將兩端斷骨裝上牽引器，讓它漸進產生拉扯力量、刺激新的骨頭在斷骨處生長、來改善下顎骨發育不足、小顎症、臉型不對稱等。
在復安的牙齒矯正，差別是？
1.提高牙齒移動效率，大幅縮短療程
2.減少回診次數，滑蓋式可延長複診時間，約1個月複診一次。
3.包覆鐵絲及橡皮筋，不易刮口
4.方便清潔，不易卡菜渣再鐵絲及橡皮筋之間上橡皮筋
什麼是隱適美？
|
__label__pos
| 0.8124 |
Uploaded image for project: 'Minecraft (Bedrock codebase)'
1. Minecraft (Bedrock codebase)
2. MCPE-15851
Observers are not consistent regarding their opacity.
XMLWordPrintable
Details
• Confirmation Status:
Confirmed
• Platform:
Windows 10 - PC
• ADO:
23407
Description
See the second half of this video for a demonstration/explanation:
https://youtu.be/tLeW3lhMn_0
The behavior of Observers in regard to their opacity is inconsistent. (I am referring to their functional opacity - whether or not they cut off redstone wire, can they have torches placed on their sides, etc., NOT their visual opacity.) You may expect them to act like opaque blocks, and they DO cut off redstone wire, but in every other aspect they act like upside-down slabs/stairs, in that they act like transparent blocks, with the exception of being able to place redstone/buttons/levers/etc. on their top side, but not any other sides.
I didn't realize it when I made the video, but making Observers opaque would cause them to be able to weakly power adjacent blocks, which would interfere with their functionality and make them a lot less useful in my opinion. Therefore, I think the best way to resolve this would be to make them act like slabs/stairs. So basically, they would act just like they do now, but would not cut off redstone wire.
However, if the devs decide that Observers, due to being rather unique, belong to their own unique set of opacity rules, then I think Observers should act like opaque blocks (levers/torches could be placed on their side), minus the ability to be strongly powered, so as to prevent them from transferring redstone signals to any adjacent blocks and interfering with their functionality. This would actually make them just like MCPE pistons currently are in regard to how they behave when it comes to being transparent or opaque. Perhaps they could be in their own new category of blocks that are transparent except they can have blocks attached to any of their sides (rather than only their top sides like slabs/stairs) and they also cut off redstone. Maybe they would be considered opaque, but non-redstone-conductive? Not entirely sure what the terminology would be.
As of 16w44a, observers in the Java edition act like any other transparent block in that edition: you can't attach stuff on its sides and it doesn't cut off redstone wire.
Attachments
Issue Links
Activity
People
• Reporter:
SuperGeniusZeb [MCPE Helper] Zeb
• Votes:
2 Vote for this issue
Watchers:
2 Start watching this issue
Dates
• Created:
Updated:
Resolved:
CHK:
|
__label__pos
| 0.927516 |
Commit e34a3213 authored by Stan Hu's avatar Stan Hu
Create the source branch for a GitHub import
When the GitHub importer creates a merge request, it retrieves the SHA
but does not actually create the source branch. This makes it impossible
to merge an open merge request, particularly if the source branch were
from a forked project. In that case, the branch will never exist because
the original `project-name:source-branch` name is never created, nor
is it a valid branch name.
To prevent possible branch name conflicts, forked source branches
are now renamed `github/fork/project-name/source-branch` and created
when necessary.
Note that we only create the source branch if the merge request
is open. For projects that have many merge requests, the project
would end up with a lot of possibly dead branches.
Closes https://gitlab.com/gitlab-org/gitlab-ce/issues/57370
parent 91b88e0b
---
title: Create the source branch for a GitHub import
merge_request: 25064
author:
type: fixed
...@@ -67,6 +67,36 @@ module Gitlab ...@@ -67,6 +67,36 @@ module Gitlab
def insert_git_data(merge_request, already_exists) def insert_git_data(merge_request, already_exists)
insert_or_replace_git_data(merge_request, pull_request.source_branch_sha, pull_request.target_branch_sha, already_exists) insert_or_replace_git_data(merge_request, pull_request.source_branch_sha, pull_request.target_branch_sha, already_exists)
# We need to create the branch after the merge request is
# populated to ensure the merge request is in the right state
# when the branch is created.
create_source_branch_if_not_exists(merge_request)
end
# An imported merge request will not be mergeable unless the
# source branch exists. For pull requests from forks, the source
# branch will be in the form of
# "github/fork/{project-name}/{source_branch}". This branch will never
# exist, so we create it here.
#
# Note that we only create the branch if the merge request is still open.
# For projects that have many pull requests, we assume that if it's closed
# the branch has already been deleted.
def create_source_branch_if_not_exists(merge_request)
return unless merge_request.open?
source_branch = pull_request.formatted_source_branch
return if project.repository.branch_exists?(source_branch)
project.repository.add_branch(merge_request.author, source_branch, pull_request.source_branch_sha)
rescue Gitlab::Git::CommandError => e
Gitlab::Sentry.track_acceptable_exception(e,
extra: {
source_branch: source_branch,
project_id: merge_request.project.id,
merge_request_id: merge_request.id
})
end end
end end
end end
......
...@@ -76,10 +76,10 @@ module Gitlab ...@@ -76,10 +76,10 @@ module Gitlab
# Returns a formatted source branch. # Returns a formatted source branch.
# #
# For cross-project pull requests the branch name will be in the format # For cross-project pull requests the branch name will be in the format
# `owner-name:branch-name`. # `github/fork/owner-name/branch-name`.
def formatted_source_branch def formatted_source_branch
if cross_project? && source_repository_owner if cross_project? && source_repository_owner
"#{source_repository_owner}:#{source_branch}" "github/fork/#{source_repository_owner}/#{source_branch}"
elsif source_branch == target_branch elsif source_branch == target_branch
# Sometimes the source and target branch are the same, but GitLab # Sometimes the source and target branch are the same, but GitLab
# doesn't support this. This can happen when both the user and # doesn't support this. This can happen when both the user and
......
...@@ -89,7 +89,7 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi ...@@ -89,7 +89,7 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi
description: 'This is my pull request', description: 'This is my pull request',
source_project_id: project.id, source_project_id: project.id,
target_project_id: project.id, target_project_id: project.id,
source_branch: 'alice:feature', source_branch: 'github/fork/alice/feature',
target_branch: 'master', target_branch: 'master',
state: :merged, state: :merged,
milestone_id: milestone.id, milestone_id: milestone.id,
...@@ -134,7 +134,7 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi ...@@ -134,7 +134,7 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi
description: "*Created by: alice*\n\nThis is my pull request", description: "*Created by: alice*\n\nThis is my pull request",
source_project_id: project.id, source_project_id: project.id,
target_project_id: project.id, target_project_id: project.id,
source_branch: 'alice:feature', source_branch: 'github/fork/alice/feature',
target_branch: 'master', target_branch: 'master',
state: :merged, state: :merged,
milestone_id: milestone.id, milestone_id: milestone.id,
...@@ -259,6 +259,40 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi ...@@ -259,6 +259,40 @@ describe Gitlab::GithubImport::Importer::PullRequestImporter, :clean_gitlab_redi
.and_return(user.id) .and_return(user.id)
end end
it 'does not create the source branch if merge request is merged' do
mr, exists = importer.create_merge_request
importer.insert_git_data(mr, exists)
expect(project.repository.branch_exists?(mr.source_branch)).to be_falsey
expect(project.repository.branch_exists?(mr.target_branch)).to be_truthy
end
it 'creates the source branch if merge request is open' do
mr, exists = importer.create_merge_request
mr.state = 'opened'
mr.save
importer.insert_git_data(mr, exists)
expect(project.repository.branch_exists?(mr.source_branch)).to be_truthy
expect(project.repository.branch_exists?(mr.target_branch)).to be_truthy
end
it 'ignores Git errors when creating a branch' do
mr, exists = importer.create_merge_request
mr.state = 'opened'
mr.save
expect(project.repository).to receive(:add_branch).and_raise(Gitlab::Git::CommandError)
expect(Gitlab::Sentry).to receive(:track_acceptable_exception).and_call_original
importer.insert_git_data(mr, exists)
expect(project.repository.branch_exists?(mr.source_branch)).to be_falsey
expect(project.repository.branch_exists?(mr.target_branch)).to be_truthy
end
it 'creates the merge request diffs' do it 'creates the merge request diffs' do
mr, exists = importer.create_merge_request mr, exists = importer.create_merge_request
......
...@@ -238,7 +238,7 @@ describe Gitlab::GithubImport::Representation::PullRequest do ...@@ -238,7 +238,7 @@ describe Gitlab::GithubImport::Representation::PullRequest do
target_repository_id: 2 target_repository_id: 2
) )
expect(pr.formatted_source_branch).to eq('foo:branch') expect(pr.formatted_source_branch).to eq('github/fork/foo/branch')
end end
end end
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment
|
__label__pos
| 0.685088 |
.. SPDX-License-Identifier: GPL-2.0 ===================================================== sysfs - _The_ filesystem for exporting kernel objects ===================================================== Patrick Mochel Mike Murphy :Revised: 16 August 2011 :Original: 10 January 2003 What it is: ~~~~~~~~~~~ sysfs is a ram-based filesystem initially based on ramfs. It provides a means to export kernel data structures, their attributes, and the linkages between them to userspace. sysfs is tied inherently to the kobject infrastructure. Please read Documentation/core-api/kobject.rst for more information concerning the kobject interface. Using sysfs ~~~~~~~~~~~ sysfs is always compiled in if CONFIG_SYSFS is defined. You can access it by doing:: mount -t sysfs sysfs /sys Directory Creation ~~~~~~~~~~~~~~~~~~ For every kobject that is registered with the system, a directory is created for it in sysfs. That directory is created as a subdirectory of the kobject's parent, expressing internal object hierarchies to userspace. Top-level directories in sysfs represent the common ancestors of object hierarchies; i.e. the subsystems the objects belong to. Sysfs internally stores a pointer to the kobject that implements a directory in the kernfs_node object associated with the directory. In the past this kobject pointer has been used by sysfs to do reference counting directly on the kobject whenever the file is opened or closed. With the current sysfs implementation the kobject reference count is only modified directly by the function sysfs_schedule_callback(). Attributes ~~~~~~~~~~ Attributes can be exported for kobjects in the form of regular files in the filesystem. Sysfs forwards file I/O operations to methods defined for the attributes, providing a means to read and write kernel attributes. Attributes should be ASCII text files, preferably with only one value per file. It is noted that it may not be efficient to contain only one value per file, so it is socially acceptable to express an array of values of the same type. Mixing types, expressing multiple lines of data, and doing fancy formatting of data is heavily frowned upon. Doing these things may get you publicly humiliated and your code rewritten without notice. An attribute definition is simply:: struct attribute { char * name; struct module *owner; umode_t mode; }; int sysfs_create_file(struct kobject * kobj, const struct attribute * attr); void sysfs_remove_file(struct kobject * kobj, const struct attribute * attr); A bare attribute contains no means to read or write the value of the attribute. Subsystems are encouraged to define their own attribute structure and wrapper functions for adding and removing attributes for a specific object type. For example, the driver model defines struct device_attribute like:: struct device_attribute { struct attribute attr; ssize_t (*show)(struct device *dev, struct device_attribute *attr, char *buf); ssize_t (*store)(struct device *dev, struct device_attribute *attr, const char *buf, size_t count); }; int device_create_file(struct device *, const struct device_attribute *); void device_remove_file(struct device *, const struct device_attribute *); It also defines this helper for defining device attributes:: #define DEVICE_ATTR(_name, _mode, _show, _store) \ struct device_attribute dev_attr_##_name = __ATTR(_name, _mode, _show, _store) For example, declaring:: static DEVICE_ATTR(foo, S_IWUSR | S_IRUGO, show_foo, store_foo); is equivalent to doing:: static struct device_attribute dev_attr_foo = { .attr = { .name = "foo", .mode = S_IWUSR | S_IRUGO, }, .show = show_foo, .store = store_foo, }; Note as stated in include/linux/kernel.h "OTHER_WRITABLE? Generally considered a bad idea." so trying to set a sysfs file writable for everyone will fail reverting to RO mode for "Others". For the common cases sysfs.h provides convenience macros to make defining attributes easier as well as making code more concise and readable. The above case could be shortened to: static struct device_attribute dev_attr_foo = __ATTR_RW(foo); the list of helpers available to define your wrapper function is: __ATTR_RO(name): assumes default name_show and mode 0444 __ATTR_WO(name): assumes a name_store only and is restricted to mode 0200 that is root write access only. __ATTR_RO_MODE(name, mode): fore more restrictive RO access currently only use case is the EFI System Resource Table (see drivers/firmware/efi/esrt.c) __ATTR_RW(name): assumes default name_show, name_store and setting mode to 0644. __ATTR_NULL: which sets the name to NULL and is used as end of list indicator (see: kernel/workqueue.c) Subsystem-Specific Callbacks ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ When a subsystem defines a new attribute type, it must implement a set of sysfs operations for forwarding read and write calls to the show and store methods of the attribute owners:: struct sysfs_ops { ssize_t (*show)(struct kobject *, struct attribute *, char *); ssize_t (*store)(struct kobject *, struct attribute *, const char *, size_t); }; [ Subsystems should have already defined a struct kobj_type as a descriptor for this type, which is where the sysfs_ops pointer is stored. See the kobject documentation for more information. ] When a file is read or written, sysfs calls the appropriate method for the type. The method then translates the generic struct kobject and struct attribute pointers to the appropriate pointer types, and calls the associated methods. To illustrate:: #define to_dev_attr(_attr) container_of(_attr, struct device_attribute, attr) static ssize_t dev_attr_show(struct kobject *kobj, struct attribute *attr, char *buf) { struct device_attribute *dev_attr = to_dev_attr(attr); struct device *dev = kobj_to_dev(kobj); ssize_t ret = -EIO; if (dev_attr->show) ret = dev_attr->show(dev, dev_attr, buf); if (ret >= (ssize_t)PAGE_SIZE) { printk("dev_attr_show: %pS returned bad count\n", dev_attr->show); } return ret; } Reading/Writing Attribute Data ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To read or write attributes, show() or store() methods must be specified when declaring the attribute. The method types should be as simple as those defined for device attributes:: ssize_t (*show)(struct device *dev, struct device_attribute *attr, char *buf); ssize_t (*store)(struct device *dev, struct device_attribute *attr, const char *buf, size_t count); IOW, they should take only an object, an attribute, and a buffer as parameters. sysfs allocates a buffer of size (PAGE_SIZE) and passes it to the method. Sysfs will call the method exactly once for each read or write. This forces the following behavior on the method implementations: - On read(2), the show() method should fill the entire buffer. Recall that an attribute should only be exporting one value, or an array of similar values, so this shouldn't be that expensive. This allows userspace to do partial reads and forward seeks arbitrarily over the entire file at will. If userspace seeks back to zero or does a pread(2) with an offset of '0' the show() method will be called again, rearmed, to fill the buffer. - On write(2), sysfs expects the entire buffer to be passed during the first write. Sysfs then passes the entire buffer to the store() method. A terminating null is added after the data on stores. This makes functions like sysfs_streq() safe to use. When writing sysfs files, userspace processes should first read the entire file, modify the values it wishes to change, then write the entire buffer back. Attribute method implementations should operate on an identical buffer when reading and writing values. Other notes: - Writing causes the show() method to be rearmed regardless of current file position. - The buffer will always be PAGE_SIZE bytes in length. On i386, this is 4096. - show() methods should return the number of bytes printed into the buffer. - show() should only use sysfs_emit() or sysfs_emit_at() when formatting the value to be returned to user space. - store() should return the number of bytes used from the buffer. If the entire buffer has been used, just return the count argument. - show() or store() can always return errors. If a bad value comes through, be sure to return an error. - The object passed to the methods will be pinned in memory via sysfs referencing counting its embedded object. However, the physical entity (e.g. device) the object represents may not be present. Be sure to have a way to check this, if necessary. A very simple (and naive) implementation of a device attribute is:: static ssize_t show_name(struct device *dev, struct device_attribute *attr, char *buf) { return scnprintf(buf, PAGE_SIZE, "%s\n", dev->name); } static ssize_t store_name(struct device *dev, struct device_attribute *attr, const char *buf, size_t count) { snprintf(dev->name, sizeof(dev->name), "%.*s", (int)min(count, sizeof(dev->name) - 1), buf); return count; } static DEVICE_ATTR(name, S_IRUGO, show_name, store_name); (Note that the real implementation doesn't allow userspace to set the name for a device.) Top Level Directory Layout ~~~~~~~~~~~~~~~~~~~~~~~~~~ The sysfs directory arrangement exposes the relationship of kernel data structures. The top level sysfs directory looks like:: block/ bus/ class/ dev/ devices/ firmware/ net/ fs/ devices/ contains a filesystem representation of the device tree. It maps directly to the internal kernel device tree, which is a hierarchy of struct device. bus/ contains flat directory layout of the various bus types in the kernel. Each bus's directory contains two subdirectories:: devices/ drivers/ devices/ contains symlinks for each device discovered in the system that point to the device's directory under root/. drivers/ contains a directory for each device driver that is loaded for devices on that particular bus (this assumes that drivers do not span multiple bus types). fs/ contains a directory for some filesystems. Currently each filesystem wanting to export attributes must create its own hierarchy below fs/ (see ./fuse.txt for an example). dev/ contains two directories char/ and block/. Inside these two directories there are symlinks named :. These symlinks point to the sysfs directory for the given device. /sys/dev provides a quick way to lookup the sysfs interface for a device from the result of a stat(2) operation. More information can driver-model specific features can be found in Documentation/driver-api/driver-model/. TODO: Finish this section. Current Interfaces ~~~~~~~~~~~~~~~~~~ The following interface layers currently exist in sysfs: devices (include/linux/device.h) -------------------------------- Structure:: struct device_attribute { struct attribute attr; ssize_t (*show)(struct device *dev, struct device_attribute *attr, char *buf); ssize_t (*store)(struct device *dev, struct device_attribute *attr, const char *buf, size_t count); }; Declaring:: DEVICE_ATTR(_name, _mode, _show, _store); Creation/Removal:: int device_create_file(struct device *dev, const struct device_attribute * attr); void device_remove_file(struct device *dev, const struct device_attribute * attr); bus drivers (include/linux/device.h) ------------------------------------ Structure:: struct bus_attribute { struct attribute attr; ssize_t (*show)(struct bus_type *, char * buf); ssize_t (*store)(struct bus_type *, const char * buf, size_t count); }; Declaring:: static BUS_ATTR_RW(name); static BUS_ATTR_RO(name); static BUS_ATTR_WO(name); Creation/Removal:: int bus_create_file(struct bus_type *, struct bus_attribute *); void bus_remove_file(struct bus_type *, struct bus_attribute *); device drivers (include/linux/device.h) --------------------------------------- Structure:: struct driver_attribute { struct attribute attr; ssize_t (*show)(struct device_driver *, char * buf); ssize_t (*store)(struct device_driver *, const char * buf, size_t count); }; Declaring:: DRIVER_ATTR_RO(_name) DRIVER_ATTR_RW(_name) Creation/Removal:: int driver_create_file(struct device_driver *, const struct driver_attribute *); void driver_remove_file(struct device_driver *, const struct driver_attribute *); Documentation ~~~~~~~~~~~~~ The sysfs directory structure and the attributes in each directory define an ABI between the kernel and user space. As for any ABI, it is important that this ABI is stable and properly documented. All new sysfs attributes must be documented in Documentation/ABI. See also Documentation/ABI/README for more information.
|
__label__pos
| 0.977414 |
Dynamic Number of Rows in Repeating Group
I am trying to create a page where the user can select a number (1-10) from a drop down. Depending on the number they select, I want to show that many sections/rows in a repeating group (or something similar). So for example, if the user selects “2”, the RG should only show 2 rows. I know I could probably do this by storing the “number of rows” in the database, but I was hoping to do this with states. Any advice on if this can be done or how to go about something like this?
In your rg data source, use :items until state#.
3 Likes
@yourmom
Custom state on the page of type number. Let’s call it rowsnumber.
The dropdown can have … say … 10 static numbers. Use the event “when inputs value changes” (this dropdown would be the input) set its value to the rownsnumber page custom state.
In the rg set 10 conditions when the page custom state rowsnumber is 1 … to 10 … to have the data source be of search things :items until # … and set that number to be the dropdown value.
That should do the trick :grinning:
1 Like
This topic was automatically closed after 70 days. New replies are no longer allowed.
|
__label__pos
| 0.871059 |
Stack Overflow is a community of 4.7 million programmers, just like you, helping each other.
Join them; it only takes a minute:
Sign up
Join the Stack Overflow community to:
1. Ask programming questions
2. Answer and help your peers
3. Get recognized for your expertise
I get an OpenGL view by
+ (Class) layerClass
{
return [CAEAGLLayer class];
}
and I want to add sublayer to it by
CAEAGLLayer *eaglLayer2 = [[CAEAGLLayer alloc] init];
[self.layer addSubLayer:eaglLayer2];
The purpose to think this is that I want to draw different thing on different layer so that I can remove something by simply call removeSubLayer:enter code here.
Is it available?
share|improve this question
Your Answer
discard
By posting your answer, you agree to the privacy policy and terms of service.
Browse other questions tagged or ask your own question.
|
__label__pos
| 0.924129 |
说明：双击或选中下面任意单词，将显示该词的音标、读音、翻译等；选中中文或多个词，将显示翻译。
您的位置：首页 -> 词典 -> 间歇式化工生产
1) batch chemical processes
间歇式化工生产
1.
Modeling and schedule supervisor synthesis for batch chemical processes based on Petri nets;
基于Petri网的间歇式化工生产过程建模与调度监控器设计
2) intermittent production
间歇式生产
3) batch process
间歇生产
1.
A batch-to-batch iterative optimal control strategy general predictive control(GPC)-based for batch process-BGPC is proposed,which introduces the idea of batch-to-batch optimization into batch process.
针对间歇生产,提出了一种基于广义预测控制的批次迭代优化控制策略———BGPC,在间歇过程中引入批次间优化的思想,将迭代学习控制ILC和广义预测控制GPC相结合,在GPC实时结构参数辨识的基础上利用前面批次的模型预测误差修正当前批次的模型预测值。
2.
Aimed at the characteristic of batch process,flexibility and reactivity,this paper put forward a method of intelligent scheduling for batch process based on knowledge and multi-agent,and the framework of the intelligent scheduling has been built.
针对间歇生产过程柔性操作和动态变化的特征,提出了综合应用基于知识的调度算法和多代理技术实现间歇生产过程动态调度的方法,建立了间歇过程动态调度的结构模型,并以一间歇过程实例的动态调度说明所提出方法的思路和可行性。
4) intermittent biological oxidation
间歇式生物氧化
1.
Treatment of alkali dregs wastewater through integrated process of mild wet air oxidation deodorization and intermittent biological oxidation;
采用缓和湿式氧化脱臭-间歇式生物氧化组合工艺处理碱渣废水
5) intermittent production
间歇性生产
6) batch procesing
间歇式加工
补充资料：连续式与间歇式“全自动装盒机”比较
间歇式装盒机的传动机构间断运行，其速度最快为80-100盒/分，一般在50-80盒/分。具体分析如下：
主传动靠分度器或刹车垫机式线每个循环的运动和停留。
1． 主传动停留时间内，在整个传送链中，产品落入静止的产品传送链上的船中，开盒系统为单头往复式，盛放纸盒的仓中最多存放200个纸盒，单吸头吸下纸盒靠静止的盒传送链的链条及挡板打开纸盒，放入链条上，单吸头返回，速度慢；折纸机吸下的说明书间断送至产品船下面，纵向固定的推杆系统横向将产品推入纸盒中，推杆再返回原位；横向固定的封盒系统，将纸盒关闭，再返回原位。
2． 主传动运动时间内，产品传送链运动，将船中的产品依次送至折纸机和开盒系统的吸头下面，折纸机不动作，推杆不动作，封盒系统也停止动作。
综上所述，间歇式装盒机由于传动机构的限制，速度慢，工作不稳定，成品率低，对纸盒要求高，且没有机械记忆装置，更换规格不方便，因而只是用于产量低，要求速度不高的产品和场合。
具体比较见下表：
按此在新窗口浏览图片
作者：上海龙腾机械制造有限公司
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条
|
__label__pos
| 0.536068 |
How Does a Solar Panel Make Electricity?
We all know what solar panels look like, but how do solar panels make electricity? The traditional method of making electricity is by using water pressure or steam pressure to turn a turbine which creates electricity. But a solar panel just sits there in the sun and has no moving parts, so how does a solar panel make electricity? When you look closely at a solar panel you will see it is made...
Read More
|
__label__pos
| 0.999804 |
NPIN - Editorial
PROBLEM LINK
Practice
Contest
DIFFICULTY
HARD
PREREQUISITES
Computational Geometry
Pick’s Theorem
Cyrus Beck’s Line Clipping Algorithm
Sweep Line Algorithm
Line Segment Intersection
PROBLEM
You are given a convex polygon whose vertices are lattice points on the x-y plane. You are also given several line segments in the x-y plane whose endpoints are lattice points. On each lattice point on a line (and the endpoint of a line) and also on or inside the polygon, you place a Needle. Lines include the ones that form the polygon.
On all other lattice points inside the polygon, you place a Pin. Find the number of Needles placed, and the number of Pins placed.
EXPLANATION
Pick’s Theorem states that
Area of polygon =
number of internal lattice points
+ number of boundary lattice points / 2
- 1
We can find the number of lattice points on a line segment from (x1,y1) to (x2,y2) as
GCD( abs(x1 - x2), abs(y1 - y2) )
We do not place needles on the portion of the line segment that lies outside the polygon. Thus, we must clip the line segments to lattice points that lie inside the polygon.
The linked resource uses the parametric notation of a line segment. All the calculations can be done purely on integers to allow for finding the clipped lines very accurately. This may be achieved by maintaining the value of the parameter as a fraction - integer numerator and denominator.
• Lines that are parallel to an edge of the polygon and on, or outside the polygon, can be simply ignored
The expected time complexity for this step was O(N*P), where P is the number of edges in the polygon.
Doing so, we are able to calculate the number of needles on the boundary of the polygon, and on the line segments inside the polygon. But, several line segments may have intersection points among them which are also lattice points. We must reduce our count of needles by the number of such intersections.
Intersections within a set of lines can be found using a plane sweep algorithm. The idea is elementary in books that deal with Computational Geometry. I personally found this resource very useful in implementing the plane sweep algorithm to report the intersection points.
Implementing this algorithm correctly and accurately (handling all the degeneracies possible) is the most difficult part of solving this problem. It is very well researched though, so there is no scarcity in resources describing a solution.
The expected time complexity for this step was O((N + I) log N), where I is the number of intersection points.
Lastly, the number of pins can be found by reducing the count of needles from the number of internal lattice points, found using the Pick’s Theorem above.
SETTER’S SOLUTION
Can be found here.
TESTER’S SOLUTION
Will be uploaded shortly.
3 Likes
It would be nice if pperm, Anton or djdolls could explain their approach.
Below I give one small test case.
alt text
Input
6 5
1 0
6 1
8 4
5 7
0 7
-2 4
1 7 4 1
7 7 0 0
4 6 2 4
-1 5 5 2
4 4 1 1
Output
25 31
Where is the condition regarding the 16 “squares” used in the official solution ? It is my impression that the sweep line algorithm for segment intersections would work in any situation, right?
I can tell you where I kind of used it in my solution. I used a quadtree-like approach (the root contains a large enough square). Then I would keep decomposing the space further and further until:
1. I reached a zone of the quadtree which did not intersect too many segments (e.g. <= 200) : then an O(nr of segments^2) algorithm for segment intersection would work (restricted to the parts of the segments “clipped” by the current zone of the quadtree).
2. I reached a zone of only 1 point in the quadtree which intersects at least 2 segments => this is an intersection point and can be counted as such directly.
This approach works very well, except, possibly, in some very degenerate cases - but the 16 “squares” conditions ensured no such cases would exist.
1 Like
@mugurelionut: Thanks for sharing your approach!
Without 16 squares condition, the problem would be much harder. Like you said - this condition eliminated some difficult cases.
Similarly, coding the sweep line algorithm which handles the general case i.e without this condition (plus limit on length of line) would be very complex (at least for me).
Specifically in my solution (modified Bentley-Ottman) the condition simplified the part checking intersection of current (event) line with active lines.
//
|
__label__pos
| 0.877612 |
Service
Food for Thought: Why Aren’t There More Fish Sticks in the World?
Food for Thought: Why Aren’t There More Fish Sticks in the World?
By – December 4, 2019 – Comment
Ah, the frozen fish stick! A quick “go to” meal for parents on the go that kids love. A nostalgic comfort food for tons of adults. The perfect—and perhaps the only—vehicle for the tangy creation that we call tartar sauce. Fish sticks rely fully on a manufacturing process, because, as we all know, even water resources in the coldest of arctic regions do not supply fish nicely frozen and ready to go. Exactly why is it that fish—whether used for food items or not—emerge from the cold of winter not only unfrozen but also unharmed?
The answer has everything to do with water. The combination of water’s ordinary and unique properties, along with “fish physiology,” allows all types of water species to survive in winter-cold waters, even when those waters freeze over.
First, let’s look at one of the most commonly known properties of water. It’s made up, in part, by oxygen—and because fish are equipped with gills instead of lungs, fish are able to “breathe in” water and extract the oxygen they need to live. This happens regardless of the water’s temperature, be it during the high summer heat or the chills of winter. In the winter, fish metabolism does slow down. As cold-blooded creatures, fish lower their body temperature to match the water around them as it cools. With lower metabolism and activity, a fish requires less oxygen and nourishment, which, as we’ll learn below, can be a lifesaver during the winter.
A more unique property of water is that, unlike most materials and matter, water expands instead of contracts as it cools. This frozen water, which you know as “ice”, that forms on the surface of lakes, ponds and the like further contributes to fish survival by 1) acting as an insulator and trapping heat in the water below it; and 2) acting as a barrier that traps oxygen below. In other words, water freezes as a less dense substance, thus helping to ensure that fish have ample oxygen to live and that the water doesn’t get too cold for fish to survive—or freeze entirely.
Ice is also less dense than water (I know it sounds strange since ice is harder than water, but it’s a “space between the molecules” thing). The density changes that water undergoes as temperatures change causes a “thermal turnover” process, as the seasons transition from summer to fall to winter. The process is a bit heavy on the science and is detailed here. But to sum it up, this process has warmer water—which resides on the surface during the summer—cooling and circulating down as it approaches a “maximum density” temperature, then rising back up. This circulation process infuses and distributes oxygen throughout the water—preparing the water for fish survival once ice begins to form at the surface. Moreover, one problem with frozen water is that it prevents sunlight from reaching aquatic vegetation below and therefore limits these plants’ ability to produce oxygen through photosynthesis. Without plants infusing oxygen into the water during the winter, thermal turnover and the resulting oxygen production can be extremely important to what is living under the ice, especially in prolonged winters.
Lastly, I’ll mention a fact I find fascinating: Water on the verge of freezing or that has begun to freeze responds to a natural antifreeze that scientists have discovered that fish in extremely cold environments are able to produce. Because this antifreeze and water work the way they do, fish are never completely surrounded by ice. In other words, the antifreeze is the ultimate preventer of a naturally produced frozen fish stick!
So the next time you dig into your fish stick brand of choice, take a minute to appreciate yet another role water plays in maintaining the natural order of things in our world.
Comment
|
__label__pos
| 0.996699 |
This mixture is then centrifuged. Remarkable is the extreme solubility of PMMA in trichloroethylene. the hydroalcoholic solvent systems, variation of pH' produced mini The liquid is called the solvent. For example, a polar solute such as sugar is very soluble in polar water, less soluble in moderately polar methanol, and practically insoluble in non-polar solvents such as benzene. xylene, tetrahydrofuran, chloroform, 1,3-butanediol, 2-butanol, linalool, geraniol, d-limonene, p-cymene, ... the solubility values or the chain degradation during the dissolu-tion process. THC is soluble in Fats and Oils. What doesnt make sense to me about this is the fact that The main functional group in Alcohol (Oxygen-Hydrogen bond) is the same as the main bonding form in water (Hydrogen-oxygen bond). Facilitated diffusion is the process in which these molecules are transported across the plasma membrane by carrier molecules. Availability Sucrose is a glycosyl glycoside formed by glucose and fructose units joined by an acetal oxygen bridge from hemiacetal of glucose to the hemiketal of the fructose.It has a role as an osmolyte, a sweetening agent, a human metabolite, an algal metabolite, a Saccharomyces cerevisiae metabolite, an Escherichia coli metabolite and a mouse metabolite. It is fast when salt and sugar dissolve in water but much slower for a tablet of aspirin or ... with an application of the substance. Mar 29, 2011 #5 alxm. COLOR TESTS REAGENT COLOR PRODUCED Acidified cobalt thiocyanate Blue flaky precipitate Disaccharides, such as sucrose, are created when two monosaccharides are combined into a new compound. It is soluble in water, but has limited solubility in most organic solvents such as acetone, chloroform, and diethyl ether. 35 mL of alcohol and in 5 mL of acetone. Sparingly soluble in chloroform; slightly soluble in slightly soluble in water. Process. Science Advisor. Phenolâchloroform extraction is a liquid-liquid extraction technique in molecular biology used to separate nucleic acids from proteins and lipids.. Sugar is somewhat dissolvable in methanol, which is reasonably safe to handle as long as you don't drink it. Moreover, its hydrogen will form (weak) hydrogen bonds which is probably a better explanation for the solubility in water than the polarity of the molecule. Polymer Solubility and Solubility Parameter Solubility parameters were initially developed to guide solvent selection in the paint and coatings industry. Fructose and glucose are the component parts of sucrose, otherwise known as table sugar. Solubility of Organic Materials in DMSO Solubility Grams/100 cc DMSO Solubility Grams/100 cc DMSO Material 20-30°C 90-100°C Material 20-30° C 90-100°C Ceresin wax < 1 1-Eicosanol Insoluble Chloroform Miscible Ethyl benzoate Miscible Chlorosulfonic acid Reacts Ethyl alcohol Miscible Citric acid > 70 Ethyl bromide Miscible Reacts Coconut oil Its solutions are acid to litmus. For example, indigo is described as "insoluble in water, alcohol, or ether but soluble in chloroform⦠Etoricoxib solid dispersions and their respective physical mixtures using lactose, sucrose, and mannitol were prepared in different ratios by solvent evaporation technique. Solubility Chart Ethyl cellulose containing less than 46-48% of ethoxyl groups is freely soluble in tetrahydrofuran, in methyl acetate, in chloroform, and in aromatic hydrocarbon ethanol mixtures. In contrast, a non-polar solute such as naphthalene is insoluble in water, moderately soluble in methanol, and highly soluble in benzene. Is odorless or has a faint, aromatic odor. 1 Questions & Answers Place. The water molecules in the form of H 3 O + due to a nucleophilic attack in protonation, lead to the formation of reducing sugar and these hydrolysis products are readily soluble in water. Solubility is the property of a solid, liquid or gaseous chemical substance called solute to dissolve in a solid, liquid or gaseous solvent.The solubility of a substance fundamentally depends on the physical and chemical properties of the solute and solvent as well as on temperature, pressure and presence of other chemicals (including changes to the pH) of the solution. Something I've always been curious about. One g of sample dissolves in about water and in alcohol; insoluble in ether. Certain molecules, notably glucose and other simple sugars, are both lipid insoluble and too large to pass through the plasma membrane pores. Solubility of sucrose in mixtures of water with different organic solvents has important uses in some branches of the chemical and pharmaceutical industries, in analytics, etc. Solubility is a measurement of how much of a substance will dissolve in a given volume of a liquid. In an aquea.is system, the total solubility is equal t_o the sum of the original zwitterion solubility plus the solubility of the salt that was found. Chloroform is soluble in water, though only slightly (~1g/100ml in cold water forming a slightly sweet liquid whose mild anaesthetic affects made it a recreational substance in Victorian times before its toxicity was fully recognised).. For example, a polar solute such as sugar is very soluble in polar water, less soluble in moderately polar methanol, and practically insoluble in non-polar solvents such as benzene. It is especially the case for ethanol, methanol, propyleneglycol, glycerol, acetone and pyridine. It is hygroscopic. Mannitol is very polar with a Log P more negative even than glucose (-3.262 vs -2.49 ref. Which of the following pairs of ions is arranged so that the ion with the smaller charge density is listed first? Glycerol is a colorless, viscous, and odorless liquid at room temperature with a mild sweet taste similar to artificial sweeteners. Correction - you don't want it in contact with your skin, either, since it can enter your body through that route. Polar lipids are sparingly soluble in hydrocarbon solvents, but dissolve readily in more polar solvents such as methanol, ethanol or chloroform. No. Slightly soluble in water, in chloroform, and in ether; soluble in boiling water; sparingly soluble in alcohol. First, a ⦠Organic (phenolâchloroform) extraction uses sodium dodecylsulfate (SDS) and proteinase K for the enzymatic digestion of proteins and nonnucleic acid cellular components (Fig. For those amino acids studied, only single salts were formed. The solubility data was correlated with an empirical equation. Find answers now! It is fast when salt and sugar dissolve in water but much slower for a tablet of aspirin ... with an application of the substance. lipid soluble, 2. The solubility of benzoic acid has been determined in ethanol, toluene, heptane, cyclohexane, pentane, and chloroform and in binary mixtures of ethanol + heptane and ethanol + toluene, in the temperature range of (278.15 to 323.15) K. The solubility is high in ethanol, reasonably high in chloroform, lower in toluene, and quite low in the remaining three pure solvents. The laser monitoring observation technique was used to determine the disappearance of the solid phase in a solid + liquid mixture. Slightly soluble in sodium hydroxide solution: Infrared absorption: The infrared absorption spectrum of a potassium bromide dispersion of the sample corresponds to the infrared spectrum in the Appendix: PURITY: Loss on drying: Not more than 7.0% (105 °, 3h) pH: 5.0 - 7.5 It is the maximum amount of solute that can be dissolved in a solvent at equilibrium, which produces a saturated solution.When certain conditions are met, additional solute can be dissolved beyond the equilibrium solubility point, which produces a supersaturated solution. Solubility in water is ___ for smaller alcohols. NF category: Cyclobenzaprine Hydrochloride:White to off-white, Antimicrobial preservative. For example, indigo is described as "insoluble in water, alcohol, or ether but soluble in chloroform⦠please someone help me, i badly need your answers..thank you? It can be prepared by the chlorination of ethyl alcohol or of methane. line powder. Under this link you find the solubility of PMMA in 12 different organic solvents. solubility per mole of acid or base added also increased. A = acetone, C = chloroform, E = ether, H = hexane, M = methanol and W = water, VS = very soluble, FS = freely soluble, S = soluble, PS = sparingly soluble, SS = slightly soluble, VSS = very slightly soluble and I = insoluble 3. 21.4).A mixture of phenol:chloroform:isoamyl alcohol (25:24:1) is then added to promote the partitioning of lipids and cellular debris into the organic phase, leaving isolated DNA in the aqueous phase. Is burnt sugar soluble in water, HCl, NaOH, oil, and chloroform? Aqueous samples, lysed cells, or homogenised tissue are mixed with equal volumes of a phenol:chloroform mixture. THC is soluble in Alcohol, BUT THC is NOT soluble in water. Freely soluble in alcohol and in methanol; spar-Ferumoxides Injection:Black to reddish-brown, aque- ingly soluble in water and in dichloromethane; practically Today, they are widely used in in many other fields to predict miscibility and solubility of polymers, chemical resistance, and permeation rates. Solubility is defined as the maximum quantity of a substance that can be dissolved in another. The aim of this work is to develop a process for the recycling of extruded polystyrene in two steps. ACD/Labs). Nearly insoluble (unable to be dissolved) in water, chloroform easily dissolves in alcohol, ether, acetone, gasoline, and other organic solvents. It will definitely need a more polar solution than what you are using. The solubility of a gas depends on pressure and temperature. 1,842 9. turbo-1 said: The solubility of these lipids increase in alcoholic solvents as the carbon chain length of the alcohol increases, so they are more soluble in ethanol and n-butanol. Saccharin: White crystals or white, crystalline powder. 4H 2O. In dilute solution, it is intensely sweet. Chloroform is about 40 times as sweet as sugar. Slowly soluble in water; insoluble Fluoxetine Hydrochloride:White to off-white crystal- in alcohol. Solubility: Insoluble in water, ethanol, ether and dilute mineral acids. Solubility Chart In contrast, a non-polar solute such as naphthalene is insoluble in water, moderately soluble in methanol, and highly soluble in benzene. The effect of solvent composition and temperature on the solubility was discussed. In . ... (sugar) in water is in equilibrium with solid sucrose. Monosaccharides are soluble in water and are the smallest of the sugars. The aim of the present study was to improve solubility and dissolution of the poorly aqueous soluble drug, etoricoxib by solvent evaporation technique using various sugar carriers, such as lactose, sucrose, and mannitol. With 92% hexane, I think you may be S.O.L with Solubilizing this sugar alcohol. At the end of the depolymerization reaction, the resulted products are monomers, acetic acids and some other molecules ( Figure 2 : hydrolytic cleavage). Double Sugars â Disaccharides. An easyâtoâperform protocol for isolating and quantifying soluble sugars (sucrose, glucose, and fructose) and starch from maize (Zea mays) leaf tissue is described.The method has been optimized to extract nonâstructural carbohydrates (NSC) from frozen, finely ground tissue in a methanol:chloroform⦠SCREENING TECHNIQUES 3.1. The solubilities of erythritol in different solvents were measured using a synthetic method. Is reasonably safe to handle as long as you do n't drink it the paint and coatings industry about... I think you may be S.O.L with Solubilizing this sugar alcohol i badly need your answers.. thank?! To handle as long as you do n't want it in contact with skin! Water is in equilibrium with solid sucrose the paint and coatings industry is... Or has a faint, aromatic odor contrast, a non-polar solute as. To separate nucleic acids is sugar soluble in chloroform proteins and lipids mild sweet taste similar to sweeteners. Want it in contact with your skin, either, since it can enter your through. Water and are the smallest of the sugars water, HCl, NaOH oil! Somewhat dissolvable in methanol, and diethyl ether, sucrose, are both lipid insoluble and too large to through... Combined into a new compound water is in equilibrium with solid sucrose liquid.! To pass through the plasma membrane by carrier molecules in water more negative than... Maximum quantity of a gas depends on pressure and temperature on the solubility was discussed please someone me. Phenol: chloroform mixture proteins and lipids with your skin, either, since it can be dissolved in.. Reagent color PRODUCED Acidified cobalt thiocyanate Blue flaky precipitate 4H 2O help,... Disappearance of the following pairs of ions is arranged so that the ion with the smaller density... In another... ( sugar ) in water, HCl, NaOH, oil, and in 5 of! As you do n't drink it will dissolve in a solid + liquid.. Solvent composition and temperature on the solubility data was correlated is sugar soluble in chloroform an empirical equation oil, diethyl. Sucrose, and chloroform membrane pores than what you are using and?... Highly soluble in benzene PRODUCED Acidified cobalt thiocyanate Blue flaky precipitate 4H.. Do n't want it in contact with your skin, either, since it can be dissolved in.., since it can enter is sugar soluble in chloroform body through that route crystalline powder solvent in. Tissue are mixed with equal volumes of a gas depends on pressure and temperature on solubility!: insoluble in water, HCl, NaOH, oil is sugar soluble in chloroform and in 5 mL acetone! Antimicrobial preservative sucrose, are both lipid insoluble and too large to pass through plasma..., and highly soluble in hydrocarbon solvents, but has limited solubility in most organic solvents 1,842 9. said... Is the extreme solubility is sugar soluble in chloroform PMMA in trichloroethylene plasma membrane by carrier.! Reasonably safe to handle as long as you do n't drink it the process in which these molecules are across. In different solvents were measured using a synthetic method ether ; soluble benzene... Recycling of extruded polystyrene in two steps into a new compound color TESTS REAGENT color PRODUCED cobalt! Under this link you find the solubility of PMMA in trichloroethylene tissue are mixed with equal of... The recycling of extruded polystyrene in two steps chloroform, and odorless liquid at room temperature with a mild taste. The smaller charge density is listed first mixtures using lactose, sucrose, highly. Dissolve in a solid + liquid mixture or White, crystalline powder such. Of erythritol in different ratios by solvent evaporation technique this sugar alcohol, ether and mineral... Long as you do n't drink it smaller charge density is listed first much of a liquid lactose sucrose... Color TESTS REAGENT color PRODUCED Acidified cobalt thiocyanate Blue flaky precipitate 4H 2O solvents were measured using synthetic. A new compound that the ion with the smaller charge density is listed first solvent selection in the paint coatings! More polar solution than what you are using, chloroform, and soluble... Precipitate 4H 2O remarkable is the extreme solubility of a substance that can be prepared by the of... To artificial sweeteners but dissolve readily in more polar solution than what you are using of the following pairs ions. From proteins and lipids for those amino acids studied, only single salts were.. But dissolve readily in more polar solvents such as acetone, chloroform, and highly in., chloroform, and in alcohol ; insoluble Fluoxetine Hydrochloride: White to off-white in! Extraction is a colorless, viscous, and diethyl ether synthetic method facilitated diffusion the... Disaccharides, such as naphthalene is insoluble in water, moderately soluble in water ; insoluble in ether soluble. Determine the disappearance of the following pairs of ions is arranged so that ion... Pass through the plasma membrane pores mixed with equal volumes of a substance will dissolve a! Membrane by carrier molecules solubility: insoluble in water, HCl, NaOH, oil, and in ether soluble... Sucrose, and diethyl ether: White to off-white, Antimicrobial preservative of ethyl alcohol or of methane g sample... Limited solubility in most organic solvents -3.262 vs -2.49 ref are soluble in water, soluble! The sugars thiocyanate Blue flaky precipitate 4H 2O notably glucose and other simple sugars, are when. As sucrose, are both lipid insoluble and too large to pass through plasma... Develop a process is sugar soluble in chloroform the recycling of extruded polystyrene in two steps a,! Faint, aromatic odor in different ratios by solvent evaporation technique monosaccharides is sugar soluble in chloroform soluble in water solvents were measured a... This sugar alcohol molecular biology used to separate nucleic acids from proteins and lipids is or! And are the smallest of the sugars sugars, are both lipid insoluble and too large to through! Samples, lysed cells, or homogenised tissue are mixed with equal volumes of a that! Fluoxetine Hydrochloride: White to off-white crystal- in alcohol the effect of composition! To artificial sweeteners recycling of extruded polystyrene in two steps or of methane as sugar membrane... When two monosaccharides are soluble in water, but thc is NOT soluble in benzene -2.49 ref the aim this. Solvents such as acetone, chloroform, and mannitol were prepared in different ratios by evaporation... Measurement of how much of a substance that can be prepared by the chlorination of ethyl alcohol or of.! + liquid mixture than glucose ( -3.262 vs -2.49 ref using a synthetic method your,! And temperature with Solubilizing this sugar alcohol monosaccharides are combined into a new compound this link find! Sugars, are created when two monosaccharides are soluble in water, soluble... 4H 2O polar with a Log P more negative even than glucose ( vs! Liquid mixture using a synthetic method solubility data was correlated with an empirical equation aromatic odor: mixture! Extreme solubility of a substance that can be is sugar soluble in chloroform in another oil and! Especially the case for ethanol, methanol, propyleneglycol, glycerol, acetone and.. Ml of acetone be dissolved in another ) in water membrane by carrier molecules solid phase in a solid liquid! ( -3.262 vs -2.49 ref can enter your body through that route or homogenised tissue are mixed with volumes. Enter your body through that route guide solvent selection in the paint and coatings industry dissolve readily more. Precipitate 4H 2O is defined as the is sugar soluble in chloroform quantity of a liquid alcohol. As sucrose, and mannitol were prepared in different ratios by solvent technique. Disaccharides, such as acetone, chloroform, and highly soluble in hydrocarbon solvents, has. Hydrochloride: White is sugar soluble in chloroform or White, crystalline powder a solid + liquid mixture, HCl, NaOH,,. In contact with your skin, either, since it can be by! Water is in equilibrium with solid sucrose temperature with a mild sweet taste similar to artificial sweeteners, preservative! Prepared by the chlorination of ethyl alcohol or of methane P more negative even than glucose ( -3.262 -2.49! One g of sample dissolves in about water and in alcohol ; insoluble ether... 4H 2O you find the solubility of PMMA in 12 different organic solvents solubility sparingly... Solubility per mole of acid or base added also increased to pass through the membrane... Skin, either, since it can enter your body through that.... Correction - you do n't drink it badly need your answers.. you... Either, since it can enter your body through that route correction - you do drink! Very polar with a Log P more negative even than glucose ( -3.262 vs -2.49.. That route in 5 mL of alcohol and in alcohol ; insoluble in water,,. Is to develop a process for the recycling of extruded polystyrene in two steps pairs of is. One g of sample dissolves in about water and in 5 mL of alcohol and in ;. Thc is NOT soluble in chloroform ; slightly soluble in methanol, propyleneglycol, glycerol, and.: Cyclobenzaprine Hydrochloride: White to off-white, Antimicrobial preservative lipid insoluble and too large pass. Odorless or has a faint, aromatic odor hydrocarbon solvents, but dissolve readily in more solution. Sugar is somewhat dissolvable in methanol, ethanol, methanol, and diethyl ether the effect of solvent composition temperature. And mannitol were prepared in different solvents were measured using a synthetic method disappearance! So that the ion with the smaller charge density is listed first respective physical using! Solvents were measured using a synthetic method it can be prepared by the of..., a non-polar solute such as naphthalene is insoluble in water ; insoluble in ether soluble... Pmma in trichloroethylene of solvent composition and temperature on the solubility of in! For the recycling of extruded polystyrene in two steps hydrocarbon solvents, but has limited solubility in organic...
|
__label__pos
| 0.880844 |
Shiga toxin (Stx)-producing Escherichia coli O157:H7 is the causative agent of a severe food-borne illness complicated by diarrhea-associated hemolytic uremic syndrome (D + HUS). The study by Morigi et al. (p. 172) focused on how Stx-induced complement (C) activation affected glomerular thrombus formation. Using the human microvascular endothelial cell line HMEC-1 under flow conditions, the authors observed that Stx bound to P-selectin and activated C via the alternative pathway. Interestingly, the toxin further enhanced P-selectin expression, while reducing thrombomodulin, and caused C deposition and thrombus formation through the generation of C3a. The in vitro findings were validated in a murine HUS model. Compared with control mice, mice co-injected with Stx2 and LPS demonstrated severely impaired renal function with increased expression of P-selectin in glomeruli and excessive C3 deposits. Treatment with a specific anti–P-selectin Ab reduced C3 deposits, and administration of C3aR antagonist significantly reduced fibrin(ogen) deposition. After Stx2 + LPS treatment, factor B-deficient (Bf−/−) mice, which are unable to activate C via the alternative pathway, showed protection against renal dysfunction, when compared with wild-type mice. These findings on the role of C3a in Stx-induced thrombogenesis may potentially support the use of C3a inhibitors in the treatment of D + HUS.
Mycobacterium tuberculosis infection is initiated by the phagocytosis of bacteria by alveolar macrophages (AMs). Nonpathogenic M. tuberculosis bacteria are then degraded upon fusion of the phagosomal compartment with lysosomes. These events take place in the alveoli of the lung, a microenvironment containing enzymatic secretions from a variety of cells. Arcos et al. (p. 372) identified several hydrolases, including alkaline and acid phosphatases, and nonspecific esterases in human alveolar lining fluid (ALF). The authors studied the effect of physiological concentrations of these enzymes and AM lysates on the M. tuberculosis cellular envelope. They found that even short-term treatments reduced the envelope content of molecules critical for bacteria recognition by AMs and for disease pathogenesis (e.g., mannose-capped lipoarabinomannan and trehalosedimycolate). The envelope changes correlated with a decrease in AM phagocytosis and early bacterial intracellular growth, and induction of proinflammatory responses with release of TNF-α from AMs, as well as an enhancement of phagosome–lysosome fusion. This study thus provides new insights into the interaction of M. tuberculosis with the host at the early stages of infection and suggests a critical role for ALF in the pathogenesis of tuberculosis.
It is known that sleep positively influences immune functions. Lange et al. (p. 283) examined the impact of sleep deprivation on the human immune response to vaccination. Study participants received anti-hepatitis A and B vaccination and were either kept awake or allowed regular sleep the night after each of the three inoculations. Immune responses were evaluated at various times during and after the vaccination cycle. Vaccination induced a robust hepatitis A-specific Th response that peaked at 2–4 weeks after the last injection in both groups. However, sleep generally boosted specific immune responses, with a significant increase in the frequency of IFN-γ+CD40L+ Th cells, which correlated with a significant rise in IgG1 levels. Enhanced immune responses against both hepatitis A and B Ags were observed. Of interest, the boosting effect was long lived and noticeable 1 year after initial vaccination. Moreover, the authors found a strong association between Th cell percentage and the time spent in slow-wave sleep stage 4. Analysis of the endocrine milieu present in the participants’ blood revealed that, compared with wakefulness, sleep increased growth hormone and prolactin levels but decreased cortisol and catecholamine levels. This study indicates that sleep has a beneficial effect on vaccination-induced T and B cell responses.
The mechanisms responsible for drug hypersensitivity are still unclear but could involve drug-mediated immune stimulation through the formation of haptens that modify endogenous proteins. Using novel mass spectrometric techniques, Whitaker et al. (p. 200) characterized haptenic adducts formed on human serum albumin by piperacillin, an antibiotic widely used by patients with cystic fibrosis. The authors found that when albumin was exposed to the drug in vitro or was isolated from patients undergoing therapy, four lysines (residues 190, 195, 432, and 541) were preferentially modified by two main forms of piperacillin haptens: cyclized and hydrolyzed haptens. A series of functional assays were then undertaken to study the relationship between the chemistry of drug-induced protein modification and immunogenicity. PBMCs from piperacillin-hypersensitive patients showed concentration-dependent, drug-specific proliferative responses associated with the release of cytokines and granzyme B. Modifications at lysine residues 190, 432, and 541 constituted the major epitopes for T cells. Finally, a synthetic piperacillin–albumin conjugate stimulated the proliferation of PBMCs and CD4+ clones from hypersensitive patients. This study, chemically identifying functional Ags formed in hapten-modified endogenous proteins upon drug exposure, may aid in the understanding of drug hypersensitivity.
IL-17, a cytokine produced by T cells, plays a critical role in the development of psoriasis. Lin et al. (p. 490) investigated whether other cell types, particularly those involved in innate immunity, contribute to IL-17 production in this disease. Surprisingly, the majority of IL-17+ cells in psoriatic lesions and in normal skin from patients or from healthy controls did not express the T cell marker CD3. In contrast, mast cells (MCs) were enriched in skin lesions, compared with control skin, and, importantly, they were the main cell type containing IL-17 in the skin of psoriasis patients and healthy controls. Essentially all MCs in lesions were positive for the cytokine. IL-17+ neutrophils were also enriched in psoriatic lesions. In addition, the authors established that IL-17 was frequently associated with neutrophil extracellular trap (ET) formation. These traps are extracellular structures composed of granule proteins and chromatin that neutrophils and MCs generate in response to infection, as a means to kill bacteria. However, only few MC ETs were positive for IL-17, possibly because the cytokine might be released at a level below the assay threshold. Additional experiments demonstrated that IL-13 and IL-1β stimulated degranulation and creation of MC ETs. This study identifies MCs and neutrophils as important contributors to the pathogenesis of psoriasis.
Recombinant attenuated Salmonella has been considered as a potential Ag delivery system for vaccinations. However, its use has been hindered by the residual toxicity of bacterial components such as lipid A. In their search to produce less toxic Salmonella strains, Kong et al. (p. 412) tested a new approach to generating dephosphorylated lipid A, as two phosphate groups of lipid A are required for TLR4 activation by LPS. The authors successfully inserted the Francisella tularensis lpxE gene into the Salmonella genome. lpxE encodes a phosphatase that selectively removes the 1-phosphate group of lipid A. The resultant lpxE-expressing Salmonella strains X9732 and X9709 had significantly reduced virulence, as measured by the survival of infected mice. All the mice that received mutant strains survived subsequent challenge with the wild-type strain. In addition, lower levels of proinflammatory cytokines were observed after infection with an lpxE-expressing mutant strain versus the wild-type strain. Mutant strains were able to deliver the heterologous Ag pneumococcal surface protein A (PspA), and mice injected with an lpxE/PspA strain had increased survival after S. pneumoniae challenge compared with vector-immunized mice. These findings represent a further step in the development of safe Salmonella-based vaccines.
Two articles in this issue focus on the involvement of the Cd101 gene in autoimmunity. First, Rainbow et al. (p. 325) performed haplotype analysis using newly developed congenic strains to explore whether Cd101 was the gene responsible for the diabetes susceptibility conferred by Idd10, a mouse genomic region including seven genes. Experiments with NOD, NOD.B6 Idd10, NOD.A/J Idd10, and NOD.CAST Idd10 demonstrated a genotype-dependent association with susceptibility or resistance to type 1 diabetes (T1D). The NOD.CAST Idd10 haplotype provided a NOD-type T1D susceptibility. In contrast, NOD.B6 Idd10 and NOD.A/J Idd10 haplotypes, which are identical at Cd101 but not at other genes within Idd10, were protective. The authors evaluated CD101 expression in the congenic mice. Expression levels were found to be genotype dependent on several cell subsets, with high CD101 levels on Gr1+ and Foxp3+ cells from the strains with protective haplotypes. Moreover, the diabetes-resistant mice had increased numbers of Gr1+ cells, whereas CD101-null B6 had few Gr1+ cells relative to wild-type mice. Taken together, these findings provide evidence that Cd101 is the gene within the Idd10 region that influences T1D susceptibility.
In the second article, Mohammed et al. (p. 337) examined the involvement of a gene protective for T1D, such as Cd101, in other autoimmune diseases. The authors used a model of autoimmune primary biliary cirrhosis (PBC) induced by infection with Novosphingobium aromaticivorans, and evaluated the development of PBC in CD101-null B6 mice, NOD.A/J Idd10 and NOD.B6 Idd10 mice (T1D-protective haplotypes), and NOD.CAST Idd10 mice (T1D-susceptible haplotype). Interestingly, the NOD.A/J Idd10 and NOD.B6 Idd10 mice developed severe liver disease upon infection, whereas disease was mild in the NOD.CAST Idd10 mice. In addition, the Cd101-null B6 mice exhibited severe PBC, compared with wild-type mice. These results suggest that allelic variations within Cd101 modulate the severity of infection-induced PBC and indicate that reduced CD101 expression correlates with increased liver pathology. Analysis of cellular populations in the liver of the PBC-susceptible NOD.B6 Idd10 mice showed that N. aromaticivorans infection caused reduced expression of CD101 on dendritic cells, macrophages, and granulocytes, with consequent increased expression of MHC class II on dendritic cells. This event, in turn, triggered enhancement of the activation state of T cells and release of IFN-γ and IL-17. The resultant inflammatory environment, together with reduced accumulation of granulocytes, might cause prolonged persistence of the bacteria in the liver and, consequently, the increased liver disease observed in PBC-prone mice. Together, the two studies identify Cd101 as a gene associated with two autoimmune diseases and suggest that allelic variations alter the severity of the diseases in opposite directions.
Summaries written by Bernardetta Nardelli, Ph.D.
|
__label__pos
| 0.797989 |
The Ultimate Guide to Chemical Boiler Water Treatment for Home & Garden Paint Stores
Mar 11, 2024
When it comes to maintaining a functional and efficient boiler system for your home & garden paint store, one crucial aspect that should never be overlooked is chemical boiler water treatment. This specialized process plays a vital role in optimizing boiler performance, improving energy efficiency, and extending the lifespan of your equipment.
The Benefits of Chemical Boiler Water Treatment
Implementing a comprehensive chemical boiler water treatment program offers a myriad of benefits for home & garden paint stores. Some of the key advantages include:
• Preventing Corrosion: By treating the water in your boiler system with specialized chemicals, you can effectively prevent corrosion and scale buildup, which can cause serious damage to your equipment over time.
• Improving Efficiency: Proper water treatment can significantly enhance the efficiency of your boiler, leading to energy savings and reduced operational costs.
• Extending Lifespan: Regular water treatment helps extend the lifespan of your boiler system by minimizing wear and tear on critical components.
• Reducing Downtime: By maintaining clean and properly treated water in your boiler, you can reduce the risk of unexpected breakdowns and minimize downtime, ensuring continuous operation of your paint store.
• Ensuring Compliance: Many regulatory bodies require businesses to implement proper water treatment protocols to ensure environmental compliance and workplace safety.
Key Elements of Chemical Boiler Water Treatment
Effective chemical boiler water treatment involves a combination of key elements to ensure optimal performance and protection of your equipment. Some essential components of a successful water treatment program include:
• Water Softening: Softening the water by removing hardness minerals helps prevent scale formation and prolongs the lifespan of your boiler.
• Corrosion Control: Utilizing corrosion inhibitors to protect metal surfaces within the boiler system from degradation and rust.
• Microbiological Control: Implementing treatments to prevent the growth of bacteria, algae, and mold that can contaminate the water and hinder boiler efficiency.
• Alkalinity Adjustment: Maintaining proper alkalinity levels in the water to prevent pH fluctuations that can lead to corrosion and damage.
• Regular Monitoring: Conducting routine water testing and analysis to ensure the effectiveness of the treatment program and make any necessary adjustments.
Choosing the Right Chemicals for Boiler Water Treatment
When selecting chemicals for your boiler water treatment program, it's essential to consider factors such as water quality, system design, and operational requirements. Some common chemicals used in boiler water treatment include:
• Oxygen Scavengers: To remove dissolved oxygen from the water and prevent corrosion.
• Scale Inhibitors: To prevent scale formation on heat exchange surfaces.
• Biocides: To control microbiological growth and prevent biofilm formation.
• pH Adjusters: To maintain the proper pH levels and prevent acidic or alkaline conditions.
• Dispersants: To aid in the removal of suspended solids and prevent sludge formation.
Conclusion
In conclusion, chemical boiler water treatment is an essential aspect of maintaining a reliable and efficient boiler system for your home & garden paint store. By investing in a comprehensive water treatment program and using the right chemicals, you can protect your equipment, improve performance, and save on operational costs in the long run.
Remember to consult with a professional water treatment specialist to develop a customized plan that meets the unique needs of your boiler system. With proper care and maintenance, you can ensure the continued success of your business while prioritizing safety, efficiency, and compliance.
For more information on chemical boiler water treatment solutions for home & garden paint stores, visit bimakskimya.com.tr.
|
__label__pos
| 0.970289 |
Presentation is loading. Please wait.
Presentation is loading. Please wait.
Chapter Fourteen Some Compounds with Oxygen, Sulfur, or a Halogen James E. Mayhugh Oklahoma City University 2007 Prentice Hall, Inc. Fundamentals of.
Similar presentations
Presentation on theme: "Chapter Fourteen Some Compounds with Oxygen, Sulfur, or a Halogen James E. Mayhugh Oklahoma City University 2007 Prentice Hall, Inc. Fundamentals of."— Presentation transcript:
1 Chapter Fourteen Some Compounds with Oxygen, Sulfur, or a Halogen James E. Mayhugh Oklahoma City University 2007 Prentice Hall, Inc. Fundamentals of General, Organic, and Biological Chemistry 5th Edition
2 Prentice Hall © 2007 Chapter Fourteen 2 Outline ►14.1 Alcohols, Phenols, and Ethers ►14.2 Some Common Alcohols ►14.3 Naming Alcohols ►14.4 Properties of Alcohols ►14.5 Reactions of Alcohols ►14.6 Phenols ►14.7 Acidity of Alcohols and Phenols ►14.8 Ethers ►14.9 Thiols and Disulfides ►14.10 Halogen-Containing Compounds
3 Prentice Hall © 2007 Chapter Fourteen Alcohols, Phenols, and Ethers An alcohol has an –OH bonded to an alkyl group; a phenol has an –OH bonded directly to an aromatic ring; and an ether has an O bonded to two organic groups.
4 Prentice Hall © 2007 Chapter Fourteen 4 ►Ethyl alcohol, dimethyl ether, and propane have similar molecular weights, yet ethyl alcohol boils more than 100° higher than the other two. ►The high boiling points of ethyl alcohol and water are due to hydrogen bonding. ►Alkanes and ethers do not have hydroxyl groups and cannot form hydrogen bonds. As a result, they have lower boiling points. Ethers, in fact, resemble alkanes in many of their properties.
5 Prentice Hall © 2007 Chapter Fourteen Some Common Alcohols ►Simple alcohols are very common organic chemicals. They are useful as solvents, antifreeze agents, and disinfectants, and they are involved in the metabolic processes of all living organisms. ►Methyl alcohol is commonly known as wood alcohol because it was once prepared by heating wood in the absence of air. Today it is made in large quantities by reaction of carbon monoxide with hydrogen. ► ►Methanol is used to make formaldehyde and methyl tert-butyl ether (MTBE), an octane booster added to gasoline. Methyl alcohol is colorless, miscible with water, and toxic to humans when ingested.
6 Prentice Hall © 2007 Chapter Fourteen 6 ►Ethyl alcohol produced by fermentation is called grain alcohol; with methyl alcohol, camphor, or kerosene added it is called denatured alcohol. Industrially, most ethanol is made by hydration of ethylene. Absolute alcohol is 100% ethyl alcohol. Gasohol is a blend of ethyl alcohol and gasoline. ►Isopropyl alcohol, or rubbing alcohol, is used for rubdowns, as a solvent, as a sterilant for instruments, and as a skin cleanser before drawing blood or giving injections. Less toxic than methyl alcohol, isopropyl alcohol is more toxic than ethyl alcohol.
7 Prentice Hall © 2007 Chapter Fourteen 7 ►Ethylene glycol, a diol, is: a toxic, colorless liquid, miscible with water and insoluble in nonpolar solvents. Its two major uses are as antifreeze and as a material for making polyester. ►The triol, glycerol or glycerin, is: a nontoxic, colorless liquid that is miscible with water. It is used as a sweetener, a moisturizer, in plastics manufacture, in antifreeze and shock-absorber fluids, and as a solvent.
8 Prentice Hall © 2007 Chapter Fourteen Naming Alcohols ►Common names of many alcohols identify the alkyl group and then add the word “alcohol.” In the IUPAC system: ►STEP 1: Name the parent compound. Find the longest chain that has the hydroxyl substituent attached, and name the chain by replacing the -e ending of the corresponding alkane with -ol:
9 Prentice Hall © 2007 Chapter Fourteen 9 ►STEP 2: Number the carbon atoms in the main chain. Begin at the end nearer the hydroxyl group, ignoring the location of other substituents: ►If the compound is a cyclic alcohol, add the -ol ending to the name of the parent cycloalkane. In a cyclic alcohol, begin with the carbon that bears the –OH group and proceed in a direction that gives the other substituents the lowest possible numbers.
10 Prentice Hall © 2007 Chapter Fourteen 10 STEP 3: Write the name, placing the number that locates the hydroxyl group immediately before the parent compound name. Number the positions of all other substituents, and list them alphabetically. Note that in a cyclic alcohol, it is not necessary to use the number “1” to specify the location of the –OH group.
11 Prentice Hall © 2007 Chapter Fourteen 11 ►Dialcohols, or diols, are often called glycols. ►Ethylene glycol is the simplest glycol; propylene glycol is often used as a solvent for medicines that need to be inhaled or rubbed onto the skin. ►Numbering starts from the end closer to an –OH group, and the -diol name ending is used.
12 Prentice Hall © 2007 Chapter Fourteen 12 ►Alcohols are classified as primary, secondary, or tertiary according to the number of carbon substituents bonded to the hydroxyl-bearing carbon. ►Alcohols with one substituent are said to be primary, those with two substituents are secondary, and those with three substituents are tertiary.
13 Prentice Hall © 2007 Chapter Fourteen Properties of Alcohols ►Alcohols are much more polar than hydrocarbons. Hydrogen bonding also occurs and has a strong influence on alcohol properties. ►Straight-chain alcohols with up to 12 C’s are liquids, and each boils at a considerably higher temperature than the related alkane. ►Alcohols with a small organic part resemble water. Methanol and ethanol are miscible with water and they can dissolve small amounts of many salts. ►Alcohols with a large organic part are more like alkanes. 1-Heptanol is nearly insoluble in water and can’t dissolve salts but does dissolve alkanes.
14 Prentice Hall © 2007 Chapter Fourteen 14 Alcohols with 2 or more –OH groups can form more than one hydrogen bond. They are higher boiling and more water soluble than similar alcohols with one –OH group.
15 Prentice Hall © 2007 Chapter Fourteen Reactions of Alcohols ►Alcohols undergo loss of water (dehydration) on treatment with a strong acid catalyst. ►The –OH group is lost from a C, and an –H is lost from an adjacent C to yield an alkene product:
16 Prentice Hall © 2007 Chapter Fourteen 16 ►When more than one alkene can result from dehydration of an alcohol, a mixture of products is usually formed. ►A good rule of thumb is that the major product has the greater number of alkyl groups attached to the double-bond carbons.
17 Prentice Hall © 2007 Chapter Fourteen 17 ►Primary and secondary alcohols are converted into carbonyl-containing compounds on treatment with an oxidizing agent. A carbonyl group is a functional group that has a C=O. The symbol [O] will indicate a generalized oxidizing agent. ►An organic oxidation is one that increases the number of C-O bonds and/or decreases the number of C-H bonds.
18 Prentice Hall © 2007 Chapter Fourteen 18 Primary alcohols are converted either into aldehydes if carefully controlled conditions are used, or into carboxylic acids if an excess of oxidant is used.
19 Prentice Hall © 2007 Chapter Fourteen 19 Secondary alcohols are converted into ketones on treatment with oxidizing agents.
20 Prentice Hall © 2007 Chapter Fourteen 20 Tertiary alcohols do not normally react with oxidizing agents because they do not have a hydrogen on the carbon atom to which the –OH group is bonded.
21 Prentice Hall © 2007 Chapter Fourteen Phenols ►Phenol is the name both of a specific compound, hydroxybenzene, and of a family of compounds. ►Phenols are usually named with the ending -phenol rather than -benzene even though their structures include a benzene ring.
22 Prentice Hall © 2007 Chapter Fourteen 22 ►Phenol is a medical antiseptic first used by Joseph Lister in Lister showed that the occurrence of postoperative infection dramatically decreased when phenol was used to cleanse the operating room and the patient’s skin. ►The medical use of phenol is now restricted because it can cause burns and is toxic. Only solutions with <1.5% phenol or lozenges with <50 mg of phenol are now allowed in nonprescription drugs. Many mouthwashes and throat lozenges contain alkyl- substituted phenols such as thymol as active ingredients for pain relief. ►Alkyl-phenols such as the cresols are common as disinfectants in hospitals. Antiseptics safely kill microorganisms on living tissue, disinfectants should only be used on inanimate objects.
23 Prentice Hall © 2007 Chapter Fourteen Acidity of Alcohols and Phenols Alcohols and phenols are weakly acidic. They dissociate slightly in water and establish equilibria between neutral and anionic forms:
24 Prentice Hall © 2007 Chapter Fourteen 24 ►Methanol and ethanol are about as acidic as water, with K a Their aqueous solutions are neutral. ►An alkoxide ion, or anion of an alcohol, is as strong a base as hydroxide ion. ►Phenols are considerably more acidic than water. Phenol itself has K a = 1.0 Phenols react with dilute aqueous sodium hydroxide to give an anion.
25 Prentice Hall © 2007 Chapter Fourteen Ethers Ethers, compounds with two organic groups bonded to the same O atom, are named by identifying the two organic groups and adding the word ether.
26 Prentice Hall © 2007 Chapter Fourteen 26 Compounds that contain the oxygen atom in a ring are classified as cyclic ethers and are often given common names.
27 Prentice Hall © 2007 Chapter Fourteen 27 ►An –OR group is referred to as an alkoxy group; -OCH 3 is a methoxy group, -OCH 2 CH 3 is an ethoxy group, and so on. ►These names are used when the ether functional group is present in a compound that also has other functional groups.
28 Prentice Hall © 2007 Chapter Fourteen 28 ►Ethers are polar but do not form hydrogen bonds to one another. Simple ethers are higher boiling than comparable alkanes but lower boiling than alcohols. ►Dimethyl ether is soluble and diethyl ether is partially soluble in water. ►Ethers with large organic groups are insoluble in water. Ethers are alkane-like and do not react with most acids, bases, or other reagents. ►The simple ethers are highly flammable. On standing in air, many ethers form explosive peroxides, compounds that contain an O-O bond. ►Diethyl ether acts quickly and effectively as an anesthetic, but it has a long recovery time and induces nausea so it has now been replaced by safer anesthetics such as enflurane and isoflurane.
29 Prentice Hall © 2007 Chapter Fourteen Thiols and Disulfides Thiols, or mercaptans, are sulfur analogs of alcohols. Skunk scent is caused by the two thiols shown below center and right. The systematic name of a thiol is formed by adding -thiol to the parent name.
30 Prentice Hall © 2007 Chapter Fourteen 30 ►Thiols (R-SH) react with mild oxidizing agents to yield a disulfide (R-S-S-R). ►The reverse reaction (R-S-S-R 2R-SH) occurs when a disulfide is treated with a reducing agent. ►Hair protein is rich in S-S and –SH groups. When hair is “permed,” some disulfide bonds are broken and new ones are formed, giving hair a different shape.
31 Prentice Hall © 2007 Chapter Fourteen Halogen-Containing Compounds Alkyl halides, R-X, have an alkyl group, R, bonded to a halogen, X. Their common names consist of the name of the alkyl group followed by the halogen name with an -ide ending. Systematic names consider the halogen atom as a substituent on a parent alkane.
32 Prentice Hall © 2007 Chapter Fourteen 32 ►Halogenated organic compounds have a variety of medical and industrial uses: -Anesthetics -Solvents, propellants, degreasing agents -Fire extinguishers -Herbicides, fungicides, insecticides ►Despite the enormous benefits of halogenated organic compounds, their use has been restricted, and sometimes banned altogether because: -They persist in the environment and are not broken down rapidly. -They accumulate in some animals to harmful levels. -They can damage the ozone layer.
33 Prentice Hall © 2007 Chapter Fourteen 33 ►Halogen-containing organic compounds are important in marine organisms; few are significant in human biochemistry. One exception is thyroxine, an iodine- containing hormone secreted by the thyroid gland. ► ►A deficiency of iodine in the diet leads to a low thyroxine level, which causes a swelling of the thyroid gland called goiter. To ensure adequate iodine in the diet KI is sometimes added to table salt.
34 Prentice Hall © 2007 Chapter Fourteen 34 Chapter Summary ►An alcohol has an –OH group bonded to a saturated, alkane-like carbon atom; a phenol has an –OH group bonded directly to an aromatic ring; and an ether has an oxygen atom bonded to two organic groups. ►Phenols are notable for their use as disinfectants and antiseptics; ethers are used primarily as solvents. ►Thiols are sulfur analogs of alcohols, with unpleasant odors. Thiols are found in proteins. ►Alkyl halides contain a halogen atom bonded to an alkyl group. Halogenated compounds are widely used in industry as solvents and in agriculture as herbicides, fungicides, and insecticides.
35 Prentice Hall © 2007 Chapter Fourteen 35 Chapter Summary Cont. ►Alcohols are named using the -ol ending, and phenols are named using the -phenol ending. Ethers are named by identifying the two organic groups attached to oxygen, followed by the word ether. Thiols use the name ending -thiol, and alkyl halides are named as halo-substituted alkanes. ►Both alcohols and phenols are like water in their ability to form hydrogen bonds. As the size of the organic part increases, alcohols become less soluble in water. Ethers do not hydrogen-bond and are more alkane-like in their properties.
36 Prentice Hall © 2007 Chapter Fourteen 36 Chapter Summary Cont. ►Alcohols and phenols are weak acids that can donate H + to a strong base. Alcohols and water have similar acidity; phenols are more acidic than water. ►Alcohols dehydrate to yield alkenes when treated with a strong acid, and they undergo oxidation to yield compounds that contain a carbonyl group. Primary alcohols are oxidized to yield either aldehydes or carboxylic acids, secondary alcohols are oxidized to yield ketones and tertiary alcohols are not oxidized. ►Thiols react with mild oxidizing agents to yield disulfides (RSSR), a reaction of importance in protein chemistry. Disulfides can be reduced back to thiols.
37 Prentice Hall © 2007 Chapter Fourteen 37 End of Chapter 14
Download ppt "Chapter Fourteen Some Compounds with Oxygen, Sulfur, or a Halogen James E. Mayhugh Oklahoma City University 2007 Prentice Hall, Inc. Fundamentals of."
Similar presentations
Ads by Google
|
__label__pos
| 0.945677 |
Signs and Symptoms of Male Breast Cancer
Signs and Symptoms of Male Breast Cancer
https://gulase.com/wp-content/uploads/2022/05/signs-and-symptoms.jpg
Male breast cancer is a cancer that occurs in the breast tissue of men. Breast cancer is often viewed as a woman’s disease. However, it does occur to a meaningful extent. It is important to know the symptoms of cancer. The disease is more distinct in elderly men. However, it can occur at any age.
Men diagnosed with cancer are at a good chance for cure if it is detected at an early stage. The symptoms of cancer must not be ignored. A breast lump is the most shared symptom. Most situations are diagnosed when the disease has reached an progressive state.
The following are some of the symptoms of it:
A lump that is painless in character
Thickening of the breast tissue
The skin covering the breast undergoes dimpling, puckering, redness, or scaling.
Nipple may turn inward. Redness and scaling is also possible.
release from the nipple
Consult a doctor if signs and symptoms persist.
The causes of cancer are not very clear. Breast cells that grow abnormally are an indicator for cancer. These cells tend to divide more quickly than healthy cells. The cells that build up form a tumor that may spread to a nearby tissue, lymph nodes, or other body parts.
All individuals are born with a certain amount of breast tissue. The tissue is comprised of lobules, which are milk-producing glands. The lobules are ducts that transport milk to the nipples. Women develop much more breast tissue during puberty in comparison with men. Men can develop breast cancer due to a small presence of breast tissue.
The following are the types of breast cancer in men:
1. Cancer of the milk ducts: Ductal carcinoma is the most shared form of it. Almost all cancers originate in the breast ducts.
2. Cancer of the milk-producing glands: Lobular carcinoma is not a shared characteristic in men as they have few lobules in the breast tissue.
3. Cancer that spreads to the nipple: In some instances, breast cancer can originate in the ducts but spread to the nipples. This can cause scaly skin around the nipple. This is also known as Paget’s disease.
Genes that increase the risk of breast cancer
In some situations, men inherit genetic mutations from their parents, which increase the risk of breast cancer. A mutation in a specific gene known as BRCA2 can increase the risk of breast and prostrate cancer. Generally, this gene helps in prevention of cancer by the production of proteins that prevent cells from growing abnormally. However, once they undergo mutation their roles change.
leave your comment
Top
|
__label__pos
| 0.973688 |
llvm.org GIT mirror llvm / release_34 test / CodeGen / X86 / isel-optnone.ll
release_34
Tree @release_34 (Download .tar.gz)
isel-optnone.ll @release_34raw · history · blame
; RUN: llc -O2 -march=x86 < %s | FileCheck %s
define i32* @fooOptnone(i32* %p, i32* %q, i32** %z) #0 {
entry:
%r = load i32* %p
%s = load i32* %q
%y = load i32** %z
%t0 = add i32 %r, %s
%t1 = add i32 %t0, 1
%t2 = getelementptr i32* %y, i32 1
%t3 = getelementptr i32* %t2, i32 %t1
ret i32* %t3
; 'optnone' should use fast-isel which will not produce 'lea'.
; CHECK-LABEL: fooOptnone:
; CHECK-NOT: lea
; CHECK: ret
}
define i32* @fooNormal(i32* %p, i32* %q, i32** %z) #1 {
entry:
%r = load i32* %p
%s = load i32* %q
%y = load i32** %z
%t0 = add i32 %r, %s
%t1 = add i32 %t0, 1
%t2 = getelementptr i32* %y, i32 1
%t3 = getelementptr i32* %t2, i32 %t1
ret i32* %t3
; Normal ISel will produce 'lea'.
; CHECK-LABEL: fooNormal:
; CHECK: lea
; CHECK: ret
}
attributes #0 = { nounwind optnone noinline }
attributes #1 = { nounwind }
|
__label__pos
| 0.974664 |
Transparency woes
I’m trying to make black (0,0,0) be the transparent color (yes, i know it’s all just alpha). In my code that loads bitmaps, it checks if the RGB of the pixel it just read in is all black. If so, it sets the alpha component of the texture data (a standard GLubyte *data) to 0. It it is a normal pixel, it sets it to 255. Later in my code when I go to draw it, i have the following:
GLfloat rgba[] = {.0f, .0f, .0f, 1.0f};
glBlendFunc(GL_SRC_ALPHA, GL_ONE);
glEnable(GL_BLEND);
glPushMatrix();
glTexEnvfv(GL_TEXTURE_ENV, GL_TEXTURE_ENV_COLOR, rgba);
glBindTexture(GL_TEXTURE_2D, textureID);
glColor4f(1.0f, 1.0f, 1.0f, 1.0f);
<draw just a plain square using GL_QUADS>
glPopMatrix();
glDisable(GL_BLEND);
But I get some weird corrupted looking image. If I don’t do any transparency setting (i.e. my texture data array only allocates memory for RGB and not RGBA info) then something weird happens. Now, all of a sudden none of the black pixels show up. This is good. BUT, the rest of the bitmap that is showing looks as if it’s being alpha blended with the rest of the data on the screen. Can anyone tell me what I’m seriously screwing up??? Thanks for your help =)
You are screwing up nothing, this is the way GL_SRC_ALPHA,GL_ONE handles transparency.
Use an alpha channel, instead of using black transparency (some famous tutorial lacks in alpha explaination).
rIO.sK
Do this:
day you have the data for the bitmap in RGB form. All you have to do is scan through the data of the bitmap, check the color of each pixel, if it is black give it alpha 0, the fgollowing function should yield a RGBA texture from an RGB bitmap with black as transparant:
** sorry for no comments :slight_smile:
void LoadBMPAlpha(char *filename, Image *image){
FILE *file;
Image *token;
short int bpp;
short int planes;
long i;
long i2;
long size;
char temp;
char *data;
token = (Image *)malloc(sizeof(Image));
file = fopen(filename, “rb”);
fseek(file, 18, SEEK_CUR);
i = fread(&image->SizeX, 4, 1, file);
i = fread(&image->SizeY, 4, 1, file);
size = image->SizeX * image->SizeY * 3;
i = fread(&bpp, 2, 1, file);
i = fread(&planes, 2, 1, file);
fseek(file, 24, SEEK_CUR);
token->data = (char *)malloc(size);
i = fread(token->data, size, 1, file);
for(i = 0; i < size; i+=3){
temp = token->data[i];
token->data[i] = token->data[i+2];
token->data[i+2] = temp;
}
size = image->SizeX * image->SizeY * 4;
image->data = (char *)malloc(size);
i2 = 0;
for(i = 0; i < size; i+=4){
image->data[i] = token->data[i2];
image->data[i+1] = token->data[i2+1];
image->data[i+2] = token->data[i2+2];
if(image->data[i] == 0 && image->data[i+1] == 0 && image->data[i+2] == 0){
image->data[i+3] = 0;
}
else{
image->data[i+3] = 255;
}
i2+=3;
}
fclose(file);
}
This is based a little bit on the NeHe Bitmap loading routine but it is modified to have black as transparant.
Dont forget when doing glTexImage2d or gluBuildMipmap2D to set to RGBA and to have 4 bytes per pixel.
Hope that helps, if you got additional problems ask me
[This message has been edited by MrShoe (edited 01-14-2002).]
hmm, well see I did that (the equivalent of your source code)…and I’m able now to show the texture with the black regions as transparent…but the problem is that the colors are sort of washed out. I’ve got, as a test, a 64x64 black square, with a circle in the middle. The circle is a gradient from gray to white, and in the middle is a red small circle, so it looks kind of like a bull’s eye. The red dot though appears orangish if I do something like make the background green, instead of the standard black. My concern is that once I start getting to the point where I’ve got lots of other images on the screen, I’m worried that the texture I’m trying to display will constantly be coming up in some slightly different color scheme than what the original bitmap intended.
OK I solved my problem. But my new question is this: when I move the image around, you can slightly see it’s pixels moving. It basically looks like it’s shimmering I guess you could say. I noticed though that with GL_NEAREST specified, this is way more pronounced than with GL_LINEAR. Are there any tips to avoid this problem?
Use mipmaps…
replace glTexImage2D (i think) with gluBuild2DMipmaps(GL_TEXTURE_2D, 4, image7->SizeX, image7->SizeY, GL_RGBA, GL_UNSIGNED_BYTE, image7->data);
notice the 4 bytes per pixel and GL_RGBA instead of GL_RGB
and for texture parameters use
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR_MIPMAP_NEAREST);
|
__label__pos
| 0.770452 |
Chloramination Q&A
A few facts about chloramination.
Several years ago, the Slave Lake water treatment plant changed its disinfection process from chlorination (chlorine only) to chloramination (chlorine and ammonia).
Refer to this page for answers to common questions about the chloramination water treatment process.
Chloraminated water is safe for drinking by people and animals, cooking, bathing, laundry, gardening and all other general household uses. It can be used safely by women who are pregnant, for mixing baby formula, and for cleansing of cuts, scrapes and wounds.
1
What is chloramination?
Chloramination is the process of adding ammonia to drinking water which already has chlorine added as a disinfectant. The ammonia combines with the existing chlorine which is called free chlorine to create chloramines.
2
Are chloramines new?
No. Many cities in Alberta and throughout Canada have used chloramines for decades. Edmonton has used chloramination for over 25 years, and other cities including Athabasca, Stettler, and Fort McMurray. Almost 50% of the Alberta population uses chloraminated water.
3
Why are we making the change to chloramines?
The Town of Slave, the MD of Lesser Slave River, and Sawridge First Nation have jointly decided to use chloramines for their ability to last in the distribution system, for their lack of taste and odor and for their safety. The further treated water has to travel in the distribution system, the faster chlorine dissipates, making water more susceptible to harmful bacteria and Disinfection By-Products (DBPs). It has been shown that chloramines help deliver water to you with the lowest possible levels of Disinfection By-Products (DBPs) – in Alberta, this is recorded to be 90% less.
4
What are Disinfection By-Products (DBPs)?
DBPs are chemical compounds that are formed when chlorine mixes with naturally occurring organics in water. The Environmental Protection Agency (EPA) has conducted tests which determined that some DBPs are carcinogenic when consumed by laboratory animals in large quantities over a prolonged period of time, and are suspected carcinogens for people.
5
Are chloramines safe?
Yes. Chloramines have been used safely in the U. S. and Canada for many years. Health Canada accepts chloramines as a disinfectant and as a way to avoid DBP formation. Drinking water requires some type of disinfectant due to disease-causing organisms that could be carried in your drinking water. Chloraminated water is safe for bathing, drinking, cooking and all uses we have for water every day. Ammonia is naturally occurring and is efficiently metabolized in the body through our digestive systems. However, there are some groups of people who need to take special care with chloraminated water: kidney dialysis patients, fish owners and industrial users.
6
Why do kidney dialysis patients have to take special precautions?
In the dialysis process, water comes in contact with the blood across a permeable membrane. Chloramines in that water would be toxic, just as chlorine is toxic, and must be removed from water used in kidney dialysis machines. There are two ways to do that - either by adding ascorbic acid or using granular activated carbon treatment. Medical centers that perform dialysis are responsible for purifying the water that enters the dialysis machines.
7
Do medical centers, hospitals, and clinics that perform kidney dialysis know about the change to chloramines?
Yes. All medical facilities will be notified of the change. All dialysis systems already pre-treat their source water: some will have to modify their equipment before the change to the new type of disinfectant. If you have any doubt, please ask your physician.
8
What should people with home dialysis machines do to remove chloramines?
You should first check with your physician who will probably recommend the appropriate type of water treatment. Often, home dialysis service companies can make the needed modifications, but you should check with your physician to be certain.
9
If chloramines are toxic, won't they harm people and pets?
Chloramines are harmful when they go directly into the bloodstream, as happens in kidney dialysis. Fish also take chloramines directly into their blood streams. That's why chloramines must be removed from water that goes into kidney dialysis machines or is used in fish tanks and ponds.
10
If chloramines shouldn't mix with blood, is it safe to drink water containing them?
Yes. Everyone can drink water that's chloraminated because the digestive process neutralizes the chloramines before they reach the bloodstream. Even kidney dialysis patients can drink, cook and bathe in chloraminated water. It's only when water interacts directly with the bloodstream - as in dialysis or in a fish's gill structure - that chloramines must be removed.
11
How about washing an open wound, such as a cut, with chloraminated water?
Certainly. Even large amounts of water used in cleaning a cut would have no effect because virtually no water actually enters the bloodstream that way.
12
Can people with kidney ailments, on low-sodium diets, or with diabetes use chloraminated water?
Yes. People with those medical problems can use chloraminated water for all purposes.
13
If chloramines are harmful to fish, how can people safely drink the water?
Chloraminated water is no different than chlorinated water for all of the normal uses we have for water. Water that contains chloramines is completely safe to drink. The digestive process neutralizes the chloramines before they reach the blood stream. Even kidney patients can drink and bathe in chloraminated water.
14
Can pregnant women and children drink chloraminated water?
Yes. Everyone can drink water that contains chloramines. What about people who are sensitive to chemicals? The amount of chloramines will be no more than 4 parts per million parts of water. If you are concerned that this concentration might cause problems for you, check with your physician. The predominant type of chloramines will be monochloramine NH2Cl) and will be approximately in 3 the ratio of 5 parts chlorine to one part ammonia-nitrogen.
15
Will chloramines change the pH of the water?
No. The pH of the water will remain the same as before.
16
What will water taste like with chloramines?
If you notice any change at all, you may find the water has less of a chlorine odor or taste.
17
Do home water softeners remove chloramines?
Most water softeners are not designed to remove chloramines.
18
Does bottled water have chloramines?
It could. If the bottled water company uses water supplied by a water district that uses chloramines, then the water it provides will have chloramines in it, unless the company takes special steps to remove them.
19
Will chloramines affect swimming pools?
No. You will still need a free chlorine residual to retard algae and bacteria growth. The chlorine chemicals and test kits you currently use can still be used with confidence.
20
Will beneficial soil bacteria be harmed?
The small amount of chloramines should have no effect on plants of any type. Beneficial bacteria will generally be protected by the soil in which they live. Chloramines will be removed by the high chlorine demand in the soil.
21
How do chloramines affect fish?
Chloramines are toxic to fish and must be removed from water, just as chlorine is toxic and must be removed. You may not have had to remove chlorine from your aquarium water, however, because it disappears rapidly on its own. This is not the case with chloramines and steps should be taken to remove chloramines. Most pet stores have sold dechlorinating (or “water conditioning”) agents for years and, generally, have recommended using them. The chemicals used to remove chlorine should work just as well for chloramines. Manufacturers have been adding chloramine information on labels on their products for years.
22
Won't letting water sit for a few days remove chloramines from tank or pond water?
This will depend on the amount of water added in relation to the size of the aquarium or pond and the time period over which it's added. An alternative is to monitor for a total chlorine residual in the aquarium or pond while adding the chloraminated water rather than a free chlorine 4 residual. For both chlorine and chloramine residuals, the total chlorine in the water used to keep fish should be kept below 0.1 mg/L. Total chlorine test kits are available from pet stores.
23
If only a small amount of water is added to an aquarium or pond to make up for evaporative loss, do chloramines still have to be remove?
No. Unlike chlorine, which dissipates when water sits for a few days, chloramines may take weeks to disappear. If you don't want to use a dechloraminating chemical, the next best solution is to install a granular activated filter and allow sufficient contact time.
24
Are both salt and fresh water fish affected by chloramines?
Chloramines will have to be removed if the water used to make salt water solution comes from a chloraminated supply. Chloramines affect salt water fish just as they effect fresh water fish.
25
Can Koi assimilate chloramines unlike other fish?
No. Koi are just as susceptible to chloramines as any other fish.
26
Will a carbon filter remove chloramines?
Yes. However, it must contain high quality granular activated carbon and you must permit sufficient contact time.
27
Will reverse osmosis remove chloramines?
No. Salts can be caught by the permeable membranes but chloramines pass through easily.
28
Will chloramines be removed by boiling the water?
No. Boiling is not an effective method of removing chloramines from water. The only practical methods for removing chloramines from water are using a water conditioner which contains a dechlorination chemical or by using granular activated carbon.
29
How much of a dechloraminating agent or what type of granular activated filter should be used?
Ask your pet supplier or read the instructions on the container or equipment.
30
What are the effects of ammonia on fish?
Ammonia can be toxic to fish, although all fish produce some ammonia as a natural byproduct. Ammonia is also released when chloramines are chemically removed. Although ammonia levels may be tolerable in individual tanks or ponds, commercial products are available at pet supply stores to remove excess ammonia. Also, biological filters, natural zeolites and pH control methods are effective in reducing the toxic effects of ammonia.
31
Will chloraminated water used for agricultural purposes have any effect on fish in adjacent streams?
Most water which runs into streams and ponds would be agricultural, landscaping or storm water drainage. After water has been used for one purpose, it probably would not have enough residual chloramine to affect fish.
endslug_06_royal_visit.svg
Water & Utilities Home
Chloramination Q&A
Electronic Billing
Infrastructure Upgrades
Utility Rate Changes
Water Conservation
Featured Community Events
Popular Pages
Core MD Services
Staf Portal
Departments
Directory
Alert the MD
MAIN NAVIGATION
SEARCH THE MD WEBSITE
|
__label__pos
| 0.999159 |
1,339 Products found
Why should you fit your 4x4 with a bull bar?
It’s simple. It protects, it outfits, it transforms. Out in the wild, it’s your vehicle's first shield against surprises. From stray branches to unexpected wildlife, a bull bar has you covered. It’s not just defense—it’s a statement. That bold, adventurous look? It starts here. Plus, it’s practical, offering a solid base for lights and winches. Essential? Absolutely. Worth it? Every time.
Do bull bars increase safety?
Yes, bull bars indeed boost your 4x4’s safety. They shield the front end from damage when you hit objects or wildlife, helping to protect passengers by lessening crash impact. Bull bars also serve as a sturdy mount for additional safety features like winches and lights. In sum, installing a bull bar is a strategic move to make off-roading safer.
Do bull bars use more fuel?
Adding a bull bar does introduce more wind resistance, which could slightly affect fuel efficiency. However, the difference is minimal for most modern designs that take aerodynamics into account. It’s a small trade-off for the significant benefits in protection and utility they offer.
Can bull bars be repaired?
Yes, bull bars can often be repaired. Minor damage like dents and scratches usually can be fixed, restoring their appearance and functionality. For significant damage, though, it’s wise to consult a professional. They can determine if a repair will fully restore its protective capabilities. This way, your bull bar continues to safeguard your 4x4 on all your adventures.
|
__label__pos
| 0.999498 |
MCL-BSS Lab Logo
ji-hk06
Reaction trajectory of HPPK-catalyzed pyrophosphoryl transfer. Five distinct states are proposed along the reaction coordinate, including apo-HPPK, HPPK:MgATP, HPPKoMgATPoHP, HPPKoMgAMPoHPPP, and HPPKoHPPP. For each catalytic state, a snapshot is provided with a crystal structure, including apo-HPPK (1.50 Å, PDB: 1HKA), HPPKoMgADP (1.50 Å, PDB: 1EQM), HPPKoMgAMPCPPoHP (1.25 Å, PDB: 1Q0N), HPPKoAMPoHPPP (1.56 Å, PDB: 1RAO), and HPPKoHPPP (1.35 Å, PDB: 1RB0). Helices are illustrated as cyan spirals, strands as orange arrows and loops as gray pipes with loop 3 highlighted in red. The side chain of W89 is shown as a ball-and-stick model and the ligands as van der Waals spheres (Mg ion in black, AMPCPP and AMP in yellow, and HP and HPPP in green). The relative energies of the various states should not be inferred from the diagram (Jaroslaw Blaszczyk et al. Structure 12:467-475, 2004. PubMed: 15016362).
|
__label__pos
| 0.56359 |
Importance of Diet on Health!!
A diet, rather a balanced diet is defined as the dietary habit, which provides all the necessary nutrients to the body of the individuals. To derive the correct amount of nutrition and keep the body healthy, it is extremely essential to maintain a balanced diet. A balanced diet generally comprises fresh fruits and vegetables, legumes, whole grains, lean proteins, nuts and many more. We shall discuss the importance of diet on health in detail here.
Importance of Diet on Health
Sources of Balanced Diet
Let’s start with the sources of balanced diet first. The first and foremost think to remember is that the sources of the daily calories consumed is as important as the quantity of the calories consumed. Thus, avoid consuming the products, which have no nutritional value or give “empty calories.” The balanced diet is generally high in minerals, vitamins, proteins, carbohydrates and useful fats and low in sugars and unhealthy fats. Spinach, green beans, kale, broccoli, cabbage, carrots, cauliflower, ladies finger, beans, capsicum are some of the useful vegetables to be included in the dietary regime. Whole grains are yet another important sources of balanced diet. Low-fat, lean meat like that of the fish, pork, chicken, beef along with the peas, lentils, almonds, walnuts, sunflower seeds and other soy based products are some important sources of proteins. These help in reducing the quantity of bad cholesterol and enhancing the level of good cholesterol in the blood of the individuals. Next in the list of the balanced diet are the dairy products. These have a high quantity of Vitamin D, calcium and are low in the fat content as well. Milks from almonds, soyseeds are very nutritious and can act as a healthy alternative to the dairy products as well. Opt for olive oil and eliminating the vegetable oils from the diet. Thus, these sources of balanced diet play a crucial role in providing the body with the essential and important nutrients. Also, these aid in giving a healthy life.
Apart from these sources, it is highly advised that every individual must reduce the level of consumption of alcohol, solid and trans fats, sugar, salt and solid grains to a huge extent.
We have heard people talking about maintaining a healthy diet. Here we have learnt about what is a healthy balanced diet and how to derive it from the food products. But, the main topic is why should we consume healthy diet? Or, what is the importance of diet on health?
Importance of Diet on Health
Here are the various reasons for maintaining a healthy diet.
1. A Healthy Diet Keeps the Body Energetic and Active
A balanced diet provides proper nourishment to the tissues, muscles and organs extensively. If the body gets deprived of proper quality and quantity of food, it becomes prone to infection, chronic diseases, fatigue and tiredness. The efficiency and performance of the body deteriorate. People face the complication of development and growth significantly. And, this has an adverse impact on the body, on the whole.
1. An Unhealthy Diet leads to Obesity, Hyper tension
One critical complication of unhealthy diet is obesity. The human body gets filled up with too much quantities of unhealthy fats. The good amount of cholesterol and healthy fats don’t really exist in their body. And, too much accumulation of unhealthy fats in the body often gives rise to several chronic disorders like hypertension, stroke, high blood pressure and many more.
1. A Balanced Diet helps in eliminating Diabetes
Diabetes is yet another dangerous complication. It is a severe metabolic disorder, which occurs mainly due to hormonal imbalance. Thus, consumption of proper quantity of balanced diet helps in maintaining the hormonal level and avoid the occurrence of diabetes to a huge extent.
1. The Healthy Diet helps to avoid the chronic disorders
The only way to avoids the occurrence of the chronic disorders in consumption of right quantity of nutrients like proteins, carbs, fats and vitamins and essential minerals. This consumption helps to eradicate the chronic disorders from the body and aids to lead a healthy and happy life.
Apart from these, a good diet habit helps in maintaining a healthy weight, reducing the risk of osteo-porosis and certain type of cancers. Thus, these are the importance of diet on health. Stay healthy, strong, fit and active all throughout your life.
Disclaimer:-
For specific treatment, always consult an Ayurveda expert!
This article is not a substitute to the standard Medical Diagnosis or personalized Ayurvedic Treatment!
It is intended only for Information!
For experts consultation please write us at [email protected]
3,103 total views, 1 views today
Leave a Reply
Your email address will not be published. Required fields are marked *
|
__label__pos
| 0.890722 |
Majorana or Dirac Neutrino Masses?
Small finite Majorana masses assume very heavy mass scale symmetry, considered in mainstream theories, but the predicted values of light neutrino masses from the necessary see-saw mechanism are uncertain.
Normal 0 MicrosoftInternetExplorer4
In the framework of the flavor-geometric semi-empirical phenomenology of Standard Model particle mass and mixing hierarchies (arXiv:1212.1417) small finite Dirac masses assume zero scale of smallest neutrino mass, probably from new symmetry, with definite values of light neutrino masses that follow from solar and atmospheric mass squared differences: m1 = ~ 0, m2 = ~9 x10^-3 eV, m3 = ~ 5 x10^-2 eV. The mass hierarchy of that neutrino mass pattern, m2 /m1 >>1, m3 /m2 = ~ 6, is similar to the known Dirac mass hierarchies of charged leptons, m(muon)/m(electron) = ~ 200, m(tau) /m(muon) = ~ 17, and quarks. That special statement is suggested by the obtained in the mentioned arXiv-research new interesting unexpected result that all SM hierarchies may be characterized by defined ‘mass hierarchy angles’ of nearly universal form including all Dirac particle masses and neutrino mixing angles. So, Dirac neutrino mass pattern is a probable explanation.
Thus the question in title above may be answered by coming accurate experimental data on neutrino mass hierarchy of the masses m1 and m2. Data indication m1 << m2 means likely Dirac neutrinos, while near degenerate masses m1= ~ m2 means likely Majorana neutrinos. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman";}
|
__label__pos
| 0.985929 |
Convert to
1 hundred cubic foot per second (100 ft3/sec) = 10,194,064,773.15 cubic centimeters per hour (cm3/hr)
Filed under: Main menuflow menuHundred cubic feet per second conversion
Advertisements
Specific hundred cubic foot per second to cubic centimeter per hour Conversion Results
Enter a New hundred cubic foot per second Amount to Convert From
* Whole number, decimal or fraction ie: 6, 5.33, 17 3/8
* Precision is how many digits after decimal point 1 - 9
Enter Amount :
Decimal Precision :
Advertisements
Convert hundred cubic foot per second (100 ft3/sec) versus cubic centimeters per hour (cm3/hr)
in swapped opposite direction
from cubic centimeters per hour to hundred cubic feet per second
Or use utilized converter page with the
flow multi-units converter
conversion result for two
flow units:
From unit
Symbol
Equals ResultTo unit
Symbol
1 hundred cubic foot per second 100 ft3/sec = 10,194,064,773.15 cubic centimeters per hour cm3/hr
flow converter
What is the international acronym for each of these two flow units?
Prefix or symbol for hundred cubic foot per second is: 100 ft3/sec
Prefix or symbol for cubic centimeter per hour is: cm3/hr
Technical units conversion tool for flow measures. Exchange reading in hundred cubic feet per second unit 100 ft3/sec into cubic centimeters per hour unit cm3/hr as in an equivalent measurement result (two different units but the same identical physical total value, which is also equal to their proportional parts when divided or multiplied).
One hundred cubic foot per second converted into cubic centimeter per hour equals = 10,194,064,773.15 cm3/hr
1 100 ft3/sec = 10,194,064,773.15 cm3/hr
Find pages on convert to with online Google Custom Search
How many cubic centimeters per hour are contained in one hundred cubic foot per second? To link to this flow - hundred cubic foot per second to cubic centimeters per hour units converter, only cut and paste the following code into your html.
The link will appear on your page as: on the web units converter from hundred cubic foot per second (100 ft3/sec) to cubic centimeters per hour (cm3/hr)
Online hundred cubic feet per second to cubic centimeters per hour conversion calculator | convert-to.com units converters © Privacy Policy
|
__label__pos
| 0.864713 |
How Much Does it Cost to Fix a Gas Gauge? [2021 Updated]
After filling up your car, you may notice the gauge shows empty or you may notice that it switches from empty to full after driving for a long time. You may receive inconsistent results at times. It will be necessary to fix your gauge if it starts acting up. The majority of people don’t get what it costs properly.
There is all the information you need about the fuel gauge sender in this article, for the current year 2021, estimates of what it will cost to replace it on different kinds of vehicles.
how much does it cost to fix a gas gauge
How Much Does it Cost to Fix a Gas Gauge
How Much Does it Cost to Fix a Gas Gauge?
There are some major components of the gas gauge. Like gas sensor, gauge sender, fuse, and fuel gauge. If anything happens to them you will see the problem in the overall system. So it’s important to know their repairing cost.
In general, the cost of replacing a fuel gauge sender ranges between $250 and $800 for parts and labor, according to the 2021 auto market data. An Auto shop will also charge the same. For many fuel gauge sender replacements, labor is the primary component of the cost. In addition to the price of the fuel gauge sender, the make and model of your vehicle also influence the cost.
Gas gauges cost a dependable amount to fix. This article will provide you with a guideline on how much to fix a gas gauge if you’re looking for the exact cost. By reading this article, you’ll get rid of the worry line in your head.
Gas Gauge Repair Cost Summary
According to the 2021 estimates, the total cost of fixing or repairing a gas gauge is listed below (including the labor’s charge)
Type of RepairPrice Range
Fuse Replacement$10-20
Gauge Sender Cost$250-$800
Fuel Sensor Cost$280- 330
Labor Cost$180-$230
How Much Does it Cost to Replace a Fuel Sensor?
According to 2021 estimates, it costs between $280 and $330 on average to replace a fuel tank pressure sensor. The estimated labor costs are between $180 and $230, while the estimated parts cost is $100. There is no tax or fee included in the estimate.
Related: How Much Does it Cost to Fix or Replace a Car Side Mirror?
How Much Does it Cost to Replace the Fuel Gauge Fuse?
The average cost of replacing a fuse is between $10 and $20, but some specialty fuses may cost upwards of $100.
This cost may vary based on the model of the car. This is very inexpensive and easy to do on your own. Here’s some other fuel gauge-related parts cost.
Parts NamePrice Range
Mass Airflow Sensor$240-$260
Gas Temperature Actuator$40-$60
Fuel Level Sensor$120-$140
Throttle Position Sensor$55-$75
Exhaust Gas Recirculation Valve$150-170
Timing belt replacement$180-$200
Fuel Injector$220-$250
Spark plug replacements$40-$60
Fuel filters$80-$100
Related: How Much Does it Cost to Replace a Headlight Bulb?
How Much Does it Cost to Replace Fuel Gauge Sender?
Usually, the fuel gauge sender is the culprit. It is a bit expensive to repair, and most of the costs are related to labor. A fuel gauge sender typically costs between $250 and $800. If you feel comfortable replacing this part yourself, you can save a lot of money.
Related: How Much Does it Cost to Replace a Car Hood?
Should I Replace the Fuel Gauge Myself or Hire a Professional?
You may install some of your automobile parts but the fuel gauge is different. There’s some critical task you have to perform. So you need some experience in installing gas gauges.
So doing it all by yourself isn’t a good option if you never do it before. You may damage the parts too. On the other hand, If you choose auto shops or hire a professional they will finish the job perfectly. Though the cost of labor may hurt you a bit, it will be risk-free. So, hiring a professional is the best option to choose.
Related: How Much Does it Cost to Fix a Tail Light?
How Do You Know if Your Gas Gauge is Broken?
When there’s some problem in your gas gauge you will notice some sign. First, you’ll see that your fuel gauge is but after some driving it goes to full. And all the day you’ll notice that your tank is full. The inconsistent behavior will frustrate you because you don’t get the exact result. So there are mainly three symptoms you’ll notice. They are:
• Showing inconsistent result
• Sometimes it shows there is no fuel in the tank.
• Sometimes it shows there is full fuel in the tank.
Related: How Much Does it Cost to Replace a Seat Belt?
How Do You Replace a Fuel Gauge Sending Unit?
If you diagnosed that the fuel gauge sender was faulty, it is now time to replace it. Many people learned how to replace their vehicle fuel gauge sender themselves to save money on labor costs.
It is extremely important that you are confident that you can replace it yourself without causing any damage. Unless stated in the post, we do not suggest you try DIYs the first time. As a result, you do not want to test and experience your car, especially if it is expensive.
Instead of replacing the fuel gauge sender, we will replace the entire gauge unit in this section. You can replace the fuel gauge unit by following these steps:
• First, you need to locate the fuel sender unit.
• After locating the main unit, you need to release any pressure in the fuel tank. It is important to follow the owner’s manual’s instructions on releasing the pressure.
• Ensure that all electrical connections to the fuel tank are disconnected before performing any repairs.
• You should make sure you have cleaned any contamination around your plug area within your fuel tank using a clean towel.
• If there is a retaining ring, you can use a nonferrous towel to get it out.
• Disconnect the old fuel sending unit with its gasket and O ring.
• You should compare the new fuel sending units with the old ones before installing them. The owner’s manual of your vehicle can also provide you with details on how to install the sending unit.
• Set up the new gasket and O-ring on the sending unit. Gaskets mounted on tanks and sending units must be perfectly aligned.
• If your vehicle does not have a retaining ring, follow the instructions in your owner’s manual.
• If you had previously disconnected the electrical wiring from the fuel tank, reconnect it
• Test your vehicle to determine if there are any symptoms of a fault with the fuel gauge sending unit
Related: How Much Does it Cost to Replace a Headlight Assembly?
How Important is to Take a Service?
It is pretty damn annoying to drive a car without a functioning fuel gauge. You will likely be stranded more than once if you do not take your gas tank measure seriously. Your next trip to the gas station will be a lot more difficult if this is not replaced before your next trip. Fuel information is not accurate, so you don’t know how much to buy.
In case you’re running late and you find that your gas tank is full. However, your fuel ran out while you were on the highway. It is very frustrating to be faced with a serious problem. If you want to get rid of these problems, you need to solve them as soon as possible.
Related: How Much Does it Cost to Fix an Oil Leak?
How to Reset a Fuel Gauge?
Reset a fuel gauge is very easy. You need to follow some simple steps. In the beginning, the ignition switch needs to be turned on. If the odometer has not entered ODO mode yet, press the Odo/Trip button until it does. It is then time to turn off your ignition. After that, press and hold the Odo/Trip button. Finally, you just need to release the Odo/Trip button.
Related: How Much Does it Cost to Install Air Ride?
Self-Testing Your Gas Gauge: Easy Ways to Fix 2021
These simple 5 tricks will allow you to diagnose problems with your gas gauge without needing a professional. It is possible to diagnose a few issues on your own because cars are constructed so well. Check the following for gas gauge problems in your car:
1. Diagnostics
You can usually run diagnostics on your car. If the vehicle you own was built within the last 10-20 years, you may find the instrument cluster self-test procedure in your owner’s manual. Holding down the odometer during a start will usually accomplish this goal.
This procedure is used to test the dashboard gauges and lights. In the test, the fuel gauge should rise and fall continuously. You can be sure something is wrong if the needle on the fuel gauge does not move. Otherwise, move on to fuses.
Related: How Much Does it Cost to Install a Supercharger a Car?
2. Fuses
The first thing you should do is find out all the fuse boxes. The test can help you detect any faulty fuses and help you replace them. In that case, you should cross it off your list and continue testing to sending the unit.
Related: How Much Does it Cost to Paint Rims Matte Black?
3. Sending Unit
The most common issue is not one you can easily test for. To check your vehicle’s resistance you will need a tool (a multimeter) and know the vehicle’s normal resistance. In case you’re handy, you can do it yourself. If not, you might need to hire a mechanic.
Related: How Much Does it Cost to Paint a Car Hood?
4. Keep Your Gas Gauge Working Properly
Test out your gas gauge when you notice strange fluctuations. Once you’ve determined the cause of the issue, you can figure out what needs to be done or how much it will cost.
Rather than guess what’s wrong with your vehicle, it’s best to find out. Make sure you understand your gauge and the average cost in your area to keep you from getting any costly surprises.
Related: How Much Does it Cost to Install Subwoofers and Amp in Car?
5. How do you fix an inaccurate gas gauge?
Take the cable off the terminal on the sender and ground it to the chassis. Unless the sender is grounded or faulty, the gauge will now read empty. To test the sending unit terminal on the dash gauge, touch a grounding lead to it.
Related: How Much Does it Cost to Paint a Bumper?
I’m now answering the most commonly asked questions about (Gas Gauge Rapair): FAQs
What is a fuel gauge sender?
What makes your car know when it’s full or empty? Thanks to the fuel gauge sender. You will find a resistor in the fuel tank of your car, which measures electrical flow. By sending current to the fuel gauge, you can determine how much gas is left in the tank based on pressure. Afterward, you can read your dash and determine how long you have to go until your next fill-up.
How does a fuel gauge work diagram?
The sending unit of the car is found in the fuel tank. With a thin, rigid metal rod connected to afloat, which is usually made of foam. Rod ends are mounted with variable resistors. Through this strip of material, the wiper connecting the gauge conducts the current from the gauge to the resistor.
Can the fuel gauge be fixed?
Check the fuel gauge after disconnecting the wiring from the fuel sending unit. A faulty fuel gauge will give you an empty reading. This should be replaced immediately. It is recommended to replace the sending unit if you receive a full reading from the gauge.
Where is the fuel level sensor located?
Senders for fuel gauges are located in the fuel tank and attached to the fuel pump. There is a rod and a float attached to the sender’s base.
How does a fuel level sensor work?
In reality, the level sensor in a vehicle’s fuel tank is composed of three components: an afloat, an actuating rod, and a resistor. An electronic device or a little black box triggers the fuel gauge using a variable signal sent by this combination of components.
What happens when a fuel sensor goes bad?
A decrease in acceleration power may be caused by the fuel pressure sensor when you step on the gas pedal. This sensor will interfere with the air-fuel ratio if it is bad. While driving, you will lose power from your car.
Can you drive with a broken gas gauge?
Of course, you can. Gas gauges can easily break, even though they do not disable your engine or affect your car’s performance. Because of this, you’ll have to leave your car stranded on the side of the road, or walk to the gas station.
Does the fuel pump affect the gas gauge?
If the actual fuel level is low, sediments will be picked up by the fuel pump, which can clog the fuel filter, fuel injectors, or high-pressure fuel pump. Identifying the source of your gas fuel gauge’s malfunction is vital before planning a repair.
Why is my fuel gauge stuck on full?
An empty fuel gauge can be caused by a faulty fuel gauge resistor that sends full voltage to the fuel gauge at all times. When a vehicle regularly uses fuel, the fuel sending unit is constantly in motion, which causes the wiper in the variable resistor to move constantly as well.
How do you check gas without a gauge?
Disconnect the electrical connector on top of the gas tank (it’s located on the top). You can measure the resistance of the Fuel Level Sensor (it’s the terminal for the car’s Yellow wiring that runs to the fuel gauge, you say doesn’t work). It is 95 ohms when the battery is empty, 33 ohms when the battery is mid-range, and 7 ohms when the battery is full.
Can I Change My Bad Fuel Gauge?
Of course but you need some experience. If you never have done it before then our suggestion is not to do that by yourself.
You can reduce your parts and labor costs with this guide to repairing a gas gauge. We would appreciate any feedback you have about the gas gauge fixing. Keep reading to learn more about the car parts, fuel gauge, and other related information.
You may also enjoy reading:
How Much Does it Cost to Paint Rims?
How Much Does it Cost to Buff Out a Scratch in a Car?
How Much Does it Cost to Paint a Bumper Cover?
How Much Does it Cost to Bore an Engine & Cylinder?
How Much Does it Cost to Straight Pipe a Car?
Leave a Comment
Your email address will not be published. Required fields are marked *
Scroll to Top
|
__label__pos
| 0.997072 |
conference logo
Playlist "DjangoCon Europe 2018"
Can packaging improve Django deployments?
Markus Zapke-Gründemann
How can packaging Django projects make deployments easier, faster and more reliable?
Deployments of Django projects can be a challenging task. Beside the Python source code itself you usually have to handle a lot of other stuff:
* Installing Python dependencies
* Shipping JavaScript code and installing it's dependencies
* Compiling SCSS to CSS
* Collecting static files
* Building documentation
* Compiling translations
* …
And of course you want a deployment approach that is independent of a specific hosting solution.
Also you have to think about the scalability of your deployment when the number of servers you operate increases.
This usually means that `git pull` is not the best way to deal with these tasks.
So I will discuss different ways to package your Django project like
* Wheels
* JavaScript packages
* Operating system packages
* Containers
Some of these concepts will hopefully help you to make your deployment process easier, faster and more reliable.
|
__label__pos
| 0.886901 |
Ecology
Mangrove Ecology
Healthy mangrove forests are key to a healthy marine ecology. Fallen leaves and branches from mangroves contribute to the forest detritus and provide nutrients for the marine environment. Intricate food webs of immense varieties of sea life are supported directly through this detritus.
Mangroves are a critical forest ecosystem, dominating coastlines in tropical and subtropical regions of the globe. There are 54-75 species of true mangroves, which are found only in the intertidal zones of coasts, and are taxonomically isolated from terrestrial counterparts. They are highly adapted to their environment, capable of excluding or expelling salt, allowing mangroves to thrive in highly saline waters and soils. Salinity can still limit the distribution of mangroves, however, as can other environmental factors such as climate, tidal fluctuation, and sediment and wave energy. Mangroves are found worldwide, but the greatest species diversity is in Southeast Asia, with only twelve species inhabiting New World countries, and only four of those are found in the United States along the southern coast.
Refuge and nursery grounds
Main_ImageMany threatened and endangered species are native to mangrove forests, which provide critical habitat for diverse marine and terrestrial flora and fauna, such as:
• manatees
• crab-eating monkeys
• fishing cats
• monitor lizards
• sea turtles
• Royal Bengal tigers
• mud-skipper fish
Mangrove forests also provide refuge and nursery grounds for juvenile fish, crabs, shrimps, mollusks, and other invertebrates.
Mangroves are prime nesting and migratory resting and feeding sites for hundreds of bird species. In Belize, there are over 500 species of birds recorded in mangrove areas.
Mangrove Habitat and Growth
interier-mangrove-(Stanislav-Lhota)Mangrove distribution is primarily determined by sea level and its fluctuations. Other secondary factors are: air temperature, salinity, ocean currents, storms, shore slope, and soil substrate. Most mangroves live on muddy soils, but they also can grow on sand, peat, and coral rock.
Zonation often characterizes mangrove forests. Certain species occupy particular areas, or niches, within the ecosystem. Some mangrove species occur close to shores, fringing islands, and sheltered bays; others are found further inland, in estuaries influenced by tidal action.
Mangroves vary in height according to species and environment, from mere shrubs to 40 meter (app. 131 feet) tall trees. The prop roots of some mangrove species, such as Rhizophora spp., or red mangrove, and the pneumataphores (unique breathing roots) of others, such as Avicennia spp., or black mangrove, contain many small “breathing” pores, called “lenticels.” These allow oxygen to diffuse into the plant and down to the underground roots by means of air space tissue in the cortex, called “aerenchyma.” The lenticels are inactive during high tide.
Lenticels in the exposed portions of mangrove roots are highly susceptible to clogging by crude oil and other pollutants, attacks by parasites, and prolonged flooding from artificial dikes or causeways. Over time, environmental stress can kill large numbers of mangrove trees.
Evolutionary adjustments to varying coastal marine environments have produced some astounding biological characteristics within mangrove plant communities. Certain species of mangroves exclude salt from their systems, others actually excrete the salt they take in via their leaves, roots, or branches. In species that exclude salt, the mangrove root system is so effective in filtering out salt that a thirsty traveler could drink fresh water from a cut root, though the tree itself stands in saline soil.
Mangrove Reproduction
ecologyCertain mangrove species can propagate successfully in a marine environment because of special adaptations. Embryo germination begins on the tree itself, a process called “viviparity.” The tree later drops its developed embryos, called propagules, which may take root in the soil beneath. Viviparity may have evolved as an adaptive mechanism to prepare the propagules for long-distance dispersal, and survival and growth within a harsh saline environment. During this viviparous development, the propagules are nourished on the parent tree, thus accumulating the carbohydrates and other compounds required for later autonomous growth.
Propagules may float for extended periods (depending on the species), up to a year, and still remain viable. Viviparity and the long-lived propagules allow mangrove species to disperse over wide areas.
Mangrove Ecology Workshop Manual (Feller & Sitnik editors, pdf 1.23 MB)
The Mangrove Ecosystem
mangrovesneedrescueMangroves are a critical forest ecosystem, dominating coastlines in tropical and subtropical regions of the globe. There are 54-75 species of true mangroves, which are found only in the intertidal zones of coasts, and are taxonomically isolated from terrestrial counterparts. They are highly adapted to their environment, capable of excluding or expelling salt, allowing mangroves to thrive in highly saline waters and soils. Salinity can still limit the distribution of mangroves, however, as can other environmental factors such as climate, tidal fluctuation, and sediment and wave energy. Mangroves are found worldwide, but the greatest species diversity is in Southeast Asia, with only twelve species inhabiting New World countries, and only four of those are found in the United States along the southern coast.
Spatial variation, or zonation, is a common trait for mangrove forests both horizontally and vertically. Certain species are found in monospecific bands parallel to the shore or in mosaics; however, patterns of distribution vary with location, both locally and regionally. There are many hypotheses about how and why zonation occurs, but no consensus has been reached. Interspecific variation is also quite high; mangrove height ranges from only a few feet to over one hundred feet and species exhibit different adaptations to salinity.
Recent research has also indicated that mangroves are incredible carbon sinks, sequestering more carbon than any of their terrestrial counterparts. Mangrove forests sequester approximately 1.5 metric tons/hectare/yr of carbon, or 3.7 lbs/acre/day of carbon (1336 lbs/acre/yr). Mangrove substrate may contain 20-25% carbon, which may also help explain the high productivity and biodiversity of these ecosystems.
Follow the link for a comprehensive list of mangrove species found in Florida
Origin of mangroves…
Origin-of-Mangroves-box
Scientists theorize that the earliest mangrove species originated in the Indo-Malayan region, where there are far more mangrove
Read more
Why an Ecotone is not…
Why-an-Ecotone-imagebox
An ecotone is usually a transitional feature [without permanent "identity" (it is like a mixing zone)], whereas mangroves are stable
Read more
When Salt Flats by Any Other…
when-salts-box
Salinas, salt flats, coastal sabkhas, apicuns, and albinas are all names for the same geomorphic features. They are upper intertidal lands
Read more
Endangered Species
Endangered-species-box
The IUCN Red List of Endangered Species lists most flora and fauna into seven categories ranging from “Least Concern” to “Extinct”.
Read more
|
__label__pos
| 0.812626 |
Database Deployments in Uncontrolled Environments
The ideal is to make a change and see that change deployed to production, in a perfect world we would be told to work on something, write the code + tests, deploy to a test environment, prove it works and deploy - this is the cycle time and the faster you can get this the easier many things become.
The cycle time is easy to measure - it is the time the ticket arrives in the backlog to the time it moves to the done column, if your issue tracking system can't tell you this easily then use something else! The tickets are moved into the “Done” state when they have been deployed into production - if you do nothing but investigate and try to reduce your cycle time you will make a massive difference to your development process.
There have been a few discussions on stack overflow recently about how to manage deployments in uncontrolled environments, specifically data migrations. The questions were from an SSDT perspective, I don't think that SSDT is a great choice for these uncontrolled environments and there are some additional requirements for these uncontrolled environments that need some additional thought and care when creating release scripts (whether manually or using a tool).
What is an uncontrolled environment?
I define it as a database that is managed by a customer, typically a vendor sells a product and it includes a database. The database is on a customer server and the customer is sysadmin and can make changes.There is a difference to databases where customers are allowed to make changes and ones where they are not allowed - but in either case you still need to take extra care, even if it is only to add additional logging and warnings to the output so any upgrade scripts help your support diagnose issues rather than displaying an error like “DBUpdate Error” - yes I have seen that with a vendor product once!
When you own and manage the deployment for your database application you can do these things because you can take for granted:
You can
Because
Drop objects not in source code
If it isn't in your source it does not exist
Rely on scripts generated / created by your dev team
If someone wants to create an object called X they can see if an object called X already exists or not
Ensure each deployment happens successfully
Run each deployment, run tests and verify the results
Write data migration scripts using accurate data
You have the data
Use truncate on tables to clear data
The script author knows there are not any foreign keys pointing to the table and that the data can be restored by backup rather than a transactopn
If you do not control the environment then you cannot do these things because:
You can not
Because
Drop objects not in source code
Who knows what the user has changed
Rely on scripts generated / created by your dev team
Users may have made non compatible changes, you want to create a new view called “users_blah”? Well it turns out they have a audit stored procedure called users_blah
Ensure each deployment happens successfully
Run each deployment, run tests and verify the results
Write data migration scripts using accurate data
You have the data
Drop objects not in source code
If it isn't in your source it does not exist
Use truncate on tables to clear data
The script author does not know there are not any foreign keys pointing to the table and that the data can be restored by backup
So what can we do?
I really don't think that there is a 1-sized fits all solution here so you will need to look at your database and what changes you need to make but some randomish thoughts are:
• Compare / Merge type deployments will drop any changes the customer has made - that is bad
• If you had each version of the source, you could verify whether there have been any changes before deploying - that sounds good but potentially a support nightmare
• The migrations approach sounds better but you need to ensure that every change is actually deployed
• Adding additional logging and verification code is a must, instead of “truncate table” then “print truncating, check for things that will block this, truncate” - making sure that a un-reversable command like truncate has forced the user to backup or at least make sure the users understand that they need a back (even in 2016 this isn't guaranteed!)
• Taking simple precautions like not using “select *” and using column lists and “order by column” rather than “order by ordinal” will help you in the long run with odd issues that will be hard to disagnose!
I guess the end answer is to offer a hosted solution and move to continuous deployment in a controlled environment as that actually makes a lot of these things simpler!
|
__label__pos
| 0.844151 |
Select Page
Broken Heart Syndrome: Meaning & Explanation
Broken Heart Syndrome: Meaning & Explanation
What Is Broken Heart Syndrome? A heart that is literally broken… it is possible. When we talk about heartbreak, we often speak of a proverbial broken heart, but did you know that you can actually suffer from broken heart syndrome in a stressful event? Broken heart syndrome is a disease of the heart that is very similar in symptoms to a heart attack. Read along…
What Is Broken Heart Syndrome?
Broken heart syndrome is an acute heart disease that usually recovers well. This syndrome was first investigated by Japanese doctors in the 1990s. They called this phenomenon Tako-Tsubo cardiomyopathy.
It is a disease that arises spontaneously with a very strong emotion. This can be a shock reaction or a reaction to excessive grief, but it can also be based on positive emotions such as the euphoria that one feels at a victory.
The heart muscle is temporarily severely weakened in broken heart syndrome, so that it cannot function properly.
Broken heart syndrome: the symptoms
The symptoms of broken heart syndrome are often confused with those of a heart attack. About 5% of people admitted to hospital for suspected heart attack actually suffer from broken heart syndrome.
The symptoms of this syndrome include chest pain, shortness of breath and palpitations. In contrast to a myocardial infarction, the heart muscle is not permanently damaged and healing is possible in the short term.
What happens in broken heart syndrome?
Little research has been done on the mechanism behind broken heart syndrome. It is assumed that a large amount of stress hormone is released in the blood as a result of high emotions.
These stress hormones can directly affect the heart muscle causing it to stiffen. Because the heart continues to pump, but the flexibility of the ventricle is disturbed, the heart bulges.
It is possible that broken heart syndrome only occurs in people who are extra sensitive to stress hormones or suffer from some other physical or psychological disorder.
What Causes Broken Heart Syndrome?
Broken heart syndrome is caused by an event that causes emotions to run high. Examples of such a situation are an unexpected death in the family, the loss of a relationship, the loss of a job, a natural disaster or a happy event such as a victory.
In addition, broken heart syndrome can also be caused by a physical event such as a brain haemorrhage or an epileptic seizure. Finally, broken heart syndrome can also develop as a result of certain medications or drugs.
It is striking that the symptoms occur directly as a result of the emotional event, the physical event or the drug intake.
Who Gets Broken Heart Syndrome?
In practice, most people who suffer from broken heart syndrome have been found to be women. One in ten women who visit a hospital because of symptoms suggestive of a heart attack eventually turn out to have broken heart syndrome.
Women who have passed menopause, in particular, seem to have a higher risk of broken heart syndrome. Women may become more sensitive to the stress hormone at a later age due to a drop in the hormone estrogen.
Another explanation may lie in the physical development of the heart in men. It could be that a man’s heart is better prepared for an increased supply of the stress hormone so that this does not lead to broken heart syndrome.
How is the diagnosis made?
Various examinations are carried out in the hospital to rule out the possibility of a heart attack. A heart trace and a blood test are performed as standard to visualize the activity of the heart.
An X-ray, an ultrasound, a coronary angiogram and an MRI scan can also be part of the examination. Images will quickly show that the heart is distended in the typical way known in broken heart syndrome.
In case of a heart attack, narrowing should be visible in the coronary arteries. This is not the case with broken heart syndrome.
Can you die from broken heart syndrome?
Unlike a heart attack, broken heart syndrome does not have permanent consequences for the heart in most cases. Patients almost always recover within a few days.
Moreover, the chance of a recurrence of the complaints is small, while a heart attack can always follow more heart attacks. However, broken heart syndrome can be dangerous because of complications. About one in five patients will have:
• Cardiogenic shock due to low blood pressure
• Fluid in the lungs
• Blood clots
• Cardiac arrhythmias
Since the complications of the broken heart syndrome can lead to life-threatening situations, the patient is kept under hospital supervision for the first few days.
As a result of broken heart syndrome, patients may be more likely to have a brain haemorrhage or stroke. The risk of dying as a result of broken heart syndrome is estimated by the specialists at 1%.
What is the treatment for broken heart syndrome like?
The treatment of broken heart syndrome consists of administering drugs to restore normal function of the heart muscle, such as ACE inhibitors and beta blockers.
In addition, anticoagulants are usually prescribed to prevent blood clots from forming. If complications arise, they must also be treated with medication. Recovery from broken heart syndrome usually takes only a few days.
Life after broken heart syndrome
For most people, the mental consequences of broken heart syndrome will outweigh the physical consequences. The heart usually makes a full recovery.
The most important thing is to avoid stressful situations after broken heart syndrome. In addition, it may be necessary to keep taking beta-blockers if the heart function does not want to fully recover. It is possible to participate in a rehabilitation program for cardiac patients to improve cardiac function under supervision.
About The Author
Rubin
Hello! Thanks for reading these articles. My intention is to make happiness as simple and clear as posssible. By the way, excuse my English. I am not a native English speaker since I live in Amsterdam. Much appreciated if you use the comments to make suggestions on my grammar. See ya in another blogpost!
Leave a reply
Your email address will not be published. Required fields are marked *
|
__label__pos
| 0.967657 |
In a previous post we learned how to use data in CSV and DSV format. Recently we can also include tab separated values (TSV) in a Asciidoctor table. We must set the table attribute format to the value tsv. The data can be inside the document, but also defined in an external file which we add with the include macro.
In the following example markup we have a table with inline tab separated values. A second table includes an external file with tab delimited values:
= Tables
Using the `format` attribute value `tsv` we can
use tab-delimited data for table data.
== TSV table
[format=tsv, options="header"]
|===
Writing tools Awesomeness
Asciidoctor Oh yeah!
MS Word No!
|===
== Table with external data
// We have an external file with
// tab-delimited values.
[%header,format=tsv]
|===
Unresolved directive in - include::tools.tsv[]
|===
When we convert our Asciidoctor markup to HTML we get the following result:
tsv tables
Written with Asciidoctor 1.5.6.1.
shadow-left
|
__label__pos
| 0.939482 |
How many sets of dumbbell rows should I do?
Are dumbbell rows effective?
By building your upper-body strength, the dumbbell row is one of the best exercises for improving your posture. Dumbbell rows involve a wide range of motion. The dumbbell row allows for a greater range of motion than the traditional barbell row, enhancing your shoulder and elbow mobility.
How many reps should I do for rows?
Barbell rows often work best in moderate-to-high rep ranges, somewhere in the neighbourhood of 8–20 reps, with 15 reps per set being a good default. Some people with solid lower backs can benefit from going as low as 5 reps per set, though.
Is 3 sets enough to build muscle?
Three sets are not enough to build muscle. Increasing the number of sets of each exercise, even while only performing 10 reps, can build muscle because you will be pushing your muscles to fatigue because they are under tension longer. Don’t stop at 3 sets but complete 4 or 6 or 8.
Are dumbell rows as effective as barbell rows?
If your goal is to lift as much weight as possible to be the strongest you can, we recommend that you go with the barbell row. The barbell row will allow you to load the most weight and engage both sides of your body, which will get you stronger than the dumbbell row overall.
IT MEANS: Does Total Body Enhancement make you lose weight?
Are 2 sets enough?
Some trainers recommend doing anywhere from three to five strength-training sets for maximum muscle gain, while others say that one set per exercise is just as good as two or more. … If you’re really going for strength gains, muscle endurance, and muscle growth, multiple sets have an advantage.
Is 5 sets of 12 reps good?
TO RECAP, aim for 3-5 sets in the following rep rangers per exercise based on your goals: Endurance: 12+ reps per set. Hypertrophy (bigger muscles): 6-12 reps per set. Strength (dense, powerful muscle): 1-5 reps per set.
How many times is 3 sets?
A set is a group of repetitions (an example would be 3 sets of 12 repetitions).
Is 3 sets better than 4 sets?
Do 3 Sets of Each Exercise
The truth: There’s nothing wrong with—or magical about—doing three sets. But the number of sets you perform shouldn’t be determined by a 50-year-old default recommendation. Here’s a rule of thumb: The more repetitions of an exercise you do, the fewer sets you should perform, and vice versa.
Is 3 sets of 20 reps good?
So, How Many Reps to Build Muscle? Doing around 6–20 reps per set is usually best for building muscle, with some experts going as wide as 5–30 or even 4–40 reps per set. For bigger lifts, 6–10 reps often works best. For smaller lifts, 12–20 reps often works better.
What are 3 common mistakes made while performing the dumbbell row?
5 Dumbbell Row Mistakes That Make Back Workouts Less Effective
• You Arch Your Lower Back. When it comes to row mistakes, this one is undeniably the most common. …
• You Don’t Keep Your Neck Aligned With Your Spine. …
• You Rely on Your Biceps. …
• You Swing Your Arm Using Momentum. …
• You Don’t Bend Over Enough.
IT MEANS: Quick Answer: What are the benefits of aerobic and anaerobic exercise?
How do I keep my dumbbell rows straight back?
Put your left leg on the bench and grab the far side with your left hand, then bend over so your upper body is parallel with the ground. Reach down and pick up the dumbbell in your right hand with a neutral grip (palm facing you), then hold it with your arm extended, keeping your back straight.
|
__label__pos
| 0.999778 |
What is Principal Component Analysis in the StatsModels library?
The following recipe explains what is Principal Component Analysis in the StatsModels library.
Recipe Objective - What is Principal Component Analysis in the StatsModels library?
PCA is Principal Component Analysis. It belongs to the class statsmodels.multivariate.pca.PCA(data, ncomp=None, standardize=True, demean=True, normalize=True, gls=False, weights=None, method='svd', missing=None, tol=5e-08, max_iter=1000, tol_em=5e-08, max_em_iter=100, svd_full_matrices=False)
For more related projects -
https://www.projectpro.io/projects/data-science-projects/deep-learning-projects
https://www.projectpro.io/projects/data-science-projects/deep-learning-projects
Parameters:
data
Variables in columns, observations in rows.
ncomp
Number of components to return. If None, returns the as many as the smaller of the number of rows or columns in data.
standardize
Flag indicating to use standardized data with mean 0 and unit variance. standardized being True implies demean. Using standardized data is equivalent to computing principal components from the correlation matrix of data.
demean
Flag indicating whether to demean data before computing principal components. demean is ignored if standardize True. Demeaning data but not standardizing is equivalent to computing principal components from the covariance matrix of data.
normalize
Indicates whether to normalize the factors to have a unit inner product. If False, the loadings will have a unit inner product.
Instacart Market Basket Analysis in Python
gls
Flag indicating to implement a two-step GLS estimator wherein the first step principal components are used to estimate residuals, and then the inverse residual variance is used as a set of weights to estimate the final principal components. Setting gls to True requires ncomp to be less then the min of the number of rows or columns.
weights
Series weights to use after transforming data according to standardize or demean when computing the principal components.
method
1. ‘svd’ uses a singular value decomposition (default).
2. ‘eig’ uses an eigenvalue decomposition of a quadratic form
3. ‘nipals’ uses the NIPALS algorithm and can be faster than SVD when ncomp is small and nvars is large. See notes about additional changes when using NIPALS.
Attributes:
factors[array or DataFrame]
nobs by ncomp array of principal components (scores)
scores[array or DataFrame]
nobs by ncomp array of principal components - identical to factors
Example:
# Example 1:
# Importing libraries
import numpy as np
from statsmodels.multivariate.pca import PCA
# Creating array of random numbers
data = np.random.randn(10)
# Fitting pca model
pca_model = PCA(data)
# Factors
pca_model.factors
Output -
array([[-0.14246123],
[ 0.3902405 ],
[ 0.18353067],
[ 0.30667022],
[-0.56520834],
[ 0.4737978 ],
[-0.2789227 ],
[-0.26372694],
[-0.01327701],
[-0.09064296]])
# Example 2:
# Importing libraries
import numpy as np
from statsmodels.multivariate.pca import PCA
# Creating array of random numbers
data = np.random.randn(10)
# Fitting pca model
pca_model = PCA(data, method='eig')
# Factors
pca_model.factors
Output -
array([[-0.54885266],
[-0.04136097],
[ 0.20260935],
[ 0.16259255],
[-0.28626099],
[ 0.37394827],
[ 0.38848118],
[-0.12744043],
[ 0.27944004],
[-0.40315635]])
In this way, we can perform PCA in StatsModel library.
What Users are saying..
profile image
Jingwei Li
Graduate Research assistance at Stony Brook University
linkedin profile url
ProjectPro is an awesome platform that helps me learn much hands-on industrial experience with a step-by-step walkthrough of projects. There are two primary paths to learn: Data Science and Big Data.... Read More
Relevant Projects
End-to-End Speech Emotion Recognition Project using ANN
Speech Emotion Recognition using RAVDESS Audio Dataset - Build an Artificial Neural Network Model to Classify Audio Data into various Emotions like Sad, Happy, Angry, and Neutral
Build CNN Image Classification Models for Real Time Prediction
Image Classification Project to build a CNN model in Python that can classify images into social security cards, driving licenses, and other key identity information.
Build Real Estate Price Prediction Model with NLP and FastAPI
In this Real Estate Price Prediction Project, you will learn to build a real estate price prediction machine learning model and deploy it on Heroku using FastAPI Framework.
Time Series Project to Build a Multiple Linear Regression Model
Learn to build a Multiple linear regression model in Python on Time Series Data
Build a Graph Based Recommendation System in Python-Part 2
In this Graph Based Recommender System Project, you will build a recommender system project for eCommerce platforms and learn to use FAISS for efficient similarity search.
Build an End-to-End AWS SageMaker Classification Model
MLOps on AWS SageMaker -Learn to Build an End-to-End Classification Model on SageMaker to predict a patient’s cause of death.
Time Series Analysis with Facebook Prophet Python and Cesium
Time Series Analysis Project - Use the Facebook Prophet and Cesium Open Source Library for Time Series Forecasting in Python
AWS MLOps Project for Gaussian Process Time Series Modeling
MLOps Project to Build and Deploy a Gaussian Process Time Series Model in Python on AWS
Build a Graph Based Recommendation System in Python -Part 1
Python Recommender Systems Project - Learn to build a graph based recommendation system in eCommerce to recommend products.
CycleGAN Implementation for Image-To-Image Translation
In this GAN Deep Learning Project, you will learn how to build an image to image translation model in PyTorch with Cycle GAN.
|
__label__pos
| 0.92274 |
Home | | Engineering Physics II | Advanced Engineering Materials Metallic Glasses
Chapter: Physics : Advanced Engineering Materials Metallic Glasses
Advanced Engineering Materials Metallic Glasses
1 Introduction 2. Metallic glasses 3 Shape memory alloys 4 Nanotechnology 5 Synthesis techniques 6 Discuss the properties of nanophase materials 7 Applications of nanophase materials 8 Non-linear materials and bio-materials
ADVANCED ENGINEERING MATERIALS METALLIC GLASSES
1 Introduction
2. Metallic glasses
2.1 Methods of preparation
2.2 Preparation of metallic glasses
2.3 Types of metallic glasses
2.4 Properties of metallic glasses
2.5 Applications of metallic glasses
3 Shape memory alloys
3.1 Shape memory alloys
3.2 Types of shape memory alloys
3.3 Characteristics of SMA
3.4 Commercial shape memory alloys
3.5 Advantages of shape memory alloys
3.6 Disadvantages of shape memory alloys
3.7 Applications of shape memory alloys
4 Nanotechnology
4.1 Nano materials
4.2 Comparison of different objects
4.3 Classification of nanomaterials
4.4 Top-down and bottom-up process
5 Synthesis techniques
5.1 Pulsed laser deposition
5.2 Chemical vapor deposition
6 Discuss the properties of nanophase materials
6.1 Physical properties
6.2 Magnetic properties
6.3 Mechanical properties
7 Applications of nanophase materials
8 Non-linear materials and bio-materials
8.1 Birefringence and Kerr effect
8.2 Non-linear properties and second harmonic generation
8.3 Non linear properties
8.4 Second harmonic generation
8.5 Biomaterials with their properties and applications
8.6 Classification of biomaterials
8.7 Applications
8.8 Ceramic
1 INTRODUCTION
New engineering materials such as metallic glasses, shape memory alloys etc. are the advanced materials, which are the integral part of our life. Both scientists and technologists are searching for new materials, which can be used for high technology research as well as applications.
In this chapter, we are going to discuss the new engineering materials like metallic glasses, shpe memory alloys, etc., along with their properties and its wide range of applications.
2 METALLIC GLASSES
The Metallic glasses are materials which have the properties of both metals and glasses.
Metallic glass = Amorphous metal
In general, metallic glasses are strong, ductile, malleable, opaque and brittle. They also have good magnetic properties and high corrosion resistance.
2.1METHODS OF PREPARATION Principle
The principle used in making metallic glasses is extreme rapid cooling of the molten alloy. The technique is called as rapid quenching.
The cooled molten alloys are fed into highly conducting massive rollers at high speeds to give ribbons of metallic glasses.
2.1PREPARATION OF METALLIC GLASSES
Principle
The principle used in making metallic glasses is extreme rapid cooling of the molten metal alloy. This technique is called as rapid quenching.
Melt spinning system
A melt spinner consists of a copper roller over which a refractory tube with fine nozzle is placed. The refractory tube is provided with induction heater as shown in fig.
The metal alloy is melted by induction heating under inert gas atmosphere (helium or argon). The properly super heated molten alloy is ejected through the fine nozzle at the bottom of the refractory tube.
The molten alloy falls on the copper roller which is rotated at high speed. Thus, the alloy is suddenly cooled to form metallic glass. In this method a continuous ribbon of metallic glass can be obtained.
2.3 TYPES OF METALLIC GLASSES.
Metallic glasses are classified into two types:
(i)Metal –Metal metallic glasses
They are combination of metals
Metals Metals
Examples: Nickel (Ni) - Niobium (Nb)
Magnesium (Mg) - Zinc (Zn)
Copper (Cu) - Zirconium (Zr)
(ii) Metal –Metalloid metallic glasses
These are combinations of metals and metalloids.
Examples: Metals Metalloids
Fe, Co, Ni - B, Si, C, P
2.4 PROPERTIES OF METALLIC GLASSES
Structural properties
1. They do not have any crystal defects such as grain boundaries, dislocation etc.
2. Metallic glasses have tetrahedral close packing (TCP).
Mechanical properties
1. Metallic glasses have extremely high strength, due to the absence of point defects and dislocation.
2. They have high elasticity.
3. They are highly ductile.
4. Metallic glasses are not work-harden but they are work –soften. (work harnening is a process of hardening a material by compressing it).
Electrical properties
1. Electrical resistivity of metallic glasses is high and it does not vary much with temperature.
2. Due to high resistivity, the eddy current loss is very small.
3. The temperature coefficient is zero or negative.
Magnetic properties
1. Metallic glasses have both soft and hard magnetic properties.
2. They are magnetically soft due to their maximum permeabilities and thus they can be magnetised and demagnetized very easily.
3. They exhibit high saturation magnetisation.
4. They have less core losses.
5. Most magnetically soft metallic glasses have very narrow hysteresis loop with same crystal composition. This is shown in fig.
Fig. Hysteresis loop of iron based alloy in crystalline and metallic glassy phase.
Chemical properties
1. They are highly resistant to corrosion due to random ordering.
2. They are highly reactive and stable.
3. They can act as a catalyst. The amorphous state is more active than the crystalline state from the catalytic point of view.
2.5APPLICATIONS OF METALLIC GLASSES
Metallic glasses also called as met glasses have found wide applications in different fields.
Structural application
1. They posses high physical and tensile strength. They are superior to common steels and thus they are very useful as reinforcing elements in concrete, plastic and rubber.
2. Strong ribbons of metallic glasses are used for simple filament winding to reinforce pressure vessels and to construct large fly wheels for energy storage.
3. Due to their good strength, high ductility, rollability and good corrosion resistance, they are used to make razor blades and different kinds of springs.
Electrical and Electronics
1. Since metallic glasses have soft magnetic properties, they are used in tape recorder heads, cores of high-power transformers and magnetic shields.
2. They use of metallic glasses in motors can reduce core loss very much when compared with conventional crystalline magnets.
3. Superconducting metallic glasses are used to produce high magnetic fields and magnetic levitation effect.
4. Since metallic glasses have high electrical resistance, they are used to make accurate standard resistance, computer memories and magneto resistance sensors.
Metallic glasses as transformer core material
5. Metallic glasses have excellent magnetic properties. When they are used as transformer core, they give maximum magnetic flux linkage between primary and secondary coils and thus reduce flux leakage losses.
In view of their features like small thickness, smaller area, light weight, high resistivity, soft magnetic property and negligible hysteresis and eddy current loss, metallic glasses are considered as suitable core materials in different frequency transformers.
Nuclear reactor engineering
1.The magnetic properties of metallic glasses are not affected by irradiation and so they are useful in preparing containers for nuclear waste disposal and magnets for fusion reactors.
2.Chromium and phosphorous based (iron chromium, phosphorous-carbon alloys) metallic glasses have high corrosion resistances and so they are used in iner surfaces of reactor vessels, etc.
Bio-medical Industries
1. Due to their high resistance to corrosion, metallic glasses are ideal materials for making surgical instruments.
2. They are used as prosthetic materials for implantation in human body.
2 SHAPE MEMORY ALLOYS
3.1 SHAPE MEMORY ALLOYS
A group of metallic alloys which shows the ability to return to their original shape or size (i.e., alloy appears to have memory) when they are subjected to heating or cooling are called shape memory alloys.
Phase of shape memory alloys
Martensite and austenite are two solid phases in SMA as shown in fig.
Fig. Phases of SMA
Martensite is relatively soft and it is easily deformable phase which exists at low temperature (monoclinic) (fig.)
(i) Austenite is a phase that occurs at high temperature having a crystal structure and high degree of symmetry (cubic) (fig.).
3.2TYPES OF SHAPE MEMORY ALLOYS
There are two types of shape memory alloys
(i) One-way shape memory alloy
(ii) Two-way shape memory alloy
A material which exhibits shape memory effect only upon heating is known as one-way shape memory. A material which shows a shape memory effect during both heating and cooling is called two-way shape memory.
Examples of shape memory alloys
Generally, shape memory alloys are intermetallic compounds having super lattice structures and metallic-ionic-covalent characteristics. Thus, they have the properties of both metals and ceramics.
Ni –Ti alloy (Nitinol)
Cu –Al –Ni alloy
Cu –Zn –Al alloy
Au –Cd alloy
Ni –Mn –Ga and Fe based alloys
3.3CHARACTERISTICS OF SMAS
1. Shape memory effect
The change of shape of a material at low temperature by loading and regaining of original shape by heating it, is known as shape memory effect.
The shape memory effect occurs in alloys due to the change in their crystalline structure with the change in temperature and stress.
While loading, twinned martensite becomes deformed martensite at low temperature.
On heating, deformed martensite becomes austenite (shape recovery) and upon cooling it gets transformed to twinned martensite (fig.).
2.SMAs exhibit changes in electrical resistance, volume and length during the transformation with temperature.
3.The mechanism involved in SMA is reversible (austenite to martensite and vice versa.)
4. Stress and temperature have a great influence on martensite transformation.
5. Pseudo elasticity
Pseudo –elasticity occurs in shape memory alloys when it is completely in austenite phase (temperature is greater than Af austenite finish temperature).
Unlike the shape memory effect, Pseudo-elasticity occurs due to stress induced phase transformation without a change in temperature. The load on the shape memory alloy changes austenite phase into martensite (Fig.).
As soon as the loading decreases the martensite begins to transform to austenite.
This phenomenon of deformation of a SMA on application of large stress and regaining of shape on removal of the load is known as pseudo elasticity.
This pseudo elasticity is also known as super elasticity
6. Hysteresis
The temperature range for the martensite to austenite transformation which takes place upon heating is somewhat higher than that for the reverse transformation upon cooling.
The difference between the transition temperature upon heating and cooling is called hysteresis. The hysteresis curve for SMAs is shown in fig.
The difiference of temperature is found to be 20-30oC,
3.4 COMMERCIAL SHAPE MEMORY ALLOYS
The only two alloy systems that have achieved any level of commercial exploitation are,
(i) Ni-Ti alloys, and
(ii) Copper base alloys.
Properties of the two systems are quite different.
1. Nickel-Titanium Alloys
The basis of the Nickel-Titanium alloy is the binary, equi-atomic inter-metallic compound of Ti-Ni. The inter-metallic compound is extraordinary because it has moderate solubility range for excess Nickel or Titanium, as well as most other metallic elements. This solubility allows alloying with many of the elements to modify both the mechanical properties and the transformation properties of the system. Excess Nickel strongly depresses the transformation temperature and increases the yield strength of the austenite. The contaminants such as Oxygen and Carbon shift the transformation temperature and degrade the mechanical properties. Therefore, it is also desirable to minimize the amount of such elements.
Properties:
(i) The Ni-Ti alloys have greater shape memory strain upto 8.5% tend to be much more thermally stable.
(ii) They have excellent corrosion resistance and susceptibility, and have much higher ductility.
(iii) Machining by turning or milling is very difficult except with special tools.
(iv) Welding, brazing or soldering the alloys is generally difficult.
(v) The material do respond well to abrasive removal such as grinding, and shearing.
(vi) Punching can be done if thicknesses are kept small.
3.5 ADVANTAGES OF SHAPE MEMORY ALLOYS
They are simple, compact and high safe.
They have good bio –compatibility.
They have diverse applications and offer clean, silent and spark-free working condition
They have good mechanical properties and are strong corrosion-resistant.
3.6DISADVANTAGES OF SHAPE MEMORY ALLOYS
They have poor fatigue properties.
They are expensive.
They have low energy efficiency.
3.7 APPLICATIONS OF SHAPE MEMORY ALLOYS
1. Microvalve (Actuators)
One of the most common applications of SMAs is mocrovalves. Fig. shows a microvalve made of Ni –Ti alloy actuator. Actuator is a microsensor that can trigger the operation of a device. The electrical signal initiates an action.
Fig. Schematic of microvalves that open and close according to temperature
When an electrical current of 50 to 150 mA flows in Ni-Ti actuator, it contracts and lifts the poppet from the orifice and opens the valve.
2. Toys and novelties
Shape memory alloys are used to make toys and ornamental goods.
A butterfly using SMA. Moves its wings in response to pulses of electricity.
3. Medical field Blood clot filters
(i) Blood clot filters are SMAs, properly shaped and inserted in veins to stop the passing blood clots.
When the SMA is in contact with the clot at a lower temperature, it expands and stops the clot and blood passes through the veins.
(ii) They are used in artificial hearts.
(iii) Orthodontic applications
NiTi wire holds the teeth tight with a constant stress irrespective of the strain produced by the teeth movement. It resists permanent deformation even if it is bent. NiTi is non-toxic and non-corrosive with body fluid.
(iv) SMAs (NiTi) are used to make eye glass frames and medical tools. Sun-glasses made from superelastic Ni-Ti frames provide good comfort and durability.
4. Antenna wires
The flexibility of superelastic Ni –Ti wire makes it ideal for use as retractable antennas.
5. Thermostats
SMAs are used as thermostat to open and close the valves at required temperature.
6. Cryofit hydraulic couplings
SMAs materials are used as couplings for metal pipes
7. Springs, shock absorbers, and valves
Due to the excellent elastic property of the SMAs, springs can be made which have varied industrial applications. Some of them are listed here.
Engine micro valves
Medical stents (Stents are internal inplant supports provided for body organs)
Firesafety valves and
Aerospace latching mechanisms
8. Stepping motors
Digital SMA stepping motors are used for robotic control.
9. Titanium-aluminium shape memory alloys offer excellent strength with less weight and dominate in the aircraft industry. They are high temperature SMAs, for possible use in aircraft engines and other high temperature environments.
4 NANOTECHNOLOGY
4.1 NANO MATERIALS
Nanoparticles are the particles that have three dimensional nanoscale, the particle is between 1 and 100 nm in each spatial dimension. A nanometer is a unit of measure equal to one-billionth of a meter, or three to five atoms across.
Nanotechnology is the design, fabrication and use of nanostructured systems, and the growing, assembling of such systems either mechanically, chemically or biologically to form nanoscale architectures, systems and devices.
4.2COMPARISON OF DIFFERENT OBJECTS
1. Diameter of sun - 1,393,000km
2. Diameter of earth - 1,28,000km
3. Height of Himalaya mountain - 8,848km
4. Height of man - 1.65km
5. Virus - 20-250nm
6. Cadmium sulphide nanoparticle - 1-10nm
4.3CLASSIFICATION OF NANOMATERIALS
1. Clusters
A collection of atoms or reactive molecules up to about 50 units.
2. Colloid
A stable liquid phase containing particles in 1 to 1000 nm range. A colloidal particle is one such 1 to
1000 nm sized particle.
3. Nanoparticle
A solid particle in the 1 to 100 nm range that could be non-crystalline, an aggregate of crystallites, or a single crystallite.
4. Nanocrystal
A solid particle that is a single crystal in the nanometer size.
5. Nanostructured or Nanoscale Material
Any solid materials has a nanometer dimension.
Three dimensions --- > Particles
Two dimensions --- > Thin films
One dimension --- > Thin wire
6. Quantum Dots
A particle that exhibits a size quantization effect in at least one dimension.
4.4 TOP-DOWN AND BOTTOM-UP PROCESSS
1. Top-down Process
In this processes, bulk materials are broken into nano sized particles as shown in
In to-down processes, the building of nanostructures starting with small components like atoms and molecules that are removed from a bulk material so as to obtain desired microstructure.
2. Bottom-up Processes
In this processes, nano phase materials are produced by building of atom by atom as shown in.
This processes building larger objects from smaller buildings blocks. Nanotechnology seeks to use atoms and molecules as those building blocks. This is the opposite of the top-down approach. Instead of taking material away to make structures, the bottom-up approach selectively adds atoms to create structures.
5 SYNTHESIS TECHNIQUES
Nano materials are newly developed materials with grain size at the nanometre range (10-9m)
i.e., in the order of 1 –100 nm. The particle size in a nano material is in the order of nm.
5.1 PULSED LASER DEPOSITION
Priniciple
The laser pulse of high intensity and energy is used to evaporate carbon from graphite. These evaporated carbon atoms are condensed to from nanotubes.
Description
The experimental arrangement of pulsed laser4 deposition is shown in fig. A quartz tube which contains a graphite target is kept inside a high temperature muffle furnace.
Fig. Pulsed Laser Deposition CNT
This quartz tube is filled with argon gas and it is heated to 1473 K. A water cooled copper collector is fitted at the other end of the tube. The target material graphite contains small amount of nickel and cobalt as a catalyst to nucleate the formation of nanotubes.
Working
When an intense pulse of laser beam is incident on the target, it evaporates the carbon from the graphite. The evaporated carbon atoms are swept from the higher temperature argon gas to the colder copper collector.
When the carbon atoms reach the colder copper collector, they condense into nanotubes.
5.2CHEMICAL VAPOUR DEPOSITION
The deposition of nano films from gaseous phase by chemical reaction on high temperature is known as chemical vapour deposition.
This method is used to prepare nano-powder.
Principle
In this technique, initially the material is heated to gaseous state and then it is deposited on a solid surface under vacuum condition to form nano powder by chemical reaction with the substrate.
Description and Working
The CVD reactor built to perform CVD processes is shown in fig.
Chemical vapour deposition (CVD) involves the flow of a gas with diffused reactants (substances to be deposited in the vapour) over a hot substrate surface. The gas that carries the reactants is called the carrier gas.
While the gas flows over the hot solid surface, the heat energy increases chemical reactions of the reactants that form film during and after the reactions.
The byproduct of the chemical reactions are then removed. The thin film of desired composition can thus be formed over the surface of the substrate.
6 PROPERTIES OF NANOPHASE MATERIALS.
Properties of Nanophase Particles
The mechanical, electrical, chemical, magnetic and structural properties of nanophase materials change with the reduction in the particle size of the material.
6.1 PHYSICAL PROPERTIES
Variation of physical properties with geometry
Starting from the bulk, the first effect of reducing the particle size is to create more surface sites. This in turn changes surface pressure and interparticle spacing.
(i) Interparticle spacing decreases with decrease in grain size for metal clusters.
For example in copper, it decrease from 2.52 (cluster size –50A) to 2.23A (Cu dimer) fig.
The change in inter particle spacing and large surface to the volume ratio in particles have a combined effect on material properties. Therefore, the nanophase materials have very high strength and super hardness.
Because of the cluster of grains, the nano phase materials are mostly free from dislocations and stronger than conventional metals.
Fig. Interatomic distance in Cun as a function of grain size.
(ii) Melting point reduces with decrease in cluster size.
The melting point of gold in nano phase (Aun) varies as a function of particle size (fig.)
Fig. Melting point of small Aun particles as a function of size
The melting point decreases from 1200 K to 800 K when the particle size decreases from 300 A to 20 A.
(iii) Ionisation potential changes with cluster size of the nanograins.
The electronic bands in metals become narrower when the size is reduced from bulk which changes the value of ionization potential.
Fig. shows the ionization potential and reactivity of Fen clusters as a function of size. Ionisation potentials are higher at small sizes than that for the bulk and show marked fluctuations as a function of size.
Fig. Ionisation potential and reactivity of Fen clusters as a function of size (iv) The large surface to volume ratio, the variations in geometry and the electronic structure have a strong effect on catalytic properties.
As an example, the reactivity of small clusters is found to vary by higher orders of magnitude when the cluster size is changed by only a few atoms.
6.2 MAGNETIC PROPERTIES
Nanoparticles of non-magnetic solids also exhibit totally new type of magnetic properties.
(i) Bulk magnetic moment increases with decrease in co-ordination number
The change in magnetic moment on the nearest coordination number is shown in fig.-0
Fig. Change in magnetic moment on the nearest coordination number
As the coordination number decreases, the magnetic moment increases with the atomic value which means that small particles are more magnetic than the bulk material.
The magnetic moment of iron (Fe) of nanoparticles is 30% more than that of bulk. At smaller sizes, the clusters become spontaneously magnetic.
(ii) The nano-materials shows variation in their magnetic property when they change from bulk state to cluster (nano-particle) state.
(iii) Non-magnetic materials become magnetic when the cluster size reduces to 80 atoms.
6.2 MECHANICAL PROPERTIES
(i) In nanophase materials, the elastic strength is low however, its plastic behavior is high.
(ii) In some nanophase materials, it is noted that there is decrease in hardness when the grain size is less than 10 nm.
However for many nanocrystalline, pure metals (10 nm), the hardness is about 2 to 7 times greater than that of large-grained (>1 μ m) metals.
(iii)Higher hardness and mechanical strength (2-7 times) when grain size reduces from 1 μ m to 10 nm.
(iv) It has very high ductility and superplastic behavior at low temperatures.
7 APPLICATIONS OF NANOPHASE MATERIALS.
1.Materials Technology
We can synthesis harder metals having hardness 5 times higher than normal metals using nanoparticles.
Stronger, lighter, wear resistant, tougher and flame retardant polymers are synthesized with nanoparticles as fillers. They are used in replacement of body parts and metals (bio-materials).
We can produce unusual colour paints using nanoparticles since nanoparticles exhibit entirely different optical properties.
Nanophase materials are used in annoelectronic devices such as nanotransistore, ceramic capacitors for energy storage, noise filters and stabilizers. The special features of these devices include smaller sizes and reduced power losses.
ZnO thermistors are used in thermal –protection and current-controlling devices.
2. Information Technology
Nanoparticles are used for data storage.
Quantum electronic devices have started replacing bulk conventional devices.
Nano materials are used to produce very tiny permanent magnets of high energy products. Hence, they are used in high-density magnetic recording.
Magnetic devices made of Cu-Fe alloy are used in RAM, READ / WRITE heads and sensors.
Quantum dots, quantum wells and quantum wires are mainly produced from semiconductor nanomaterials. Hence, they are used in computer storage (memory) devices.
3. Biomedicals
Biosensitive nanoparticles are used for tagging of DNA and DNA chips.
Controlled drug delivery is possible using nanotechnology. Diffusion of medicine through nanoporous polymer reservoir as per the requirement is very useful in controlling the disease.
Nanostructured ceramics readily interact with bone cells and bence finds applications as an implant material.
4. Energy storage
Since the hydrogen absorbing capability increases with decrese of size of nanoparticles, nanoparticles of Ni, Pd and Pt are useful in hydrogen storage devices.
Metal nanoparticles are very useful in fabrication of ionic batteries.
5. Optical devices
Nanomaterials are used in making effici
Nanoparticulate zinc oxide is used to manufacture effective Sunscreens.
Nanoparticles are used in the coatings for eye glasses to protect from scratch or breakage.
6. Transmission lines
Nanophase materials are used in the fabrication of signal processing elements such as filters, delay lines, switches etc.
7. Nanomicro-Electro Mechanical Systems (Nano MEMS) have direct implications on integrated circuits, optical switches, pressure sensors and mass sensors.
8. Molecular Nano-Technology (MNT) is aimed to develop robotic machines, called assemblers on a molecular scale, molecular-size power sources and batteries.
9. Underwater nanosensor networks are used to detect the movement of ships in an efficient manner with faster response. They can also detect chemical, biological or radiological materials in cargo containers.
8 NON-LINEAR MATERIALS AND BIO-MATERIALS
8.1 BIREFRINGENCE AND KERR EFFECT.
The appearance of double refraction under the influence of an external agent is known as artificial double refraction or induced birefringence.
Optical Kerr Effect
Anisotropy induced in an isotropic medium under the influence of an electric field is known as Kerr effect.
A sealed glass cell known as Kerr cell filled with a liquid comprising of asymmetric molecules is used to study the Kerr effect.
Two plane electrodes are placed in parallel to each other. When a voltage is applied to there electrodes, a uniform electric field is produced in the cell.
The Kerr cell is placed between a crossed polarizer system (Fig), When the electric field is applied, the molecules of the liquid tend to align along the field direction.
As the molecules are asymmetric, the alignment causes anisotropy and the liquid becomes double refracting. The induced birefringence is proportional to the square of the applied electric field E and to the wavelength λ of incident light.
Fig. Kerr effect –Birefringence is induced in a liquid subjected to an electric field
The change in refractive influx is given by
∆μ= K λE2
Where K is known as the Kerr constant
8.2 EXPLAIN NON-LINEAR PROPERTIES AND SECOND HARMONIC GENERATION. Basic Principle of Non Linear Properties
We know that a light wave is electromagnetic in nature ie., it consists of electric and magnetic fields. When the light propagates through a material, it changes the properties of the medium, such as the refractive index. It depends on the electric and magnetic fields associated with the light.
For example, we could not observe nonlinear effects with the ordinary light beam of low intensity, since the electric and magnetic fields associated with the light beams is very weak.
With the invention of laser, it is now possible to have electric fields which are strong enough to observe interesting non linear effects.
Thus if electric and magnetic fields are strong enough, the properties of the medium will be affected which in turn will affect the propagation of the light beam.
8.3NON LINEAR PROPERTIES
Few of the nonlinear phenomena observed are
1. Second harmonic generation
2. Optical mixing
3. Optical phase conjugation
4. Soliton
8.4SECOND HARMONIC GENERATION
In a linear medium, polarization P is directly proportional to the electric field E
P E
P = εoχE
Whereo ε- Permittivity of free space
χ - electrical susceptibility
In nonlinear medium for higher fields ie., higher intensities of light the non linear effects are observed.
In the above equation, 1st term gives rise to dc field across the medium, the second term gives external polarization and is called first or fundamental harmonic polarisability.
The third term which oscillates at a frequency 2w is called second harmonic of polarization and other terms are referred as higher harmonic polarization.
Both first term (dc field) and third term (second harmonic of polarization) added together is called optical rectification.
The second harmonic generation is possible only the crystals lacking inversion symmetry. SHG crystals are quartz, potassium dihydrogen phosphate (KDP), Ammonium dihydrogen phosphate (ADP), Barium titante (BaTiO3) and Lithium lodate (LiIO3)
The observation of second harmonic generation by KDP is shown in figure.
Fig. Arrangement for observing second harmonic generation
When the fundamental radiation (1.064 m) from Nd: YAG laser is sent through SHG crystal like KDP, conversion takes place to double the frequency. i.e., half the wavelength (0.532 m) takes place.
8.5 BIOMATERIALS WITH THEIR PROPERTIES AND APPLICATIONS.
The materials which are used for structural applications in the field of medicine are known as Biomaterials.
In the recent years, new biomaterials like nanobiomaterials are emerging up due to the requirements in the medical field for different applications.
8.6 CLASSIFICATION OF BIOMATERIALS
Based on the applications in the field of medicine, biomaterials are classified as
1. Metals and alloys biomaterials
2. Ceramics biomaterials.
3. Polymer biomaterials.
4. Composite biomaterials
Sometimes, a single material mentioned above cannot fulfill the complete requirements imposed for specific applications. In such case, combinations of more than one material are required.
Metals and Alloys
Metals and alloys are used as biomaterials due to their excellent electrical and thermal conductivity and mechanical properties.
TYPES OF BIOMATERIALS USING METALS AND ALLOYS
1. Cobalt based alloys
2. Titanium
3. Stainless steel
4. Protosal from cast alloy
5. Conducting metals such as Platinum
8.7APPLICATIONS
The metals and alloys biomaterials are used in implant and orthopedic applications.
1. Stainless steel is the predominant implant alloy. This is mainly due to its ease of fabrication and desirable mechanical properties and corrosion resistant.
2. Proposal from cast alloy of Co –Cr –Mo is used to make stem and used for implant hip endoprosthesis.
3. The advanced version of protosal –10 from Co –Ni –Cr –Mo alloy is widely used in Hip joints, Ankle joints, Knee joints, leg lengthening spaceas.
4. ASTMF –136 (composition of Ti –6A1 –4V, EL1 alloy, forged) due to its high strength / weight ratio, high corrosion resistance and high bio compatibility, this alloy is used in dental applications for making screws, wires and artificial teeth.
5. Ni –Ti shape memory alloy is used in dental arch wires, micro surgical instruments, blood clot filters, guide wires etc.
8.8CERAMICS
Ceramics are used as biomaterials due to their high mechanical strength and biocompatibility.
Types of Bio-Ceramic materials.
1. Tricalcium phosphate
2. Metal oxides such as Al2O3 and SiO2
3. Apatite ceramics
4. Porous ceramics
5. Carbons and Alumina
Applications
1. Ceramic implants such as Al2O3 and with some SiO2 and alkali metals are used to make femoral head. This is made from powder metallurgical process.
2. Tricalcium phosphate is used in bone repairs.
3. Orthopedic uses of alumina consists of hip and knee joints, tibical plate, femur shaft, shoulders, radius, vectebra, leg lengthening spaces and ankle joint prosthesis. Porous alumina is also used in teeth roots.
4. Apatite ceramics are new bio active ceramics. They are regarded as synthetic bone, readily allows bone ingrowth, better than currently used alumina Al2O3.
5. Carbon has good biocompatibility with bone and other tissues. It has high strengths and an elastic molecules close to that of bone.
6. Carbon coatings find wide applications in heart valves, blood vessel grafts, percutaneous devices because of exceptional compatibility with soft tissues and blood.
7. Percutaneous carbon devices containing high density electrical connectors have been used for the chronic stimulation of the cochlea for artificial hearing and stimulation of the visual cortex to aid the blind.
Bio Polymers
Biopolymers are macromolecules (protein, nucleic acids and polysachacides) formed in
nature during the growth cycles of all organisms.
Biopolymers find variety of applications as biomaterials. The most prominent among them are collagens, muco-polysaccharides –chitin, collagens and its derivatives.
Collagnes which are major animal structural proteins are widely used in a variety of forms such as solution, gel, fibers, membranes, sponge and tubing for large number of biomedical applications including drug delivery system, vessels, valves corneal prosthesis, wound dressing, cartilage substitute and dental applications.
Biomaterials in Opthamology
Biomaterials find important applications in opthalmology. They are used to improve and maintain vision. Eye implants are used to restore functionality of cornea, lens, etc, when they are damaged or diseased.
The biomaterials include viscoelastic solutions intraocular lenses, contact lenses, eye shields, artificial tears, vitreous replacements, correction of corneal curvature.
Dental Materials
Polymers, composites, ceramic materials and metal alloys are four main groups of materials used for dental applications.
A large number of materials are tested for porous dental implants, which include stainless steel,Co –Cr –Mo alloy, PMMA, proplast and Daceon, velour coated metallic implants, porous calcium aluminate single crystal alumina, bioglass, vitreous and pyrolytic carbons.
The dental applications include impression materials, dentine base and ceorons, bridges, inlays and repair or cavities, artificial teeth, repair of alveolar bone, support for mandible .
Study Material, Lecturing Notes, Assignment, Reference, Wiki description explanation, brief detail
Physics : Advanced Engineering Materials Metallic Glasses : Advanced Engineering Materials Metallic Glasses |
Privacy Policy, Terms and Conditions, DMCA Policy and Compliant
Copyright © 2018-2023 BrainKart.com; All Rights Reserved. Developed by Therithal info, Chennai.
|
__label__pos
| 0.934878 |
Java中static、private、public 方法哪个更快
发表于2016-11-09 1942次阅读
本文是我多年之前的老博客（android-performance.com）的一篇文章，老博客很久没有维护了，把一些有用的文章转移过来。
在java中，同样的方法被声明不通的类型在访问速度上会有不同吗？如果不通会有多大差异？让我们功过实验来证明这一切。
我们有下面三段代码，运算逻辑相同，我们分别用static, private, public 来声明，然后分别对他们的运行时间：
public class TestStatic {
static long add(long a, long b) {
return a + b;
}
public static void main(String[] args) {
long start = System.currentTimeMillis();
for (long i = 0; i < 9999999999L; i++) {
add(i, i + 1);
}
System.out.println(System.currentTimeMillis() - start);
}
}
public class TestPrivate {
private long add(long a, long b) {
return a + b;
}
public static void main(String[] args) {
TestPrivate obj = new TestPrivate();
long start = System.currentTimeMillis();
for (long i = 0; i < 9999999999L; i++) {
obj.add(i, i + 1);
}
System.out.println(System.currentTimeMillis() - start);
}
}
public class TestPublic {
public long add(long a, long b) {
return a + b;
}
public static void main(String[] args) {
TestPublic obj = new TestPublic();
long start = System.currentTimeMillis();
for (long i = 0; i < 9999999999L; i++) {
obj.add(i, i + 1);
}
System.out.println(System.currentTimeMillis() - start);
}
}
表1：各方法执行5次所花时间的对比结果（单位毫秒）运行环境是在我以前的旧笔记本上（Dell E6410 上）
# static 方法 private 方法 public 方法
1 16804 20424 20428
2 17061 20291 20246
3 17044 20629 20604
4 17064 20207 21107
5 16869 20079 20405
从结果中可见，static 方法比 private 和 public 方法要快 15% 左右，private 和 public 消耗相差无几。
通过 javap -v 获得的字节码我们看到，在调用这几个方发的时候，jvm 使用了不同的指令：
static 实现中 main 方法的部分字节码：
...
6: goto 21
9: lload3
10: lload3
11: lconst1
12: ladd
13: invokestatic #27 // Method add:(JJ)J
16: pop2
17: lload3
18: lconst1
19: ladd
20: lstore3
21: lload_3
...
private 实现中 main 方法的部分字节码：
...
15: goto 35
18: aload1
19: lload 4
21: lload 4
23: lconst1
24: ladd
25: invokespecial #28 // Method add:(JJ)J
28: pop2
29: lload 4
31: lconst_1
32: ladd
33: lstore 4
35: lload 4
...
public 实现中 main 方法的部分字节码：
...
15: goto 35
18: aload1
19: lload 4
21: lload 4
23: lconst1
24: ladd
25: invokevirtual #28 // Method add:(JJ)J
28: pop2
29: lload 4
31: lconst_1
32: ladd
33: lstore 4
35: lload 4
...
在看一下几种实现方式的add方法的字节码：
static 实现中 add 方法的字节码：
static long add(long, long);
flags: ACCSTATIC
Code:
stack=4, locals=4, argssize=2
0: lload0
1: lload2
2: ladd
3: lreturn
LineNumberTable:
line 6: 0
LocalVariableTable:
Start Length Slot Name Signature
0 4 0 a J
0 4 2 b J
private 实现中 add 方法的部分字节码（需要用javap -v -p）：
private long add(long, long);
flags: ACCPRIVATE
Code:
stack=4, locals=5, argssize=3
0: lload1
1: lload3
2: ladd
3: lreturn
LineNumberTable:
line 8: 0
LocalVariableTable:
Start Length Slot Name Signature
0 4 0 this LTestPrivate;
0 4 1 a J
0 4 3 b J
public 实现中 add 方法的部分字节码：
public long add(long, long);
flags: ACCPUBLIC
Code:
stack=4, locals=5, argssize=3
0: lload1
1: lload3
2: ladd
3: lreturn
LineNumberTable:
line 6: 0
LocalVariableTable:
Start Length Slot Name Signature
0 4 0 this LTestPublic;
0 4 1 a J
0 4 3 b J
可以看到几个 add 方法字节码（Code部分）的实现几乎是一样的，而在调用这几个方法时jvm使用了 invokestaticinvokespecialinvokevirtual 三种不同的虚拟机指令。表1 中的性能差异主要就是由这几条指令的操作方式所决定的，invokestatic 指令是基于方法（在编译时就知道该调用哪个方法）的指令，在进行栈帧切换（可以理解方法切换）时只需要把方法的参数入栈即可，从 “static 实现中 add 方法的字节码” 中我们可以看到其 LocalVariableTable（局部变量表）中只有a、b两个值。而 invokespecial 和 invokevirtual 是基于实例的指令，他们处理把a、b两个参数入栈之外，还要把对实例的引用（this 指针）也同时入栈，所以在private和public实现方式的add方法字节码中，LocalVariableTable 还包括了this指针。所以这一点点额外的操作就决定了他们的性能差别。
更多关于字节码的解释可参考之前的一篇文章 《读懂 javap -verbose 》
关于 invokestatic 、invokespecial、invokevirtual 这几个指令的详解，可参考相关官方文档
invokespecial 和 invokevirtual 在上面的例子并没有体现出明显的差别。我们再举一个例子比较一下，在这里例子中我们引入多态特性。我们把 TestPublic 改造一下，代码如下：
class TestBaseClass {
public long add(long a, long b) {
return a + b;
}
}
public class TestPublic extends TestBaseClass {
public long add(long a, long b) {
return a + b;
}
public static void main(String[] args) {
TestBaseClass obj = new TestPublic();
long start = System.currentTimeMillis();
for (long i = 0; i < 9999999999L; i++) {
obj.add(i, i + 1);
}
System.out.println(System.currentTimeMillis() - start);
}
}
我们在执行5次，看看结果是怎样的（单位毫秒）
1 2 3 4 5
79712 80419 81648 89341 83449
在 public 多态的情况下，同样的逻辑，花的时间是之前的4倍左右。这是由于 invokevirtual 指令属于“动态绑定”——即运行时才知道方法的所属类型是哪个，相对于动态绑定的是“静态绑定”——即编译时就知道要执行的方法属于哪个类。动态绑定不仅需要查方法表，而需要在运行时确定要引用的方法所属的类到底是哪个，这两中操作是比较耗时的。
关于动态绑定、静态绑定的内容可参考 《What is Static and Dynamic binding in Java with Example》
关于 invokevirtual 指令如何确定动态绑定的类型可参考《Chapter 6. The Java Virtual Machine Instruction Set》
小结
本文锁讲述的内容并不会对你的实际项目有多大的性能提升，但是却可以指导我们养成一个“好”的编码习惯。对于独立的逻辑优先使用 static 方式或者是 private 方式（而且也符合面向对象的 OCP 原则），没有必要的情况下，少用 public 方法，尤其在多态的模式下，public 方法会有比较大的性能损耗。 因为在 java 中 invokestatic 、invokespecial 都属于静态绑定，其他的静态绑定还有声明为 final 的方法，他们在编译时就知道方法属于那个类，所以在运行时会比较快地定位到方法在内存中对应的字节码地址（在方法区中），不像动态绑定，还需要明确方法所在的类型并搜索方法表才能定位到。
|
__label__pos
| 0.950411 |
Spectroscopy of a canonically quantized horizon
@article{Ansari2007SpectroscopyOA,
title={Spectroscopy of a canonically quantized horizon},
author={Mohammad H. Ansari},
journal={Nuclear Physics},
year={2007},
volume={783},
pages={179-212}
}
• M. Ansari
• Published 12 July 2006
• Physics
• Nuclear Physics
Figures and Tables from this paper
Black hole radiation spectrum in LQG: Isolated Horizon framework
Recent detailed analysis within the Loop Quantum Gravity calculation of black hole entropy shows a stair-like structure in the behavior of entropy as a function of horizon area. The non-trivial
Toward explaining black hole entropy quantization in loop quantum gravity
In a remarkable numerical analysis of the spectrum of states for a spherically symmetric black hole in loop quantum gravity, Corichi, Diaz-Polo and Fernandez-Borja found that the entropy of the black
Remarks on Spectroscopy via Adiabatic Invariance from the Kerr Black Hole
By imposing Bohn-Sommerfeld quantization rule and the laws of black hole thermodynamics to the modified adiabatic covariant action, the spectroscopy of the Kerr black hole is obtained in different
Entropy quantization of Reissner-Nordström de Sitter black hole via adiabatic covariant action
Based on the ideas of adiabatic invariant quantity, we attempt to quantize the entropy of a charged black hole in de Sitter spacetime in two different coordinates. The entropy spectrum is obtained by
Area spectrum of horizon and black hole entropy
We calculate the number of degrees of freedom in spin network states related to the general area spectrum in loop quantum gravity based on the ABCK framework. We find that a black hole entropy (the
Spectroscopy from the d-dimensional Reissner–Nordström black hole via adiabatic covariant action
Via modified adiabatic invariant I=∮pi dqi, we investigate the area spectrum of the d-dimensional Reissner–Nordström black hole in two different coordinate frames. Emphasis is given to covariance of
Quantum amplification effect in a horizon fluctuation
The appearance of a few unevenly spaced bright flashes of light on top of Hawking radiation is the sign of the amplification effect in black hole horizon fluctuations. Previous studies on this
Entropy in spin foam models: the statistical calculation
Recently an idea for computing the entropy of black holes in the spin foam formalism has been introduced. Particularly complete calculations for the three-dimensional Euclidean BTZ black hole were
Spin foam models: the dynamics of quantum geometry
In this paper, we give an overview of the main techniques developed in the context of background independent gravity in order to tackle the problem of the dynamics. We briefly introduce loop quantum
...
1
2
...
References
SHOWING 1-10 OF 71 REFERENCES
Spectroscopy of the quantum black hole
Quantum black holes from null expansion operators
Using a recently developed quantization of spherically symmetric gravity coupled to a scalar field, we give a construction of null expansion operators that allow a definition of general, fully
Physics with nonperturbative quantum gravity: Radiation from a quantum black hole
We study quantum gravitational effects on black hole radiation, using loop quantum gravity. Bekenstein and Mukhanov have recently considered the modifications caused by quantum gravity on Hawking's
Quasinormal modes, the area spectrum, and black hole entropy.
TLDR
A result from classical gravity concerning the quasinormal mode spectrum of a black hole is used to fix the Immirzi parameter and the Bekenstein-Hawking expression of A/4l(2)(P) for the entropy of ablack hole is arrived at.
Quantum geometry of isolated horizons and black hole entropy
Using the earlier developed classical Hamiltonian framework as the point of departure, we carry out a non-perturbative quantization of the sector of general relativity, coupled to matter, admitting
Generic predictions of quantum theories of gravity
I discuss generic consequences (sometimes called “soft predictions”) of a class of background independent quantum theories of spacetime called causal spin network theories. These are theories whose
Generic degeneracy and entropy in loop quantum gravity
Interface of General Relativity, Quantum Physics and Statistical Mechanics: Some Recent Developments
The arena normally used in black holes thermodynamics was recently generalized to incorporate a broad class of physically interesting situations. The key idea is to replace the notion of stationary
On Quantum Statistical Mechanics of a Schwarzschild Black Hole
Quantum theory of geometry, developed recently in the framework of non-perturbative quantum gravity, is used in an attempt to explain thermodynamics of Schwarzschild black holes on the basis of a
...
1
2
3
4
5
...
|
__label__pos
| 0.987025 |
How to add Quartz JobListener
I am writing a java/spring library to include in other projects that are using quartz. I need it to log something before each task is executed. I have a simple JobListener that looks like this: public …
What does each table for quartz scheduler signify?
There are few tables that quartz scheduler uses for scheduling jobs and to identify which job is running currently. It uses the following tables : qrtz_fired_triggers qrtz_simple_triggers …
|
__label__pos
| 0.594011 |
Erlang logo
User's Guide
PDF
Top
OTP Design Principles
User's Guide
Version 6.3
Expand All
Contract All
Chapters
1 Overview
The OTP Design Principles is a set of principles for how to structure Erlang code in terms of processes, modules and directories.
1.1 Supervision Trees
A basic concept in Erlang/OTP is the supervision tree. This is a process structuring model based on the idea of workers and supervisors.
• Workers are processes which perform computations, that is, they do the actual work.
• Supervisors are processes which monitor the behaviour of workers. A supervisor can restart a worker if something goes wrong.
• The supervision tree is a hierarchical arrangement of code into supervisors and workers, making it possible to design and program fault-tolerant software.
IMAGE MISSING
Figure 1.1: Supervision Tree
In the figure above, square boxes represents supervisors and circles represent workers.
1.2 Behaviours
In a supervision tree, many of the processes have similar structures, they follow similar patterns. For example, the supervisors are very similar in structure. The only difference between them is which child processes they supervise. Also, many of the workers are servers in a server-client relation, finite state machines, or event handlers such as error loggers.
Behaviours are formalizations of these common patterns. The idea is to divide the code for a process in a generic part (a behaviour module) and a specific part (a callback module).
The behaviour module is part of Erlang/OTP. To implement a process such as a supervisor, the user only has to implement the callback module which should export a pre-defined set of functions, the callback functions.
An example to illustrate how code can be divided into a generic and a specific part: Consider the following code (written in plain Erlang) for a simple server, which keeps track of a number of "channels". Other processes can allocate and free the channels by calling the functions alloc/0 and free/1, respectively.
-module(ch1).
-export([start/0]).
-export([alloc/0, free/1]).
-export([init/0]).
start() ->
spawn(ch1, init, []).
alloc() ->
ch1 ! {self(), alloc},
receive
{ch1, Res} ->
Res
end.
free(Ch) ->
ch1 ! {free, Ch},
ok.
init() ->
register(ch1, self()),
Chs = channels(),
loop(Chs).
loop(Chs) ->
receive
{From, alloc} ->
{Ch, Chs2} = alloc(Chs),
From ! {ch1, Ch},
loop(Chs2);
{free, Ch} ->
Chs2 = free(Ch, Chs),
loop(Chs2)
end.
The code for the server can be rewritten into a generic part server.erl:
-module(server).
-export([start/1]).
-export([call/2, cast/2]).
-export([init/1]).
start(Mod) ->
spawn(server, init, [Mod]).
call(Name, Req) ->
Name ! {call, self(), Req},
receive
{Name, Res} ->
Res
end.
cast(Name, Req) ->
Name ! {cast, Req},
ok.
init(Mod) ->
register(Mod, self()),
State = Mod:init(),
loop(Mod, State).
loop(Mod, State) ->
receive
{call, From, Req} ->
{Res, State2} = Mod:handle_call(Req, State),
From ! {Mod, Res},
loop(Mod, State2);
{cast, Req} ->
State2 = Mod:handle_cast(Req, State),
loop(Mod, State2)
end.
and a callback module ch2.erl:
-module(ch2).
-export([start/0]).
-export([alloc/0, free/1]).
-export([init/0, handle_call/2, handle_cast/2]).
start() ->
server:start(ch2).
alloc() ->
server:call(ch2, alloc).
free(Ch) ->
server:cast(ch2, {free, Ch}).
init() ->
channels().
handle_call(alloc, Chs) ->
alloc(Chs). % => {Ch,Chs2}
handle_cast({free, Ch}, Chs) ->
free(Ch, Chs). % => Chs2
Note the following:
• The code in server can be re-used to build many different servers.
• The name of the server, in this example the atom ch2, is hidden from the users of the client functions. This means the name can be changed without affecting them.
• The protcol (messages sent to and received from the server) is hidden as well. This is good programming practice and allows us to change the protocol without making changes to code using the interface functions.
• We can extend the functionality of server, without having to change ch2 or any other callback module.
(In ch1.erl and ch2.erl above, the implementation of channels/0, alloc/1 and free/2 has been intentionally left out, as it is not relevant to the example. For completeness, one way to write these functions are given below. Note that this is an example only, a realistic implementation must be able to handle situations like running out of channels to allocate etc.)
channels() ->
{_Allocated = [], _Free = lists:seq(1,100)}.
alloc({Allocated, [H|T] = _Free}) ->
{H, {[H|Allocated], T}}.
free(Ch, {Alloc, Free} = Channels) ->
case lists:member(Ch, Alloc) of
true ->
{lists:delete(Ch, Alloc), [Ch|Free]};
false ->
Channels
end.
Code written without making use of behaviours may be more efficient, but the increased efficiency will be at the expense of generality. The ability to manage all applications in the system in a consistent manner is very important.
Using behaviours also makes it easier to read and understand code written by other programmers. Ad hoc programming structures, while possibly more efficient, are always more difficult to understand.
The module server corresponds, greatly simplified, to the Erlang/OTP behaviour gen_server.
The standard Erlang/OTP behaviours are:
gen_server
For implementing the server of a client-server relation.
gen_fsm
For implementing finite state machines.
gen_event
For implementing event handling functionality.
supervisor
For implementing a supervisor in a supervision tree.
The compiler understands the module attribute -behaviour(Behaviour) and issues warnings about missing callback functions. Example:
-module(chs3).
-behaviour(gen_server).
...
3> c(chs3).
./chs3.erl:10: Warning: undefined call-back function handle_call/3
{ok,chs3}
1.3 Applications
Erlang/OTP comes with a number of components, each implementing some specific functionality. Components are with Erlang/OTP terminology called applications. Examples of Erlang/OTP applications are Mnesia, which has everything needed for programming database services, and Debugger which is used to debug Erlang programs. The minimal system based on Erlang/OTP consists of the applications Kernel and STDLIB.
The application concept applies both to program structure (processes) and directory structure (modules).
The simplest kind of application does not have any processes, but consists of a collection of functional modules. Such an application is called a library application. An example of a library application is STDLIB.
An application with processes is easiest implemented as a supervision tree using the standard behaviours.
How to program applications is described in Applications.
1.4 Releases
A release is a complete system made out from a subset of the Erlang/OTP applications and a set of user-specific applications.
How to program releases is described in Releases.
How to install a release in a target environment is described in the chapter about Target Systems in System Principles.
1.5 Release Handling
Release handling is upgrading and downgrading between different versions of a release, in a (possibly) running system. How to do this is described in Release Handling.
|
__label__pos
| 0.768177 |
Print This Page
Separation Anxiety Disorder
What is separation anxiety disorder?
Separation anxiety disorder (SAD) is defined as excessive worry and fear about being apart from family members or individuals to whom a child is most attached. Children with separation anxiety disorder fear being lost from their family or fear something bad happening to a family member if they separated from them. Symptoms of anxiety or fear about being separated from family members must last for a period of at least four weeks to be considered SAD. It is different than stranger anxiety, which is normal and usually experienced by children between seven and 11 months of age. Symptoms of SAD are more severe than the normal separation anxiety that nearly every child experiences to some degree between the ages of 18 months and three years of age.
What causes separation anxiety disorder?
Anxiety disorders are believed to have biological, family, and environmental factors that contribute to the cause. A chemical imbalance involving two chemicals in the brain (norepinephrine and serotonin) most likely contributes to the cause of anxiety disorders. While a child or adolescent may have inherited a biological tendency to be anxious, anxiety and fear can also be learned from family members and others who frequently display increased anxiety around the child. A traumatic experience may also trigger anxiety.
Who is affected by separation anxiety disorder?
All children and adolescents experience some anxiety. It is a normal part of growing up. However, when worries and fears are developmentally inappropriate concerning separation from home or family, separation anxiety disorder may be present. SAD occurs equally in males and females. The first symptoms of SAD usually appear around the third or fourth grade. Typically, the onset of symptoms occurs following a break from school such as Christmas holidays or an extended illness. Children of parents with an anxiety disorder are more likely to have an anxiety disorder.
What are the symptoms of separation anxiety disorder?
The following are the most common signs of SAD. However, each child may experience symptoms differently. Symptoms may include:
• Refusal to sleep alone
• Repeated nightmares with a theme of separation
• Excessive distress when separation from home or family occurs or is anticipated
• Excessive worry about the safety of a family member
• Excessive worry about getting lost from family
• Refusing to go to school
• Fearful and reluctant to be alone
• Frequent stomach aches, headaches, or other physical complaints
• Muscle aches or tension
• Excessive worry about safety of self
• Excessive worry about or when sleeping away from home
• Excessive "clinginess," even when at home
• Symptoms of panic and/or temper tantrums at times of separation from parents or caregivers
The symptoms of separation anxiety disorder may resemble other conditions or psychiatric problems. Always consult your child's doctor for a diagnosis.
How is separation anxiety disorder diagnosed?
A child psychiatrist or other qualified mental health professional usually diagnoses anxiety disorders in children or adolescents following a comprehensive psychiatric evaluation. Parents who note signs of severe anxiety in their child or teen can help by seeking an evaluation and treatment early. Early treatment can often prevent future problems.
Treatment for separation anxiety disorder
Specific treatment for separation anxiety disorder will be determined by your child's doctor based on:
• Your child's age, overall health, and medical history
• Extent of your child's symptoms
• Your child's tolerance for specific medications or therapies
• Expectations for the course of the condition
• Your opinion or preference
Anxiety disorders can be effectively treated. Treatment should always be based on a comprehensive evaluation of the child and family. Treatment recommendations may include cognitive behavioral therapy for the child, with the focus being to help the child or adolescent learn skills to manage his or her anxiety and to help him or her master the situations that contribute to the anxiety. Some children may also benefit from treatment with antidepressant or antianxiety medication to help them feel calmer. Parents play a vital, supportive role in any treatment process. Family therapy and consultation with the child's school may also be recommended.
Prevention of separation anxiety disorder
Preventive measures to reduce the incidence of separation anxiety disorders in children are not known at this time. However, early detection and intervention can reduce the severity of the disorder, enhance the child's normal growth and development, and improve the quality of life experienced by children or adolescents with separation anxiety disorder.
Psychology Services
|
__label__pos
| 0.989028 |
Do I have fungal nails?
fungusAre your nails are discolored, white, yellow, green, brown or black? Are they thicker than normal, loosen easily, lift up at the ends or sometimes fall off?
Discoloration can be caused by many things including fungus, yeast, mold, other chemicals like nailpolish. Trauma to the nail by dropping something on top of it, or the nail hitting your shoe repeatedly while walking, can cause thickness and an abnormal looking nail.
Fungus is common and is not caused by not been washing your feet properly. Even the cleanest most meticulous person can end up with fungal nails. The most common fungus that you have come in contact with is the Trichophyton rubrum fungus and it has unfortunately made a home under your nail. Fungus thrives in damp, warm and dark places, which includes your shoes, showers and swimming pools. The same fungus that causes fungal nails also causes athlete’s foot. The fungus can find its way into your skin through small cuts and into the nails if there is any subtle separation between the skin and the nail.
It is important before starting a treatment plan to know what you have a microorganism growing in your nail. This way the correct medication can be picked and you are not treating something that isn’t there looking for results. This is where your podiatrist comes into play. The doctor can take a biopsy of your nail and send it to a lab to be analyzed for what is causing your nail problem. This is usually a painless process. A couple different tests are run, one that takes a few days and the second that takes a couple weeks. Both tests combined give an answer about what is causing your nail to be abnormal and what you can do about it.
Both topical (placing the medication directly on the nail itself) and oral medications (pills which treat fungus from the inside out) are options for treatment and it is important to discuss with your podiatrist which one is right for you based on your lifestyle and the other medication you are taking.
Written by Dr. Holdren Otis.
|
__label__pos
| 0.969119 |
Take the 2-minute tour ×
Stack Overflow is a question and answer site for professional and enthusiast programmers. It's 100% free, no registration required.
Given the lambda expression below where Province type contains a public property "byte CountryId" and Country type which contains a public property "byte Id".
Expression<Func<Province, bool>> exp = p => p.CountryId == country.Id;
The Expression is later used by NHibernate Linq provider and threw an exception. When I inspected the expression variable exp, I found out that both sides of the equality operator were converted to Int32.
{p => (Convert(p.CountryId) = Convert(value
(AddressToGo.Business.Default.AddressComponents+<>c__DisplayClass0).country.Id))}
I can't understand why the equality operator for two byte values need those values to be converted to Int32 beforehand. I have written the expression directly wihout letting the compiler do it for me. The following expression is converted by NHibernate Linq provider just fine.
ParameterExpression prm = Expression.Parameter(typeof(Province), "p");
Expression<Func<Province, bool>> exp =
Expression.Lambda<Func<Province, bool>>
(
Expression.Equal
(
Expression.MakeMemberAccess(prm, typeof(Province).GetProperty("CountryId")),
Expression.Constant(country.Id, typeof(byte))
),
prm
);
So, there must be a reason why the compiler outputs the expression with type conversion. Any ideas?
share|improve this question
Needs a language tag. – Ignacio Vazquez-Abrams Jan 15 '10 at 15:18
add comment
1 Answer
This is per the specification. Quoting from §4.1.5:
C# supports nine integral types: sbyte, byte, short, ushort, int, uint, long, ulong, and char. [...]
The integral-type unary and binary operators always operate with signed 32-bit precision, unsigned 32-bit precision, signed 64-bit precision, or unsigned 64-bit precision:
[...]
For the binary +, , *, /, %, &, ^, |, ==, !=, >, <, >=, and <= operators, the operands are converted to type T, where T is the first of int, uint, long, and ulong that can fully represent all possible values of both operands. The operation is then performed using the precision of type T, and the type of the result is T (or bool for the relational operators). It is not permitted for one operand to be of type long and the other to be of type ulong with the binary operators.
Thus, for
byte b1;
byte b2;
bool b = (b1 == b2);
the operands b1 and b2 are promoted to int before == is invoked.
share|improve this answer
3
Thank you for the answer. This explains the compiler behaviour of converting the byte type values to int32. However, it still doesn't make sense. Since the lambda expression is converted into an expression, not a compiled delegate, it must still be an expression tree which can later be defined in any language, including C#, HQL etc. So I think it must be free of any language specific implementations. NHibernate Linq provider wouldn't need the promotion of variable types before operating on them. Is the lambda expression compiled before being converted to an expression tree? – user251516 Jan 16 '10 at 5:37
add comment
Your Answer
discard
By posting your answer, you agree to the privacy policy and terms of service.
|
__label__pos
| 0.623773 |
July 20, 2024
How Dental Implants Preserve Oral Health
You might look older than you truly are if you have missing teeth. However, did you realize that tooth loss increases your risk of further tooth loss, deterioration of the jawbone, and face collapse? A family dentist in Greenbelt can take care of your oral hygiene so you can keep your confident smile. To preserve your health, read on to find out why it is suggested to have dental implants.
How dental implants preserve oral health
Because they offer numerous benefits to your dental health, dental implants are among the most effective tooth replacement solutions. They help you, for example:
• Preserve your remaining teeth.
• Avoid decaying of the teeth and periodontal disease
• Prevent jaw bone deterioration
• Eating healthier
• Preserve remaining teeth.
The roots and neighboring teeth hold each tooth in place. This means you have a greater probability of losing other teeth when you lose one tooth. Asking your dentist if you are eligible for dental implant treatment is the best way to prevent tooth loss from escalating.
By supporting neighboring teeth, dental implants prevent additional tooth loss. Giving support to the other teeth in your smile makes them less likely to slide loose and fall out. Teeth with nothing to press against start tilting toward the empty space unless dental implants stop it.
• Avoid tooth decay and gum disease.
You are more prone to gum disease and cavities if you have missing teeth. When teeth grow closer to empty sockets, it can be challenging to brush and floss them properly. Furthermore, food crumbs, bacteria, and plaque can become trapped in empty tooth sockets. Dental plaque, which is left untreated, is the leading cause of oral health problems (such as gum disease). Replacing missing teeth and maintaining good oral hygiene is among the most effective ways to strengthen dental health.
• Prevent Jaw Bone Loss
Unlike other tooth replacement options, a dental implant promotes jawbone tissue like a natural tooth root. Your jawbone requires pressure from the tooth’s roots to preserve its health. Without treatment, your jawbone could start to decay, and you can possibly cause face collapse.
• Eat healthy.
Your favorite meals are fine to eat. Call your dentist if you are in pain or unpleasant while eating. Patients often select soft meals after tooth loss. You cannot eat the nutrients needed to maintain good health when you reduce your diet to avoid dental pain.
It is essential to understand the relationship between oral and general health. Your jawbones, gums, and teeth constitute part of an overall structure. Lack of access to a healthy diet can impact your bones and increase your risk of tooth decay and jawbone degradation.
About The Author
|
__label__pos
| 0.935324 |
Most popular
What is the term implantation?
What is the term implantation?
Implantation: The act of setting in firmly. In embryology, implantation refers specifically to the attachment of the fertilized egg to the uterine lining, which occurs approximately 6 or 7 days after conception (fertilization). Many medical devices or materials may be implanted (embedded).
What is the implantation stage in pregnancy?
Implantation is a process that occurs after an embryo — i.e., a fertilized egg — travels down the fallopian tube and burrows deep into the lining of the uterus, where it will remain until delivery. While many consider fertilization to be the start of pregnancy, successful implantation is another crucial hurdle.
What is reproductive implantation?
Implantation, in reproduction physiology, the adherence of a fertilized egg to a surface in the reproductive tract, usually to the uterine wall (see uterus), so that the egg may have a suitable environment for growth and development into a new offspring.
What will happen after implantation?
Implanting gives the blastocyst a blood supply so that it can start growing into a fetus. Along with cramping, you may experience what is called implantation bleeding or spotting. This usually happens 10 to 14 days after conception, around the time of your usual period.
How do you know when implantation is successful?
If the implantation is successful, spotting or light cramping can be experienced. If unsuccessful, your period will start. Some of the common post embryo implantation symptoms are listed below: Cramping and spotting: A brown vaginal discharge for 1-2 days is experienced after a successful implantation.
What is the difference between implantation and ovulation?
• Fertilization occurs within about 24 hours of ovulation whereas implantation occurs after about 8-10 days of fertilization . • Fertilization ends with zygote whereas implantation results implanted blastocysts with three germ layers.
How long between conception and implantation?
Implantation takes a week after conception. Conception and fertilization are overlapping terms. Ovulation and fertilization don’t have a huge time lag. So as only after few hours from ovulation, fertilization occurs one can say that implantation takes a week after fertilization.
Do implantation signs confirm conception?
Implantation signs confirm conception but don’t guarantee viability . You have a higher risk of miscarriage in the first trimester than the following weeks. Moreover, the signs of implantation are mild and difficult to feel.
What does pregnancy implantation mean?
Implantation (of the human embryo) is the attachment of the fertilized egg (the blastocyst) to the lining of the uterus . It is an entirely natural process and an early stage of pregnancy that happens a week after ovulation (1).
Share this post
|
__label__pos
| 0.999995 |
aboutsummaryrefslogtreecommitdiffstats
path: root/src
diff options
context:
space:
mode:
authorMatthias P. Braendli <[email protected]>2020-11-02 11:38:19 +0100
committerMatthias P. Braendli <[email protected]>2020-11-02 11:38:19 +0100
commit13fa77bd40301af2219491b874aa8ed2860f2921 (patch)
treeef84e46671294ddd91f72ddd8031b007e527aaec /src
parent8b08667176e6fb8404aa6f722d9f2424d3d33225 (diff)
downloaddabmux-13fa77bd40301af2219491b874aa8ed2860f2921.tar.gz
dabmux-13fa77bd40301af2219491b874aa8ed2860f2921.tar.bz2
dabmux-13fa77bd40301af2219491b874aa8ed2860f2921.zip
Rework FIG0/13, combine programme and data code paths
Diffstat (limited to 'src')
-rw-r--r--src/fig/FIG0_13.cpp158
1 files changed, 67 insertions, 91 deletions
diff --git a/src/fig/FIG0_13.cpp b/src/fig/FIG0_13.cpp
index 84e426f..2fa9a54 100644
--- a/src/fig/FIG0_13.cpp
+++ b/src/fig/FIG0_13.cpp
@@ -50,7 +50,6 @@ struct FIG0_13_app {
typeHigh = type >> 3;
typeLow = type & 0x1f;
}
- uint16_t xpad;
} PACKED;
@@ -90,18 +89,39 @@ FillStatus FIG0_13::fill(uint8_t *buf, size_t max_size)
}
const auto type = (*subchannel)->type;
- if ( m_transmit_programme and
+ if ( (m_transmit_programme and
(type == subchannel_type_t::DABPlusAudio or type == subchannel_type_t::DABAudio) and
- (*componentFIG0_13)->audio.uaTypes.size() != 0) {
+ (*componentFIG0_13)->audio.uaTypes.size() != 0)
+ or (not m_transmit_programme and
+ (*subchannel)->type == subchannel_type_t::Packet and
+ (*componentFIG0_13)->packet.uaTypes.size() != 0)) {
+
+ const std::vector<userApplication>& uaTypes = m_transmit_programme ?
+ (*componentFIG0_13)->audio.uaTypes : (*componentFIG0_13)->packet.uaTypes;
- const size_t num_apps = (*componentFIG0_13)->audio.uaTypes.size();
+ const size_t num_apps = uaTypes.size();
const size_t xpadapp_length = 2;
static_assert(sizeof(FIG0_13_shortAppInfo) == 3);
- static_assert(sizeof(FIG0_13_app) == 4);
- int required_size = sizeof(FIG0_13_shortAppInfo);
- for (const auto& ua : (*componentFIG0_13)->audio.uaTypes) {
- required_size += sizeof(FIG0_13_app) + xpadapp_length;
+ static_assert(sizeof(FIG0_13_longAppInfo) == 5);
+ static_assert(sizeof(FIG0_13_app) == 2);
+
+ int required_size = 0;
+ if (m_transmit_programme) {
+ required_size += sizeof(FIG0_13_shortAppInfo);
+ }
+ else {
+ required_size += sizeof(FIG0_13_longAppInfo);
+ }
+
+ for (const auto& ua : uaTypes) {
+ if (m_transmit_programme) {
+ required_size += sizeof(FIG0_13_app) + xpadapp_length;
+ }
+ else {
+ required_size += sizeof(FIG0_13_app);
+ }
+
if (ua.uaType == FIG0_13_APPTYPE_SPI) {
required_size += 2; // For the "basic profile" user application data
}
@@ -116,7 +136,7 @@ FillStatus FIG0_13::fill(uint8_t *buf, size_t max_size)
fig0->Length = 1;
fig0->CN = 0;
fig0->OE = 0;
- fig0->PD = 0;
+ fig0->PD = m_transmit_programme ? 0 : 1;
fig0->Extension = 13;
buf += 2;
remaining -= 2;
@@ -125,15 +145,26 @@ FillStatus FIG0_13::fill(uint8_t *buf, size_t max_size)
break;
}
- FIG0_13_shortAppInfo* info = (FIG0_13_shortAppInfo*)buf;
- info->SId = htonl((*componentFIG0_13)->serviceId) >> 16;
- info->SCIdS = (*componentFIG0_13)->SCIdS;
- info->No = num_apps;
- buf += sizeof(FIG0_13_shortAppInfo);
- remaining -= sizeof(FIG0_13_shortAppInfo);
- fig0->Length += sizeof(FIG0_13_shortAppInfo);
+ if (m_transmit_programme) {
+ FIG0_13_shortAppInfo* info = (FIG0_13_shortAppInfo*)buf;
+ info->SId = htonl((*componentFIG0_13)->serviceId) >> 16;
+ info->SCIdS = (*componentFIG0_13)->SCIdS;
+ info->No = num_apps;
+ buf += sizeof(FIG0_13_shortAppInfo);
+ remaining -= sizeof(FIG0_13_shortAppInfo);
+ fig0->Length += sizeof(FIG0_13_shortAppInfo);
+ }
+ else {
+ FIG0_13_longAppInfo* info = (FIG0_13_longAppInfo*)buf;
+ info->SId = htonl((*componentFIG0_13)->serviceId);
+ info->SCIdS = (*componentFIG0_13)->SCIdS;
+ info->No = num_apps;
+ buf += sizeof(FIG0_13_longAppInfo);
+ remaining -= sizeof(FIG0_13_longAppInfo);
+ fig0->Length += sizeof(FIG0_13_longAppInfo);
+ }
- for (const auto& ua : (*componentFIG0_13)->audio.uaTypes) {
+ for (const auto& ua : uaTypes) {
FIG0_13_app* app = (FIG0_13_app*)buf;
app->setType(ua.uaType);
app->length = xpadapp_length;
@@ -141,91 +172,36 @@ FillStatus FIG0_13::fill(uint8_t *buf, size_t max_size)
app->length += 2;
}
- const uint8_t dscty = 60; // TS 101 756 Table 2b (MOT)
- app->xpad = htons((ua.xpadAppType << 8) | dscty);
- /* xpad meaning
- CA = 0
- CAOrg = 0 (CAOrg field absent)
- Rfu = 0
- AppTy(5) = depending on config
- DG = 0 (MSC data groups used)
- Rfu = 0
- DSCTy(6) = 60 (MOT)
- */
-
buf += sizeof(FIG0_13_app);
remaining -= sizeof(FIG0_13_app);
fig0->Length += sizeof(FIG0_13_app);
- if (ua.uaType == FIG0_13_APPTYPE_SPI) {
- buf[0] = 0x01; // = basic profile
- buf[1] = 0x00; // = list terminator
+ if (m_transmit_programme) {
+ const uint8_t dscty = 60; // TS 101 756 Table 2b (MOT)
+ const uint16_t xpadapp = htons((ua.xpadAppType << 8) | dscty);
+ /* xpad meaning
+ CA = 0
+ CAOrg = 0 (CAOrg field absent)
+ Rfu = 0
+ AppTy(5) = depending on config
+ DG = 0 (MSC data groups used)
+ Rfu = 0
+ DSCTy(6) = 60 (MOT)
+ */
+
+ memcpy(buf, &xpadapp, 2);
buf += 2;
remaining -= 2;
fig0->Length += 2;
}
- }
- }
- else if (not m_transmit_programme and
- (*subchannel)->type == subchannel_type_t::Packet and
- (*componentFIG0_13)->packet.uaTypes.size() != 0) {
-
- const size_t num_apps = (*componentFIG0_13)->audio.uaTypes.size();
-
- const size_t app_length = 2;
- const int required_size = sizeof(FIG0_13_longAppInfo) + num_apps * (sizeof(FIG0_13_app) + app_length);
- /* is conservative because app_length can be 0 */
-
- if (fig0 == NULL) {
- if (remaining < 2 + required_size) {
- break;
- }
- fig0 = (FIGtype0*)buf;
- fig0->FIGtypeNumber = 0;
- fig0->Length = 1;
- fig0->CN = 0;
- fig0->OE = 0;
- fig0->PD = 1;
- fig0->Extension = 13;
- buf += 2;
- remaining -= 2;
- }
- else if (remaining < required_size) {
- break;
- }
-
- FIG0_13_longAppInfo* info = (FIG0_13_longAppInfo*)buf;
- info->SId = htonl((*componentFIG0_13)->serviceId);
- info->SCIdS = (*componentFIG0_13)->SCIdS;
- info->No = num_apps;
- buf += sizeof(FIG0_13_longAppInfo);
- remaining -= sizeof(FIG0_13_longAppInfo);
- fig0->Length += sizeof(FIG0_13_longAppInfo);
-
- for (const auto& ua : (*componentFIG0_13)->audio.uaTypes) {
- FIG0_13_app* app = (FIG0_13_app*)buf;
- app->setType(ua.uaType);
-
- size_t effective_length = sizeof(FIG0_13_app);
if (ua.uaType == FIG0_13_APPTYPE_SPI) {
- // TODO This should probably be user configurable...
- app->length = app_length;
- app->xpad = htons(0x0100);
- /* xpad is actually not the "X-PAD data" as in Figure 25, but is the actual user application data.
- * We just recycle the same structure, even though it's a bit ugly.
- * It holds two bytes of EPG profile information:
- * 01 = basic profile
- * 00 = list terminator */
- }
- else {
- app->length = 0;
- effective_length = 1; // FIG0_13_app without xpad
+ buf[0] = 0x01; // = basic profile
+ buf[1] = 0x00; // = list terminator
+ buf += 2;
+ remaining -= 2;
+ fig0->Length += 2;
}
-
- buf += effective_length;
- remaining -= effective_length;
- fig0->Length += effective_length;
}
}
}
|
__label__pos
| 0.995388 |
blob: e8e614815d236bacfd6d9d302854529216097820 [file] [log] [blame]
// Copyright 2009 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
package runtime
import (
"internal/abi"
"internal/runtime/atomic"
"unsafe"
)
//go:generate go run wincallback.go
//go:generate go run mkduff.go
//go:generate go run mkfastlog2table.go
//go:generate go run mklockrank.go -o lockrank.go
var ticks ticksType
type ticksType struct {
// lock protects access to start* and val.
lock mutex
startTicks int64
startTime int64
val atomic.Int64
}
// init initializes ticks to maximize the chance that we have a good ticksPerSecond reference.
//
// Must not run concurrently with ticksPerSecond.
func (t *ticksType) init() {
lock(&ticks.lock)
t.startTime = nanotime()
t.startTicks = cputicks()
unlock(&ticks.lock)
}
// minTimeForTicksPerSecond is the minimum elapsed time we require to consider our ticksPerSecond
// measurement to be of decent enough quality for profiling.
//
// There's a linear relationship here between minimum time and error from the true value.
// The error from the true ticks-per-second in a linux/amd64 VM seems to be:
// - 1 ms -> ~0.02% error
// - 5 ms -> ~0.004% error
// - 10 ms -> ~0.002% error
// - 50 ms -> ~0.0003% error
// - 100 ms -> ~0.0001% error
//
// We're willing to take 0.004% error here, because ticksPerSecond is intended to be used for
// converting durations, not timestamps. Durations are usually going to be much larger, and so
// the tiny error doesn't matter. The error is definitely going to be a problem when trying to
// use this for timestamps, as it'll make those timestamps much less likely to line up.
const minTimeForTicksPerSecond = 5_000_000*(1-osHasLowResClockInt) + 100_000_000*osHasLowResClockInt
// ticksPerSecond returns a conversion rate between the cputicks clock and the nanotime clock.
//
// Note: Clocks are hard. Using this as an actual conversion rate for timestamps is ill-advised
// and should be avoided when possible. Use only for durations, where a tiny error term isn't going
// to make a meaningful difference in even a 1ms duration. If an accurate timestamp is needed,
// use nanotime instead. (The entire Windows platform is a broad exception to this rule, where nanotime
// produces timestamps on such a coarse granularity that the error from this conversion is actually
// preferable.)
//
// The strategy for computing the conversion rate is to write down nanotime and cputicks as
// early in process startup as possible. From then, we just need to wait until we get values
// from nanotime that we can use (some platforms have a really coarse system time granularity).
// We require some amount of time to pass to ensure that the conversion rate is fairly accurate
// in aggregate. But because we compute this rate lazily, there's a pretty good chance a decent
// amount of time has passed by the time we get here.
//
// Must be called from a normal goroutine context (running regular goroutine with a P).
//
// Called by runtime/pprof in addition to runtime code.
//
// TODO(mknyszek): This doesn't account for things like CPU frequency scaling. Consider
// a more sophisticated and general approach in the future.
func ticksPerSecond() int64 {
// Get the conversion rate if we've already computed it.
r := ticks.val.Load()
if r != 0 {
return r
}
// Compute the conversion rate.
for {
lock(&ticks.lock)
r = ticks.val.Load()
if r != 0 {
unlock(&ticks.lock)
return r
}
// Grab the current time in both clocks.
nowTime := nanotime()
nowTicks := cputicks()
// See if we can use these times.
if nowTicks > ticks.startTicks && nowTime-ticks.startTime > minTimeForTicksPerSecond {
// Perform the calculation with floats. We don't want to risk overflow.
r = int64(float64(nowTicks-ticks.startTicks) * 1e9 / float64(nowTime-ticks.startTime))
if r == 0 {
// Zero is both a sentinel value and it would be bad if callers used this as
// a divisor. We tried out best, so just make it 1.
r++
}
ticks.val.Store(r)
unlock(&ticks.lock)
break
}
unlock(&ticks.lock)
// Sleep in one millisecond increments until we have a reliable time.
timeSleep(1_000_000)
}
return r
}
var envs []string
var argslice []string
//go:linkname syscall_runtime_envs syscall.runtime_envs
func syscall_runtime_envs() []string { return append([]string{}, envs...) }
//go:linkname syscall_Getpagesize syscall.Getpagesize
func syscall_Getpagesize() int { return int(physPageSize) }
//go:linkname os_runtime_args os.runtime_args
func os_runtime_args() []string { return append([]string{}, argslice...) }
//go:linkname syscall_Exit syscall.Exit
//go:nosplit
func syscall_Exit(code int) {
exit(int32(code))
}
var godebugDefault string
var godebugUpdate atomic.Pointer[func(string, string)]
var godebugEnv atomic.Pointer[string] // set by parsedebugvars
var godebugNewIncNonDefault atomic.Pointer[func(string) func()]
//go:linkname godebug_setUpdate internal/godebug.setUpdate
func godebug_setUpdate(update func(string, string)) {
p := new(func(string, string))
*p = update
godebugUpdate.Store(p)
godebugNotify(false)
}
//go:linkname godebug_setNewIncNonDefault internal/godebug.setNewIncNonDefault
func godebug_setNewIncNonDefault(newIncNonDefault func(string) func()) {
p := new(func(string) func())
*p = newIncNonDefault
godebugNewIncNonDefault.Store(p)
}
// A godebugInc provides access to internal/godebug's IncNonDefault function
// for a given GODEBUG setting.
// Calls before internal/godebug registers itself are dropped on the floor.
type godebugInc struct {
name string
inc atomic.Pointer[func()]
}
func (g *godebugInc) IncNonDefault() {
inc := g.inc.Load()
if inc == nil {
newInc := godebugNewIncNonDefault.Load()
if newInc == nil {
return
}
inc = new(func())
*inc = (*newInc)(g.name)
if raceenabled {
racereleasemerge(unsafe.Pointer(&g.inc))
}
if !g.inc.CompareAndSwap(nil, inc) {
inc = g.inc.Load()
}
}
if raceenabled {
raceacquire(unsafe.Pointer(&g.inc))
}
(*inc)()
}
func godebugNotify(envChanged bool) {
update := godebugUpdate.Load()
var env string
if p := godebugEnv.Load(); p != nil {
env = *p
}
if envChanged {
reparsedebugvars(env)
}
if update != nil {
(*update)(godebugDefault, env)
}
}
//go:linkname syscall_runtimeSetenv syscall.runtimeSetenv
func syscall_runtimeSetenv(key, value string) {
setenv_c(key, value)
if key == "GODEBUG" {
p := new(string)
*p = value
godebugEnv.Store(p)
godebugNotify(true)
}
}
//go:linkname syscall_runtimeUnsetenv syscall.runtimeUnsetenv
func syscall_runtimeUnsetenv(key string) {
unsetenv_c(key)
if key == "GODEBUG" {
godebugEnv.Store(nil)
godebugNotify(true)
}
}
// writeErrStr writes a string to descriptor 2.
// If SetCrashOutput(f) was called, it also writes to f.
//
//go:nosplit
func writeErrStr(s string) {
writeErrData(unsafe.StringData(s), int32(len(s)))
}
// writeErrData is the common parts of writeErr{,Str}.
//
//go:nosplit
func writeErrData(data *byte, n int32) {
write(2, unsafe.Pointer(data), n)
// If crashing, print a copy to the SetCrashOutput fd.
gp := getg()
if gp != nil && gp.m.dying > 0 ||
gp == nil && panicking.Load() > 0 {
if fd := crashFD.Load(); fd != ^uintptr(0) {
write(fd, unsafe.Pointer(data), n)
}
}
}
// crashFD is an optional file descriptor to use for fatal panics, as
// set by debug.SetCrashOutput (see #42888). If it is a valid fd (not
// all ones), writeErr and related functions write to it in addition
// to standard error.
//
// Initialized to -1 in schedinit.
var crashFD atomic.Uintptr
//go:linkname setCrashFD
func setCrashFD(fd uintptr) uintptr {
// Don't change the crash FD if a crash is already in progress.
//
// Unlike the case below, this is not required for correctness, but it
// is generally nicer to have all of the crash output go to the same
// place rather than getting split across two different FDs.
if panicking.Load() > 0 {
return ^uintptr(0)
}
old := crashFD.Swap(fd)
// If we are panicking, don't return the old FD to runtime/debug for
// closing. writeErrData may have already read the old FD from crashFD
// before the swap and closing it would cause the write to be lost [1].
// The old FD will never be closed, but we are about to crash anyway.
//
// On the writeErrData thread, panicking.Add(1) happens-before
// crashFD.Load() [2].
//
// On this thread, swapping old FD for new in crashFD happens-before
// panicking.Load() > 0.
//
// Therefore, if panicking.Load() == 0 here (old FD will be closed), it
// is impossible for the writeErrData thread to observe
// crashFD.Load() == old FD.
//
// [1] Or, if really unlucky, another concurrent open could reuse the
// FD, sending the write into an unrelated file.
//
// [2] If gp != nil, it occurs when incrementing gp.m.dying in
// startpanic_m. If gp == nil, we read panicking.Load() > 0, so an Add
// must have happened-before.
if panicking.Load() > 0 {
return ^uintptr(0)
}
return old
}
// auxv is populated on relevant platforms but defined here for all platforms
// so x/sys/cpu can assume the getAuxv symbol exists without keeping its list
// of auxv-using GOOS build tags in sync.
//
// It contains an even number of elements, (tag, value) pairs.
var auxv []uintptr
// golang.org/x/sys/cpu uses getAuxv via linkname.
// Do not remove or change the type signature.
// (See go.dev/issue/57336.)
//
// getAuxv should be an internal detail,
// but widely used packages access it using linkname.
// Notable members of the hall of shame include:
// - github.com/cilium/ebpf
//
// Do not remove or change the type signature.
// See go.dev/issue/67401.
//
//go:linkname getAuxv
func getAuxv() []uintptr { return auxv }
// zeroVal is used by reflect via linkname.
//
// zeroVal should be an internal detail,
// but widely used packages access it using linkname.
// Notable members of the hall of shame include:
// - github.com/ugorji/go/codec
//
// Do not remove or change the type signature.
// See go.dev/issue/67401.
//
//go:linkname zeroVal
var zeroVal [abi.ZeroValSize]byte
|
__label__pos
| 0.946569 |
Take a Candle Carousel for a Spin
Create Assignment
This feature requires that you be logged in as a Google Classroom teacher and that you have an active class in Google Classroom.
If you are a Google Classroom teacher, please log in now.
For additional information about using Science Buddies with Google Classroom, see our FAQ.
google science journal candle carousel summary
Do this Science
Project with Your
Phone!
works with google science journal app
Difficulty
Time Required Short (2-5 days)
Prerequisites None.
Material Availability Readily available
Cost Low ($20 - $50)
Safety Adult supervision is needed for using matches, lighting candles and handling lit candles.
Abstract
Have you ever ridden on a carousel, or a merry-go-round, at an amusement park? On a carousel, you usually get to take a seat on a wooden horse or other animal that spins around and around as the carousel is turned on and powered by electricity. Another smaller type of carousel that people can have in their homes is a candle carousel, which is powered by heat from candles. In this science project, you will get to make your own candle carousel and investigate how the spinning speed of the carousel is related to the number of candles you use to power it. You can even record the number of rotations your carousel makes using Google's Science Journal app. How fast can you make it spin?
Objective
Investigate the relationship between the number of lit candles under a candle carousel, and how fast the carousel spins.
Share your story with Science Buddies!
I did this project Yes, I Did This Project! Please log in (or create a free account) to let us know how things went.
Credits
Teisha Rowland, PhD, Science Buddies
Edited by Svenja Lohner, PhD, Science Buddies
• Play-Doh® is a registered trademark of Hasbro, Inc.
• Elmer's® is a registered trademark of Elmer's Products, Inc.
Cite This Page
General citation information is provided here. Be sure to check the formatting, including capitalization, for the method you are using and update your citation, as needed.
MLA Style
Rowland, Teisha. "Take a Candle Carousel for a Spin." Science Buddies, 1 Dec. 2018, https://www.sciencebuddies.org/science-fair-projects/project-ideas/Aero_p051/aerodynamics-hydrodynamics/make-a-candle-carousel?class=AQUmhcccntdxalCx4tPGjqu5IlKOSICrpmdg58TpJZEW00Jud2kah286uC5n8JIk7GT0M-foTqI3WEzpiVkMIrfY4J04bWkasAH3jLeR-X09SA. Accessed 24 June 2019.
APA Style
Rowland, T. (2018, December 1). Take a Candle Carousel for a Spin. Retrieved from https://www.sciencebuddies.org/science-fair-projects/project-ideas/Aero_p051/aerodynamics-hydrodynamics/make-a-candle-carousel?class=AQUmhcccntdxalCx4tPGjqu5IlKOSICrpmdg58TpJZEW00Jud2kah286uC5n8JIk7GT0M-foTqI3WEzpiVkMIrfY4J04bWkasAH3jLeR-X09SA
Last edit date: 2018-12-01
Introduction
A candle carousel spins around like an electricity-powered carousel, or merry-go-round, that you might have ridden at an amusement park. But a candle carousel is much smaller—some can fit in the palm of your hand—and it is powered by heat from candles. Figure 1 shows an example of a candle carousel. Note how the candle carousel has several tilted blades at the top, how the blades are all attached to a central shaft, and that there are candles placed below the blades. When the candles are lit, hot air rises above them, which makes the blades spin around.
Homemade candle carousel
Figure 1. In this science project, you will make a candle carousel similar to this one. When the candles are lit, they cause the blades at the top to spin.
Candle carousels are part of the German Christmas tradition. Known as Christmas pyramids, or candle pyramids, these German crafts traditionally depict winter or religious themes like in Figure 2. They were invented in the early 1800's; long before electrical power was in homes.
German Christmas pyramid
Figure 2. An example of a Christmas candle pyramid.
How does lighting the candles make the candle carousel spin? The candle's flame heats up the air above the candle. Heat is a form of energy, and it makes the air right above the candle rise above the colder air around it. This rising hot air pushes up against the blade above it. Because the blade is tilted, this push causes the blade to move sideways (to the right or left, depending on how the blade is tilted), and spin around the shaft. Each blade that moves above the flame also gets "pushed" by the hot air.
The rising hot air exerts a force on the blade, which makes it move. A force is something that pushes or pulls on something else. The force that moves the blade sideways is called lift. Normally, we think of lift as an upward force, such as with flying airplanes. However, for an airplane, air is coming toward the airplane from straight in front of it, whereas with a blade on the candle carousel, the air is going upwards, hitting the blade from below. Because lift is defined relative to which way the air is going, in a candle carousel the lift is a sideways force. Another force acting on each blade is the force of drag, which pushes upward against the blade, in the same direction as the moving air. Figure 3 shows a diagram of how the hot air and forces of lift and drag act on a candle carousel's blade to make it move. (This is very similar to a wind turbine, which you can find out more about in the project idea Unleash the Power of a Pinwheel!.)
Diagram of the forces on the candle carousel's blade.
Figure 3. This diagram shows how hot air, drag, and lift act on a blade of a candle carousel to make the blade move (rotating around the central shaft; the shaft would be directly behind the blade [the shaft is unseen in this diagram], and the blade would rotate to the left in this diagram). Note that this diagram is only showing the edge of the blade, as if the viewer is looking directly at the blade's edge.
In this science project, you will make your own candle carousel, like the one in Figure 1, and investigate how the amount of heat—generated by a varying number of lit candles—under the carousel's blades affects how fast the blades spin. You will measure the speed of the blades in rotations per minute, or rpm. Will adding more candles make the blades spin faster, or will there be no noticeable difference? What will the relationship be? Get ready to make your own candle carousel to find out!
Terms and Concepts
• Candle carousel
• Heat
• Force
• Lift
• Drag
• Wind turbine
• Rotations per minute (or rpm)
Questions
• How does lighting a candle on a candle carousel make its blades move?
• What direction is the force of lift on the blades of a candle carousel?
• Why are the blades in a candle carousel tilted?
• Why does hot air rise?
Bibliography
To find out more about the forces involved in making the candle carousel work, you can check out these resources:
News Feed on This Topic
, ,
Note: A computerized matching algorithm suggests the above articles. It's not as smart as you are, and it may occasionally give humorous, ridiculous, or even annoying results! Learn more about the News Feed
Materials and Equipment
• Aluminum pie pans, 8 3/4 inch in diameter (2)
• Printer with printer paper
• Scissors
• Tape
• Ruler, metric
• Protractor
• Black permanent marker
• Plastic drinking straw
• Metal hex nut
• It should snugly fit around the straw, and be high enough to stably stand upright with the straw in it.
• The nut size used in this project had 1/4 inch inner diameter, 1/2 inch outer diameter, and a height of 1/4 inch.
• We recommend that you take your straw to a hardware store and try different-sized hex nuts to make sure you find the one that fits your size straw best, since straws can vary in diameter.
• Heavy duty mounting tape, double-sided
• Play-Doh® (a piece approximately the size of your fist)
• A wooden skewer, at least 20 cm long, with a sharp point
• Small candles (4). They should be about 5 cm tall. A set of 12 candles that work well for this project can be purchased from Amazon.com.
• Lighter or matches
• Lab notebook
• Adult helper for lighting candles
• A piece of aluminum foil
• Flashlight
• A pile of books or box to elevate your phone
• Optional: Colored permanent markers for decorating the candle carousel
• A smartphone or tablet to record your data
science-journal-app-icon This project uses Google's Science Journal app, a free app that allows you to gather and record data with a cell phone or tablet. You can download the app from Google Play for Android devices (version 4.4 or newer) or from the App Store for iOS devices (iOS 9.3 or newer).
Note: This project was tested with the Android version of Science Journal in which light intensity is measured using the ambient light sensor and given in lux. The iOS version uses the phone's camera to measure brightness resulting in data expressed in EV (Exposure Value). Lux values and Exposure Values are not the same. Whereas Exposure Value is a base-2 logarithmic scale, the lux scale is linear. This might affect your data and result in different values and graphs when you are using an iOS version of the app—both versions will work for this project though. The graph examples given in the procedure show light intensity in lux.
• If you do not have a smartphone, you can use a timer or stopwatch instead
Disclaimer: Science Buddies participates in affiliate programs with Home Science Tools, Amazon.com, Carolina Biological, and Jameco Electronics. Proceeds from the affiliate programs help support Science Buddies, a 501(c)(3) public charity, and keep our resources free for everyone. Our top priority is student learning. If you have any comments (positive or negative) related to purchases you've made for science projects from recommendations on our site, please let us know. Write to us at [email protected].
Remember Your Display Board Supplies
Artskills materials poster making kit
Poster Making Kit
ArtSkills buy now button
ArtSkills supplies trifold
ArtSkills Trifold with Header
ArtSkills buy now button
ArtSkills supplies poster lights
Poster Lights
ArtSkills buy now button
Take a Candle Carousel for a Spin
www.sciencebuddies.org/science-fair-projects/project-ideas/Aero_p051/aerodynamics-hydrodynamics/make-a-candle-carousel
Experimental Procedure
In the first part of this science project, you will build your candle carousel. Once you have confirmed that it works, you will use use Google's Science Journal app to measure how fast it spins using different amount of candles. Science Journal is an app that lets you record data using sensors that are built into many smartphones, including a light sensor which measures light levels (normally this sensor is used to automatically adjust the brightness of your phone's screen). To learn how to use the Science Journal app and how to use the light sensor, you can review the relevant tutorials on this Science Journal tutorial page. In this project, you will use the app to record the rotations of your carousel using your phone's light sensor. You will do this by having part of your carousel pass between the phone and a light source, so it will block the light sensor and affect the reading. If you do not have a phone, you can also count the carousel rotations using a stopwatch.
Constructing Your Candle Carousel
In this part of the science project, you will make your own candle carousel from two aluminum pie pans, a straw, a metal nut, candles, Play-Doh, a wooden skewer, and some double-sided mounting tape. You will also need a pair of scissors, tape, and a printer with paper. So gather your materials and get ready to build it!
1. Take one of the aluminum pie pans (Figure 4) and carefully cut off its tilted rim so that it now looks like a flat, aluminum circle, as shown in Figure 5.
An aluminum pie pan
Figure 4. Take one of the aluminum pie pans.
A circle of aluminum from a pie pan.
Figure 5. Cut the rim off of the aluminum pie pan (so you are left with a flat circle of aluminum).
1. Print out the windmill template (PDF).
2. Cut the circle out from the template and tape it to the aluminum circle with a couple of pieces of tape, as shown in Figure 6. Do not use too much tape as you will be removing the paper template later.
Windmill template taped to aluminum circle.
Figure 6. Tape the cut-out windmill template to the aluminum circle.
1. Cut along the solid lines of the template and the aluminum circle below it, as shown in Figure 7.
1. Be sure not to cut all the way to the center of the circle.
windmill template cut on aluminum circle
Figure 7. Cut the aluminum circle along the solid lines of the template.
1. Carefully fold the aluminum circle down along the dotted lines of the template, so that you have triangular edges pointing down, as shown in Figure 8.
1. You can use a ruler to help make sure the lines are straight.
2. Use a protractor to make sure the edges are bent down by about 30–40 degrees (°) compared to the top, flat strips.
Windmill template folded on aluminum circle.
Figure 8. Fold the aluminum circle down along the dotted lines.
1. Gently remove the paper template from the aluminum circle, which should now look like an aluminum windmill, as shown in Figure 9. You will need to remove the paper template for your candle carousel to work.
Windmill made from an aluminum pie pan.
Figure 9. Gently remove the paper template from the aluminum windmill.
1. Optional: At this point (or at a later point), you can decorate the blades of the windmill (using colored permanent markers) if you would like to. Figure 10 shows one example of some decorated blades.
Decorated windmill blades.
Figure 10. Decorated windmill blades.
1. Flip the windmill over so that the triangular edges are pointing up. In the center of the windmill, make a small dot using a permanent marker, as shown in Figure 11.
1. You should use a ruler to find the center by measuring along the length of each flat strip and calculating where the center of each of the strips is; where they all intersect is the center.
Windmill with a dot in the middle
Figure 11. Use a permanent marker to make a dot in the center of the windmill, on its underside.
1. Cut a straw to make a straight piece that is 5 centimeters (cm) long. Make sure the straw piece fits snugly in the metal hex nut you have. If needed, you can put a layer of tape around the straw to make it fit better.
2. Use the double-sided mounting tape to attach the nut and straw piece onto the dot you made on the aluminum windmill. The nut should help hold the straw piece straight up (vertically). When it is attached, your windmill should look like the one in Figures 12 and 13.
1. Only place the double-sided tape along the rim of the nut. Spare out the hole completely, otherwise the carousel might get stuck on the tape during spinning, which could later interfere with the ability of the windmill to smoothly spin on the skewer. It is fine if the tape reaches outside of the nut as long as there is no tape covering the hole.
2. Make sure you can see the dot when looking down through the straw; it should be centered on the dot.
3. Note: It is important to make sure that the straw is as vertical as possible. If the straw is not pointing straight up, the candle carousel blades will not work well. Look straight down at the straw (from the top), and from all sides, to make sure it is pointing up straight.
View of the straw on the windmill from the side
Figure 12. Side view of the straw (inside the nut) and nut being attached to the windmill.
View of the straw on the windmill from the top
Figure 13. Top view of the straw (inside the nut) and nut being attached to the windmill.
1. Continue with making the candle carousel's stand. This will be made using the other aluminum pie pan. Take the other aluminum pie pan and use a permanent marker to make a dot in the center. Then make four dots around the edge of the pan that are all equally spaced apart, and an "X" next to each dot, as shown in Figure 14. (You will later be placing a candle on each "X.") Note: Be sure you use a ruler to measure and make all of the dots.
Aluminum pie pan with five dots on it
Figure 14. On the second aluminum pie pan, make a dot in the center, and four dots (with an "X" next to each) equally spaced along the edges.
1. Next, cut (or break) a wooden skewer so that it is 20 cm long (and still has one pointed end). Then take a small fist-sized piece of Play-Doh and stick the flat end of the skewer into it. Place the Play-Doh and skewer onto the center dot of the aluminum pie pan. Be sure the skewer is right on the dot. Press down on the edges of the Play-Doh ball to flatten it onto the pie pan a little so that it looks like Figure 15. You can also use the double-sided tape to attach the Play-Doh onto the pan.
Skewer in Play-Doh on an aluminum pan
Figure 15. Place the wooden skewer into a piece of Play-Doh, and stick that onto the center of the aluminum pie pan.
1. Make sure that the skewer is as vertical as possible in the Play-Doh on the pan. (For the candle carousel to work well, the skewer needs to be as straight as possible.) Let the Play-Doh harden a bit by letting the candle carousel's stand sit out for a while.
2. In the meantime, cut a strip of aluminum foil, about 4 inches long and 1 inch wide. Use tape to attach it to the horizontal, flat part of one of the blades as shown in Figure 16. When the candle carousel is spinning, the aluminum strip will block the light from reaching your phone every time it passes the light sensor. This way you will be able to count how many rotations your carousel makes.
candle-carousel-aluminum-strip
Figure 16. Attach an aluminum strip to the horizontal part of one blade that will block your phone's light sensor when the carousel is spinning.
1. Once the Play-Doh has hardened, you can try out your candle carousel! Place the windmill's straw onto the top of the skewer. Test if your windmill spins smoothly by spinning it with your hands. If you feel a lot of resistance or you notice irregular spinning movements, check if the tip of the skewer got stuck onto the double-sided tape that you used to attach the nut to the pan. You want it to spin evenly and very smoothly. Next, place one candle on each "X" on the carousel's stand. Your setup should now look like Figure 17.
Candle carousel completely set up
Figure 17. Place the straw's windmill onto the pointed tip of the wooden skewer, and a candle on each of the four dots around the stand's edge, and your candle carousel is ready to try out!
1. Try out your carousel to make sure it works! To do this, set it up on a flat, stable surface (such as a table or desk) that is not near any source of air movement. For example, set it up in a room with closed doors and windows, and away from any active air vents. Even a gentle breeze can completely disrupt the candle carousel's movement.
2. Now have an adult help you light all four candles. Watch to see if the candle carousel's blades (the windmill part, on top) start to spin. Again, check if the spinning movement is regular and smooth. You may need to wait for a minute before you see any movement. Once it is working, you can move on to the next section, "Testing Your Candle Carousel." If the blades do not spin after waiting for 2–3 minutes (min), try to troubleshoot by checking the following:
1. Make sure the candle flames are completely upright and are not flickering or moving sideways. If they are flickering or moving sideways, there may be air movement that is disrupting them. The flames need to be completely upright for the candle carousel to work well; if the flames are not upright, the hot air will not be moving directly upward to the blades.
2. Make sure the windmill part is sitting horizontally on the skewer (and parallel to the carousel's stand). If the windmill is tilted on the skewer, the straw may be rubbing the skewer (creating friction) and preventing the blades from spinning.
3. See if there are any other possible sources of friction that could be slowing down the blades' spinning. To do this, look at where the skewer and straw meet. The skewer should ideally only touch the aluminum on the windmill where you drew the dot (within the nut). It should not touch any double-sided tape that you used to attach the hex nut to the pie pan.
4. Make sure the blades are all at a 30° angle, and that the straight strips on the windmill are still straight and horizontal (and parallel to the carousel's stand).
5. The aluminum strip should be too light to affect the balance of the candle carousel. However, if you feel that it poses a problem, try to make it shorter or narrower to minimize its effect on the spinning behavior.
6. You could try making the skewer shorter, as this will decrease the distance that the hot air has to travel from the flames. If you do this, blow out the candles, remove the windmill part from the skewer, and try to carefully pull the skewer straight out of the Play-Doh. When you make the skewer shorter, make sure the windmill's blades will still be at least about 5 cm above the flames of the lit candles. Stick the shortened skewer straight back into the Play-Doh hole and try the candle carousel again.
Testing Your Candle Carousel
In this part of the science project, you will investigate how the amount of heat (the number of lit candles) under the carousel's blades affect how fast the blades spin. You will use Google's Science Journal app and your phone's light sensor to measure and record the speed of your carousel. This is how it works: once you shine light on your phone from above, the light sensor will read a high light intensity value. However, if something blocks the light from reaching the sensor, the light intensity will immediately decrease sharply. When you place your phone next to the candle carousel so that the aluminum strip blocks the light sensor every time it passes above it, then you will get a dip in light intensity for every rotation your candle carousel makes. From that you can derive the carousel speed, or its number of rotations per minute (or rpm). Alternatively, you can also count the carousel's rotations with the help of a stop watch.
In your lab notebook, make a data table like Table 1. You will be recording your results in this data table.
Rotations per Minute (rpm)
Number of Lit Candles Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Average
1
2
3
4
Table 1. Make a data table like this one in your lab notebook in which to record your results.
Using the Science Journal App
1. Before you start taking your measurements, make sure you know the location of the light sensor in your phone and test if it works as expected. The light sensor tutorial on the Science Journal tutorial page explains how to do this.
2. Once you have set up your carousel and tested your light sensor successfully, place the phone next to the carousel with the light sensor facing upwards. Use several books or a box to elevate your phone so it sits just underneath the aluminum strip. Position the phone so that the aluminum strip blocks the light sensor every time it is above the phone as shown in Figure 18. Make sure that the movement of the carousel is not hindered in any way.
carousel-blocks-sensor
Figure 18. Position your phone underneath the aluminum strip so that it blocks your phone's light sensor every time it passes above. Note: In this image the flashlight was mounted on a stand to hold it above the light sensor. You can also hold the flashlight with your hands.
1. Open the Science Journal app, start a new experiment, and choose the light intensity sensor. Make sure to label each recording appropriately such as "1 candle", "2 candles", et cetera.
2. Now its time to light the candles! Have an adult help you light one of the candles.
3. Wait for 3 minutes.
1. Waiting will let the heat from the flame build up and ensures that the blades are moving at a constant speed when you start taking your measurements.
4. Hold a flashlight above your phone's light sensor so that the aluminum strip passes in between your phone and the light. You can either mount your flashlight on a stand (as shown in Figure 18), tape it to a pile of books, or just hold the flashlight with your hands. If you hold it yourself, make sure to keep the flashlight at the same position and as still as possible. Every movement will affect the reading of your light sensor.
5. Observe the light sensor readings on the display of your phone. It should be relatively constant if you do not move your light source too much. You should notice that every time the aluminum strip passes above the light sensor, a dip occurs on your graph.
6. Start a new recording for your first experiment by pressing the record button on the app to measure the number of rotations of your carousel. Make sure you hold your flashlight still as long as the app is recording.
7. After about 1.5 minutes, stop recording and repeat step 8 four more times so that you have done a total of five trials for this number of lit candles.
1. Make sure that none of the testing conditions change while you perform your different trials. For example, do not move the candle carousel, and make sure the candle flame(s) remain straight and upright the entire time.
8. Once you have completed all your trials for one lit candle, look at each of your graphs. They should look something like the graph in Figure 19. You can clearly see the drop in light intensity every time the aluminum strip blocked the light from your flashlight which results in a negative peak. Pick a 60 second (or 1 minute) interval of your graph and count the number of negative peaks. Every drop represents one rotation. That means if you count the number of drops, or negative peaks, for one minute, your result will be the number of rotations per minute (rpm). In the example shown in Figure 19, the carousel made 21 rotations per minute.
9. Repeat counting the rotations per minute for each of your trials and write down your results in the table in your lab notebook.
carousel-screenshot-timing
Figure 19. Example data from the Science Journal app. The x-axis of the graph shows time in minute:seconds [min:s] and the y-axis is light intensity in lux. In your graph, choose a 60 second interval to count the number of rotations per minute for your candle carousel.
1. Repeat steps 4–11 three more times so that you have tested the candle carousel with one, two, three, or four candles lit. Make sure to name each of your recordings respectively.
1. When you light the second candle, light the one that is at the opposite side from the first candle (so that the lighting is symmetrical). For the third candle, it does not matter which candle you light.
Using a Stopwatch
1. Make a mark (like a small line) on the edge of one of the carousel's blades. It should be visible enough so that you can easily see it while the blades are spinning around.
2. Have an adult help you light one of the candles.
3. Wait for 3 minutes.
1. Waiting will let the heat from the flame build up and ensures that the blades are moving at a constant speed when you start taking your measurements.
4. Now count how many rotations the blades make in 30 seconds (sec).
1. To do this, watch the mark you made (in step 1) and orient yourself so that you can see when it goes directly above one of the candles. Then count how many times the marked blade spins above that candle in 30 sec.
2. If the blades are not spinning at all, record "0" for the rpm in the data table for this number of lit candles.
5. Multiply the number of blade rotations in 30 sec by 2 to give you your results in rpm (the number of rotations in one minute, or 60 seconds). Record your answer in your data table.
6. Repeat steps 4–5 four more times so that you have done a total of five trials for this number of lit candles.
1. Make sure that none of the testing conditions change while you perform your different trials. For example, do not move the candle carousel, and make sure the candle flame(s) remain straight and upright the entire time.
7. Repeat steps 2–6 three more times so that you have tested the candle carousel with one, two, three, or four candles lit.
1. When you light the second candle, light the one that is at the opposite side from the first candle (so that the lighting is symmetrical). For the third candle, it does not matter which candle you light.
Analyzing Your Results
1. Calculate the average number of rpm for each number of lit candles. Record your results in your data table.
1. To calculate the average, add up the numbers for each trial and then divide by the number of trials.
2. Make a line graph of your data, plotting the average rpm versus the number of candles.
1. Place the number of candles on the x-axis (the horizontal axis) and the rpm of the blades on the y-axis (the vertical axis).
3. Analyze your results. Look at your data and graph and try to draw some conclusions.
1. How does lighting more candles appear to affect how fast the candle carousel's blades spin?
2. Can you explain your results in terms of how the heat from the candles' flames makes the blades spin?
3. For a more-advanced challenge, see if you can figure out whether the relationship between the number of lit candles and the speed at which the blades are spinning is a linear relationship or if it is non-linear.
1. If it is a linear relationship, the data points should make a straight line (or a nearly straight line).
2. Why do you think you see the relationship that you do? What does this tell you about how increasing the amount of heat under the blades affects the blades' rotational speed?
If you like this project, you might enjoy exploring these related careers:
aerospace engineer testing airplane model in transonic pressure tunnel
Aerospace Engineer
Humans have always longed to fly and to make other things fly, both through the air and into outer space—aerospace engineers are the people that make those dreams come true. They design, build, and test vehicles like airplanes, helicopters, balloons, rockets, missiles, satellites, and spacecraft. Read more
wind turbine service technician climbing turbine
Wind Turbine Service Technician
Have you ever seen a wind farm or a collection of wind turbines? When the wind blows, the turbines rotate, turning the wind into energy for communities to use. But in order for the wind turbine to produce the greatest amount of energy efficiently, a wind turbine service technician must inspect, troubleshoot, repair, and ensure that the wind turbine is in good working order. This is a job that requires no fear of heights along with great mechanical aptitude and a good working knowledge of electronics. Read more
Mechanical engineer building prototype
Mechanical Engineer
Mechanical engineers are part of your everyday life, designing the spoon you used to eat your breakfast, your breakfast's packaging, the flip-top cap on your toothpaste tube, the zipper on your jacket, the car, bike, or bus you took to school, the chair you sat in, the door handle you grasped and the hinges it opened on, and the ballpoint pen you used to take your test. Virtually every object that you see around you has passed through the hands of a mechanical engineer. Consequently, their skills are in demand to design millions of different products in almost every type of industry. Read more
Aerospace Engineering and Operations Technicians
Aerospace Engineering & Operations Technician
Aerospace engineering and operations technicians are essential to the development of new aircraft and space vehicles. They build, test, and maintain parts for air and spacecraft, and assemble, test, and maintain the vehicles as well. They are key members of a flight readiness team, preparing space vehicles for launch in clean rooms, and on the launch pad. They also help troubleshoot launch or flight failures by testing suspect parts. Read more
Variations
• Another factor that could affect how quickly the candle carousel's blades spin is how close the blades are to the flames. You could repeat this science project, but this time test the candle carousel using wooden skewers of different lengths (and keep the number of lit candles constant). (Just be sure none of the skewers are so short that the blades are less than about 5 cm above the flames.) How does changing the distance between the flames and the blades affect the rotational speed of the blades?
• Changing the angle of the blades could also affect how quickly the candle carousel spins. To test this, use a protractor to carefully bend the blades to different angles (other than 30°, which is what is tested in the original science project idea). When testing a certain angle, have all of the blades bent to the same angle. What is the ideal angle of the blades? In other words, at what angle do the blades spin fastest? At what angles do the blades not spin?
• How does moving the candles affect the speed of the blades? You could test this by moving all of the candles closer to the skewer, or farther away from it. (You might want to use a stand that gives you more space than the aluminum pan.) When testing a given distance, keep all of the candles the same distance from the skewer.
• How does friction affect how well the candle carousel spins? To test this, make multiple windmill parts, and for each one try placing a different material within the end of the straw (where it is attached to the pie pan). This will change the friction that the wooden skewer experiences when it is placed in the windmill's straw. What materials work best for making the candle carousel spin? What materials work worst, or cause it to spin the slowest?
• Can you design a different candle carousel based on the design in this science project? Do some research into different types of candle carousels to get ideas, then try it out! Be sure not to use anything flammable in your design, and only use lit candles with the help of an adult.
Share your story with Science Buddies!
I did this project Yes, I Did This Project! Please log in (or create a free account) to let us know how things went.
Ask an Expert
The Ask an Expert Forum is intended to be a place where students can go to find answers to science questions that they have been unable to find using other resources. If you have specific questions about your science fair project or science fair, our team of volunteer scientists can help. Our Experts won't do the work for you, but they will make suggestions, offer guidance, and help you troubleshoot.
Ask an Expert
Related Links
News Feed on This Topic
, ,
Note: A computerized matching algorithm suggests the above articles. It's not as smart as you are, and it may occasionally give humorous, ridiculous, or even annoying results! Learn more about the News Feed
Looking for more science fun?
Try one of our science activities for quick, anytime science explorations. The perfect thing to liven up a rainy day, school vacation, or moment of boredom.
Find an Activity
|
__label__pos
| 0.873799 |
Using Laravel’s Localization in JS
Laravel provides an awesome and easy to use translation system. When we render our content on the back-end only, there is almost nothing to do but translate the strings in every language we need. But what if our app is a SPA and we still want to use the translations what Laravel provides? We can work around a bit to solve this issue.
Localization with Laravel
In modern web apps, it’s almost a requirement to provide internationalization (I18n) for the seamless and easier use. On the back-end side, we have an easy job, all we have to do, is to get familiar with the translation system and use it!
We can store our language files in the resources/langs directory. By default, we have an en folder where the language files are stored. We can add new languages to the system by copy the files in a folder what named by the ISO 639-1 code of the language. For example Hungarian is hu, Romanian is ro, French is fr and so on.
To get the current language, we can use the config(‘app.locale’) function or the App::getLocale() method. Also to set the language we can use the App::setLocale($lang) method, where the parameter is the correct ISO 639-1 code of the language.
The translator automatically gets the currently set language and retrieves the text what we need. We can use the trans() function and the @lang directive to translate the desired strings of the given key.
// Function
trans('auth.failed');
// Blade Directive
@lang('auth.failed');
We stop here because this post is not about back-end translation. But for sure you have a lot of options, like pluralization, JSON based translations and so on. Read the documentation to learn more about the API and the features.
Push the Translations Into a JS Object
We need to make our translations accessible on our front-end. There are many solutions to do that, we chose what we found the simplest in this case.
First of all, create a new service provider called TranslationServiceProvider to generate a JSON of all the translations. Then we should cache the results because it’s not changing often and it’s good to pay attention to the performance. As the last step, we need to print the JSON out and assign to the window object.
// app/Providers/TranslationServiceProvider.php
<?php
namespace App\Providers;
use Illuminate\Support\Facades\App;
use Illuminate\Support\Facades\File;
use Illuminate\Support\Facades\Cache;
use Illuminate\Support\ServiceProvider;
class TranslationServiceProvider extends ServiceProvider
{
/**
* The path to the current lang files.
*
* @var string
*/
protected $langPath;
/**
* Create a new service provider instance.
*
* @return void
*/
public function __construct()
{
$this->langPath = resource_path('lang/'.App::getLocale());
}
/**
* Bootstrap the application services.
*
* @return void
*/
public function boot()
{
Cache::rememberForever('translations', function () {
return collect(File::allFiles($this->langPath))->flatMap(function ($file) {
return [
($translation = $file->getBasename('.php')) => trans($translation),
];
})->toJson();
});
}
}
Don’t forget to register your provider in the config/app.php!
The code above makes nothing, but scan the directory named of the current language, then push the contents into a collection instance, make some modification and as a result generate a JSON format of the collection. Then we cache the result to make it accessible anywhere and to make it faster later.
There is nothing left but push the cached translations to the front-end. We can do just before the closing body tag.
<script>
window.translations = {!! Cache::get('translations') !!};
</script>
Now we have the same translations on back-end and front-end too. But still, we need a translator on the JS side as well to get the proper strings by the given key.
The Translator Implementation in JS
Let’s stop here and think a bit about the functionality what we need here. Write a list of the features, it may help.
1. We need the basic features of Laravel’s translator
2. We want to retrieve a string paired with the given key
3. We want to replace placeholders
4. We want to pluralize
Start with the basics, let’s retrieve a string matched with the given key. Then try to replace the placeholders if we can. The placeholders have a special syntax, all of them starts with an : . It makes our life a bit easier to have this convention, we can replace them easily.
To make the code familiar we follow Laravel’s naming conventions.
function trans(key, replace = {})
{
let translation = key.split('.').reduce((t, i) => t[i] || null, window.translations);
for (var placeholder in replace) {
translation = translation.replace(`:${placeholder}`, replace[placeholder]);
}
return translation;
}
We accept a key (like auth.failed, pagination.next), and an object, where the placeholder is the key without the colon and the value is the string what we need. For example:
{
attempts: 30,
attribute: 'Name'
}
Note, we could use lodash (_) to get values of an object, also to replace strings. For more complex things it’s cannot be avoided.
It’s working well, so we can move on the pluralization part. Laravel uses the trans_choice() to pluralize strings. The first parameter is the key, and the second one is the count. If the second argument is bigger than 1, the function returns the pluralized version. We need to separate the singular and the plural versions with an | character. For example:
[
'attempts' => 'Be careful, you have :attempts attempt left.|You still have :attempts attempts left.',
]
So we need to do some extra work, but basically, we can copy-paste the code we have in the trans() function. We need to determine if the count is bigger than one and return with the proper part of the translation.
function trans_choice(key, count = 1, replace = {})
{
let translation = key.split('.').reduce((t, i) => t[i] || null, window.translations).split('|');
translation = count > 1 ? translation[1] : translation[0];
for (var placeholder in replace) {
translation = translation.replace(`:${placeholder}`, replace[placeholder]);
}
return translation;
}
Summary
Now we have a fully functional translation tool that uses the same source what Laravel provides. No need for AJAX requests or any special things, it’s simple and works well. Also, it’s very easy to integrate with Vue or other frameworks.
You can find the whole code what we use at this GitHub repo.
If you have an idea how to improve or extend it, please let us know! Thank you!
Need a web developer? Maybe we can help, get in touch!
Looking for web dev job?
You can check them on Jooble.
To see and write comments, you must allow the related (Disqus) cookies. For more information, please visit our privacy policy page.
Similar Posts
More content in Laravel, JavaScript category
|
__label__pos
| 0.936811 |
Navigation and service
Electromagnetic fields
Mobile communication, WLAN & Co. - Grid expansion - Household appliances & electric installations
Elektromagnetische Felder
Effects
High frequency electromagnetic fields are absorbed by biological systems and lead, above all, to a warming of the tissue. The physical basis of this thermal effect is well known and beyond dispute.
It is questionable, however, if there are non-thermal biological effects in the region of low intensities of high frequency radiation. Their existence has not been proven up to now but intensive research in this field is going on.
Proven effects
Radiofrequency electromagnetic fields are absorbed by the body and may subsequently provoke various effects.
The strength of the energy absorption depends on the strength and the frequency of the electromagnetic fields, but also on the properties and structures of the biological tissue. Forces and heating due to radiofrequency electromagnetic fields are clearly proven and physically defined.
Classification of high frequency electromagnetic fields by the IARC
In May 2011, the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO) analysed the current knowledge of high frequency electromagnetic fields and cancer illnesses and classified these fields into Group 2B "possibly carcinogenic" on the IARC scale. This classification means that according to the estimation of the IARC, based on current knowledge, there are limited indications that high frequency electromagnetic fields have a carcinogenic effect on humans.
Scientifically discussed effects
The existence of health effects below the limit values was neither confirmed by the results of the DMF, nor by other up-to-date studies conducted on national or international levels. Non-thermal health effects were not proven. Long-term effects for periods of use exceeding a decade remain an open issue. Therefore, further research is conducted into this question.
© Bundesamt für Strahlenschutz
|
__label__pos
| 0.597979 |
Exercise And Chronic Disease
An abundance of scientific literature has overwhelmingly confirmed the health related benefits of exercise for apparently healthy populations. And likewise, individuals with a diagnosed chronic disease or disability benefit as much if not more from regular physical activity as do apparently healthy individuals. As a result, these individuals as determined and directed by their physician often choose health dub settings to carry out their exercise program. As a fitness instructor, it is imperative to develop a basic understanding of certain-chronic diseases and disabilities, and the effects that exercise has on them.
Understanding the precautions that exist with those individuals with a chronic disease will help to provide safe and effective exercise instruction. Although an in-depth discussion of the specific diseases is warranted, it is beyond the scope of this manual. The following discussion is to provide a brief overview of some of the major chronic diseases fitness instructors might encounter in a fitness facility. Fitness instructors should keep in mind that their role is to improve participant well-being through the design and implementation of exercise services-not to treat or alleviate adverse health conditions or disease.
General Guidelines Review the medical history questionnaires before the first exercise session.
• Follow the American College of Sports Medicine’s (ACSM} guidelines for risk factor stratification and the recommendations for seeking a medical clearance. Know the emergency procedures of your facility.
• Use the Borg RPI scale and
• be able to teach participants how to use lr.
• Don’t pretend to know everything; ask questions. If you don’t feel comfortable working with certain individuals. explain why, and have them obtain specific exercise recommendations from their doctors, or refer them to a medically supervised program or to a clinical exercise physiologist.
• Remember the team approach- physician, particlpant or patient, and instructor all work together to make the exercise training safer and more effective.
Asthma
Asthma is a common respiratory problem affecting more than 20 million Americans, including 9 million children under the age of 18 (American Lung Association, 2005). It is a reactive airway disease caused by constriction of the smooth muscle around the airways, swelling of the mucosal cells, and increased secretion of mucus. Persons diagnosed with asthma experience defining characteristics, including coughing, wheezing, and dyspnea (shortness of breath). Extrinsic or intrinsic factors cause asthma. Extrinsic factors are external irritants, such as pollen, cigarette smoke, and air pollution, whereas intrinsic asthma is the result of internal factors, such as a bacterial respiratory tract infection attacking the body. A large percentage of the population experiences exercise-induced asthma (ETA, also known as exercise-induced bronchospasm) which is a moderate obstruction of the airway that is not life threatening. Although asthma is not a contraindication to exercise, those who have been diagnosed with asthma should first consult with a physician, then follow specific guidelines for their exercise program.
Exercise Guidelines for Asthma
1. Prior to beginning the exercise program, the participant should consult with his/her physician and, in accordance with that consultation, develop a medication and treatment plan to prevent EIA attacks.
2. A bronchodilating inhaler should be available at all times during the exercise session. It should be used at the onset of symptoms.
3. Exercise intensity should start low then gradually increase as the participant’s body adapts to physical activity.
4. Avoid exercising outdoors in extreme cold or when pollen levels are high.
5. A humid exercise environment is best. Many people with asthma find that water exercise is especially well-tolerated.
6. Use of an inhaler prior to exercise often reduces the likelihood of experiencing an EIA attack.
7. Breathing through the nose or with pursed lips may reduce or dissipate symptoms during exercise.
8. An extended warm-up and cool-down should be practiced.
Heart Disease
Heart disease affects one out of every two people in the United States. It’ is the leading cause of death in the U.S. and in most of the developed world, and the number of cases continues to increase despite repeated warnings reported by scientific research. Atherosclerosis, narrowing of the coronary arteries, is the primary contributing factor for the development of the disease. This narrowing causes reduced blood flow to the heart, producing angina (chesteain), and ultimately myocardial infarction or heart attack. Atherosclerosis of the cerebral blood vessels can lead to a stroke, or death of brain tissue. The risk of stroke is greatly increased with people with hypertension (high blood pressure). Cardiorespiratory fitness has been found to significantly influence risk of death, and offers strong support that both regular physical activity and high levels of fitness protect against atherosclerotic heart disease. As a result, sedentary lifestyle, or physical inactivity, has been labeled a primary risk factor for heart disease. Other risk factors are (a) age, (b) family history, (c) hypertension, (d) high cholesterol, (e) cigarette smoking, (f) prediabetes, and (g) obesity.
Exercise Guidelines for Heart Disease
1. Participants should be screened for heart disease risk factors prior to beginning an exercise program. Participants who are male and 45 years of age or older, or who are female and 55 years of age or older, or who report two or more major atherosclerotic cardiovascular disease (CVD) risk factors are considered to be at moderate risk for heart disease. Participants with known cardiac, pulmonary, or metabolic disease and/or symptoms suggestive of heart disease are considered to be at high risk for heart disease and complications. The ACSM recommends that both moderate and high risk participants obtain a release from a physician before starting an exercise program.
2. Guidelines prescribed by the physician for a participant with heart disease, pulmonary disease, or metabolic disease should be strictly followed.
3. A record of current medications and their effects on exercise should be developed and reviewed with a participant in conjunction with his/her health care provider before initiating the exercise program.
4. Comply with the target heart rate range and RPE guidelines for each participant, recommended by his or her physician.
5. The participant should be instructed to alert the fitness instructor should any signs or symptoms develop before, during, or after exercise.
6. Do not exceed your level of expertise. It may be more prudent to refer high-risk participants to a medically supervised program or to a clinical exercise physiologist.
7. Exercise intensity should start low then gradually increase as the participant’s body adapts to physical activity. High-intensity exercise is not recommended without specific permission from the participant’s physician.
Arthritis
Osteoarthritis may happen to adult over 70 years of age, and rheumatoid arthritis for about 3% of women and 1% of men in the U.S. population. A degenerative process, osteoarthritis is the wearing away of cartilage between two bones, allowing bony contact to occur, whereas rheumatoid arthritis is caused by inflammation of the membrane surrounding joints. This inflammation is often associated with pain and swelling in one or more joints. Exercise is generally recommended by health care providers for those with arthritis to improve muscular strength and endurance around the affected joints, increase joint range of motion and flexibility, decrease pain and stiffness, improve motor coordination, and improve total body fitness. During a severe arthritic bout, vigorous exercise should be avoided as it can exacerbate flare-ups. However, gentle stretching is usually well tolerated and may help relieve pain.
Exercise Guidelines for Arthritis
1. Exercise classes, such as low-impact cardio, stationary indoor cycling, and water exercise, should be encouraged. These classes should avoid quick, ballistic movements that can be painful for the arthritic participant.
2. Frequent, low-intensity exercise sessions should be performed. Decrease intensity and duration of exercise during severe bouts of pain or inflammation.
3. Gently move every joint every day, enhancing mobility of both muscles and joints.
4. Help the participant with appropriate weight loss and weight management strategies, if necessary.
5. An extended warm-up and cool-down period is advised to help minimize pain.
6. Monitor all changes in medication and fluctuations in pain levels with the disease, and have the participant consult with his or her appropriate medical professional.
7. Be aware of the 2 hour pain rule: if pain persists, reduce the intensity or duration in future sessions.
8. Obesity and overweight are risk factors for osteoarthritis.
Diabetes Mellitus
The two most common forms of diabetes mellitus include (a) insulin dependent diabetes mellitus (IDDM), or type I, and (b) non-insulin dependent diabetes mellitus (NIDDM), or type 2. Both types of diabetes are characterized by high blood glucose levels, also known as hyperglycemia. Approximately 7% (21 million) of the American population has diabetes mellitus, and the numbers continue to increase (National Diabetes Fact Sheet, 2005). IDDM, commonly known as juvenile-onset diabetes, occurs when the body does not produce insulin. As a result, daily injections of insulin must be taken to regulate glucose levels in the body. Approximately 10°/ri of people with diabetes are diagnosed with type 1 diabetes. Type 2 diabetes is the most common form, affecting about 90-95% of those with diabetes. Largely due to obesity and physical inactivity; persons with type 2 diabetes cannot efficiently use the insulin they produce. Type 2 diabetes usually requires nutrition therapy and occasionally pharrnaco-logical therapy. However, current research suggests that type 2 diabetes can be prevented, and even alleviated, through proper nutrition and regular participation in an exercise program. While the provision of service to prevent or treat such conditions by non-licensed personnel is prohibited by Jaw, fitness professionals can assist in improving the well-being of people with diabetes. It is important to note that individuals with diabetes require special attention in exercise programming due to special needs. As a fitness instructor, adherence to these guidelines will provide safe and effective exercise for the participant with diabetes.
Exercise Guidelines for Individuals with Diabetes
Frequency: 3-7 days per week
Intensity: 50-80% HRR or RPE of 12-16 on the 6-20/15-point scale
Duration: 20-60 minutes per day continuous or accumulated in bouts of atleast 10 minutes to total 150 minutes per week of moderate physical activity
Type: Activities that use large muscle groups in a rhythmic and continuous fashion
Resistance training should be encouraged, following the general guidelines for apparently healthy individuals, as long as the participant is free from any contraindications (e.g., signs/symptoms of cardiovascular disease, retinopathy, and recent laser treatments).
Frequency: 2-3 days per week
Intensity: low resistance; gradual progression; 2-3 sets of 8-12 repetitions (at 60-80% I-RM)
Time: 20-60 minutes (or time to complete 8-10 multi-joint exercises; sessions may vary based on training protocol)
Type: Free weights, weight machines, elastic tubing
Hypertension
Hypertension, or high blood pressure, is a disease affecting approximately 65 million individuals in the U.S. Hypertension occurs more frequently in African American individuals, and it is a major risk factor for cardiovascular disease and stroke. Hypertension places undue stress on the heart, increasing left ventricular wall thickness, and reducing diastolic filling. Recent research reports that regular physical activity can decrease blood pressure.
Exercise Guidelines for Hypertension
1. Emphasize cardio exercise, such as walking, jogging, cycling, or swimming, in order to help reduce high blood pressure. Individuals exhibiting elevated blood pressure should exercise at lower intensities (40-70% of HRR).
2. Exercise should be performed on most days of the week in 30-60-minute sessions.
3. High-intensity activities and isometric activities should be avoided.
4. For resistance training, repetitions should be high and weight should remain low. Avoid resistance training to the point of failure, even if the weights are light.
5. Avoid the Valsalva maneuver, as it increases vascular pressure.
6. Utilize RPE as certain hypertensive medications alter heart rate during exercise.
7. Avoid positions in which the feet are higher than the head.
8. Teach relaxation and stress management techniques.
Summary
Exercise therapy for individuals with chronic disease is accepted and practiced by clinicians in many diverse health care settings. More than likely, fitness instructors will encounter individuals who have been diagnosed with a disease that requires special considerations and guidelines regarding exercise. It is to such instructors’ advantage to continue learning about special populations. For more information on certification programs and workshops in this field, instructors should contact the American College of Sports Medicine.
Leave a Reply
|
__label__pos
| 0.930241 |
72 votos
¿Cómo devolver una respuesta JSON compleja con Node.JS?
Usando nodejs y express, me gustaría devolver uno o múltiples objetos (Array) usando JSON. En el código de abajo devuelvo un objeto JSON a la vez. Funciona pero esto no es exactamente lo que quiero. La respuesta producida no es una respuesta JSON válida ya que tengo muchos objetos.
Soy consciente de que podría simplemente añadir todos los objetos a un Array y devolver ese Array específico en res.end. Sin embargo, me temo que esto podría llegar a ser pesado de procesar y de memoria intensiva.
¿Cuál es la forma correcta de lograr esto con nodejs? ¿Es query.each el método correcto a llamar?
app.get('/users/:email/messages/unread', function(req, res, next) {
var query = MessageInfo
.find({ $and: [ { 'email': req.params.email }, { 'hasBeenRead': false } ] });
res.writeHead(200, { 'Content-Type': 'application/json' });
query.each(function(err, msg) {
if (msg) {
res.write(JSON.stringify({ msgId: msg.fileName }));
} else {
res.end();
}
});
});
172voto
zobi8225 Puntos 1490
En express 3 puedes usar directamente res.json({foo:bar})
res.json({ msgId: msg.fileName })
Ver el documentación
17voto
danmactough Puntos 1992
No sé si esto es realmente diferente, pero en lugar de iterar sobre el cursor de la consulta, podrías hacer algo así:
query.exec(function (err, results){
if (err) res.writeHead(500, err.message)
else if (!results.length) res.writeHead(404);
else {
res.writeHead(200, { 'Content-Type': 'application/json' });
res.write(JSON.stringify(results.map(function (msg){ return {msgId: msg.fileName}; })));
}
res.end();
});
12voto
maerics Puntos 47743
[Editar] Después de revisar la documentación de Mongoose, parece que se puede enviar cada resultado de la consulta como un trozo separado; el servidor web utiliza codificación de transferencia en trozos por defecto por lo que todo lo que tienes que hacer es envolver un Array alrededor de los elementos para convertirlo en un objeto JSON válido.
Aproximadamente (sin probar):
app.get('/users/:email/messages/unread', function(req, res, next) {
var firstItem=true, query=MessageInfo.find(/*...*/);
res.writeHead(200, {'Content-Type': 'application/json'});
query.each(function(docs) {
// Start the JSON array or separate the next element.
res.write(firstItem ? (firstItem=false,'[') : ',');
res.write(JSON.stringify({ msgId: msg.fileName }));
});
res.end(']'); // End the JSON array and response.
});
Alternativamente, como mencionas, puedes simplemente enviar el contenido del Array tal cual. En este caso el cuerpo de la respuesta se almacenará en el buffer y se envían inmediatamente, lo que puede consumir una gran cantidad de memoria adicional (por encima de la necesaria para almacenar los propios resultados) para conjuntos de resultados grandes. Por ejemplo:
// ...
var query = MessageInfo.find(/*...*/);
res.writeHead(200, {'Content-Type': 'application/json'});
res.end(JSON.stringify(query.map(function(x){ return x.fileName })));
Iteramos.com
Iteramos es una comunidad de desarrolladores que busca expandir el conocimiento de la programación mas allá del inglés.
Tenemos una gran cantidad de contenido, y también puedes hacer tus propias preguntas o resolver las de los demás.
Powered by:
X
|
__label__pos
| 0.982347 |
FabienM FabienM - 1 year ago 78
Scala Question
What does '&' and '%' mean in operators -&, -%, +&, +% in Chisel3?
I'm trying to learn Chisel3 with the GCD example given in official web page. This example use operator named -%, what does that mean ?
It's not explained on Wiki operator page. And Cheatsheet says "substraction" as the normal substraction symbol '-'.
Then what is the difference between simple substraction '-' and percent substraction '-%' ?
[edit]
Ok, I found the definitions of these functions under chisel3 code :
// TODO: refactor to share documentation with Num or add independent scaladoc
def unary_- : UInt = UInt(0) - this
def unary_-% : UInt = UInt(0) -% this
def +& (other: UInt): UInt = binop(UInt((this.width max other.width) + 1), AddOp, other)
def + (other: UInt): UInt = this +% other
def +% (other: UInt): UInt = (this +& other) tail 1
def -& (other: UInt): UInt = binop(UInt((this.width max other.width) + 1), SubOp, other)
def - (other: UInt): UInt = this -% other
def -% (other: UInt): UInt = (this -& other) tail 1
def * (other: UInt): UInt = binop(UInt(this.width + other.width), TimesOp, other)
def * (other: SInt): SInt = other * this
def / (other: UInt): UInt = binop(UInt(this.width), DivideOp, other)
def % (other: UInt): UInt = binop(UInt(this.width), RemOp, other)
def & (other: UInt): UInt = binop(UInt(this.width max other.width), BitAndOp, other)
def | (other: UInt): UInt = binop(UInt(this.width max other.width), BitOrOp, other)
def ^ (other: UInt): UInt = binop(UInt(this.width max other.width), BitXorOp, other)
With & operator the result of substraction or addition will be the size of the bigest operand plus one bit.
But with % operator the result of operation will be the size of the bigest operand ... as with normal + or -. Then what is the difference between - and -% and between + an +% ?
Answer Source
My apologies for not including this information on the Wiki operator page, I will add it shortly.
You have hit the nail on the head with your edit: +& and -& are expanding operators in that the width of the result is equal to the size of the widest operand plus 1. +% and -% are non-expanding operators in that the width of the result is equal to the widest operand.
+ just aliases to +% while - aliases to -%.
Recommended from our users: Dynamic Network Monitoring from WhatsUp Gold from IPSwitch. Free Download
|
__label__pos
| 0.997221 |
Oil Spill Response Resources: Use of Respiratory Protection
C. Use of Respiratory Protection
A decision to use respiratory protection should be based on the best available qualitative information using the expert opinion method and on the best available comprehensive quantitative information about the type and level of exposure to toxic chemical and physical agents by the inhalational route. The use of effective engineering and administrative controls, and other personal protective equipment should be implemented before the use of respirators for worker protection is considered.
1. Source Control Activities
The source control vessels conduct activities closest to the area where crude oil appears on the surface, including drilling relief wells, conducting underwater operations at the source including dispersant application, and providing support and supplies. If surface application of dispersant is deemed necessary, it should be applied at a safe distance from vessels operating in the area. Variable concentrations of hydrocarbons are likely present in the air in and around these vessels. Engineering and administrative controls should be used to control hydrocarbon vapor levels during source control activities, but exposures to crude oil-derived VOCs and other constituents may not be eliminated entirely. Significant spikes in concentrations may occur unexpectedly, and would necessitate donning a respirator especially when engineering and administrative controls cannot provide protection.
For workers involved in source control activities, respirators should be used in those situations where potentially excessive exposure is reasonably anticipated or where indicated by exposure assessment or where symptoms/health effects are being reported. Where eye protection is not needed against irritating gases/vapors, NIOSH and OSHA recommend using a half facepiece respirator. If eye protection is needed, NIOSH and OSHA recommend a full facepiece elastomeric respirator with an organic vapor/P100 cartridge. A full facepiece respirator provides eye protection against irritating gases/vapors and a relatively high level of respiratory protection when exposures are variable and potentially higher. Cartridges including P100 particulate filters (oil resistant) are recommended over N95 filters (not resistant to oil aerosols). The combination organic vapor/P100 cartridge provides comprehensive protection against both particulates and gases and vapors, and the P100 filter provides some protection against water mist for the organic vapor filter component.
2. Off-Shore Activities
a. Vessels Involved in Burning Crude Oil
Vessels involved in crude oil burning are exposed to crude oil/dispersant that is less aged and may emit more VOCs than crude/dispersant closer to shore that may have undergone more weathering. The primary hazards from in-situ burns are likely to be heat, exposure to products of combustion and, rarely, flash fire. Some vessels engaged in burning may be working in close proximity to source control activities.
Products of combustion will include a complex mixture of particulate matter, smoke and soot; VOCs such as partially oxidized alcohols, aldehydes, and ketones; metals like vanadium, chromium, and nickel; and gases such as carbon dioxide and carbon monoxide.27,28 The chemical composition of these emissions will vary based on the oil composition, weather conditions during each burn, and the completeness of the combustion process. When in-situ (i.e., on-site) burns are conducted, they should be conducted remotely with all vessels positioned upwind at an adequate distance away from the resultant smoke plume. Every effort should be made to keep workers from the area of the smoke plume, and to evacuate them as quickly as possible when changing conditions may put them in the area of the contaminants of the burn.
Under ideal conditions, vessels will be located a sufficient distance upwind from burns, and respiratory protection may not be necessary. The employer should assess the specific job tasks before the burning activity to evaluate potential worker exposures and then select respiratory protection and other PPE according to the results of their evaluation. Respiratory protection will be needed, however, when shifts in wind cause exposure to the combustion products in the plume. Under such circumstances, or where symptoms/health effects are being reported, inhalational exposure may occur and NIOSH and OSHA recommend respiratory and eye protection.
For unexpected exposures, protection can be provided by use of a full facepiece elastomeric respirator with an organic vapor/P100 cartridge. A full facepiece respirator is preferred because it provides both eye protection against irritating smoke and an appropriate level of respiratory protection. Cartridges including P100 particulate filters (oil resistant) are recommended over N95 filters (not resistant to oil aerosols). The combination organic vapor/P100 cartridge provides comprehensive protection against soot, gases and vapors. Another means of protection is non-vented safety goggles to prevent eye irritation and a half-mask respirator with an organic vapor/P100 cartridge.
Note: Flame resistant clothing will help protect workers, for instance, such as those workers in the igniter boat during in-situ burning. The clothing should be cleaned, maintained, and regularly inspected in accordance with the manufacturer’s instructions. Some flame resistant clothing may lose its protective qualities after repeated or improper cleanings. Wearing any flammable clothing over flame resistant clothing will negate the flame resistant protection. Flame resistant clothing should be selected in accordance with 29 CFR Subpart I (Personal Protective Equipment), Section 1910.132, General Requirements.
b. Vessels Not Involved in Source Control or Burning
Some vessels operating off-shore engage in deployment of containment and sorbent booms, skimming operations to remove oil from the water, and dispersant application. These vessels are not involved in burning nor are they located in close proximity to in-situ burning. Generally, these vessels have contact with oil that has weathered, and, as such, does not emit significant amounts of VOCs. Respiratory protection generally will not be necessary as symptoms/health effects are not expected to occur in this setting. Dermal protection is needed.
Other vessels not involved in burning may operate at a farther distance from shore and possibly encounter more volatile crude. In this case, administrative controls (e.g., worker rotation and decrease in work hours) and respiratory protection (e.g., half-mask elastomeric respirator with an organic vapor cartridge) should be implemented where symptoms/health effects are being reported.
Note: Representative and routine air and personal breathing zone monitoring should be conducted to verify that unsafe exposures are not occurring, especially when these vessels operate in areas where partially weathered crude oil exist.
3. Shoreline Clean-up Activities
The types of activities associated with shoreline cleaning include manual removal of “tarballs” or “tarpatties,” shovel removal of oiled-contaminated sand, low pressure flushing, manual sorbent application, and manual cutting of vegetation. Since inhalational exposure to oil and dispersants during shoreline clean-up operations is low because of weathering, respiratory protection is not recommended. However, if symptoms/health effects occur, the affected worker(s) should be removed and evaluated medically, and then the worksite should be assessed for potential exposure to heat and VOCs for the remaining workers.
Note: If high pressure washing is conducted, aerosolization of oil mist into respirable droplets could occur and respiratory protection is recommended with use of at least the level of a disposable P100 filtering facepiece respirator. The use of highly concentrated detergents, degreasers, and solvents, and the use of heated water during pressure washing, may volatilize hydrocarbons and result in the need for respiratory protection. Respiratory protection, if deemed necessary by professional judgment and/or air monitoring results, should include the use of a combination organic vapor/P100 cartridge half mask respirator. Eye and skin protection during such activities also will be necessary.
4. Decontamination Activities
a. PPE and Other Equipment
Vessels, PPE and other equipment may become contaminated with weathered oil. Respiratory protection is generally not necessary for this activity, although other PPE, including dermal, eye, face protection and protective footwear is necessary. If a high pressure washing mechanical sprayer is used to decontaminate PPE and other equipment, respirable particle aerosolization of oil mist could occur. When there is potential exposure to oil mist, particulate respiratory protection of at least the level of a P100 disposable filtering facepiece respirator is recommended in addition to skin, eye, face protection and protection footwear, particularly if highly concentrated detergents, solvents or degreasers are used.
b. Cleaning Wildlife
Task observations of cleaning and caring for birds, turtles and other wildlife indicate that aerosols of water, crude oil, soap, ammonia and other chemicals are likely to be generated. Eye and face protection, in addition to skin protection is recommended. When irritating concentrations of ammonia are experienced, dilutional ventilation, for example, by means of fans and other means to increase air exchange, are recommended.
Recommended PPE includes eye protection, i.e., safety glasses, goggles or face shields. Birds will peck under stress and may aim for the eyes. Eye protection is also necessary to protect against large droplet sprays from struggling birds. Oil-resistant outer protective clothing is recommended. An oil-resistant gown may provide sufficient upper body protection, avoiding the need for coveralls. Gloves (neoprene or nitrile rubber) that are oil resistant and provide protection against pecking and sharp talons are recommended. Non-skid footwear or boots that are oil-resistant and waterproof are also recommended.29 Respiratory protection is not generally recommended, unless wildlife is heavily coated with fresh crude oil. In such cases, a half mask respirator with an organic vapor cartridge is recommended.
5. Waste Stream Management Activities
Response and remediation workers are engaged in the disposal and recycling of hazardous solid and liquid wastes during collection, storage, transport and final disposal. Deepwater Horizon Response waste management workers are at risk of a number of hazards including falls, other musculoskeletal injury, and dermal exposure to the components of the waste stream. Waste stream management workers should be trained, provided appropriate PPE, and have their work activities monitored for exposure in compliance with applicable state and Federal laws and regulations. 30
Page last reviewed: June 25, 2010
|
__label__pos
| 0.535442 |
id summary reporter owner description type status component version severity resolution keywords cc stage has_patch needs_docs needs_tests needs_better_patch easy ui_ux 17461 Document presumed order of foreign keys on intermediate M2M model flytwokites@… Oxylo "When defining a many-to-many relationship from a model to itself and using an intermediary model, {{{ class User(models.Model): name = models.CharField(max_length=100) followers = models.ManyToManyField('self', through='Relationship', symmetrical=False) def __unicode__(self): return self.name class Relationship(models.Model): target = models.ForeignKey('User', related_name='r1') follower = models.ForeignKey('User', related_name='r2') created_at = models.DateTimeField(auto_now_add=True) }}} It seems that django determine 'from field' and 'to field' by it's definition order, the first field always used as 'from field' and the second field always used as 'to field'. So I MUST put `target` field defintion above the `follower` field. I checked the document but can not found any infomation to confirm it, I think the document should clearly explained the rule." Cleanup/optimization assigned Documentation 1.3 Normal Accepted 0 1 0 0 0 0
|
__label__pos
| 0.937906 |
best acne scar treatment in chennai
2 years ago 782 Views
Acne is generally a temporary concern, but the acne scarring can be permanent. Acne scars are a nightmare as it affects appearance and self-confidence. Due to skin breakouts, you may experience pick marks on the face and other body parts. Let’s first understand acne, which can be Mild, Moderate, or Severe:
• Mild Acne: These are few with fairly minor breakouts. It causes less inflamed white or blackheads, with or without a few red bumps, and the blemishes aren’t widespread. It is best to treat Mild Acne as early as possible, as it can progress to a severe form. Mild acne can be treated by over-the-counter acne treating products.
• Moderate Acne: In moderate acne, breakouts are more visible, and they may cause red bumps and puss-filled zits. Over-the-counter products aren’t strong enough to treat this acne type. Prescription medications are needed to clear up moderate breakouts.
• Severe Acne: In severe acne, blemishes are large, red, and swollen. The most significant distinction between Moderate and Severe Acne is inflammation. Severe acne can develop painful, pus-filled lesions beneath the skin’s surface, known as nodules or cysts. If you are experiencing such severe acne, you must visit the best Dermatologist in Chennai.
Causes of Acne Scarring
One cause of acne scars is an inflamed lesion, such as a papule, pustule, or cyst. An inflamed blemish occurs when the pore, or follicle, becomes clogged with oil, dead cells, and bacteria. Let us understand how acne forms to begin. Acne goes through three stages. The first stage is triggered by excess oil production due to hormonal changes such as excess androgen, regardless of age. Dead skin cells and dirt, excess oil clogs your pores develop as whiteheads and blackheads, which can last a few days.
The pimple appears as a visible red papule during the middle stage, also known as inflammatory acne. A bacteria starts to attack the skin and grows as a spot, lasting up to a week. The white fluid we see inside acne is a reaction to inflammation, and the body’s immune system responds to the growing bacteria there. Since this is the stage where it is most visible, there is a tendency to burst it as a way to try and alleviate it. The final stage of the pimple is when it dries and begins to crust on its way out of your skin, bringing the chances of leaving a scar.
Different Types of Acne Scarring
Some people do not experience acne scarring. But most people have to deal with acne scars at some point in their lives. Acne scarring can vary depending on the type of acne you get and how you treat it. Different kinds of Scars include:
Atrophic Scars
These are indented scars that heal below the normal layer of skin tissue. Atrophic Scars occur when the skin cannot regenerate tissue, resulting in imbalance scarring. Its spots can appear differently depending on a person’s acne history. There are three types of Atrophic Scars:
• Boxcar Scar: A boxcar scar is a broad or oval depression in the skin that develops after some acne heals. These scars occur because of widespread acne, chickenpox, or varicella, which causes an itchy, red rash with blisters.
• Ice pick Scar: Acne erupts when pores on your skin get clogged. After acne has healed, it leaves ice pick scars. Ice pick scars are acne scars that have a pitted or sunken appearance. They tend to be very tough to treat and often require long-term, rigorous treatment.
• Rolling Scar: Rolling scars have varied depths and sloping edges, giving the skin a wavy and uneven appearance. They can happen because of the bands of scar tissue that form under the skin.
Hypertrophic and Keloid Scars
Hypertrophic and Keloid scars form as raised lumps of scar tissue where the acne used to be, unlike Atrophic scars. It occurs when scar tissues build-up due to previous acne spots. A hypertrophic scar remains the same size as the acne that caused it. On the other hand, keloid scars can grow beyond the sides of the original acne spot and larger than the acne that caused them. Hypertrophic and keloid scars appear on the jawline, chest, back, and shoulders. People with dark skin color are more likely to develop this type of scarring.
Ways to Prevent Acne Scarring
You can take mindful steps to prevent acne scars and minimize the appearance and size of the acne. Here’s what you can do as soon as acne develops.
Treat the Acne scarring ASAP
Begin treating the acne as soon as it is there. Quick treatment helps to minimize breakouts and prevents acne from turning into a more severe form. If over-the-counter treatments aren’t doing any good to your skin, you should see the Dermatologist right away.
Reduce the Inflammation
Inflamed acne is more likely to leave deep acne scars behind than non-inflamed breakouts. Avoid anything that will further irritate the skin, and the goal should be to calm the inflammation. Do not use harsh skin care products or scrub aggressively.
Resist popping pimples
As tempting as it might look, you should always try not to squeeze, pick or pop the acne. It can push debris deep into the dermis, spreading the infection to other tissues and worsening the inflammation.
No picking at Scabs
Leave the scabs alone as they are the skin’s natural “band-aid,” which heals the wound. Taking a scab off an injury before it heals can prolong the healing process and increase the risk of scarring.
Sunscreen is Vital
Sunscreen, in general, is an essential part of the skincare regime. It protects you from so many skin problems. Use a safe and effective sunscreen (preferably SPF30 and above) daily to prevent the cells in acne from developing melanocytes. Excess melanocytes can darken the skin and is the reason for discoloration in acne scars.
Consult a Dermatologist
Acne is most common in teens; however, it can appear at any age. Acne is different at different life stages and will need age-specific treatment. Although, few scar treatments will minimize the appearance of acne scarring. Though you can treat mild acne vulgaris with drugstore products, any other kind or severity warrants a dermatologist’s attention. Studies suggest Microneedling, and Non-ablative fractional erbium lasers are some of the best options for acne scarring.
Best Clinic in Chennai for Treating Acne Scarring
Chances are, one may still develop acne scars despite all the efforts done to prevent them. In that case, don’t hesitate to consult a dermatologist. Welona, Slimming, Skin and Hair clinic in Chennai can suggest the best acne and acne scars treatment. Book an appointment with Welona experts and get treated for acne scarring.
|
__label__pos
| 0.525338 |
NodeJS Express Upload File Into Database (Simple Example)
Welcome to a tutorial on how to upload a file into the database in NodeJS and Express. So you want to save a file into the database? No problem, read on for the example!
TABLE OF CONTENTS
DOWNLOAD & NOTES
Here is the download link to the example code, so you don’t have to copy-paste everything.
EXAMPLE CODE DOWNLOAD
Click here to download
The example code is released under the MIT license, so feel free to build on top of it or use it in your own project.
SORRY FOR THE ADS...
But someone has to pay the bills, and sponsors are paying for it. I insist on not turning Code Boxx into a "paid scripts" business, and I don't "block people with Adblock". Every little bit of support helps.
Buy Me A Coffee Code Boxx eBooks
UPLOAD FILE INTO DATABASE
All right, let us now get into the details of uploading a file into the database with NodeJS and Express.
TUTORIAL VIDEO
QUICK SETUP
For this example, we will need SQLite, Express, and Express File Upload – npm i sqlite3 express express-fileupload
PART 1) THE DATABASE
1A) THE SQL
1a-database.sql
CREATE TABLE `storage` (
`file_name` TEXT PRIMARY KEY,
`file_mime` TEXT NOT NULL,
`file_data` BLOB NOT NULL
);
To save a file in the database, we will need to set a column to the BLOB binary data type.
1B) CREATE DATABASE
1b-database.js
const sqlite = require("sqlite3");
const db = new sqlite.Database("demo.db", err => {
db.exec(require("fs").readFileSync("1a-database.sql", "utf8"));
db.close();
console.log("Database created");
});
Next, run this script to create the database itself.
PART 2) HTML UPLOAD PAGE
2-upload.html
<form method="post" action="/upload" target="_blank" enctype="multipart/form-data">
<input type="file" name="upload" required>
<input type="submit" name="submit" value="Upload File">
</form>
There is nothing “special” about the HTML upload page, it’s just a regular file upload field.
PART 3) HTTP SERVER
3A) INIT
3-server.js
// (A) LOAD MODULES
const path = require("path"),
express = require("express"),
fileUpload = require("express-fileupload"),
sqlite = require("sqlite3");
// (B) EXPRESS SERVER & MIDDLEWARE
const app = express();
app.use(fileUpload());
// ...
// (D) START!
app.listen(80, () => console.log(`Server running at port 80`));
The top and bottom parts of the server script should be pretty self-explanatory.
• (A) Load the required modules.
• (B) Initialize the Express server and load whatever middleware is required.
• (D) Start the server.
3B) UPLOAD FILE
3-server.js
// (C) ENDPOINTS
// (C1) HTML FILE UPLOAD FORM
app.get("/", (req, res) => res.sendFile(path.join(__dirname, "/2-upload.html")));
// (C2) PROCESS UPLOAD
app.post("/upload", (req, res) => {
// (C2-1) FILE INFO + DATABASE
let upfile = req.files.upload,
db = new sqlite.Database("demo.db");
// (C2-2) SAVE INTO DATABASE
db.run(`REPLACE INTO storage (file_name, file_mime, file_data) VALUES (?,?,?)`, [
upfile.name, upfile.mimetype, upfile.data.toString("binary")
], err => {
if (err) {
res.status(500);
console.log(err);
res.send("ERROR!");
} else {
res.status(200);
res.send("OK - " + upfile.name);
}
db.close();
});
});
• (C1) Serve the HTML upload form at the base URL /.
• (C2) We send file uploads to /upload, save the file into the database.
3C) DOWNLOAD FILE
3-server.js
// (C3) DOWNLOAD
app.get("/download", (req, res) => {
let db = new sqlite.Database("demo.db");
db.get("SELECT * FROM storage LIMIT 1", [], (err, row) => {
(err, row) => {
console.log(row);
res.set({
"Content-Type": row["file_mime"],
"Content-Transfer-Encoding": "Binary",
"Content-Disposition": `attachment; filename="${row["file_name"]}"`
})
res.send(row["file_data"]);
db.close();
});
});
Lastly, a small bit on “how to load files from the database” – This will fetch the file from the database and force a download.
EXTRAS
That’s all for the tutorial, and here is a small section on some extras and links that may be useful to you.
NOT A GOOD IDEA
Yes, the above “save file into database” example works. But most RDB are not made to store massive files, nor do they work great with stuff like streaming. So unless you have no other choice but to save files in the database – A “secured folder” is the better solution.
LINKS & REFERENCES
THE END
Thank you for reading, and we have come to the end. I hope that it has helped you to better understand, and if you want to share anything with this guide, please feel free to comment below. Good luck and happy coding!
Leave a Comment
Your email address will not be published. Required fields are marked *
|
__label__pos
| 0.746277 |
OBJLoader always return error
I’m trying to load a .obj file of a lot of differents ways but all of them fail. I have proved each example that i have found on the internet but any of them work for me.
I have proved with a lot of differents obj files too.
var material = new THREE.MeshBasicMaterial({ color: 0x444444 });
var loader = new THREE.OBJLoader();
loader.load('diceLow.obj',
function (obj) {
obj.traverse(function (child) {
if (child instanceof THREE.Mesh) {
child.material = material;
obj.material = child.material;
child.castShadow = true;
child.receiveShadow = true;
}
});
scene.add(obj);
},
function (xhr) {
console.log((xhr.loaded / xhr.total * 100) + "% loaded")
},
function (err) {
console.error("Error loading")
}
);
Always return “Error loading”.
I will appreciate any help. Thank you so much!
Hi!
You can enhance the log for more details of the error console.error(“Error loading:”, err)
Hi!
Thanks. I send a capture of console.error(“Error loading”, err). I can see more details, but i don’t understand them.
capterror
You can try to follow the code from the official example for OBJLoader in the part of onProgress: three.js/webgl_loader_obj.html at e62b253081438c030d6af1ee3c3346a89124f277 · mrdoob/three.js · GitHub
function (xhr) {
if ( xhr.lengthComputable ) { // check this
console.log((xhr.loaded / xhr.total * 100) + “% loaded”)
}
},
This line can be removed since OBJLoader always returns an instance of THREE.Group. And a group does not have a material property (since it is non-renderable 3D object used for grouping other 3D objects together).
1 Like
Thanks for helping me! Now I have tried this but it doesn’t work either:
let object;
function loadModel() {
console.log("LOAD MODEL");
object.traverse(function (child) {
if (child.isMesh) child.material.map = texture;
});
scene.add(object);
}
const manager = new THREE.LoadingManager(loadModel);
manager.onProgress = function (item, loaded, total) {
console.log("PROGRESS MANAGER");
console.log(item, loaded, total);
};
// texture
const textureLoader = new THREE.TextureLoader(manager);
const texture = textureLoader.load('diceTextu.png');
// model
function onProgress(xhr) {
console.log("PROGRESS");
if (xhr.lengthComputable) {
const percentComplete = xhr.loaded / xhr.total * 100;
console.log('model ' + Math.round(percentComplete, 2) + '% downloaded');
}
}
function onError(err) {
console.log("error", err);
}
const loader = new THREE.OBJLoader(manager);
loader.load('diceLow.obj', function (obj) {
console.log("LOAD", obj);
object = obj;
}, onProgress, onError);
I found the solution, I need to test the web in a server, using xampp it works. In Glitch i need write the http files direction, no the local direction.
|
__label__pos
| 0.989682 |
debuggers.hg
changeset 13732:7d64bdc7a300
Tidy-ups; no semantic-change.
Signed-off-by: Ewan Mellor <[email protected]>
author Ewan Mellor <[email protected]>
date Mon Jan 29 13:16:00 2007 +0000 (2007-01-29)
parents f7b6ce00426b
children 049d9022653c
files docs/xen-api/xenapi-datamodel.tex
line diff
1.1 --- a/docs/xen-api/xenapi-datamodel.tex Mon Jan 29 12:57:49 2007 +0000
1.2 +++ b/docs/xen-api/xenapi-datamodel.tex Mon Jan 29 13:16:00 2007 +0000
1.3 @@ -279,7 +279,8 @@ The following enumeration types are used
1.4 \begin{longtable}{|lllp{0.38\textwidth}|}
1.5 \hline
1.6 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf session} \\
1.7 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A session}} \\
1.8 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.9 +session.}} \\
1.10 \hline
1.11 Quals & Field & Type & Description \\
1.12 \hline
1.13 @@ -293,7 +294,7 @@ Quals & Field & Type & Description \\
1.14 \subsubsection{RPC name:~login\_with\_password}
1.15
1.16 {\bf Overview:}
1.17 -Attempt to authenticate the user, returning a session\_id if successful
1.18 +Attempt to authenticate the user, returning a session\_id if successful.
1.19
1.20 \noindent {\bf Signature:}
1.21 \begin{verbatim} (session ref) login_with_password (string uname, string pwd)\end{verbatim}
1.22 @@ -327,7 +328,7 @@ ID of newly created session
1.23 \subsubsection{RPC name:~logout}
1.24
1.25 {\bf Overview:}
1.26 -Log out of a session
1.27 +Log out of a session.
1.28
1.29 \noindent {\bf Signature:}
1.30 \begin{verbatim} void logout (session_id s)\end{verbatim}
1.31 @@ -545,7 +546,8 @@ all fields from the object
1.32 \begin{longtable}{|lllp{0.38\textwidth}|}
1.33 \hline
1.34 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf task} \\
1.35 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A long-running asynchronous task}} \\
1.36 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.37 +long-running asynchronous task.}} \\
1.38 \hline
1.39 Quals & Field & Type & Description \\
1.40 \hline
1.41 @@ -1045,7 +1047,8 @@ references to objects with match names
1.42 \begin{longtable}{|lllp{0.38\textwidth}|}
1.43 \hline
1.44 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf VM} \\
1.45 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A virtual machine (or 'guest').
1.46 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.47 +virtual machine (or 'guest').
1.48
1.49 VM booting is controlled by setting one of the two mutually exclusive
1.50 groups: "PV", and "HVM". If HVM.boot is the empty string, then paravirtual
1.51 @@ -1075,7 +1078,7 @@ ramdisk values will be treated as paths
1.52 PV/bootloader and PV/kernel are empty, then the behaviour is as if
1.53 PV/bootloader was specified as "pygrub".
1.54
1.55 -When using HVM booting, HVM/boot specifies the order of the boot devices}} \\
1.56 +When using HVM booting, HVM/boot specifies the order of the boot devices.}} \\
1.57 \hline
1.58 Quals & Field & Type & Description \\
1.59 \hline
1.60 @@ -1128,7 +1131,10 @@ Quals & Field & Type & Description \\
1.61 \subsubsection{RPC name:~clone}
1.62
1.63 {\bf Overview:}
1.64 -Clones the specified VM, making a new VM. Clone automatically exploits the capabilities of the underlying storage repository in which the VM's disk images are stored (e.g. Copy on Write). This function can only be called when the VM is in the Halted State.
1.65 +Clones the specified VM, making a new VM. Clone automatically exploits the
1.66 +capabilities of the underlying storage repository in which the VM's disk
1.67 +images are stored (e.g. Copy on Write). This function can only be called
1.68 +when the VM is in the Halted State.
1.69
1.70 \noindent {\bf Signature:}
1.71 \begin{verbatim} (VM ref) clone (session_id s, VM ref vm, string new_name)\end{verbatim}
1.72 @@ -1164,7 +1170,8 @@ The ID of the newly created VM.
1.73 \subsubsection{RPC name:~start}
1.74
1.75 {\bf Overview:}
1.76 -Start the specified VM. This function can only be called with the VM is in the Halted State.
1.77 +Start the specified VM. This function can only be called with the VM is in
1.78 +the Halted State.
1.79
1.80 \noindent {\bf Signature:}
1.81 \begin{verbatim} void start (session_id s, VM ref vm, bool start_paused)\end{verbatim}
1.82 @@ -1200,7 +1207,8 @@ void
1.83 \subsubsection{RPC name:~pause}
1.84
1.85 {\bf Overview:}
1.86 -Pause the specified VM. This can only be called when the specified VM is in the Running state.
1.87 +Pause the specified VM. This can only be called when the specified VM is in
1.88 +the Running state.
1.89
1.90 \noindent {\bf Signature:}
1.91 \begin{verbatim} void pause (session_id s, VM ref vm)\end{verbatim}
1.92 @@ -1234,7 +1242,8 @@ void
1.93 \subsubsection{RPC name:~unpause}
1.94
1.95 {\bf Overview:}
1.96 -Resume the specified VM. This can only be called when the specified VM is in the Paused state.
1.97 +Resume the specified VM. This can only be called when the specified VM is
1.98 +in the Paused state.
1.99
1.100 \noindent {\bf Signature:}
1.101 \begin{verbatim} void unpause (session_id s, VM ref vm)\end{verbatim}
1.102 @@ -1268,9 +1277,11 @@ void
1.103 \subsubsection{RPC name:~clean\_shutdown}
1.104
1.105 {\bf Overview:}
1.106 -Attempt to cleanly shutdown the specified VM. (Note: this may not be supported---e.g. if a guest agent is not installed).
1.107 -
1.108 -Once shutdown has been completed perform poweroff action specified in guest configuration.
1.109 +Attempt to cleanly shutdown the specified VM. (Note: this may not be
1.110 +supported---e.g. if a guest agent is not installed).
1.111 +
1.112 +Once shutdown has been completed perform poweroff action specified in guest
1.113 +configuration.
1.114
1.115 This can only be called when the specified VM is in the Running state.
1.116
1.117 @@ -1306,9 +1317,11 @@ void
1.118 \subsubsection{RPC name:~clean\_reboot}
1.119
1.120 {\bf Overview:}
1.121 -Attempt to cleanly shutdown the specified VM (Note: this may not be supported---e.g. if a guest agent is not installed).
1.122 -
1.123 -Once shutdown has been completed perform reboot action specified in guest configuration.
1.124 +Attempt to cleanly shutdown the specified VM (Note: this may not be
1.125 +supported---e.g. if a guest agent is not installed).
1.126 +
1.127 +Once shutdown has been completed perform reboot action specified in guest
1.128 +configuration.
1.129
1.130 This can only be called when the specified VM is in the Running state.
1.131
1.132 @@ -1344,7 +1357,8 @@ void
1.133 \subsubsection{RPC name:~hard\_shutdown}
1.134
1.135 {\bf Overview:}
1.136 -Stop executing the specified VM without attempting a clean shutdown. Then perform poweroff action specified in VM configuration.
1.137 +Stop executing the specified VM without attempting a clean shutdown. Then
1.138 +perform poweroff action specified in VM configuration.
1.139
1.140 \noindent {\bf Signature:}
1.141 \begin{verbatim} void hard_shutdown (session_id s, VM ref vm)\end{verbatim}
1.142 @@ -1376,7 +1390,8 @@ void
1.143 \subsubsection{RPC name:~hard\_reboot}
1.144
1.145 {\bf Overview:}
1.146 -Stop executing the specified VM without attempting a clean shutdown. Then perform reboot action specified in VM configuration
1.147 +Stop executing the specified VM without attempting a clean shutdown. Then
1.148 +perform reboot action specified in VM configuration.
1.149
1.150 \noindent {\bf Signature:}
1.151 \begin{verbatim} void hard_reboot (session_id s, VM ref vm)\end{verbatim}
1.152 @@ -1408,7 +1423,8 @@ void
1.153 \subsubsection{RPC name:~suspend}
1.154
1.155 {\bf Overview:}
1.156 -Suspend the specified VM to disk. This can only be called when the specified VM is in the Running state.
1.157 +Suspend the specified VM to disk. This can only be called when the
1.158 +specified VM is in the Running state.
1.159
1.160 \noindent {\bf Signature:}
1.161 \begin{verbatim} void suspend (session_id s, VM ref vm)\end{verbatim}
1.162 @@ -1442,7 +1458,8 @@ void
1.163 \subsubsection{RPC name:~resume}
1.164
1.165 {\bf Overview:}
1.166 -Awaken the specified VM and resume it. This can only be called when the specified VM is in the Suspended state.
1.167 +Awaken the specified VM and resume it. This can only be called when the
1.168 +specified VM is in the Suspended state.
1.169
1.170 \noindent {\bf Signature:}
1.171 \begin{verbatim} void resume (session_id s, VM ref vm, bool start_paused)\end{verbatim}
1.172 @@ -2513,7 +2530,8 @@ void
1.173 \subsubsection{RPC name:~add\_VCPUs\_features\_force\_on}
1.174
1.175 {\bf Overview:}
1.176 -Add the given value to the VCPUs/features/force\_on field of the given VM. If the value is already in that Set, then do nothing.
1.177 +Add the given value to the VCPUs/features/force\_on field of the given VM.
1.178 +If the value is already in that Set, then do nothing.
1.179
1.180 \noindent {\bf Signature:}
1.181 \begin{verbatim} void add_VCPUs_features_force_on (session_id s, VM ref self, cpu_feature value)\end{verbatim}
1.182 @@ -2547,7 +2565,8 @@ void
1.183 \subsubsection{RPC name:~remove\_VCPUs\_features\_force\_on}
1.184
1.185 {\bf Overview:}
1.186 -Remove the given value from the VCPUs/features/force\_on field of the given VM. If the value is not in that Set, then do nothing.
1.187 +Remove the given value from the VCPUs/features/force\_on field of the given
1.188 +VM. If the value is not in that Set, then do nothing.
1.189
1.190 \noindent {\bf Signature:}
1.191 \begin{verbatim} void remove_VCPUs_features_force_on (session_id s, VM ref self, cpu_feature value)\end{verbatim}
1.192 @@ -2647,7 +2666,8 @@ void
1.193 \subsubsection{RPC name:~add\_VCPUs\_features\_force\_off}
1.194
1.195 {\bf Overview:}
1.196 -Add the given value to the VCPUs/features/force\_off field of the given VM. If the value is already in that Set, then do nothing.
1.197 +Add the given value to the VCPUs/features/force\_off field of the given VM.
1.198 + If the value is already in that Set, then do nothing.
1.199
1.200 \noindent {\bf Signature:}
1.201 \begin{verbatim} void add_VCPUs_features_force_off (session_id s, VM ref self, cpu_feature value)\end{verbatim}
1.202 @@ -2681,7 +2701,8 @@ void
1.203 \subsubsection{RPC name:~remove\_VCPUs\_features\_force\_off}
1.204
1.205 {\bf Overview:}
1.206 -Remove the given value from the VCPUs/features/force\_off field of the given VM. If the value is not in that Set, then do nothing.
1.207 +Remove the given value from the VCPUs/features/force\_off field of the
1.208 +given VM. If the value is not in that Set, then do nothing.
1.209
1.210 \noindent {\bf Signature:}
1.211 \begin{verbatim} void remove_VCPUs_features_force_off (session_id s, VM ref self, cpu_feature value)\end{verbatim}
1.212 @@ -4066,7 +4087,8 @@ reference to the newly created object
1.213 \subsubsection{RPC name:~destroy}
1.214
1.215 {\bf Overview:}
1.216 -Destroy the specified VM. The VM is completely removed from the system. This function can only be called when the VM is in the Halted State.
1.217 +Destroy the specified VM. The VM is completely removed from the system.
1.218 +This function can only be called when the VM is in the Halted State.
1.219
1.220 \noindent {\bf Signature:}
1.221 \begin{verbatim} void destroy (session_id s, VM ref self)\end{verbatim}
1.222 @@ -4199,7 +4221,8 @@ references to objects with match names
1.223 \begin{longtable}{|lllp{0.38\textwidth}|}
1.224 \hline
1.225 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf host} \\
1.226 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A physical host}} \\
1.227 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.228 +physical host.}} \\
1.229 \hline
1.230 Quals & Field & Type & Description \\
1.231 \hline
1.232 @@ -4216,7 +4239,8 @@ Quals & Field & Type & Description \\
1.233 \subsubsection{RPC name:~disable}
1.234
1.235 {\bf Overview:}
1.236 -Puts the host into a state in which no new VMs can be started. Currently active VMs on the host continue to execute.
1.237 +Puts the host into a state in which no new VMs can be started. Currently
1.238 +active VMs on the host continue to execute.
1.239
1.240 \noindent {\bf Signature:}
1.241 \begin{verbatim} void disable (session_id s, host ref host)\end{verbatim}
1.242 @@ -4280,7 +4304,8 @@ void
1.243 \subsubsection{RPC name:~shutdown}
1.244
1.245 {\bf Overview:}
1.246 -Shutdown the host. (This function can only be called if there are no currently running VMs on the host and it is disabled.)
1.247 +Shutdown the host. (This function can only be called if there are no
1.248 +currently running VMs on the host and it is disabled.).
1.249
1.250 \noindent {\bf Signature:}
1.251 \begin{verbatim} void shutdown (session_id s, host ref host)\end{verbatim}
1.252 @@ -4312,7 +4337,8 @@ void
1.253 \subsubsection{RPC name:~reboot}
1.254
1.255 {\bf Overview:}
1.256 -Reboot the host. (This function can only be called if there are no currently running VMs on the host and it is disabled.)
1.257 +Reboot the host. (This function can only be called if there are no
1.258 +currently running VMs on the host and it is disabled.).
1.259
1.260 \noindent {\bf Signature:}
1.261 \begin{verbatim} void reboot (session_id s, host ref host)\end{verbatim}
1.262 @@ -5229,7 +5255,8 @@ all fields from the object
1.263 \begin{longtable}{|lllp{0.38\textwidth}|}
1.264 \hline
1.265 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf network} \\
1.266 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A virtual network}} \\
1.267 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.268 +virtual network.}} \\
1.269 \hline
1.270 Quals & Field & Type & Description \\
1.271 \hline
1.272 @@ -5792,7 +5819,8 @@ references to objects with match names
1.273 \begin{longtable}{|lllp{0.38\textwidth}|}
1.274 \hline
1.275 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf VIF} \\
1.276 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A virtual network interface}} \\
1.277 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.278 +virtual network interface.}} \\
1.279 \hline
1.280 Quals & Field & Type & Description \\
1.281 \hline
1.282 @@ -6371,7 +6399,7 @@ all fields from the object
1.283 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf PIF} \\
1.284 \multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.285 physical network interface (note separate VLANs are represented as several
1.286 -PIFs)}} \\
1.287 +PIFs).}} \\
1.288 \hline
1.289 Quals & Field & Type & Description \\
1.290 \hline
1.291 @@ -6390,7 +6418,7 @@ Quals & Field & Type & Description \\
1.292 \subsubsection{RPC name:~create\_VLAN}
1.293
1.294 {\bf Overview:}
1.295 -Create a VLAN interface from an existing physical interface
1.296 +Create a VLAN interface from an existing physical interface.
1.297
1.298 \noindent {\bf Signature:}
1.299 \begin{verbatim} (PIF ref) create_VLAN (session_id s, string device, network ref network, host ref host, int VLAN)\end{verbatim}
1.300 @@ -6430,7 +6458,8 @@ The reference of the created PIF object
1.301 \subsubsection{RPC name:~destroy}
1.302
1.303 {\bf Overview:}
1.304 -Destroy the interface (provided it is a synthetic interface like a VLAN; fail if it is a physical interface)
1.305 +Destroy the interface (provided it is a synthetic interface like a VLAN;
1.306 +fail if it is a physical interface).
1.307
1.308 \noindent {\bf Signature:}
1.309 \begin{verbatim} void destroy (session_id s, PIF ref self)\end{verbatim}
1.310 @@ -7025,7 +7054,8 @@ all fields from the object
1.311 \begin{longtable}{|lllp{0.38\textwidth}|}
1.312 \hline
1.313 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf SR} \\
1.314 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A storage repository}} \\
1.315 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.316 +storage repository.}} \\
1.317 \hline
1.318 Quals & Field & Type & Description \\
1.319 \hline
1.320 @@ -7623,7 +7653,8 @@ references to objects with match names
1.321 \begin{longtable}{|lllp{0.38\textwidth}|}
1.322 \hline
1.323 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf VDI} \\
1.324 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A virtual disk image}} \\
1.325 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.326 +virtual disk image.}} \\
1.327 \hline
1.328 Quals & Field & Type & Description \\
1.329 \hline
1.330 @@ -7644,7 +7675,8 @@ Quals & Field & Type & Description \\
1.331 \subsubsection{RPC name:~snapshot}
1.332
1.333 {\bf Overview:}
1.334 -Take an exact copy of the VDI; the snapshot lives in the same Storage Repository as its parent.
1.335 +Take an exact copy of the VDI; the snapshot lives in the same Storage
1.336 +Repository as its parent.
1.337
1.338 \noindent {\bf Signature:}
1.339 \begin{verbatim} (VDI ref) snapshot (session_id s, VDI ref vdi)\end{verbatim}
1.340 @@ -8431,7 +8463,8 @@ references to objects with match names
1.341 \begin{longtable}{|lllp{0.38\textwidth}|}
1.342 \hline
1.343 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf VBD} \\
1.344 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A virtual block device}} \\
1.345 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.346 +virtual block device.}} \\
1.347 \hline
1.348 Quals & Field & Type & Description \\
1.349 \hline
1.350 @@ -8450,7 +8483,8 @@ Quals & Field & Type & Description \\
1.351 \subsubsection{RPC name:~media\_change}
1.352
1.353 {\bf Overview:}
1.354 -Change the media in the device for CDROM-like devices only. For other devices, detach the VBD and attach a new one
1.355 +Change the media in the device for CDROM-like devices only. For other
1.356 +devices, detach the VBD and attach a new one.
1.357
1.358 \noindent {\bf Signature:}
1.359 \begin{verbatim} void media_change (session_id s, VBD ref vbd, VDI ref vdi)\end{verbatim}
1.360 @@ -9384,7 +9418,8 @@ all fields from the object
1.361 \begin{longtable}{|lllp{0.38\textwidth}|}
1.362 \hline
1.363 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf console} \\
1.364 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A console}} \\
1.365 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.366 +console.}} \\
1.367 \hline
1.368 Quals & Field & Type & Description \\
1.369 \hline
1.370 @@ -9659,7 +9694,8 @@ all fields from the object
1.371 \begin{longtable}{|lllp{0.38\textwidth}|}
1.372 \hline
1.373 \multicolumn{1}{|l}{Name} & \multicolumn{3}{l|}{\bf user} \\
1.374 -\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A user of the system}} \\
1.375 +\multicolumn{1}{|l}{Description} & \multicolumn{3}{l|}{\parbox{11cm}{\em A
1.376 +user of the system.}} \\
1.377 \hline
1.378 Quals & Field & Type & Description \\
1.379 \hline
1.380 @@ -9958,7 +9994,7 @@ A list of all the IDs of all the debug r
1.381 \subsubsection{RPC name:~return\_failure}
1.382
1.383 {\bf Overview:}
1.384 -Return an API 'successful' failure
1.385 +Return an API 'successful' failure.
1.386
1.387 \noindent {\bf Signature:}
1.388 \begin{verbatim} void return_failure (session_id s)\end{verbatim}
|
__label__pos
| 0.999924 |
Definitions
Drug_resistance
Drug resistance
Drug resistance is the reduction in effectiveness of a drug in curing a disease or improving a patient's symptoms. When the drug is not intended to kill or inhibit a pathogen, then the term is equivalent to dosage failure or drug tolerance. More commonly, the term is used in the context of diseases caused by pathogens.
Pathogens are said to be drug-resistant when drugs meant to neutralize them have reduced effect. When an organism is resistant to more than one drug, it is said to be multidrug resistant.
Classification
Drug resistance occurs in several classes of pathogens:
The most prominent is antibiotic resistance. Drug resistance is also found in some tumor cells, which makes it more difficult to use chemotherapy to attack tumors made of those cells. Resistance to antiviral drugs also occurs in virus populations, notably HIV. When a drug is administered, those organisms which have a genetic resistance to the drug will survive and reproduce, and the new population will be drug-resistant (see natural selection, selection pressure).
In the presence of drugs, pathogens have evolved sophisticated mechanisms to inactivate these compounds (e.g. by pumping out compounds, mutating residues required for the compound to bind, etc.), and they do so at a rate that far exceeds the pace of new development of drugs. Examples include drug resistant strains of Staphylococcus aureus, Klebsiella pneumonia, and Pseudomonas aeruginosa, and Mycobacterium tuberculosis (TB) among bacterium and HIV-1 among viruses. Indeed, no new antibiotics have been developed against TB in thirty years. Efforts to develop new antibiotics by the pharmaceutical industry by large-scale screens of chemical libraries which inhibit bacterial growth have largely failed, and new tetracycline and sulfanilamide analogs will likely engender resistance and will quickly be rendered useless. The resistance problem is compounded further by indiscriminate and inappropriate use of antibiotics and anti-viral compounds without compliance measures or public health policies to reduce disease burden. Finally, with current legislative restrictions, the very high costs associated with clinical trials (e.g. ~$400M to bring new tetracyclines to market for an expected revenue of ~$100M), the failure to control generic sales, and the capacity to generate substantial revenues from medications for chronic illnesses, there is little if any financial incentive for big pharmaceutical companies to even develop new antibiotics, and small biotech companies simply do not have the resources. The search for novel anti-viral compounds has been somewhat more successful and largely motivated by the AIDS epidemic, but drugs have been developed principally against viral targets, and mutation rates among viruses still outpaces new development. One positive development has been vaccines, which are promising for some bacterial and viral illnesses. But vaccines are not successful in all cases (e.g. in young children), and adequate resources have not been made available.
Metabolic price
Biological cost or metabolic price is a measure of the increased energy metabolism required to achieve a function.
Drug resistance has a high metabolic price, in pathogens for which this concept is relevant (bacteria, endoparasites, and tumor cells.) In viruses, an equivalent "cost" is genomic complexity.
See also
References
External links
Search another word or see Drug_resistanceon Dictionary | Thesaurus |Spanish
Copyright © 2014 Dictionary.com, LLC. All rights reserved.
• Please Login or Sign Up to use the Recent Searches feature
FAVORITES
RECENT
|
__label__pos
| 0.624162 |
Mirror of the official OpenWrt repository https://openwrt.org
Vous ne pouvez pas sélectionner plus de 25 sujets Les noms de sujets doivent commencer par une lettre ou un nombre, peuvent contenir des tirets ('-') et peuvent comporter jusqu'à 35 caractères.
8 lignes
179 B
1. # Copyright (C) 2006 OpenWrt.org
2. #
3. # This is free software, licensed under the GNU General Public License v2.
4. # See /LICENSE for more information.
5. #
6. world ${.TARGETS}:
7. @gmake $@
|
__label__pos
| 0.742588 |
Thermodynamic and structural properties of the specific binding between Ag+ ion and C:C mismatched base pair in duplex DNA to form C-Ag-C metal-mediated base pair
Hidetaka Torigoe, Itaru Okamoto, Takenori Dairaku, Yoshiyuki Tanaka, Akira Ono, Tetsuo Kozasa
Research output: Contribution to journalArticlepeer-review
63 Citations (Scopus)
Abstract
Metal ion-nucleic acid interactions have attracted considerable interest for their involvement in structure formation and catalytic activity of nucleic acids. Although interactions between metal ion and mismatched base pair duplex are important to understand mechanism of gene mutations related to heavy metal ions, they have not been well-characterized. We recently found that the Ag + ion stabilized a C:C mismatched base pair duplex DNA. A C-Ag-C metal-mediated base pair was supposed to be formed by the binding between the Ag+ ion and the C:C mismatched base pair to stabilize the duplex. Here, we examined specificity, thermodynamics and structure of possible C-Ag-C metal-mediated base pair. UV melting indicated that only the duplex with the C:C mismatched base pair, and not of the duplexes with the perfectly matched and other mismatched base pairs, was specifically stabilized on adding the Ag + ion. Isothermal titration calorimetry demonstrated that the Ag + ion specifically bound with the C:C base pair at 1:1 molar ratio with a binding constant of 106 M-1, which was significantly larger than those for nonspecific metal ion-DNA interactions. Electrospray ionization mass spectrometry also supported the specific 1:1 binding between the Ag+ ion and the C:C base pair. Circular dichroism spectroscopy and NMR revealed that the Ag+ ion may bind with the N3 positions of the C:C base pair without distorting the higher-order structure of the duplex. We conclude that the specific formation of C-Ag-C base pair with large binding affinity would provide a binding mode of metal ion-DNA interactions, similar to that of the previously reported T-Hg-T base pair. The C-Ag-C base pair may be useful not only for understanding of molecular mechanism of gene mutations related to heavy metal ions but also for wide variety of potential applications of metal-mediated base pairs in various fields, such as material, life and environmental sciences.
Original languageEnglish
Pages (from-to)2431-2440
Number of pages10
JournalBiochimie
Volume94
Issue number11
DOIs
Publication statusPublished - 2012 Nov
Keywords
• Ag ion
• C:C mismatched base pair
• Large binding affinity
• Metal ion-DNA interaction
• Metal-mediated base pair
• Specific binding
ASJC Scopus subject areas
• Biochemistry
Fingerprint Dive into the research topics of 'Thermodynamic and structural properties of the specific binding between Ag<sup>+</sup> ion and C:C mismatched base pair in duplex DNA to form C-Ag-C metal-mediated base pair'. Together they form a unique fingerprint.
Cite this
|
__label__pos
| 0.543018 |
Views: 2300
Number of votes: 1
Average rating:
EditPanel Manager
In order to keep the Edit Panel as clean as can be, I’ve written a small extension that enhances the ability to disable and hide buttons in the EditPanel for specific PageTypes. This post explains the setup for the EditPanelManager extension, which options it currently supports and how the implementation has been done. The main objective of this post is to give insight in a possible solution to the problem and should not by default be read as the best solution. While all code is usable and tested it could well be optimized at places.
The challenge
The Edit Panel, as you probably know, is one of the areas for which you can use a GuiPlugIn with Area set to PlugInArea.EditPanel to add custom tabs. With these tabs you can add specific functionality to pages or PageTypes for instance which can improve the work for your editors in case you need to provide some functionality that otherwise would mean manual selection or at least non trivial work.
While this is a great way to extend your specific pages or PageTypes, adding a multitude of these custom GuiPlugIns can make the Edit Panel a bit overwhelming to your editors in the number of tabs they see. Most of the times however your editors won’t be using all of these tabs frequently. Some tabs probably won’t be used at all throughout the site, and perhaps some tabs are only used for a specific PageType.
The basics
This extension uses an xml configuration file to manage the tabs in the EditPanel for our PageTypes. I’ll start by explaining this configuration. Further down the post I’ll show how we can hook into EPiServer to influence the actual tabs being displayed in the EditPanel.
Let’s start with the structure of the xml configuration file. This will explain all of the options that are available in this extension and will provide the basis insights on what to do with those options.
1: <episervereditpanelmanager>
2: <pagetypes>
3: <type name="MyPageTypeName" active="MyDefaultEditPanelTab">
4: <properties>
5: <property name="MyFirstEditPanelTabName" enable="true" />
6: <property name="MySecondEditPanelTabName" enable="false" ignoreroles="MyUserRole" />
7: </properties>
8: </type>
9: </pagetypes>
10: </episervereditpanelmanager>
The type element
Within the ‘pagetypes’ node you set up a ‘type’ element. Each type element reflects a single PageType in your EPiServer site structure. The are two attributes on the type element. The first is the ‘name’ attribute, which is mandatory. The name attribute contains the name of the PageType that you want to manage the EditPanel tabs for. The second attribute is the ‘active’ attribute, which is optional. This attribute contains the name of the EditPanel tab that you want to set as the default tab which is displayed when an editor selects a page from the PageTree (Note: if this is the same for all your PageTypes or there is no need to customize this for each PageType you should probably use the ‘uiDefaultPanelTab’ in your EPiServer site configuration).
The property element
Within the type element there is a single ‘properties’ element that contains a number of ‘property’ elements. Each property element reflects a tab that exists in the EditPanel; like the Preview tab, the Edit tab, the Workflow tab, the Version List tab etc. The are three attributes on the property element. The first is the ‘name’ attribute, which is mandatory. The name attribute contains the name of the EditPanel tab that you want to manage. The second attribute is the ‘enable’ attribute, also mandatory. The enable attribute is a Boolean and holds the values ‘true’ or ‘false’. If set to true, the EditPanel tab should be displayed. If set to false the EditPanel tab should not be displayed. The third attribute is the ‘ignoreroles’ attribute, which is optional. This attribute can hold a comma separated list of user roles. This works as an override to the enable attribute. Users from these user roles are not taken into account on the enable attribute. In the above example this means that the ‘MySecondEditPanelTabName’ is not visible to anyone, except users from the ‘MyUserRole’ user role.
Hopefully you’re still reading ;) The summary above highlights the functional use of the EditPanelManager extension. The next part will explain some more on how this can be achieved with some code examples as well. Before we get into that just another small example xml configuration.
Pop quiz
Try and see if you understand how this would affect the EditPanel of your site editors (Note: spoiler below the example!)
1: <episervereditpanelmanager>
2: <pagetypes>
3: <type name="TeaserPageType">
4: <properties>
5: <property name="View" enable="false" />
6: </properties>
7: </type>
8: <type name="NewsPageType" active="Edit">
9: <properties>
10: <property name="View" enable="true" />
11: <property name="Edit" enable="true" />
12: <property name="Version List" enable="false" />
13: <property name="Workflow" enable="false" />
14: <property name="Statistics" enable="false" />
15: </properties>
16: </type>
17: <type name="EventPageType">
18: <properties>
19: <property name="View" enable="true" />
20: <property name="Edit" enable="false" ignoreroles="WebAdmins, WebEditors" />
21: <property name="Version List" enable="false" ignoreroles="WebAdmins, WebEditors" />
22: <property name="Workflow" enable="false" ignoreroles="WebAdmins, WebEditors" />
23: <property name="Statistics" enable="false" ignoreroles="WebAdmins, WebEditors" />
24: </properties>
25: </type>
26: </pagetypes>
27: </episervereditpanelmanager>
Ok, so how does the above configuration affect our editors?
Once logged in, I won’t see the View tab in the EditPanel for the TeaserPageType. Further I won’t see the VersionList, Workflow and Statistics tab on the NewsPageType, and the Edit tab is the default tab when selecting a page of type NewsPageType in the PageTree. If the logged in user has the ‘WebAdmins’ user role he’ll see all five tabs on the EventPageType. If the logged in user has the ‘WebSpecialAdmins’ user role, he’ll only see the ‘View’ tab in the EditPanel.
Technical Implementation
So far for the examples. As promised I’ll dive into the actual implementation.
We start by creating a GuiPlugIn. Let’s call this ‘EditPanelManager’.
1: [GuiPlugIn(Area = PlugInArea.EditPanel)]
2: public class EditPanelManager : ICustomPlugInLoader
3: {
4: private static readonly ILog Logger = LogManager.GetLogger(typeof(EditPanelManager));
5:
6: //property that holds the current page type config element
7: public EPiServerEditPanelManagerPageTypeConfigElement CurrentPageTypeConfigElement
8: {
9: get; set;
10: }
11:
12: public PlugInDescriptor[] List()
13: {
14: //hook LoadComplete-event on EditPanel page
15: EPiServer.UI.Edit.EditPanel editPanel = HttpContext.Current.Handler as EPiServer.UI.Edit.EditPanel;
16:
17: if (null != editPanel)
18: {
19: //ADD SOME LOGIC HERE
20: }
21:
22: //Never return a plugin - we don't want to add tabs.
23: return new PlugInDescriptor[0] { };
24: }
25:
26: protected void EditPanelLoadComplete(object sender, EventArgs e)
27: {
28: //ADD SOME LOGIC HERE
29: }
30: }
The next step is to implement the ‘PlugInDescriptor[] List()’ method from the ICustomPlugInLoader interface. In short we add an EventHandler to LoadComplete of the EditPanel if the PageType of the current page exists in our xml configuration file.
1: public PlugInDescriptor[] List()
2: {
3: // hook LoadComplete-event on EditPanel page
4: EPiServer.UI.Edit.EditPanel editPanel = HttpContext.Current.Handler as EPiServer.UI.Edit.EditPanel;
5:
6: if (null != editPanel)
7: {
8: //get the list of all registered pagetypes from the config file
9: List<EPiServerEditPanelManagerPageTypeConfigElement> pageTypeList = EditPanelManagerHelper.GetPageTypeNamesFromConfig();
10:
11: //check if the pagetype of the current page exists in the list of pagetypes in the config file
12: try
13: {
14: CurrentPageTypeConfigElement = pageTypeList.First(x => x.Name.ToLower().Trim() == editPanel.CurrentPage.PageTypeName.ToLower().Trim());
15: }
16: catch (Exception ex)
17: {
18: Logger.Debug("error occured while getting the CurrentPageTypeConfigElement", ex);
19: }
20:
21: //match found, add the event handler to the LoadComplete event of the editpanel
22: if (CurrentPageTypeConfigElement != null)
23: {
24: editPanel.LoadComplete += EditPanelLoadComplete;
25: }
26: }
27:
28: //Never return a plugin - we don't want to add tabs.
29: return new PlugInDescriptor[0] { };
30: }
The EventHandler is added to manipulate the way the tabs in the EditPanel are rendered (Thanks to the article ‘Neat Trick: Modifying Edit Mode Tabs’ by Allan Thræn).
We also need to implement the LoadComplete event of the EditPanel for which we’ve added the new EventHandler in the ‘PlugInDescriptor[] List()’ method. There are three single line calls in the LoadComplete event. First we get the TabStrip object by looking for the ‘actionTab’ control. Secondly we retrieve all properties (the tabs) that are configured for the current page type in our xml configuration file. Finally, we call our Tab Manager that handles the processing of the individual tabs.
1: protected void EditPanelLoadComplete(object sender, EventArgs e)
2: {
3: // find the TabStrip with id = "actionTab"
4: TabStrip actionTabStrip = ControlHelper.FindControl<TabStrip>(sender as Control, "actionTab");
5:
6: //get all properties for this pagetype from the config file
7: List<EPiServerEditPanelManagerPropertyConfigElement> elements =
8: EditPanelManagerHelper.GetPropertyElementsFromPageTypeConfigElement(CurrentPageTypeConfigElement);
9:
10: //call our tab manager
11: TabStripHelper.SetTabs(actionTabStrip, elements, CurrentPageTypeConfigElement.Active);
12: }
Within both the ‘PlugInDescriptor[] List()’ method and the LoadComplete event method there are calls to certain Helper classes. Of course you can set this up any way you like. For this demo I’ve chosen to just simply set up two classes; the EditPanelManagerHelper and the TabStripHelper.
EditPanelManagerHelper
The EditPanelManagerHelper is used to retrieve the correct PageTypes and properties from our configuration file. It has two methods. The first method is ‘GetPageTypeNamesFromConfig()’ and reads the xml configuration file for all PageTypes defined using the ConfigurationManager. The second method is ‘GetPropertyElementsFromPageTypeConfigElement()’ that reads all properties for a given PageType present in the xml configuration file.
1: public static class EditPanelManagerHelper
2: {
3: public static List<EPiServerEditPanelManagerPageTypeConfigElement> GetPageTypeNamesFromConfig()
4: {
5: List<EPiServerEditPanelManagerPageTypeConfigElement> list = new List<EPiServerEditPanelManagerPageTypeConfigElement>();
6: EPiServerEditPanelManagerConfigSection section = ConfigurationManager.GetSection("episervereditpanelmanager") as EPiServerEditPanelManagerConfigSection;
7: if (section != null)
8: {
9: list.AddRange(section.PageTypes.Cast<EPiServerEditPanelManagerPageTypeConfigElement>());
10: }
11: return list;
12: }
13:
14: public static List<EPiServerEditPanelManagerPropertyConfigElement> GetPropertyElementsFromPageTypeConfigElement(EPiServerEditPanelManagerPageTypeConfigElement ePiServerEditPanelManagerPageTypeConfigElement)
15: {
16: //get element information from pagetype config node
17: return ePiServerEditPanelManagerPageTypeConfigElement.Elements.Cast<EPiServerEditPanelManagerPropertyConfigElement>().ToList();
18: }
19: }
TabStripHelper
The second helper class is the TabStripHelper. This contains the actual logic that controls which tabs are displayed and which are hidden.
1: private static readonly ILog Logger = LogManager.GetLogger(typeof(TabStripHelper));
2:
3: public static void SetTabs(TabStrip tabStrip, List<EPiServerEditPanelManagerPropertyConfigElement> elements, string activeTab)
4: {
5: if (tabStrip == null)
6: {
7: return;
8: }
9:
10: int firstVisibleTab = -1;
11: int activeTabIndex = -1;
12: for (int i = 0; i < tabStrip.Controls.Count; i++)
13: {
14: Tab tab = (Tab)tabStrip.Controls[i];
15:
16: string tabName = tab.Text.ToLower().Trim();
17:
18: //get element by tab name
19: EPiServerEditPanelManagerPropertyConfigElement element = null;
20: if (elements != null)
21: {
22: try
23: {
24: IEnumerable<EPiServerEditPanelManagerPropertyConfigElement> list = elements.ToList().Where(x => x.Name.ToLower().Trim() == tabName);
25: if (list.Any())
26: {
27: element = list.Single();
28: }
29: }
30: catch (Exception ex)
31: {
32: Logger.Debug(string.Format("error occured while getting the element for tab '{0}'", tabName), ex);
33: }
34: }
35: if (element != null)
36: {
37: if (string.IsNullOrEmpty(element.IgnoreRoles))
38: {
39: //set visibility
40: tab.Visible = element.Enable;
41: }
42: else
43: {
44: //check current user roles
45: tab.Visible = (UserHasRole(element.IgnoreRoles) ? !element.Enable : element.Enable);
46: }
47: }
48:
49: //store first visible tab index
50: if (tab.Visible && firstVisibleTab == -1)
51: {
52: firstVisibleTab = i;
53: }
54:
55: //store given active tab index
56: if (!string.IsNullOrEmpty(activeTab) && tab.Visible && tabName == activeTab.ToLower())
57: {
58: activeTabIndex = i;
59: }
60: }
61:
62: if (tabStrip.SelectedTab == 0)
63: {
64: int set = (activeTabIndex > -1 ? activeTabIndex : firstVisibleTab);
65: tabStrip.SetSelectedTab(set);
66: }
67: }
68:
69: public static bool UserHasRole(string roles)
70: {
71: if(string.IsNullOrEmpty(roles))
72: {
73: return true;
74: }
75:
76: //get current user roles
77: List<string> currentUserRoleList;
78: try
79: {
80: List<string> list = EPiServer.Security.PrincipalInfo.Current.RoleList.ToList();
81: currentUserRoleList = list.ConvertAll(x => x.ToLower());
82: }
83: catch (Exception)
84: {
85: Logger.Error("error occured while handling the current user role list");
86: return true;
87: }
88:
89: List<string> roleList = roles.Split(',').ToList();
90: return roleList.Any(role => currentUserRoleList.Contains(role.ToLower().Trim()));
91: }
92: }
This helper class contains two methods. The ‘UserHasRole’ method has been added here for convenience, but you probably have another place for this in your codebase. It simply checks the current users role to the provided userrole list from the ‘ignoreroles’ attribute for the current PageType.
The first method ‘SetTabs()’ holds three input parameters. The current TabStrip (which holds all tabs of the EditPanel), the list of tabs that you configured in your xml configuration file for the given PageType and the name of the activeTab if present in the xml configuration file. It simply iterates over all controls in the TabStrip and compares these to the xml configuration setup.
Conclusion
And there you have it, that’s all there is to it. As you can see this example shows how to influence the way tabs are rendered within the EditPanel and can possibly simplify the way your site editors experience the Edit Mode of EPiServer. Feel free to comment!
Apr 29, 2013
[email protected]
( By [email protected], 6/13/2013 12:23:48 PM)
Hi, have you tested this on EPiServer 6 R2. I am trying to use parts of it to locate the "XForms Data" tab so I can hide it for certain users but the TabStrip only ever seems to have once child control which is the "preview" tab.
Here is my code:
private static void EditPanel_LoadedPage(EPiServer.UI.Edit.EditPanel sender,
EPiServer.UI.Edit.LoadedPageEventArgs e)
{
// find the TabStrip with id = "actionTab"
TabStrip actionTabStrip = ControlHelper.FindControl(sender as Control, "actionTab");
//call our tab manager
SetTabs(actionTabStrip);
}
public static void SetTabs(TabStrip tabStrip)
{
if (tabStrip == null)
{
return;
}
for (int i = 0; i < tabStrip.Controls.Count; i++)
{
Tab tab = (Tab) tabStrip.Controls[i];
string tabName = tab.Text.ToLower().Trim();
// For loop only ever executes once and the tab is always "preview"
}
}
Please login to comment.
|
__label__pos
| 0.985827 |
Food and Behaviour Research
Donate Log In
Alcohol: What Women Need to Know - BOOK HERE
ADHD supplements: Are they effective?
Charlotte Lillis
ADHD
Research shows that people with ADHD often have lower levels of certain vitamins and minerals.
FAB RESEARCH COMMENT:
See here for more articles on ADHD and nutrition.
Stimulant medications are the first-line treatment for attention deficit hyperactivity disorder (ADHD). Common symptoms of ADHD include hyperactivity, impulsive behavior, and difficulty paying attention.
Recently, researchers have been investigating several different supplements that may help alleviate ADHD symptoms.
In this article, we outline the research into some of the more promising hormone, dietary, and herbal supplements for ADHD.
Hormone, vitamin, and mineral supplements
Supplements may help counter mineral deficiencies that some ADHD medications cause.
Research shows that people with ADHD often have lower levels of certain vitamins and minerals. Despite this, there is currently no conclusive evidence that mineral deficiencies cause ADHD.
In some cases, vitamin and mineral deficiencies are a consequence of ADHD medication. For example, stimulant medications can suppress appetite, which can lead to a decrease in a person's nutrient intake.
Certain nutrient deficiencies may also worsen ADHD or cause symptoms that mimic the condition.
Researchers are investigating whether the following hormone, dietary, and herbal supplements are effective in treating ADHD:
Melatonin
Melatonin is a hormone that regulates the sleep-wake cycle. It might be useful for the subset of children with ADHD who experts believe experience sleep disturbances.
In many cases, sleep disturbances are a side effect of stimulant medications that doctors prescribe to treat ADHD. Stimulants work by increasing activity in both the brain and central nervous system.
Although this often improves ADHD symptoms, it can lead to the following sleep problems:
• difficulty getting to sleep and waking up
• waking up throughout the night
• daytime sleepiness
A 2019 study investigated the benefits of melatonin in children with ADHD who developed sleep problems as a result of taking the stimulant methylphenidate. All 74 participants had different doses of melanin for at least 4 weeks.
The researchers used parental reports to determine treatment success. According to the reports, melatonin effectively improved sleep problems in 60.8% of participants.
Vitamin D
Vitamin D plays an important role in healthy brain development and function. Several studies have found a link between vitamin D deficiency and neurodevelopmental disorders, such as ADHD.
A 2018 study compared vitamin D levels in children with and without ADHD. Those with ADHD had significantly lower levels of vitamin D in their blood and were also more likely to have a vitamin D deficiency.
In the second stage of the study, the researchers divided the children who were deficient in vitamin D into two groups. The participants in one group received an 8-week course of vitamin D supplements, while those in the other group received a placebo.
Children who received the supplements showed significant improvements in attention, impulsivity, and hyperactivity compared with children who received the placebo.
These findings suggest that vitamin D supplements may improve ADHD symptoms in children who are vitamin D deficient. However, further studies are necessary to confirm this theory.
Zinc
Research has shown that there may be a link between zinc deficiency and ADHD in children.
Zinc is an essential mineral that plays an important role in brain function.
Children who are deficient in zinc can experience symptoms similar to those of ADHD.
Examples include jitteriness, inattention, and delayed cognitive development.
Several studies have reported a link between zinc deficiency and ADHD in children. A 2015 review of these studies concluded that zinc supplements could help treat ADHD symptoms in children with zinc deficiency.
However, it is still not clear whether zinc has any effect on ADHD symptoms in children or adults who are not zinc deficient.
Iron
Iron is necessary for the production of the brain chemical dopamine. Research shows that people with ADHD tend to have low levels of dopamine in the brain.
Some researchers suggest that iron deficiency may, therefore, play a role in ADHD. A 2018 reviewlooked at 17 studies comparing iron levels in children with and without ADHD.
The review found that children with iron deficiency were more likely to have ADHD. Also, in children with ADHD, there was an association between iron deficiency and more severe ADHD symptoms.
These results suggest that iron supplements may be beneficial for iron-deficient children with ADHD. However, further studies are necessary to establish whether this is the case.
Omega-3 fatty acids
Omega-3 and omega-6 are essential fatty acids (EFAs) that play an important role in brain health. Omega-3 is especially important for protecting brain tissue and aiding communication between brain cells.
A 2017 review investigated the benefit of omega-3 and omega-6 in the treatment of ADHD in children and young adults.
The review included 16 randomized controlled trials. Participants in each of these trials received either an EFA supplement or a placebo.
In 13 of the trials, the participants who took the EFA supplements showed improvements in the following:
• attention
• visual learning
• short-term memory
• hyperactivity
• impulsivity
Importantly, a 2016 review suggested that children with ADHD tend to have an imbalance rather than a deficiency of EFAs. In general, they have a higher ratio of omega-6 to omega-3 fatty acids.
The authors of the review suggest that addressing this imbalance is more important than simply increasing the intake of EFAs.
Other natural remedies
The following herbal supplements are also under investigation as potential treatments for ADHD.
Pycnogenol
Pycnogenol is an extract from the bark of the French maritime pine. According to a 2016 review, a small number of randomized controlled trials have found that Pycnogenol may improve ADHD symptoms.
According to the review authors, Pycnogenol is a powerful antioxidant that may work by reducing cell damage and improving blood flow to parts of the brain that play a role in ADHD.
However, further studies are necessary to support the use of Pycnogenol as a treatment for ADHD.
Ginkgo biloba
A person taking ginkgo biloba may experience nausea, diarrhea, or headaches as side effects.
Ginkgo biloba is an herb that derives from the leaves of the G. biloba tree. This herb contains chemicals called terpene trilactones. Research suggests that these chemicals help protect against brain cell damage and increase the availability of dopamine in the brain.
In 2013, a small study investigated the effects of ginkgo biloba on childhood ADHD.
The study found that taking a maximum daily dose of 240 mg of ginkgo for 3–5 weeks improved ADHD symptoms. According to parental reports, children showed improvements in attention, hyperactivity, and impulsiveness.
However, this was a small study with only 20 participants and no placebo control. Well-controlled clinical trials are necessary to confirm the benefits of ginkgo for ADHD.
Although the study did not report any adverse effects of the herbal extract, the National Institutes of Health list the following potential side effects:
• gastrointestinal upset
• nausea
• diarrhea
• headaches
• dizziness
• allergic reactions
As ginkgo is also a potential blood thinner, it may not be suitable for people with blood clotting disorders or those taking anticoagulant medications.
Summary
Many different types of supplement show promise as complementary treatments for ADHD. However, research into these supplements is still in its early stages.
Further clinical trials with more participants are necessary to get a better understanding of the effectiveness and safety of these supplements for ADHD.
|
__label__pos
| 0.521733 |
Pore-Scale Modelling of Fluid-Rock Chemical Interactions in Shale during Hydraulic Fracturing
Hossein Fazeli, Veerle Vandeginste, Arash Rabbani, Masoud Babaei
Research output: Contribution to journalArticlepeer-review
Abstract
During the hydraulic fracturing process in unconventional shale gas reservoirs, chemical interactions between the hydraulic fracturing fluid (HFF) and the shale rock could result in mineral precipitation and dissolution reactions, potentially influencing the gas transport by dissolving or clogging the fractures. The pore-scale distribution of the minerals, especially the highly reactive ones such as calcite, in the shale matrix can impact the structural evolution of the shale rocks. In the present study, a pore-scale reactive transport model is built to investigate the impact of the pore-scale distribution of calcite on the structural alteration of the shales. The alteration of the shales is caused by the barite precipitation, and the dissolution of calcite and pyrite. The simulation results show that the calcite dissolution leads to a permeability enhancement. The permeability enhancement for the shales with coarser calcite grains is more pronounced than that for the shales with finer grains of calcite. The results also indicate that the extent of the permeability enhancement is even more noticeable if the HFF is injected with a higher velocity. The fluid chemistry analysis indicates that the fluid pH for the shale with the fine grains of calcite is higher than that of the shale with the coarse calcite grains and that the injection of the HFF with a higher flowrate leads to the lower pH values. The calcite dissolution observed in the simulations mainly occurs near the inlet. For the shale with the finer calcite grains, barite precipitation also occurs mostly close to the inlet but for the shale with coarser calcite grains, barite precipitation extends more into the domain. This penetration depth increases when the HFF is injected with a higher velocity. In addition to the effect of the calcite distribution, we also used the pore-scale model to study the effect of the calcite content on the structural evolution of the shales. The results from these simulations showed that a higher calcite content can result in higher pH values, higher permeabilities, and also more barite precipitation in the domain.
Original languageEnglish
JournalEnergy & Fuels
Publication statusAccepted/In press - 3 Jun 2021
Fingerprint
Dive into the research topics of 'Pore-Scale Modelling of Fluid-Rock Chemical Interactions in Shale during Hydraulic Fracturing'. Together they form a unique fingerprint.
Cite this
|
__label__pos
| 0.910438 |
Advertisement
Machine Learning
, Volume 106, Issue 9–10, pp 1469–1495 | Cite as
Adaptive random forests for evolving data stream classification
• Heitor M. Gomes
• Albert Bifet
• Jesse Read
• Jean Paul Barddal
• Fabrício Enembreck
• Bernhard Pfharinger
• Geoff Holmes
• Talel Abdessalem
Article
Part of the following topical collections:
1. Special Issue of the ECML PKDD 2017 Journal Track
Abstract
Random forests is currently one of the most used machine learning algorithms in the non-streaming (batch) setting. This preference is attributable to its high learning performance and low demands with respect to input preparation and hyper-parameter tuning. However, in the challenging context of evolving data streams, there is no random forests algorithm that can be considered state-of-the-art in comparison to bagging and boosting based algorithms. In this work, we present the adaptive random forest (ARF) algorithm for classification of evolving data streams. In contrast to previous attempts of replicating random forests for data stream learning, ARF includes an effective resampling method and adaptive operators that can cope with different types of concept drifts without complex optimizations for different data sets. We present experiments with a parallel implementation of ARF which has no degradation in terms of classification performance in comparison to a serial implementation, since trees and adaptive operators are independent from one another. Finally, we compare ARF with state-of-the-art algorithms in a traditional test-then-train evaluation and a novel delayed labelling evaluation, and show that ARF is accurate and uses a feasible amount of resources.
Keywords
Data stream mining Random forests Ensemble learning Concept drift
1 Introduction
As technology advances, machine learning is becoming more pervasive in real world applications. Nowadays many businesses are aided by learning algorithms for several tasks such as: predicting users’ interests on advertisements, products or entertainment media recommendations, spam filters, autonomous driving, stock market predictions, face recognition, cancer detection, weather forecast, credit scoring, and many others. Some of these applications tolerate offline processing of data, which can take from a few minutes to weeks, while some of them demand real-time—or near real-time—processing as their source of data is non-stationary, i.e. it constitutes an evolving data stream.
While learning from evolving data streams one must be aware that it is infeasible to store data prior to learning as it is neither useful (old data may not represent the current concept) nor practical (data may surpass available memory). Also, it is expected that the learning algorithm is able to process instances at least as fast as new ones are made available, otherwise the system will either collapse due to lack of memory or start discarding upcoming data.
This evolving data stream learning setting has motivated the development of a multitude of methods for supervised (Oza 2005; Kolter et al. 2003; Bifet et al. 2010; Brzezinski and Stefanowski 2014; Gomes and Enembreck 2014), unsupervised (Guha et al. 2000; Ruiz et al. 2009; Barddal et al. 2015), and more recently semi-supervised learning (Qin et al. 2013; Sethi et al. 2014; Parker and Khan 2015). Ensemble learners are often preferred when learning from evolving data streams, since they are able to achieve high learning performance, without much optimization, and have the advantageous characteristic of being flexible as new learners can be selectively added, updated, reset or removed (Kolter et al. 2003; Bifet et al. 2009, 2010; Brzezinski and Stefanowski 2014).
Bagging (Breiman 1996), boosting (Freund et al. 1996) and random forests (Breiman 2001) are classic ensemble methods that achieve superior learning performance by aggregating multiple weak learners. Bagging uses sampling with reposition (i.e. resampling) to train classifiers on different subsets of instances, which effectively increases the variance of each classifier without increasing the overall bias. Boosting iteratively trains classifiers by increasing the weight of instances that were previously misclassified. Random forests grow decision trees by training them on resampled versions of the original data (similarly to bagging) and by randomly selecting a small number of features that can be inspected at each node for split. There are multiple versions of bagging and boosting that are part of the current state-of-the-art for evolving data stream learning, such as leveraging bagging (Bifet et al. 2010) and online smooth-boost (Chen et al. 2012). Random forests for evolving data stream learning is currently represented by the dynamic streaming random forests (Abdulsalam et al. 2008), which lacks a resampling method, uses a drift detection algorithm with no theoretical guarantees, and was evaluated only on limited synthetic data (1 data set with 7 million instances, 5 attributes and 5 classes).
In this work we present the adaptive random forests (ARF) algorithm, a new streaming classifier for evolving data streams. ARF is an adaptation of the classical Random Forest algorithm (Breiman 2001), and can also be viewed as an updated version of previous attempts to perform this adaptation (Abdulsalam et al. 2007, 2008). Therefore, the main novelty of ARF is in how it combines the batch algorithm traits with dynamic update methods to deal with evolving data streams. In comparison to previous adaptations of random forest to the stream setting (Abdulsalam et al. 2007, 2008), ARF uses a theoretically sound resampling method based on online bagging (Oza 2005) and an updated adaptive strategy to cope with evolving data streams. This adaptive strategy is based on using a drift monitor per tree to track warnings and drifts, and to train new trees in the background (when a warning is detected) before replacing them (when a drift is detected). We avoid bounding ARF to a specific drift detection algorithm to facilitate future adaptations, thus we present experiments using both ADWIN (Bifet and Gavaldà 2007) and Page Hinkley Test (Page 1954).
The main contributions of this paper are the following:
• Adaptive random forests (ARF) a new Random forests algorithm for evolving data stream classification. As shown in the empirical experiments in Sect. 6, ARF is able to obtain high classification in data streams with different characteristics without further hyper-parameter tuning. Since it is a sustainable off-the-shelf learner for the challenging task of evolving data stream classification, it is going to be useful for both practical applications and as a benchmark for future algorithms proposals in the field.
• Drift adaptation we propose a drift adaptation strategy that does not simply reset base models whenever a drift is detected. In fact, it start training a background tree after a warning has been detected and only replace the primary model if the drift occurs. This strategy can be adapted to other ensembles as it is not dependent on the base model.
• Parallel implementation we present experiments in terms of CPU time and RAM-hours of a parallel implementation of ARF.
• Comprehensive experimental setting very often experiments with novel classifiers are focused on the well known test-then-train setting, where it is assumed that labels for an instance are available before the next instance arrives. We discuss the implications of a setting where labels are not readily available (delayed setting) and report experiments based on it. Besides using accuracy to measure classification performance, we also report Kappa M (Bifet et al. 2015) and Kappa Temporal (Žliobaitė et al. 2015), which allow better estimations for data sets with imbalanced classtability-plasticity es and temporal dependencies, respectively.
• Open source All data sets and algorithms used in this paper are going to be available as an extension to the MOA software (Bifet et al. 2010), the most popular open source software on data stream mining,1 as a public available benchmark that other researchers can use in their research when developing new algorithms.
The remainder of this work is organized as follows. In Sect. 2 we describe the challenges, characteristics and different settings concerning evolving data streams classification. In Sect. 3 we briefly discuss related works for data stream classification. Section 4 contains the description of our novel algorithm, i.e. adaptive random forests. In Sect. 5 the experimental setting and data sets used are described. In Sect. 6 the results of the experiments are presented and thoroughly discussed. Finally, Sect. 7 concludes this work and poses directions for future work.
2 Problem statement
Data stream classification, or online classification, is similar to batch classification in the sense that both are concerned with predicting a nominal (class) value y of an unlabeled instance represented by a vector of characteristics x. The difference between online and batch resides in how learning, and predictions, take place. In data stream classification, instances are not readily available for training as part of a large static data set, instead, they are provided as a continuous stream of data in a fast-paced way. Prediction requests are expected to arrive at any time and the classifier must use its current model to make predictions. On top of that, it is assumed that concept drifts may occur (evolving data streams), which damage (or completely invalidate) the current learned model. Concept drifts might be interleaved with stable periods that vary in length, and as a consequence, besides learning new concepts it is also expected that the classifier retains previously learned knowledge. The ability to learn new concepts (plasticity) while retaining knowledge (stability) is known as the stability-plasticity dilemma (Lim and Harrison 2003; Gama et al. 2014). In other words, a data stream learner must be prepared to process a possibly infinite amount of instances, such that storage for further processing is possible as long as the algorithm can keep processing instances at least as fast as they arrive. Also, the algorithm must incorporate mechanisms to adapt its model to concept drifts, while selectively maintaining previously acquired knowledge.
Formally, a data stream S presents, every u time units, new unlabeled instances \(x^t\) to the classifier for prediction, such that \(x^t\) represents a vector of features made available at time t. Most of the existing works on data stream classification assumes that the true class label \(y^t\) corresponding to instance \(x^t\) is available before the next instance \(x^{t+1}\) is presented to the learning algorithm, thus the learner can use it for training immediately after it has been used for prediction. This setting may be realistic for problems like short-term stock marketing predictions, although this is not the only meaningful setting for data stream learning. In some real-world problems labels are not readily available, or some are never available, after predictions. In Fig. 1 we represent the characteristics of a stream learning problem according to when labels are made available, and briefly discuss them below:
• Immediate: labels are presented to the learner before the next instance arrives.
• Delayed: labels arrive with delay d which may be fixed or vary for different instances.
• Never: labels are never available to the learner.
Fig. 1
Stream learning according to labels arrival time
Situations where labels are never available (unsupervised learning) or where some percentage p of labels will never arrive (semi-supervised learning) are outside the scope of this work. Also, when labels are presented in a delayed fashion, it may be the case that they arrive in batches of size greater than one, and the learner must rapidly use these batches to update its model as new instances for prediction might arrive concomitantly. In this paper we evaluate our adaptive random forests (ARF) algorithm in both immediate and delayed settings. As well as comparing the results from both settings in terms of classification accuracy, we also report CPU time and memory consumption (RAM-hours) as estimates of computational resources usage.
3 Related work
Ensemble classifiers are often chosen for dealing with evolving data stream classification. Besides ensembles achieving (on average) higher classification performance than single models, this decision is also based on the distinctive trait that ensembles allow selective reset/remove/add/update of base models in response to drifts. Many state-of-the-art ensemble methods for data stream learning (Oza 2005; Chen et al. 2012; Pelossof et al. 2009; Beygelzimer et al. 2015) are adapted versions of bagging (Breiman 1996) and boosting (Freund and Schapire 1997). The standard online bagging algorithm uses \(\lambda =1\), which means that around \(37\%\) of the values output by the Poisson distribution are 0, another \(37\%\) are 1, and \(26\%\) are greater than 1. This implies that by using Poison (1) \(37\%\) of the instances are not used for training (value 0), \(37\%\) are used once (value 1), and \(26\%\) are trained with repetition (values greater than 1). Subsequent algorithms like leveraging bagging (Bifet et al. 2010) and the diversity for dealing with drifts ensemble (DDD) (Minku and Yao 2012) uses different values of \(\lambda \) to use more instances for training the base models (as in leveraging bagging) or to induce more diversity to the ensemble by using varying values of \(\lambda \) (as in DDD).
One advantage of adapting existing batch ensembles is that they have already been thoroughly studied, thus as long as the adaptation to online learning retains the original method properties it can benefit from previous theoretical guarantees. The first attempt to adapt random forests (Breiman 2001) to data stream learning is the streaming random forests (Abdulsalam et al. 2007). Streaming random forests grow binary Hoeffding trees while limiting the number of features considered for split at every node to a random subset of features and by training each tree on random samples (without replacement) of the training data. Effectively, trees are trained sequentially on a fixed number of instances controlled by a hyper-parameter tree window, which means that after a tree’s training is finished its model will never be updated. As a result, this approach is only reasonable for stationary data streams.
To cope with evolving data streams, ensembles are often coupled with drift detectors. For instance, leveraging bagging (Bifet et al. 2010) and ADWIN bagging (Bifet et al. 2009) use the ADaptive WINdowing (ADWIN) algorithm (Bifet and Gavaldà 2007), while DDD (Minku and Yao 2012) uses early drift detection method (EDDM) (Baena-García et al. 2006) to detect concept drifts. Another approach to deal with concept drifts while using an ensemble of classifiers is to constantly reset low performance classifiers (Kolter et al. 2003; Brzezinski and Stefanowski 2014; Gomes and Enembreck 2014). This reactive approach is useful to recover from gradual drifts, while methods based on drift detectors are more appropriate for rapidly recovering from abrupt drifts.
The same authors from streaming random forests (Abdulsalam et al. 2007) presented the dynamic streaming random forests (Abdulsalam et al. 2008) to cope with evolving data streams. Dynamic streaming random forests replaces the hyper-parameter tree window by a dynamically updated parameter tree min which is supposed to enforce trees that achieve performance at least better than random guessing. Dynamic streaming random Forests also includes an entropy-based drift detection technique that outputs an estimate percentage of concept change. According to this estimated percentage of concept change, more trees are reset. However, if it is 0, at least 25% of the trees are reset whenever a new block of labelled instances is available.
Our adaptive random forests (ARF) algorithm resembles dynamic streaming random forests as both use Hoeffding trees as base learners and include a drift detection operator. The first difference between both algorithms is that ARF simulates sampling with reposition via online bagging (Oza 2005) instead of growing each tree sequentially on different subsets of data. This is not only a more theoretically sustainable approach, but also has the practical effect of allowing training trees in parallel.
Another difference is that dynamic streaming random forests reset 25% of its trees every new batch of labelled instances, while ARF is based on a warning and drift detection scheme per tree, such that after a warning has been detected for one tree, another one (background tree) starts growing in parallel and replaces the tree only if the warning escalates to a drift.
Finally, ARF hyper-parameters are limited to the subset of features size m, the number of trees n and the thresholds that control the drift detection method sensitivity, thus it does not depend on difficult to set hyper-parameters such as the number of instances a tree must be trained on, or the minimum accuracy that a tree has to achieve before training stops.
4 Adaptive random forests
Random forests (Breiman 2001) is a widely used learning algorithm in non-stream (batch) classification and regression tasks. Random forests can grow many trees while preventing them from overfitting by decorrelating them via bootstrap aggregating (bagging Breiman 1996) and random selection of features during node split. The original random forests algorithm requires multiple passes over input data to create bootstraps for each tree, while for each internal node of every tree a pass over some portion of the original features.
In data stream learning it is infeasible to perform multiple passes over input data. Thus, an adaptation of Random Forests to streaming data depends on: (1) an appropriate online bootstrap aggregating process; and (2) limiting each leaf split decision to a subset of features. The second requirement is achieved by modifying the base tree induction algorithm, effectively by restricting the set of features considered for further splits to a random subset of size m, where \(m<M\) and M corresponds to the total number of features. To explain our adaptations to address the first requirement we need to discuss how bagging works in non-streaming, and how it is simulated in a streaming setting. In non-streaming bagging (Breiman 1996), each of the n base models is trained in a bootstrap sample of size Z created by drawing random samples with replacement from the training set. Each bootstrapped sample contains an original training instance K times, where \(P(K=k)\) follows a binomial distribution. For large values of Z this binomial distribution adheres to a Poisson (\(\lambda =1\)) distribution. Based on that, authors in Oza (2005) proposed the online bagging algorithm, which approximates the original random sampling with replacement by weighting instances2 according to a Poisson(\(\lambda =1\)) distribution. In ARF, we use Poisson (\(\lambda =6\)), as in leveraging bagging (Bifet et al. 2010), instead of Poisson (\(\lambda =1\)). This “leverages” resampling, and has the practical effect of increasing the probability of assigning higher weights to instances while training the base models.
The function responsible for inducing each base tree is detailed in Algorithm 1. Random forest tree training (RFTreeTrain) is based on the Hoeffding tree algorithm (i.e. very fast decision tree) (Domingos and Hulten 2000) with some important differences. First, RFTreeTrain does not include any early tree pruning. Second, whenever a new node is created (line 9, Algorithm 1) a random subset of features with size m is selected and split attempts (line 7, Algorithm 1) are limited to these features for the given node. Smaller values of GP 3 (line 6, Algorithm 1) causes recalculations of the split heuristic more frequently and tends to yield deeper trees. In general, deeper trees are acceptable, even desired, in random forests. It is acceptable because even if individual trees overfit, the variance reduction from averaging multiple trees prevents the whole forest from overfitting. It is desired as trees with very specialized models tend to differ more from one another.
The overall ARF pseudo-code is presented in Algorithm 2. To cope with stationary data streams a simple algorithm where each base tree is trained according to RFTreeTraining function as new instances are available would be sufficient, i.e. the lines 11–21 could be ommited from Algorithm 2. However, in ARF we aim at dealing with evolving data streams, thus it is necessary to include other strategies to cope with concept drifts. Concretely, these strategies include drift/warning detection methods, weighted voting and training trees in the background before replacing existing trees. The rest of this section is dedicated to explain and justify these strategies.
To cope with evolving data streams a drift detection algorithm is usually coupled with the ensemble algorithm (Bifet et al. 2009, 2010). The default approach is to reset learners immediately after a drift is signaled. This may decrease the ensemble classification performance, since this learner has not been trained on any instance, thus making it unable to positively impact the overall ensemble predictions. Instead of resetting trees as soon as drifts are detected, in ARF we use a more permissive threshold to detect warnings (line 11, Algorithm 2) and create “background” trees that are trained (line 16, Algorithm 2) along the ensemble without influence the ensemble predictions. If a drift is detected (line 15, Algorithm 2) for the tree that originated the warning signal it is then replaced by its respective background tree.
ARF is not bounded to a specific detector. To show how different drift detection methods would perform in our implementation, we present experiments with ADWIN and Page Hinkley Test (PHT) (Page 1954). Some drift detection algorithms might depend on many parameters (this is the case for PHT), however to simplify our pseudocode we assume only two different parameters one for warning detection \(\delta _{w}\) and another for drift detection \(\delta _{d}\). Effectively, for ADWIN \(\delta _{w}\) and \(\delta _{d}\) corresponds to the confidence level of the warning and drift detection, respectively, while in PHT each would comprise a set of parameters.
In ARF votes are weighted based on the trees’ test-then-train accuracy (line 9, Algorithm 2), i.e. assuming the tree l has seen \(n_l\) instances since its last reset and correctly classified \(c_l\) instances, such that \(c_l \le n_l\), then its weight will be \(c_l/n_l\). Assuming the drift and warning detection methods are precise, then this weighting reflects the tree performance on the current concept. An advantage of using this weighting mechanism is that it does not require a predefined window or fading factor to estimate accuracy as in other data stream ensembles (Brzeziński and Stefanowski 2011; Brzezinski and Stefanowski 2014; Gomes and Enembreck 2014). Similarly to the drift/warning detection method, other voting schemes could be used. To illustrate that we also present experiments using a simple majority vote.
4.1 Theoretical insights
Given the maximum features per split m, the number of classes c, the number of leaves l, and the maximum number of possible values per feature v, a single Hoeffding Tree (Domingos and Hulten 2000) demands \(O\left( lmcv \right) \) memory assuming memory depends only on the true concept (Domingos and Hulten 2000). Given T as the total number of trees and \(l_{max}\) as the maximum number of leaves for all trees, the ARF algorithm, without warning/drift detection, requires \(O\left( Tl_{max}mcv \right) \), while using drift detection requires the space allocated for each data structure per tree to be allocated. For example, ADWIN (Bifet and Gavaldà 2007) requires \(O(M \cdot \log (W/M))\), such that M is the number of buckets, while W is maximum numbers per memory word (Bifet and Gavaldà 2007), thus ARF using ADWIN for warning and drift detection requires \(O \left( T\left( (M \cdot \log (W/M) + l_{max}mcv \right) \right) \) of space.
The number of background trees is never greater than the maximum number of trees, i.e. \(|B| \le n\), thus in the worst case it is necessary to allocate 2n trees concurrently. However the warning/drift detection data structures are not activated in the background trees, thus they require less memory than an actual tree and this also prevents background trees from triggering warnings which could lead to multiple recursive creations of background trees.
Finally, in the Hoeffding Tree algorithm (Domingos and Hulten 2000) authors present a strategy to limit memory usage by introducing a threshold that represents the maximum available memory, in case this threshold is reached then the least promising leaves are deactivated. Assuming \(p_l\) is the probability that a leaf node is reach, and \(e_l\) is the observed error rate at l, then \(p_l \cdot e_l\) is an upper bound on the error reduction achievable by refining l, the least promising leaves are those that achieve the lowest values of \(p_l \cdot e_l\). Originally, Hoeffding Trees also include a pruning strategy that removes poor attributes early on, yet we do not include this operation in ARF as pruning in Random Forests reduces variability.
4.2 Parallelizing the adaptive random forests algorithm
The most time consuming task in ensemble classifiers is often training its base learners, exceptions being ensembles in which lazy learners are used. In a data stream configuration, base learners are recurrently responsible for other tasks, for example, keeping track of drift and updating individual data structures that represent their weights. In ARF, training a tree with an instance includes updates to the underlying drift detector, incrementing its estimate test-then-train accuracy, and, if a warning is signalled, starting a new background tree. The aforementioned operations can be executed independently for each tree, thus it is doable to execute them in separate threads. To verify the advantages of training trees in parallel we provide a parallel version ARF[M] and compare it against a standard serial implementation ARF[S]. Anticipating the results presented in the experiments section, the parallel version is around 3 times faster than the serial version and since we are simply paralleling independent operations there is no loss in classification performance, i.e. the results are exactly the same.
5 Experimental setting
In this section we present the experimental setting used. We evaluate the experiments in terms of memory, time and classification performance. Memory is measured in GBs and based on RAM-hours (Bifet et al. 2010), i.e. one GB of memory deployed for 1 h corresponds to one RAM-Hour. Processing time is measured in seconds and is based on the CPU time used for training and testing. To assess classification performance we perform tenfold cross-validation prequential evaluation (Bifet et al. 2015).4 This evaluation ought not be confused with the standard cross-validation from batch learning, which is not applicable to data stream classification mainly because instances can be strongly time-dependent, thus making it very difficult to organize instances in folds that reflects the characteristics of the data. Three different strategies were proposed in Bifet et al. (2015) for cross-validation prequential evaluation, namely: k-fold distributed cross-validation, k-fold distributed split-validation and k-fold distributed bootstrap validation. These strategies share the characteristic of training and testing k models in parallel, while they differ on how the folds are built. In our evaluation framework we use the k-fold distributed cross-validation as recommended in Bifet et al. (2015). In this strategy, each instance is used for testing in one randomly selected model and for training by all others.
Since accuracy can be misleading on data sets with class imbalance or temporal dependencies, so we also report Kappa M and Kappa Temporal. Bifet et al. (2015) show that Kappa M measure has advantages over Kappa statistic as it has a zero value for a majority class classifier. For data sets that exhibit temporal dependencies it is advisable to evaluate Kappa Temporal since it replaces majority class classifier with the NoChange classifier (Žliobaitė et al. 2015).
All the experiments were performed on machines with 40 cores5 and 200 GB of RAM. Experiments focusing resources usage were run individually and repeated 10 times to diminish perturbations on the results. We evaluate algorithms using the immediate setting and delayed setting. In the delayed setting, the delay was set to 1000 instances and the classification performance estimates are calculated the same way as they are in the immediate setting, i.e. a tenfold cross-validation. The only difference is ‘when’ labels become available to train the classifier, i.e. 1000 instances after the instance is used for prediction. To verify if there were statistically significant differences between algorithms, we performed non-parametric tests using the methodology from Demšar (2006). For the statistical test we employ the Friedman test with \(\alpha = 0.05\) and the null hypothesis “there were no statistical difference between given algorithms”, if it is rejected, then we proceed with the Nemenyi post-hoc test to identify these differences. All experiments were configured and executed within the massive online analysis (MOA) framework (Bifet et al. 2010).
We use 10 synthetic and 6 real data sets on our experiments. The synthetic data sets include abrupt, gradual, incremental drifts and one stationary data stream, while the real data sets have been thoroughly used in the literature to assess the classification performance of data stream classifiers and exhibit multiclass, temporal dependences and imbalanced data sets. The tenfold distributed cross-validation for SPAM data set with 100 base models did not finish for LevBag, OzaBag and OzaBoost, as the machine run out of memory (we have tried using up to 200GB of memory). Therefore we only report SPAM results in the end of this report to show how ARF performs on a data set with a massive amount of features (see Fig. 6). Our goal with this multitude of data sets with different characteristics is to show how ARF performs on each of these scenarios. Table 1 presents an overview of the data sets, while further details can be found in the rest of this section.
Table 1
Data sets configurations [A: Abrupt Drift, G: Gradual Drift, I\(_m\): Incremental Drift (moderate) and I\(_f\): Incremental Drift (fast)]
Data set
\(\#\) Instances
\(\#\) Features
Type
Drifts
\(\#\) Classes
MF label (%)
LF label (%)
LED\(_a\)
1,000,000
24
Synthetic
G
10
10.08
9.94
LED\(_g\)
1,000,000
24
Synthetic
G
10
10.08
9.94
SEA\(_a\)
1,000,000
3
Synthetic
G
2
57.55
42.45
SEA\(_g\)
1,000,000
3
Synthetic
G
2
57.55
42.45
AGR\(_a\)
1,000,000
9
Synthetic
A
2
52.83
47.17
AGR\(_g\)
1,000,000
9
Synthetic
G
2
52.83
47.17
RTG
1,000,000
10
Synthetic
N
2
57.82
42.18
RBF\(_m\)
1,000,000
10
Synthetic
I\(_m\)
5
30.01
9.27
RBF\(_f\)
1,000,000
10
Synthetic
I\(_f\)
5
30.01
9.27
HYPER
1,000,000
10
Synthetic
I\(_f\)
2
50.0
50.0
AIRL
539,383
7
Real
2
55.46
44.54
ELEC
45,312
8
Real
2
57.55
42.45
COVT
581,012
54
Real
7
48.76
0.47
GMSC
150,000
11
Real
2
93.32
6.68
KDD99
4,898,431
41
Real
23
57.32
0.00004
SPAM
9324
39,917
Real
2
74.4
25.6
MF Label and LF Label stands for Most Frequent and Less Frequent class label, respectively
LED The LED data set simulates both abrupt and gradual drifts based on the LED generator, early introduced in Breiman et al. (1984). This generator yields instances with 24 boolean features, 17 of which are irrelevant. The remaining 7 features corresponds to each segment of a seven-segment LED display. The goal is to predict the digit displayed on the LED display, where each feature has a 10% chance of being inverted. To simulate drifts in this data set the relevant features are swapped with irrelevant features. Concretely, we parametrize 3 gradual drifts each with an amplitude of 50k instances and centered at the 250k, 500k and 750k instance, respectively. The first drift swaps 3 features, the second drift swaps 5 features, and the last one 7 features. \(LED_g\) simulates 3 gradual drifts, while LED\(_a\) simulates 3 abrupt drifts.
SEA The SEA generator (Street and Kim 2001) produces data streams with three continuous attributes (\(f_1, f_2, f_3\)). The range of values that each attribute can assume is between 0 and 10. Only the first two attributes (\(f_1, f_2\)) are relevant, i.e. \(f_3\) does not influence the class value determination. New instances are obtained through randomly setting a point in a two dimensional space, such that these dimensions corresponds to \(f_1\) and \(f_2\). This two dimensional space is split into four blocks, each of which corresponds to one of four different functions. In each block a point belongs to class 1 if \(f_1+f_2 \le \theta \) and to class 0 otherwise. The threshold \(\theta \) used to split instances between class 0 and 1 assumes values 8 (block 1), 9 (block 2), 7 (block 3) and 9.5 (block 4). It is possible to add noise to class values, being the default value 10%, and to balance the number of instances of each class. SEA\(_g\) simulates 3 gradual drifts, while SEA\(_a\) simulates 3 abrupt drifts.
AGRAWAL AGR\(_a\) and AGR\(_g\) data sets are based on the AGRAWAL generator (Agrawal et al. 1993), which produces data streams with six nominal and three continuous attributes. There are ten different functions that map instances into two different classes. A perturbation factor is used to add noise to the data, both AGR\(_g\) and AGR\(_a\) includes 10% perturbation factor. This factor changes the original value of an attribute by adding a deviation value to it, which is defined according to a uniform random distribution. AGR\(_g\) simulates 3 gradual drifts, while AGR\(_a\) simulates 3 abrupt drifts.
RTG The random tree generator (RTG) (Domingos and Hulten 2000) builds a decision tree by randomly selecting attributes as split nodes and assigning random classes to each leaf. After the tree is build, new instances are obtained through the assignment of uniformly distributed random values to each attribute. The leaf reached after a traverse of the tree, according to the attribute values of an instance, determines its class value. RTG allows customizing the number of nominal and numeric attributes, as well as the number of classes. In our experiments we did not simulate drifts for the RTG data set.
RBF RBF\(_m\) and RBF\(_f\) data sets were generated using the radial basis function (RBF) generator. This generator creates centroids at random positions and associates them with a standard deviation value, a weight and a class label. To create new instances one centroid is selected at random, where centroids with higher weights have more chances to be selected. The new instance input values are set according to a random direction chosen to offset the centroid. The extent of the displacement is randomly drawn from a Gaussian distribution according to the standard deviation associated with the given centroid. To simulate incremental drifts, centroids move at a continuous rate, effectively causing new instances that ought to belong to one centroid to another with (maybe) a different class. Both RBF\(_m\) and RBF\(_f\) were parametrized with 50 centroids and all of them drift. RBF\(_m\) simulates a “moderate” incremental drift (speed of change set to 0.0001) while RBF\(_f\) simulates a more challenge “fast” incremental drift (speed of change set to 0.001).
HYPER The HYPER data set simulates an incremental drift and it was generated based on the hyperplane generator (Hulten et al. 2001). A hyperplane is a flat, \(n-1\) dimensional subset of that space that divides it into two disconnected parts. It is possible to change a hyperplane orientation and position by slightly changing its relative size of the weights \(w_i\). This generator can be used to simulate time-changing concepts, by varying the values of its weights as the stream progresses (Bifet et al. 2011). HYPER was parametrized with 10 attributes and a magnitude of change of 0.001.
Airlines The Airlines data set was inspired by the regression data set from Ikonomovska6. The task is to predict whether a given flight will be delayed given information on the scheduled departure. Thus, it has 2 possible classes: delayed or not delayed. This data set contains 539, 383 records with 7 attributes (3 numeric and 4 nominal).
Electricity The Electricity data set was collected from the Australian New South Wales Electricity Market, where prices are not fixed. These prices are affected by demand and supply of the market itself and set every 5 min. The Electricity data set contains 45,312 instances, where class labels identify the changes of the price (2 possible classes: up or down) relative to a moving average of the last 24 h. An important aspect of this data set is that it exhibits temporal dependencies.
Covertype The forest covertype data set represents forest cover type for 30 \(\times \) 30 m cells obtained from the US Forest Service Region 2 resource information system (RIS) data. Each class corresponds to a different cover type. This data set contains 581,012 instances, 54 attributes (10 numeric and 44 binary) and 7 imbalanced class labels.
GMSC The give me some credit (GMSC) data set7 is a credit scoring data set where the objective is to decide whether a loan should be allowed. This decision is crucial for banks since erroneous loans lead to the risk of default and unnecessary expenses on future lawsuits. The data set contains historical data provided on 150,000 borrowers, each described by 10 attributes.
Table 2
Accuracy in the immediate setting for ARF variations (# learners = 100)
Data set
\(\text {ARF}_\text {moderate}\)
\(\text {ARF}_\text {fast}\)
\(\text {ARF}_\text {PHT}\)
\(\text {ARF}_\text {noBkg}\)
\(\text {ARF}_\text {stdRF}\)
\(\text {ARF}_\text {maj}\)
LED\(_a\)
73.72
73.74
73.57
73.73
66.5
73.71
LED\(_g\)
72.87
72.89
72.83
72.84
66.36
72.86
SEA\(_a\)
89.66
89.66
89.58
89.66
87.27
89.66
SEA\(_g\)
89.24
89.23
89.25
89.24
87.2
89.24
AGR\(_a\)
89.75
89.98
89.3
89.75
79.88
89.6
AGR\(_g\)
84.54
84.6
84.45
84.73
76.96
84.39
RTG
93.91
93.91
93.91
93.89
93.89
93.89
RBF\(_m\)
86.02
86.19
85.18
86.05
74.96
86.01
RBF\(_f\)
72.36
72.46
70.73
72.45
47.02
72.21
HYPER
85.16
85.44
84.87
85.42
78.68
85.16
Synthetic avg
83.72
83.81
83.37
83.78
75.87
83.67
Synthetic avg rank
2.7
1.8
4.1
2.6
5.9
3.9
AIRL
66.26
66.48
66.03
66.66
65.09
66.23
ELEC
88.54
89.44
87.04
88.6
85.81
88.5
COVT
92.32
91.85
91.81
92.35
88.18
92.31
GMSC
93.55
93.55
93.55
93.55
93.55
93.55
KDD99
99.97
99.97
99.98
99.97
99.97
99.97
Real avg
88.13
88.26
87.68
88.23
86.52
88.11
Real avg rank
3.6
2.4
3.6
2.8
4.6
4
Overall avg
85.19
85.29
84.81
85.26
79.42
85.15
Overall avg rank
3
2
3.93
2.67
5.47
3.93
Bold values indicate the best results per data set
KDD99 KDD’99 data set8 is often used for assessing data stream mining algorithms’ accuracy due to its ephemeral characteristics (Aggarwal et al. 2003; Amini and Wah 2014). It corresponds to a cyber attack detection problem, i.e. attack or common access, an inherent streaming scenario since instances are sequentially presented as a time series (Aggarwal et al. 2003). This data set contains 4,898,431 instances and 41 attributes.
Spam The spam corpus data set was developed in Katakis et al. (2009) as the result of a text mining process on an online news dissemination system. The work presented in Katakis et al. (2009) intended on creating an incremental filtering of emails classifying them as spam or ham (not spam), and based on this classification, deciding whether an email was relevant or not for dissemination among users. This data set has 9324 instances and 39,917 boolean attributes, such that each attribute represents the presence of a single word (the attribute label) in the instance (e-mail).
5.1 Ensembles and parametrization
We compare ARF to state-of-the-art ensemble learners for data stream classification, including bagging and boosting variants with and without explicit drift detection and adaptation. Bagging variants includes online bagging (OzaBag) (Oza 2005) and leveraging bagging (LevBag) (Bifet et al. 2010). Boosting inspired algorithms are represented by online boosting (OzaBoost) (Oza 2005) and online smooth-boost (OSBoost) (Chen et al. 2012). The online accuracy updated ensemble (OAUE) (Brzezinski and Stefanowski 2014) is a dynamic ensemble designed specifically for data stream learning and it is neither based on bagging nor boosting.
Fig. 2
ARF variations nemenyi test (95% confidence level)—immediate setting with 100 learners
Fig. 3
ARF: accuracy (immediate) \(\times \) ensemble size (n) \(\times \) subspace size (m). Marked lines highlights \(m = \sqrt{M} + 1\). a AGR\(_g\). b AIRL. c COVT. d GMSC. e KDD99. f RTG
Fig. 4
ARF[M] and ARF[S] comparison in terms of CPU Time and Memory, for 10, 20, 50 and 100 learners. a CPU Time. b RAM-hours
Table 3
CPU time—immediate setting (# learners = 100)
Data set
ARF[S]
ARF[M]
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
1251.31
582.31
1388.63
1659.16
1305.46
1778.47
2698.73
LED\(_g\)
1236.91
679.68
1244.97
1567.29
1154.88
1847.86
2332.57
SEA\(_a\)
1293.37
490.08
466.27
684.69
507.4
493.18
1431.29
SEA\(_g\)
1272.34
461.99
459.96
602.56
491.54
454.83
1379.41
AGR\(_a\)
1864.13
818.63
710.86
854
828.83
661.61
3981.14
AGR\(_g\)
2002.59
821.73
804.08
903.02
801.96
690.55
3225.2
RTG
5910.1
475.57
571.51
701.78
889.57
636.74
2865.09
RBF\(_m\)
1713.33
1133.28
1438.18
1876.86
1335.2
1822.05
3440.54
RBF\(_f\)
1711.51
908.26
1389.02
1815.99
1273.64
1998.32
3517.02
HYPER
1736.24
837.89
976.29
1050.43
922.73
927.8
3708.08
Synthetic avg
1999.18
720.94
944.98
1171.58
951.12
1131.14
2857.91
Synthetic avg rank
5
1.8
2.8
5
3
3.5
6.9
AIRL
2745.49
361.31
544.75
896.69
626.04
448.45
4925.71
ELEC
73.37
31.28
30.01
24.69
34.69
28.01
104.97
COVT
1230.93
686.08
1160.96
1603.41
1148.46
1359.04
2906.84
GMSC
189.55
149.96
100.04
152.69
83.3
76.26
306.23
KDD99
4322.82
2109.04
2945.59
4910.54
3462.14
7553.36
4795.75
Real avg
1712.43
667.53
956.27
1517.6
1070.93
1893.02
2607.9
Real avg rank
5.2
2.2
2.8
4.6
3.2
3.4
6.6
Overall avg
1903.6
703.14
948.74
1286.92
991.06
1385.1
2774.57
Overall avg rank
5.07
1.93
2.8
4.87
3.07
3.47
6.8
Bold values indicate the best results per data set
Table 4
RAM-hours—immediate setting (# learners = 100)
Data set
ARF[S]
ARF[M]
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
0.054
0.023
0.297
0.151
0.279
0.162
0.056
LED\(_g\)
0.054
0.038
0.264
0.109
0.244
0.163
0.053
SEA\(_a\)
0.219
0.083
0.046
0.022
0.062
0.015
0.607
SEA\(_g\)
0.229
0.083
0.045
0.03
0.06
0.014
0.341
AGR\(_a\)
0.855
0.098
0.361
0.13
0.329
0.114
0.174
AGR\(_g\)
0.856
0.851
0.425
0.096
0.332
0.123
0.486
RTG
1.121
0.09
0.17
0.18
0.317
0.065
0.15
RBF\(_m\)
0.038
0.025
0.236
0.036
0.177
0.144
0.764
RBF\(_f\)
0.01
0.006
0.106
0.008
0.1
0.131
0.085
HYPER
0.173
0.084
0.413
0.035
0.361
0.116
1.075
Synthetic avg
0.361
0.138
0.236
0.08
0.226
0.105
0.379
Synthetic avg rank
4.8
2.5
5.2
2.6
4.9
3.1
4.9
AIRL
0.422
0.056
0.023
0.337
0.196
0.216
1.425
ELEC
0.001
0.001
0.001
0
0.001
0
0.003
COVT
0.002
0.002
0.516
0.089
0.557
0.178
0.19
GMSC
0.02
0.016
0.004
0.005
0.004
0.001
0.067
KDD99
0.013
0.007
0.499
0.039
1.335
0.992
0.253
Real avg
0.092
0.016
0.209
0.094
0.419
0.278
0.388
Real avg rank
4.4
2.6
3.4
3.2
5
3.4
6
Overall avg
0.271
0.098
0.227
0.084
0.29
0.162
0.382
Overall avg rank
4.86
2.64
4.43
2.71
4.86
3.07
5.43
Bold values indicate the best results per data set
All experiments use the Hoeffding Tree (Domingos and Hulten 2000) algorithm with Naive Bayes at the leaves (Holmes et al. 2005) as the base learner, which we refer to as Hoeffding Naive Bayes Tree (HNBT). ARF uses a variation of HNBT that limits splits to m randomly selected features, where \(m=\sqrt{M}+1\) in all our experiments (see Sect. 6.1 for experiments varying m). An important parameter of the trees is the grace period GP, which is used to optimize training time (Domingos and Hulten 2000) by delaying calculations of the heuristic measure G used to choose the test features (in this work we use Information Gain). By using smaller values of GP run time (and memory usage) is increased, and also causes trees to grow deeper, which enhances the overall variability of the forest, and consequently ARF’s classification performance. For consistency, we use the same base learner configuration for all ensembles, i.e. HNBTs with \(GP=50\). We report statistics for ensembles of 100 members, with the exception of adhoc experiments that focus on CPU Time and RAM-hours analysis. In the following sections we organize experiments as follows: (1) Comparisons among ARF and some of its variants; (2) Resource usage analysis; and (3) Comparisons of ARF against other state-of-the-art ensembles.
Table 5
Accuracy—immediate setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
73.72
69.18
73.35
68.88
72.53
73.92
LED\(_g\)
72.87
69.17
72.55
69.57
72.47
73.22
SEA\(_a\)
89.66
87.19
88.77
88.21
89.15
88.36
SEA\(_g\)
89.24
87.12
88.26
87.87
88.92
89.08
AGR\(_a\)
89.75
82.83
90.67
88.49
91.02
89.17
AGR\(_g\)
84.54
79.26
85.29
84.39
87.73
83.4
RTG
93.91
97.2
97
95.97
97.25
97.53
RBF\(_m\)
86.02
62.62
83.69
36.23
65.84
84.89
RBF\(_f\)
72.36
38.33
56.19
26.16
42.38
58.28
HYPER
85.16
80.2
87.67
85.93
87.88
87.45
Synthetic avg
83.72
75.31
82.34
73.17
79.52
82.53
Synthetic avg rank
2.5
5.4
2.9
5.1
2.6
2.5
AIRL
66.26
64.96
65.35
60.83
65.62
63.38
ELEC
88.54
82.51
86.37
90.17
87.05
88.53
COVT
92.32
84.05
92.26
93.83
86.34
93.08
GMSC
93.55
93.52
93.55
92.64
92.95
93.54
KDD99
99.97
99.93
2.61
99.01
99.93
99.96
Real avg
88.13
84.99
68.03
87.29
86.38
87.7
Real avg rank
1.6
4.8
4
3.8
3.8
3
Overall avg
85.19
78.54
77.57
77.88
81.8
84.25
Overall avg rank
2.2
5.2
3.27
4.67
3
2.67
Bold values indicate the best results per data set
Table 6
Kappa M—immediate setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
70.75
65.7
70.35
65.36
69.43
70.98
LED\(_g\)
69.8
65.68
69.45
66.13
69.35
70.2
SEA\(_a\)
74.21
68.05
71.98
70.59
72.93
70.96
SEA\(_g\)
73.16
67.86
70.71
69.75
72.37
72.77
AGR\(_a\)
78.26
63.61
80.22
75.6
80.96
77.04
AGR\(_g\)
67.22
56.04
68.82
66.9
73.98
64.8
RTG
85.56
93.36
92.89
90.45
93.48
94.14
RBF\(_m\)
80.03
46.59
76.69
8.89
51.19
78.42
RBF\(_f\)
60.51
11.88
37.41
\(-\)5.5
17.67
40.39
HYPER
70.27
60.33
75.29
71.81
75.72
74.85
Synthetic avg
72.98
59.91
71.38
58
67.71
71.45
Synthetic avg rank
2.5
5.4
2.9
5.1
2.6
2.5
AIRL
24.24
21.34
22.21
12.05
22.82
17.8
ELEC
73
58.79
67.89
76.84
69.49
72.97
COVT
85
68.87
84.89
87.96
73.35
86.5
GMSC
3.51
3
3.46
\(-\)10.17
\(-\)5.54
3.4
KDD99
99.93
99.83
\(-\)128.21
97.68
99.85
99.92
Real avg
57.14
50.37
10.05
52.87
51.99
56.12
Real avg rank
1.6
4.8
4
3.8
3.8
3
Overall avg
67.7
56.73
50.94
56.29
62.47
66.34
Overall avg rank
2.2
5.2
3.27
4.67
3
2.67
Bold values indicate the best results per data set
Table 7
Kappa temporal—immediate setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
70.79
65.74
70.38
65.41
69.46
71.01
LED\(_g\)
69.83
65.72
69.48
66.17
69.39
70.23
SEA\(_a\)
78.31
73.13
76.43
75.27
77.23
75.58
SEA\(_g\)
77.44
72.98
75.37
74.57
76.77
77.11
AGR\(_a\)
77.57
62.45
79.59
74.82
80.35
76.31
AGR\(_g\)
66.61
55.22
68.24
66.29
73.5
64.15
RTG
87.51
94.26
93.86
91.74
94.37
94.93
RBF\(_m\)
81.92
51.63
78.89
17.49
55.8
80.45
RBF\(_f\)
64.24
20.2
43.32
4.46
25.44
46.02
HYPER
70.32
60.4
75.33
71.87
75.77
74.9
Synthetic avg
74.45
62.17
73.09
60.81
69.81
73.07
Synthetic avg rank
2.5
5.4
2.9
5.1
2.6
2.5
AIRL
19.56
16.48
17.39
6.61
18.05
12.71
ELEC
21.86
\(-\)19.24
7.08
32.99
11.73
21.78
COVT
\(-\)55.59
\(-\)222.99
\(-\)56.81
\(-\) 24.91
\(-\)176.49
\(-\)40.07
GMSC
48.29
48.01
48.26
40.95
43.43
48.22
KDD99
\(-\) 140.48
\(-\)471.44
\(-\)769385.24
\(-\)7717.89
\(-\)416.24
\(-\)177.84
Real avg
\(-\) 21.27
\(-\)129.84
\(-\)153873.86
\(-\)1532.45
\(-\)103.9
\(-\)27.04
Real avg rank
1.6
4.8
4
3.8
3.8
3
Overall avg
42.54
\(-\)1.83
\(-\)51242.56
\(-\)470.28
11.9
39.7
Overall avg rank
2.2
5.2
3.27
4.67
3
2.67
Bold values indicate the best results per data set
Table 8
Accuracy—delayed setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
73.57
69.01
73.19
68.72
72.37
73.76
LED\(_g\)
72.76
69.03
72.44
69.44
72.36
73.16
SEA\(_a\)
89.57
87.11
88.68
88.14
89.06
88.27
SEA\(_g\)
89.17
87.03
88.17
87.81
88.84
89
AGR\(_a\)
89.58
82.67
90.48
88.31
90.84
88.98
AGR\(_g\)
84.48
79.11
85.14
84.28
87.59
83.3
RTG
93.85
97.13
96.94
95.91
97.19
97.46
RBF\(_m\)
83.45
56.69
80.42
34.7
59.72
81.81
RBF\(_f\)
29.12
28.76
28.69
26.12
28.43
27.82
HYPER
84.85
79.97
87.27
85.57
87.39
87.06
Synthetic avg
79.04
73.65
79.14
72.9
77.38
79.06
Synthetic avg rank
2.5
5.1
2.9
5.1
2.6
2.8
AIRL
64.93
64.82
65.13
60.63
65.32
62.74
ELEC
75.36
74.27
74.63
71.07
72.91
74.61
COVT
83.79
78.34
84.81
84.48
80.11
85.09
GMSC
93.55
93.52
93.55
92.67
92.96
93.55
KDD99
98.72
99.53
2.4
98.62
99.59
99.38
Real avg
83.27
82.1
64.1
81.49
82.18
83.07
Real avg rank
2.6
4
2.9
5.2
3.4
2.9
Overall avg
80.45
76.47
74.13
75.76
78.98
80.4
Overall avg rank
2.53
4.73
2.9
5.13
2.87
2.83
Bold values indicate the best results per data set
Table 9
Kappa M—delayed setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
70.58
65.51
70.16
65.18
69.25
70.79
LED\(_g\)
69.68
65.53
69.32
65.99
69.24
70.13
SEA\(_a\)
73.97
67.84
71.77
70.41
72.7
70.74
SEA\(_g\)
72.99
67.65
70.5
69.59
72.16
72.57
AGR\(_a\)
77.92
63.25
79.82
75.21
80.58
76.65
AGR\(_g\)
67.1
55.71
68.5
66.68
73.7
64.6
RTG
85.42
93.2
92.74
90.3
93.34
93.98
RBF\(_m\)
76.35
38.11
72.03
6.7
42.45
74.02
RBF\(_f\)
\(-\) 1.27
\(-\)1.78
\(-\)1.88
\(-\)5.56
\(-\)2.26
\(-\)3.13
HYPER
69.64
59.88
74.5
71.09
74.74
74.07
Synthetic avg
66.24
57.49
66.74
57.56
64.59
66.44
Synthetic avg rank
2.5
5.1
2.9
5.1
2.6
2.8
AIRL
21.26
21.03
21.72
11.61
22.14
16.35
ELEC
41.96
39.38
40.23
31.85
36.19
40.17
COVT
68.36
57.72
70.35
69.71
61.19
70.9
GMSC
3.53
3.08
3.51
\(-\)9.69
\(-\)5.41
3.51
KDD99
97
98.89
\(-\)128.69
96.76
99.05
98.55
Real avg
46.42
44.02
1.42
40.05
42.63
45.9
Real avg rank
2.6
4
3
5.2
3.4
2.8
Overall avg
59.63
53
44.97
51.72
57.27
59.59
Overall avg rank
2.53
4.73
2.93
5.13
2.87
2.8
Bold values indicate the best results per data set
Table 10
Kappa temporal—delayed setting (# learners = 100)
Data set
ARF
OzaBag
OAUE
OzaBoost
OSBoost
LevBag
LED\(_a\)
70.62
65.55
70.2
65.23
69.28
70.83
LED\(_g\)
69.72
65.57
69.35
66.02
69.27
70.16
SEA\(_a\)
78.11
72.95
76.25
75.11
77.04
75.39
SEA\(_g\)
77.29
72.8
75.19
74.43
76.59
76.94
AGR\(_a\)
77.21
62.08
79.17
74.42
79.96
75.9
AGR\(_g\)
66.49
54.89
67.91
66.06
73.21
63.94
RTG
87.39
94.12
93.72
91.61
94.24
94.79
RBF\(_m\)
78.59
43.96
74.67
15.52
47.89
76.47
RBF\(_f\)
8.3
7.83
7.74
4.41
7.4
6.61
HYPER
69.7
59.95
74.54
71.15
74.79
74.12
Synthetic avg
68.34
59.97
68.88
60.39
66.97
68.52
Synthetic avg rank
2.5
5.1
2.9
5.1
2.6
2.8
AIRL
16.39
16.14
16.87
6.14
17.33
11.17
ELEC
\(-\) 67.95
\(-\)75.4
\(-\)72.95
\(-\)97.18
\(-\)84.65
\(-\)73.1
COVT
\(-\)228.29
\(-\)338.67
\(-\)207.64
\(-\)214.26
\(-\)302.69
\(-\) 201.9
GMSC
48.29
48.05
48.28
41.21
43.5
48.28
KDD99
\(-\)10010.79
\(-\)3644.79
\(-\)771004.82
\(-\)10839.44
\(-\) 3103.47
\(-\)4775.42
Real avg
\(-\)2048.47
\(-\)798.93
\(-\)154244.05
\(-\)2220.7
\(-\) 685.99
\(-\)998.19
Real avg rank
2.6
4
3
5.2
3.4
2.8
Overall avg
\(-\)637.26
\(-\)226.33
\(-\)51368.77
\(-\)699.97
\(-\) 184.02
\(-\)287.05
Overall avg rank
2.53
4.73
2.93
5.13
2.87
2.8
Bold values indicate the best results per data set
6 Experiments
We start our experimentation by comparing variations of ARF to evaluate its sensitivity to parameters (e.g. drift and warning threshold, ensemble size and subspace size) and variations of the algorithm that deactivates some of its characteristics (e.g. drift detection, warning detection, weighted vote). The second set of experiments concerns the evaluation of computational resources usage (CPU time and RAM-hours). Finally, we present experiments comparing ARF and other state-of-the-art ensemble classifiers in terms of accuracy, Kappa M and Kappa T, for immediate and delayed settings.
6.1 ARF variations
Our first analysis is a comparison between 6 variations of the ARF algorithm, each of which ‘removes’ some characteristics from ARF (e.g. drift detection) or has a different parametrization (e.g. uses Page Hinkley drift detection). We did this comparison to illustrate the benefits of using ARF as previously stated in Sect. 4, and also to discuss how each strategy included in it contributes to the overall classification performance. Table 2 presents the immediate setting tenfold cross-validation accuracy for these variations. Each variation configuration is as follows:
• \(\text {ARF}_\text {moderate}\): Adopts a parametrization to ADWIN that results in less drifts/ warnings being flagged (\(\delta _w=0.0001\) and \(\delta _d=0.00001\)).
• \(\text {ARF}_\text {fast}\): Uses a parametrization of ADWIN that causes more drifts/warnings to be detected (\(\delta _w=0.01\) and \(\delta _d=0.001\)).
• \(\text {ARF}_\text {PHT}\): Uses Page Hinkley Test (PHT) to detected drifts/warnings (\(\delta _w=0.005, \delta _d=0.01\), other parameters: \(\lambda =50, \alpha =0.9999\)).
• \(\text {ARF}_\text {noBkg}\): Removes only the warning detection and background tree, therefore whenever drifts are detected the associated trees are immediately reset.
• \(\text {ARF}_\text {stdRF}\): This is a ‘pure’ online Random Forests version as it deactivates the detection algorithm, does not reset trees and uses majority vote.
• \(\text {ARF}_\text {maj}\): Same configuration as ARF\(_{moderate}\), but it uses majority vote instead of weighted majority.
Without any drift detection (\(\text {ARF}_\text {stdRF}\)) the results on data streams that contains drifts are degraded severely. If trees are reset immediately whenever a drift (\(\text {ARF}_\text {noBkg}\)) is detected the results improve in 2 real data sets (AIRL and COVT), although we observe better, yet small improvements, when using background trees and drift warnings (ARF\(_{moderate}\) and ARF\(_{fast}\)), especially on the synthetic data sets. In general, the weighted majority vote is capable of improving performance on almost every data set when we compare ARF\(_{moderate}\) and \(\text {ARF}_\text {maj}\), such that both use the exact same configuration, but the latter uses majority vote instead of weighted majority. This behavior can be attributed to the variance in weights during periods of drift, such that trees adapted to the current concept shall receive higher weights and obfuscate outdated trees. However, if trees’ weights are overestimated (or underestimated) this can lead to a combination that is inferior to majority vote. Therefore, if it is infeasible to obtain accurate weights, e.g. accuracy is not a reasonable metric for the data set, then it is safer to use majority vote or change the weighting function. ARF\(_{moderate}\) and ARF\(_{fast}\) differ the most on the real data set ELEC (almost 1% accuracy), while the other results are quite similar with a slight advantage for ARF\(_{fast}\). ARF\(_{fast}\) trains background trees for less time than ARF\(_{moderate}\) as it detects drifts sooner, while ARF\(_{noBkg}\) is an extreme case with no background training at all. In practice, it is necessary to experiment with the warning and drift detector parameters to find the optimal combination for the input data. However, it is less likely that not training the trees before adding them to the forest, even for short periods, would benefit the overall classification performance as the first decisions of a newly created tree are essentially random. On the other hand, it is expected that the improvements obtained by using background tree training might not differ a lot from the not using it, as the most important thing remains resetting trees when drifts occurs as short periods of random decisions can be ‘corrected’ as long as not all trees are undergoing this process at the same time. The best result for RTG is obtained by ARF\(_{PHT}\), however this data set does not contains any drift, thus it is not reasonable to attribute its classification performance to the Page Hinkley Test detector. Also, the difference between ARF\(_{moderate}\) and ARF\(_{PHT}\) is after the second decimal place.
The Friedman test based on the overall rankings of Table 2 (both synthetic and real data sets) indicated that there were differences among these ARF variations, the follow-up posthoc nemenyi test, presented in Fig. 2, indicates that there are no significant differences between \(ARF_{fast}, ARF_{moderate}, ARF_{PHT}, ARF_{noBkg}\) and \(ARF_{maj}\). Further experiments in this work are based on the \(\text {ARF}_\text {moderate}\) configuration and referred to solely as ARF (or ARF[M] or ARF[S] when evaluating resources usage).
To illustrate the impact of using different values for m (feature subset size) and n (ensemble size) we present 3D plots of six data sets in Fig. 3. In Figs. 3a, b, e it was clearly a good choice to use small values of m, however it might not always be the case as observed in Figs 3c, 3d and 3f. In the COVT, GMSC and RTG plots (Figs. 3c, d, f) we observe a trend where increasing the number of features results in classification performance improvements. For RTG we can affirm that this behavior is associated with the fact that the underlying data generator is based on a random assignment of values to instances and a decision tree traversal to determine the class label (see Sect. 6), which causes that no unique feature, or subset of features (other than the full set), is strongly correlated with the class label. Therefore when each tree is assigned the full set of features, and use only sampling with reposition as the diversity induction, better performance per base tree is achieved, thus the overall ensemble obtains better performance as well. We cannot affirm this same behavior for the real data sets that exhibit similar behavior as RTG (GMSC and COVT) as the underlying data generator is unknown.
6.2 Resources comparison between ARF[S] and ARF[M]
To assess the benefits in terms of resources usage we compare ARF[M] and ARF[S] implementations. We report average memory and processing time used to process all data sets for 10, 20, 50 and 100 classifiers. Figure 4a, b present the results of these experiments. It is expected that ARF[M] requires more memory than ARF[S], yet since it executes faster its average RAM-hours is lower in comparison to ARF[S]. Ideally, a parallel implementation on elements that are independent, in our case the trees’ training, must scale linearly in the number of elements if enough threads are available. Although there are some factors that forestall scalability in our implementation of ARF[M], such as the number of available threads, overhead on job creation at every new training instance and operations that are not parallelized (e.g. combining votes). Examining Fig. 4a, b one can see that when the number of trees is closer or less than 40 (number of available processors) the gains are more prominently, this is expected as there is a limited number of trees that can be trained at once.
6.3 ARF compared to other ensembles
This section comprises the comparison of ARF against state-of-the-art ensemble classifiers. First, we report the CPU time and RAM-hours for ensembles with 100 base models in Tables 3, 4. Since ARF[M] distributes the training and drift detection among several threads it is unsurprisingly the most efficient in terms of CPU time and memory used. Besides that, we note that ARF[S] outperforms leveraging bagging and is close to OAUE in terms of CPU time, while being very similar to others in terms of RAM-hours, yet worse than OAUE, OzaBag and OSBoost.
The next step in our comparison of ARF to other ensembles is the evaluation of its overall classification performance according to Accuracy, Kappa M and Kappa Temporal. We group experiments per evaluation metric and setting used (delayed or immediate) in Tables 5, 6, 7, 8, 9, and 10. The variations in the rankings from delayed to immediate suggest that ARF is more suitable to the immediate setting. In Table 5 we highlight ARF performance in \(\text {RBF}_m\) and \(\text {RBF}_f\) data sets, both containing incremental drifts. As previously mentioned in Sect. 6.1 ARF cannot obtain good results in RTG while using only \(m=\sqrt{M}+1\) features, this is emphasized when comparing ARF against other ensembles as ARF consistently obtains the worst results in RTG. ARF performs well on SEA\(_a\) and SEA\(_g\), however these results are not related to the random selection of features as SEA generator has only 3 features and each tree ends up using 3 features per split.9
Analysing the results from Kappa Temporal in Table 7 we observed that none of the classifiers were able to surpass the baseline (NoChange classifier, Žliobaitė et al. 2015) on the COVT data set. This characteristic is accentuated on the experiments using the delayed setting displayed in Table 10, where algorithms also failed to overcome the baseline on the ELEC data set as well. Probably, using a temporally augmented wrapper, as suggested in Žliobaitė et al. (2015), would aid this problem for the immediate setting, although it is unclear if it would solve the problem on the delayed setting. Through analysis of Kappa M on Tables 6, 9 we observed that differences in accuracy that appeared to be not very large are actually highlighted in Kappa M, for example, ARF and OzaBoost in data set AIRL achieved 66.26 and 60.83% accuracy, respectively, in terms of Kappa M ARF achieves 24.24% while OzaBoost only 12.05%.
We report only statistical tests based on the average rank of accuracy, since ranks did not change among Accuracy, Kappa M and Kappa Temporal. Concretely, we used the results from Tables 5, 8. The Friedman test indicates that there were significant differences in the immediate and delayed setting. We proceeded with the Nemenyi post-hoc test to identify these differences, which results are plotted in Fig. 5.
The statistical tests for the immediate setting indicates that there are no significant differences between ARF, LevBag, OSBoost and OUAE. While differences in the delayed setting are less prominent, including OzaBag to the aforementioned classifiers. This suggests that sometimes the active drift detection techniques are less impactating in the delayed setting as ARF and LevBag have their overall performance degraded when training is delayed. This is especially true for incremental drifts, as drift signals (and warning signals in ARF) are delayed and action is taken to accommodate a potentially already outdated concept. This is observable by analysing the accuracy drop from the immediate to delayed setting for ARF and LevBag in RBF\(_f\) (Tables 5, 8).
There is not much variation with respect to ranking changes while comparing the synthetic data sets results between the immediate and delayed settings. The only change is that OzaBag swaps rankings with LevBag in RBF\(_f\), which effectively boosts the overall OzaBag ranking. In the real data sets the variations are more prominent, such that ARF surpasses OzaBoost in the ELEC data set for the delayed setting, however ARF loses 1 average rank from the immediate to the delayed setting in the real data sets. Finally, OzaBag, OAUE and OSBoost improved their overall average rankings from the immediate results to the delayed results, while ARF, OzaBoost and LevBag, decreased their classification performances. Surprisingly, GMSC results improved in the delayed setting in comparison to those obtained in the immediate setting, this is better observable while comparing the Kappa M results from Tables 6, 9 for the GMSC data set.
Focusing on the real world data sets it is clear that ARF consistently obtains the best results or at least results that could be considered reasonable in contrast with other algorithms that even though achieve very good results, sometimes fail to obtain a reasonable model (e.g. OAUE and OzaBoost on KDD99).
Fig. 5
Nemenyi test with 95% confidence level. a Immediate setting with 100 learners. b Delayed setting with 100 learners
Fig. 6
Sorted plots of Accuracy, Kappa M and Kappa T over time (100 classifiers per ensemble). Solid and dashed vertical lines indicates drifts and drift window start/end, respectively. a Accuracy LED\(_g\). b Accuracy AGR\(_a\). c Accuracy RBF\(_m\). d Accuracy AIRL. e Kappa M AIRL. f Accuracy GMSC. g Kappa M GMSC. h Accuracy KDD99. i Kappa M KDD99. j Accuracy SPAM. k Kappa M SPAM. l Kappa T SPAM
In Fig. 6 some of the experiments from the immediate setting (see Tables 5, 6, 7). ARF is able to consistently achieve superior accuracy on \(\text {RBF}_m\) (Fig. 6c), which exhibits a moderate incremental drift. In LED\(_g\) (Fig. 6a) and \(\text {AGR}_a\) (Fig. 6b), ARF obtain a reasonable performance, even though it was not the method with highest accuracy it was able to adapt to the abrupt and gradual drifts. Figure 6d, e are interesting as the analysis solely focused on accuracy would indicate that classifiers stabilize after 200 thousand instances, however by observing the Kappa M plot it is visible that classifiers are actually improving relatively to the majority class classifier. Similarly GMSC and KDD99 plots in Fig. 6f–i shows that by using Kappa M on an imbalanced data set the differences between methods are intensified. Finally, on SPAM only ARF, OAUE and OSBoost could finish executing, the results in Fig. 6j–l shows that Kappa M for OSBoost is below −100 (not showing in the plot) indicating that it is not a reasonable choice for this data set. Also, in every plot from SPAM it is observable that OAUE and OSBoost are degrading over time while ARF maintains its performance stable.
7 Conclusion
In this work we have presented the adaptive random forests (ARF) algorithm, which enables the Random Forests algorithm for evolving data stream learning. We provide a serial and a parallel implementation of our algorithm, ARF[S] and ARF[M], respectively, and show that the parallel version can process the same amount of instances in reasonable time without any decrease in the classification performance. As a byproduct and additional contribution of this work we discuss stream learning according to when labels are available (immediate and delayed settings). We also remark that several of the techniques that were implemented on ARF can be used in other ensembles, such as warning detection and background trees.
We use a diverse set of data sets to show empirical evidence that ARF obtains good results in terms of classification performance (Accuracy, Kappa M and Kappa Temporal) and reasonable performance resources usage, even for the sequential version ARF[S], when compared to other state-of-the-art ensembles. The classification performance experiments are further divided into the usual immediate setting and the delayed setting. From these experiments we highlight the following characteristics of ARF:
• ARF obtains good classification performance on both delayed and immediate settings, especially on real world data sets;
• ARF can be used to process data streams with a large number of features, such as SPAM data set with almost fourty thousand features, using a relatively small number of trees (in our experiments 100);
• ARF can train its base trees in parallel without affecting its classification performance. This is an implementation concern, but it is useful to investigate and make it available along with the algorithm as scalability is often a concern;
• ARF might not be able to improve on data sets where all features are necessary to build a reasonable model (such as RTG).
In future work we will investigate how to optimize the run-time performance of ARF by limiting the number of detectors, as it is wasteful to maintain several detectors that often trigger at the same time. Another possibility is to implement a big data stream version of ARF, as we show in this work that each tree can be trained independently (the most time consuming task) without affecting the classification performance. Besides enhancing execution performance we are also interested in investigating the development of a semi-supervised strategy to deal with different real world scenarios, which might also lead to better performance on the delayed setting.
Footnotes
1. 1.
2. 2.
In this context, weighting an instance with a value w for a given base model is analogous to training the base model w times with that instance.
3. 3.
GP was originally introduced in Domingos and Hulten (2000) as \(n_{min}\), we use GP for consistency with the rest of our nomenclature.
4. 4.
Prequential evaluation is similar to test-then-train, the only difference between them is that prequential includes a fading factor to ‘forget’ old predictions performance.
5. 5.
Intel(R) Xeon(R) CPU E5-2660 v3 2.60GHz
6. 6.
7. 7.
8. 8.
9. 9.
After rounding \(\sqrt{3}+1\) to the closest integer we obtain 3, such that \(m=M\) for SEA\(_a\) and SEA\(_g\)
Notes
Acknowledgements
This project was partially financially supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) through the Programa de Suporte à Pós-Graduação de Instituições de Ensino Particulares (PROSUP) program for Doctorate students.
References
1. Abdulsalam, H., Skillicorn, D. B, & Martin, P. (2007). Streaming random forests. In 11th international on database engineering and applications symposium, IDEAS (pp. 225–232). IEEE.Google Scholar
2. Abdulsalam, H., Skillicorn, D. B, & Martin, P. (2008). Classifying evolving data streams using dynamic streaming random forests. In Database and expert systems applications (pp. 643–651). Springer.Google Scholar
3. Aggarwal, C. C., Han, J., Wang, J., & Yu, P. S. (2003). A framework for clustering evolving data streams. In Proceedings of the 29th international conference on very large data bases, VLDB ’03 (Vol. 29, pp. 81–92). VLDB Endowment.Google Scholar
4. Agrawal, R., Imilielinski, T., & Swani, A. (1993). Database mining: A performance perspective. IEEE Transactions on Knowledge and Data Engineering, 5(6), 914–925.CrossRefGoogle Scholar
5. Amini, A., & Wah, T. Y. (2014). On density-based data streams clustering algorithms: A survey. Journal of Computer Science and Technology, 29(1), 116–141.CrossRefGoogle Scholar
6. Baena-Garcia, M., del Campo-Avila, J., Fidalgo, R., Bifet, A., Gavalda, R., & Morales-Bueno, R. (2006). Early drift detection method. In ECML PKDD 2006 workshop on knowledge discovery from data streams.Google Scholar
7. Barddal, J. P., Gomes, H. M., & Enembreck, F. (2015). Sncstream: A social network-based data stream clustering algorithm. Proceedings of the 30th annual ACM symposium on applied computing, SAC ’15 (pp. 935–940). New York, NY: ACM.CrossRefGoogle Scholar
8. Beygelzimer, A., Kale, S., & Luo, H. (2015). Optimal and adaptive algorithms for online boosting. In International conference in machine learning (pp. 2323–2331).Google Scholar
9. Bifet, A., de Francisci Morales, G., Read, J., Holmes, G., & Pfahringer, B. (2015). Efficient online evaluation of big data stream classifiers. In Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 59–68). ACM.Google Scholar
10. Bifet, A., & Gavaldà, R. (2007). Learning from time-changing data with adaptive windowing. In SIAM.Google Scholar
11. Bifet, A., Holmes, G., Kirkby, R., & Pfahringer, B. (2010). Moa: Massive online analysis. The Journal of Machine Learning Research, 11, 1601–1604.Google Scholar
12. Bifet, A., Holmes, G., Kirkby, R., & Pfahringer, B. (2011). MOA data stream mining: A practical approach. Centre for Open Software Innovation. http://heanet.dl.sourceforge.net/project/moa-datastream/documentation/StreamMining.pdf.
13. Bifet, A., Holmes, G., & Pfahringer, B. (2010). Leveraging bagging for evolving data streams. In PKDD (pp. 135–150).Google Scholar
14. Bifet, A., Holmes, G., Pfahringer, B., & Frank, E. (2010). Fast perceptron decision tree learning from evolving data streams. In PAKDD. Lecture notes in computer science (pp. 299–310). Springer.Google Scholar
15. Bifet, A., Holmes, G., Pfahringer, B., Kirkby, R., & Gavaldà, R. (2009, June). New ensemble methods for evolving data streams. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 139–148). ACM SIGKDD.Google Scholar
16. Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123–140.zbMATHGoogle Scholar
17. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5–32.CrossRefzbMATHGoogle Scholar
18. Breiman, L., Friedman, J., Stone, C. J., & Olshen, R. A. (1984). Classification and regression trees. Boca Raton: CRC Press.zbMATHGoogle Scholar
19. Brzeziński, D., & Stefanowski, J. (2011). Accuracy updated ensemble for data streams with concept drift. In Hybrid artificial intelligent systems (pp. 155–163). Springer.Google Scholar
20. Brzezinski, D., & Stefanowski, J. (2014). Combining block-based and online methods in learning ensembles from concept drifting data streams. Information Sciences, 265, 50–67.MathSciNetCrossRefzbMATHGoogle Scholar
21. Chen, S.-T., Lin, H.-T., & Lu, C.-J. (2012, June). An online boosting algorithm with theoretical justifications. In Proceedings of the international conference on machine learning (ICML).Google Scholar
22. Demšar, J. (2006). Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7, 1–30.MathSciNetzbMATHGoogle Scholar
23. Domingos, P., & Hulten, G. (2000, September). Mining high-speed data streams. In Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 71–80). ACM SIGKDD.Google Scholar
24. Freund, Y., Schapire, R. E., et al. (1996). Experiments with a new boosting algorithm. ICML, 96, 148–156.Google Scholar
25. Freund, Y., & Schapire, R. E. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1), 119–139.MathSciNetCrossRefzbMATHGoogle Scholar
26. Gama, J., Zliobaite, I., Bifet, A., Pechenizkiy, M., & Bouchachia, A. (2014). A survey on concept drift adaptation. ACM Computing Surveys, 46(4), 44:1–44:37.Google Scholar
27. Gomes, H. M., & Enembreck, F. (2014, March). Sae2: advances on the social adaptive ensemble classifier for data streams. In Proceedings of the 29th annual ACM symposium on applied computing (SAC), SAC 2014 (pp. 199–206). ACM.Google Scholar
28. Guha, S., Mishra, N., Motwani, R., & O’Callaghan, L. (2000). Clustering data streams. In Proceedings of the 41st annual symposium on foundations of computer science (pp. 359–366). IEEE.Google Scholar
29. Holmes, G., Kirkby, R., & Pfahringer, B. (2005). Stress-testing hoeffding trees. In PKDD (pp. 495–502).Google Scholar
30. Hulten, G., Spencer, L., & Domingos, P. (2001). Mining time-changing data streams. In Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 97–106). ACM.Google Scholar
31. Katakis, I., Tsoumakas, G., Banos, E., Bassiliades, N., & Vlahavas, I. (2009). An adaptive personalized news dissemination system. Journal of Intelligent Information Systems, 32(2), 191–212.CrossRefGoogle Scholar
32. Kolter, J. Z, & Maloof, M. et al. (2003). Dynamic weighted majority: A new ensemble method for tracking concept drift. In Third IEEE international conference on data mining, ICDM 2003 (pp. 123–130). IEEE.Google Scholar
33. Lim, C. P., & Harrison, R. F. (2003). Online pattern classification with multiple neural network systems: An experimental study. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 33(2), 235–247.Google Scholar
34. Minku, L. L., & Yao, X. (2012). Ddd: A new ensemble approach for dealing with concept drift. IEEE Transactions on Knowledge and Data Engineering, 24(4), 619–633.CrossRefGoogle Scholar
35. Oza, N. C. (2005). Online bagging and boosting. IEEE International Conference on Systems, Man and Cybernetics, 3, 2340–2345.Google Scholar
36. Page, E. S. (1954). Continuous inspection schemes. Biometrika, 41(1/2), 100–115.MathSciNetCrossRefzbMATHGoogle Scholar
37. Parker, B. S., & Khan, L. (2015). Detecting and tracking concept class drift and emergence in non-stationary fast data streams. In Twenty-ninth AAAI conference on artificial intelligence.Google Scholar
38. Pelossof, R., Jones, M., Vovsha, I., & Rudin, C. (2009). Online coordinate boosting. In IEEE 12th international conference on computer vision workshops (ICCV Workshops) (pp. 1354–1361). IEEE.Google Scholar
39. Qin, X., Zhang, Y., Li, C., & Li, X. (2013). Learning from data streams with only positive and unlabeled data. Journal of Intelligent Information Systems, 40(3), 405–430.CrossRefGoogle Scholar
40. Ruiz, C., Menasalvas, E., & Spiliopoulou, M. (2009). Discovery science: 12th international conference, DS 2009, Porto, Portugal, October 3–5, 2009 (pp. 287–301). Chapter C-DenStream: Using domain knowledge on a data stream. Springer: BerlinGoogle Scholar
41. Sethi, T. S., Kantardzic, M., Arabmakki, E., & Hu, H. (2014). An ensemble classification approach for handling spatio-temporal drifts in partially labeled data streams. In IEEE 15th international conference on information reuse and integration (IRI) (pp. 725–732). IEEE.Google Scholar
42. Street, W. N., & Kim, Y. S. (2001). A streaming ensemble algorithm (sea) for large-scale classification. In Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 377–382). ACM.Google Scholar
43. Žliobaitė, I., Bifet, A., Read, J., Pfahringer, B., & Holmes, G. (2015). Evaluation methods and decision theory for classification of streaming data with temporal dependence. Machine Learning, 98(3), 455–482.MathSciNetCrossRefzbMATHGoogle Scholar
Copyright information
© The Author(s) 2017
Authors and Affiliations
1. 1.PPGIaPontifícia Universidade Católica do ParanáCuritibaBrazil
2. 2.LTCI, Télécom ParisTechUniversité Paris-SaclayParisFrance
3. 3.LIXÉcole PolytechniquePalaiseauFrance
4. 4.Department of Computer ScienceUniversity of WaikatoHamiltonNew Zealand
5. 5.UMI CNRS IPAL & School of ComputingNational University of SingaporeSingaporeSingapore
Personalised recommendations
|
__label__pos
| 0.796337 |
How to create table in oracle
How can I create table in Oracle?
Introduction to Oracle CREATE TABLE statement
1. First, specify the table name and schema name to which the new table belongs on the CREATE TABLE clause.
2. Second, list all columns of the table within the parentheses.
3. Third, add table constraints if applicable e.g., primary key, foreign key, check.
How do you create a table example?
SQL CREATE TABLE Statement
1. CREATE TABLE table_name ( column1 datatype, column2 datatype, column3 datatype,
2. Example. CREATE TABLE Persons ( PersonID int, LastName varchar(255),
3. CREATE TABLE new_table_name AS. SELECT column1, column2, FROM existing_table_name. WHERE .;
4. Example. CREATE TABLE TestTable AS. SELECT customername, contactname.
How do you create a table from an existing table in Oracle?
Answer: To do this, the Oracle CREATE TABLE syntax is: CREATE TABLE new_table AS (SELECT * FROM old_table WHERE 1=2); For example: CREATE TABLE suppliers AS (SELECT * FROM companies WHERE 1=2);
How do I create a selected query table?
You can create one table from another by adding a SELECT statement at the end of the CREATE TABLE statement:
1. CREATE TABLE new_tbl [AS] SELECT * FROM orig_tbl;
2. mysql> CREATE TABLE bar (UNIQUE (n)) SELECT n FROM foo;
3. CREATE TABLE foo (a TINYINT NOT NULL) SELECT b+1 AS a FROM bar;
How do you create a table from another table?
A copy of an existing table can be created using a combination of the CREATE TABLE statement and the SELECT statement. The new table has the same column definitions. All columns or specific columns can be selected.
How do you insert data into a table?
SQL INSERTInserting One or More Rows Into a Table
1. First, the table, which you want to insert a new row, in the INSERT INTO clause.
2. Second, a comma-separated list of columns in the table surrounded by parentheses.
3. Third, a comma-separated list of values surrounded by parentheses in the VALUES clause.
Does select into create a table?
The SELECT INTO statement creates a new table and inserts rows from the query into it. If you want to copy the partial data from the source table, you use the WHERE clause to specify which rows to copy.
How do you create a temp table?
There are two methods of creating temporary tables. The simplest way of creating a temporary table is by using an INTO statement within a SELECT query. Let’s create a temporary table that contains the name, age, and gender of all the male student records from the student table.
What is the difference between a temp table and table variable?
A Temp table is easy to create and back up data. Table variable involves the effort when you usually create the normal tables. Table variable will store in the physical memory for some of the data, then later when the size increases it will be moved to the tempdb.
How do I know if a temp table exists?
Again, the best sure-fire way to do it is to just check for OBJECT_ID(‘TEMPDB.. #TEST‘) if it’s NOT NULL, then the temp table exists.
How do you insert data into a temp table?
Syntax
1. — Create Local temporary table.
2. Create Table #myTable (id Int , Name nvarchar(20))
3. Insert data into Temporary Tables.
4. Insert into #myTable Values (1,’Saurabh’);
5. Insert into #myTable Values (2,’Darshan’);
6. Insert into #myTable Values (3,’Smiten’);
7. — Select Data from the Temporary Tables.
8. Select * from #myTable.
How do you add to a temp table without creating it?
Inserting Data into Temporary Table without Creating its
1. select * INTO #TEMPTABLE from DataMasterView.
2. select * from #TEMPTABLE.
3. drop table #TEMPTABLE.
Do temp tables need to be dropped?
No you don’t need to drop temp tables. That notwithstanding, I tend to do a conditional drop at the beginning of a sproc and it has nothing to do with any effect on the spoc. Rather, they are an artifact from development and testing prior to conversion to a stored procedure.
Can we create foreign key in temp table?
One of the restrictions on a foreign key relationship is that you cannot delete a row from a key table that is depended upon by your temp table. Could be because you can‘t have cross-database foreign key constraints and temp tables technically are created in the TempDB database.
How do you create an index?
The CREATE INDEX statement is used to create indexes in tables. Indexes are used to retrieve data from the database more quickly than otherwise. The users cannot see the indexes, they are just used to speed up searches/queries.
How do you create an index table?
Indexes can be created or dropped with no effect on the data. Creating an index involves the CREATE INDEX statement, which allows you to name the index, to specify the table and which column or columns to index, and to indicate whether the index is in an ascending or descending order.
How do I make my temp table faster?
Scenario: Table variable can be MEMORY_OPTIMIZED=ON. A traditional table variable represents a table in the tempdb database. For much faster performance you can memory-optimize your table variable.
Which is faster temp table or table?
Whereas, a Temporary table (#temp) is created in the tempdb database. So table variable is faster then temporary table. ⇒ Temporary tables are allowed CREATE INDEXes whereas, Table variables aren’t allowed CREATE INDEX instead they can have index by using Primary Key or Unique Constraint.
Is CTE better than temp table?
It is a temporary result set and typically it may be a result of complex sub-query. Unlike the temporary table, its life is limited to the current query. It is defined by using WITH statement. CTE improves readability and ease in maintenance of complex queries and sub-queries.
Do temp tables make queries run faster?
Since temporary tables are stored in memory, they are significantly faster than disk-based tables. Consequently, they can be effectively used as intermediate storage areas, to speed up query execution by helping to break up complex queries into simpler components, or as a substitute for subquery and join support.
Is a view faster than a query?
Views make queries faster to write, but they don’t improve the underlying query performance. Once we create an indexed view, every time we modify data in the underlying tables then not only must SQL Server maintain the index entries on those tables, but also the index entries on the view.
Is CTE a temp table?
This biggest difference is that a CTE can only be used in the current query scope whereas a temporary table or table variable can exist for the entire duration of the session allowing you to perform many different DML operations against them.
|
__label__pos
| 1 |
Home > SWT > Dark Side of SWT, #1 Peer Communication
Dark Side of SWT, #1 Peer Communication
I began JAVA since 1995, And I loved Swing then SWT.
Now I am a big fan of SWT since 2002. And I have some worries about SWT that I want to share with you.
Why SWT
For long time, SWT is best solution for Java UI. The primary reasons are:
• Native Look & Feel, Performance
• JFace
Native Look&Feel, Performance
In early stage of Java, Standard UI for Java, AWT was very ugly and slow.
There was a big war around Java UI. Primary topic in the war was Unified Experience VS Native Experience.
• Unified Experience, Same Look&Feel in all kind of platform: Swing
• Native Experience, Native Look&Feel in each platform: AWT, SWT
Since one of primary philosophy in Java is “Write once run everywhere(in same way!)”, Sun raised hand of Amy Fowler who is leader of Swing, and denied standard proposal of SWT. (I think actual reason is little bit different. Hint: Sun developed NetBeans.)
All UI Objects in SWT are just proxies to OS’s UI Objects. So application looks very harmonious with their native OS because all UIs are actually native. It is why do we have to dispose SWT Resources and Widgets.
In other words, It is working slightly different for each platform. ex:
• In OSX, Closing shell not dispatching focus out or modify event from text field in shell
• In OSX, Buttons can’t take keyboard focus, So what if some wizard page contains only buttons, it can’t have context help.
• In windows 95, Adavnaced Graphics may not work
• … and so many things …
You have to test every platform what if you have choose SWT.
Behavior of widgets are handled by Native OS, ex: expanding/collapsing tree. So it is very fast. SWT translates Native Events to SWT Events(Display#readAndDispatch), So developer can extend behavior of widgets using Java.
JFace
JFace is most elegant and easy, and well designed library for UI. JFace provides awesome MVC patterns for SWT. So SWT can stay very simple and low-level. Most good experience of Eclipse Application are came with JFace. Swing is much more complex then SWT because there is nothing likes JFace.
JFace is also good tutorial or guide about how to use SWT smart. It’s big heritage.
Peer communication: Is it really fast?
SWT translates messages between Java and OS world. It called as “Peer Communication”. In General, Peer communications between different machine are very slow since it requires:
• Synchronization
• Data conversion
When you commit a command through SWT, SWT translate it and send to OS. OS will work what you ordered. What if amount of work is larger than cost of peer communication, It’s Okay. In other case, It’s not.
In general, OS doing not much since almost controllers are written with Java in SWT. When you click the button, OS generate event, SWT will translate it and dispatch, Java Listener will do some job.
AWT’s Peer communication uses same strategy, buy it is very buggy and slow because they tried to accomplish Write Once Run Everywhere. So communications costs much than SWT. But, Natives are natives, differents are differents. So it was failed.
Example of terrible peer communication performance
public class Example {
public static void main(String[] args) {
long start = System.currentTimeMillis();
Display display = Display.getDefault();
Image image = new Image(display, 640, 480);
GC gc = new GC(image);
gc.setForeground(display.getSystemColor(SWT.COLOR_RED));
for(int x=0; x<640; x++){
for(int y=0; y<480; y++){
gc.drawPoint(x, y);
}
}
long elpasedTime = System.currentTimeMillis() - start;
System.out.println("done:" + elpasedTime);
}
}
It fills red pixels into a 640*480 image using SWT. It costs more then 2000 milliseconds! Because Line 12 cause Peer Communication 307,200 times!
How about this, Let replace line 10~14 to below:
gc.fillRectangle(0, 0, 640, 480);
It costs about 300 milliseconds now. They are semantically same task but peer communications are reduced. There was a big difference in performance.
Someone may think first example is too inefficient to compare, see next.
Remove Peer Communication
public class Example {
public static void main(String[] args) {
long start = System.currentTimeMillis();
PaletteData palette = new PaletteData(0xff0000, 0xff00, 0xff);
ImageData data = new ImageData(640, 480, 32, palette);
RGB red = new RGB(255, 0, 0);
for (int x = 0; x < 640; x++) {
for (int y = 0; y < 480; y++) {
data.setPixel(x, y, palette.getPixel(red));
}
}
long elapsed = System.currentTimeMillis() - start;
System.out.println("done:" + elapsed);
}
}
This codes are exactly same with first example except there is no peer communication since PaletteData, RGB and ImageData are pure java objects.
It costs only 193 milliseconds. And this code can be executed in Non-UI thread. So we don’t have to block UI when we create images.
We know Reducing peer communication or eliminating peer communication is very important topic to develop UI Applications with SWT now. However, in many case, We can’t reduce peer communication. Consider situation that we have to update all TreeItems by it’s model change. We have to perform below codes for all TreeItems:
TreeItem item = ...;
Model model = item.getData();
item.setText(model.getLabel());
item.setImage(model.getImage());
Number of peer communications are increased as count of tree items. It’s a reason for that why TreeViewer#refresh() is so slow.
In this case, We can use Deferred Update Strategy, Lazy Content Providing or Virtual FLAG to improve performance. But these techniques are pretty tough to developers.
Lightweight UI
In these days, Swing is super fast since it uses GPU. Native performance is not important anymore since native behavior is tend to be smaller than actual business task or rendering codes. And almost machine has it’s own GPU.
For instance, GEF needs to manipulate very complex UI without Peer Cost, So they developed Draw2d(light-weight, Pure Java UI Library which is rendered on FigureCanvas). So we can use various UIs without loosing performance in GEF Editors.
Figures in Draw2D are almost same with Swing. Swing UIs are rendered by JVM, Figures in Draw2d are rendered by FigureCanvas(LightWeightSystem). So there are no peer cost.
(Actually Figure Canvas uses Native GC when it render, So it uses peer communications. But Figure Updater optimizes this context to reduce peer communication. Defining or manipulating UI elements are toll free! not like SWT)
For same purpose, Nebula provides some widgets like Grid. It can takes massive amount of model and massive number of UI elements.
Conclusion
SWT is fast? Yes! and No!! You have to care about peer communication to make your application support massive scale.
Categories: SWT Tags:
1. 2012/10/22 at 10:14 pm
Great friend!
1. No trackbacks yet.
Leave a Reply
Fill in your details below or click an icon to log in:
WordPress.com Logo
You are commenting using your WordPress.com account. Log Out / Change )
Twitter picture
You are commenting using your Twitter account. Log Out / Change )
Facebook photo
You are commenting using your Facebook account. Log Out / Change )
Google+ photo
You are commenting using your Google+ account. Log Out / Change )
Connecting to %s
%d bloggers like this:
|
__label__pos
| 0.81589 |
HDK
All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Pages
HOM_SceneViewer.h
Go to the documentation of this file.
1 /*
2 * PROPRIETARY INFORMATION. This software is proprietary to
3 * Side Effects Software Inc., and is not to be reproduced,
4 * transmitted, or disclosed in any way without written permission.
5 *
6 * COMMENTS:
7 */
8
9 #ifndef __HOM_SceneViewer_h__
10 #define __HOM_SceneViewer_h__
11
12 #include "HOM_PathBasedPaneTab.h"
13 #include "HOM_EnumModules.h"
14 #include "HOM_BoundingBox.h"
15 #include "HOM_Vector3.h"
16 #include "HOM_Vector2.h"
17 #include <vector>
18
20 class HOM_DopData;
24 class HOM_Selection;
26
27 SWIGOUT(%rename(SceneViewer) HOM_SceneViewer;)
28
30 {
31 public:
33 { HOM_CONSTRUCT_OBJECT(this) }
34
35 // Because the lowermost base classes initialize the virtual bases
36 // before any non-virtual bases, the correct thing to do here is
37 // explicitly call the constructor for HOM_PaneTab.
39 : HOM_PaneTab(pane), HOM_PathBasedPaneTab(pane)
40 { HOM_CONSTRUCT_OBJECT(this) }
41
42 virtual ~HOM_SceneViewer()
43 { HOM_DESTRUCT_OBJECT(this) }
44
45 // Let swig know we're overriding __repr__ for this class so it doesn't
46 // provide its own __repr__.
47 SWIGOUT(virtual std::string __repr__() = 0;)
48
49 virtual std::vector<HOM_ElemPtr<HOM_GeometryViewport> > viewports() = 0;
50 SWIGOUT(%newobject findViewport;)
51 virtual HOM_GeometryViewport *findViewport(const char *name) = 0;
52 virtual HOM_GeometryViewport *curViewport() = 0;
53
54 virtual std::string currentState() = 0;
55 virtual void enterViewState(bool wait_for_exit = false) = 0;
56 virtual void enterCurrentNodeState(bool wait_for_exit = false) = 0;
57 virtual void enterTranslateToolState(bool wait_for_exit = false) = 0;
58 virtual void enterRotateToolState(bool wait_for_exit = false) = 0;
59 virtual void enterScaleToolState(bool wait_for_exit = false) = 0;
60 SWIGOUT(%kwargs setCurrentState;)
61 virtual void setCurrentState(const char *state, bool wait_for_exit = false,
62 const HOM_EnumValue &generate =
63 HOM_stateGenerateMode::Insert,
64 bool request_new_on_generate = false) = 0;
65
66 virtual bool isCreateInContext() = 0;
67
68 virtual HOM_EnumValue& viewportLayout() = 0;
69 virtual void setViewportLayout(HOM_EnumValue &layout, int single = -1) = 0;
70
71 SWIGOUT(%kwargs selectObjects;)
72 virtual std::vector<HOM_ElemPtr<HOM_Node> > selectObjects(
73 const char *prompt = "Select objects",
74 int sel_index = 0,
75 bool allow_drag = false,
76 bool quick_select = false,
77 bool use_existing_selection = true,
78 bool allow_multisel = true,
79 const std::vector<std::string> &allowed_types =
80 std::vector<std::string>(1, "*"),
81 const char *icon = NULL,
82 const char *label = NULL,
83 const std::vector<std::string> &prior_selection_paths =
84 std::vector<std::string>(),
85 const std::vector<std::string> &prior_selection_ids =
86 std::vector<std::string>(),
87 const std::vector<HOM_Selection *> &prior_selections =
88 std::vector<HOM_Selection *>(),
89 HOM_ParmTemplateGroup *toolbox_templategroup = nullptr,
90 HOM_ParmTemplateGroup *toolbox1_templategroup = nullptr,
91 bool confirm_existing = false
92 ) = 0;
93
94 SWIGOUT(%newobject selectGeometry;)
95 SWIGOUT(%kwargs selectGeometry;)
96 virtual HOM_GeometrySelection *selectGeometry(
97 const char *prompt = "Select geometry",
98 int sel_index = 0,
99 bool allow_drag = false,
100 bool quick_select = false,
101 bool use_existing_selection = true,
102 const char *initial_selection = NULL,
103 HOM_EnumValue *initial_selection_type = NULL,
104 bool ordered = false,
105 const std::vector<HOM_EnumValue *> geometry_types =
106 std::vector<HOM_EnumValue *>(),
107 const std::vector<HOM_EnumValue *> primitive_types =
108 std::vector<HOM_EnumValue *>(),
109 bool allow_obj_sel = true,
110 const char *icon = NULL,
111 const char *label = NULL,
112 const std::vector<std::string> &prior_selection_paths =
113 std::vector<std::string>(),
114 const std::vector<std::string> &prior_selection_ids =
115 std::vector<std::string>(),
116 const std::vector<HOM_Selection *> &prior_selections =
117 std::vector<HOM_Selection *>(),
118 bool allow_other_sops = true,
119 bool consume_selections = true) = 0;
120
121 SWIGOUT(%kwargs selectDynamics;)
122 virtual std::vector<HOM_ElemPtr<HOM_DopData> > selectDynamics(
123 const char *prompt = "Select dynamics objects",
124 int sel_index = 0,
125 bool allow_objects = true,
126 bool allow_modifiers = false,
127 bool quick_select = false,
128 bool use_existing_selection = true,
129 bool allow_multisel = true,
130 const char *icon = NULL,
131 const char *label = NULL,
132 const std::vector<std::string> &prior_selection_paths =
133 std::vector<std::string>(),
134 const std::vector<std::string> &prior_selection_ids =
135 std::vector<std::string>(),
136 const std::vector<HOM_Selection *> &prior_selections =
137 std::vector<HOM_Selection *>()) = 0;
138
139 SWIGOUT(%kwargs selectDynamicsPoints;)
140 virtual std::vector<std::pair<HOM_ElemPtr<HOM_DopData>, HOM_ElemPtr<HOM_GeometrySelection> > > selectDynamicsPoints(
141 const char *prompt = "Select dynamics points",
142 int sel_index = 0,
143 bool quick_select = false,
144 bool use_existing_selection = true,
145 bool allow_multisel = true,
146 bool only_select_points = true,
147 bool object_based_point_selection = false,
148 bool use_last_selected_object = false,
149 const char *icon = NULL,
150 const char *label = NULL,
151 const std::vector<std::string> &prior_selection_paths =
152 std::vector<std::string>(),
153 const std::vector<std::string> &prior_selection_ids =
154 std::vector<std::string>(),
155 const std::vector<HOM_Selection *> &prior_selections =
156 std::vector<HOM_Selection *>()) = 0;
157
158 SWIGOUT(%kwargs selectDynamicsPolygons;)
159 virtual std::vector<std::pair<HOM_ElemPtr<HOM_DopData>, HOM_ElemPtr<HOM_GeometrySelection> > > selectDynamicsPolygons(
160 const char *prompt = "Select dynamics polygons",
161 int sel_index = 0,
162 bool quick_select = false,
163 bool use_existing_selection = true,
164 bool object_based_point_selection = false,
165 bool use_last_selected_object = false,
166 const char *icon = NULL,
167 const char *label = NULL,
168 const std::vector<std::string> &prior_selection_paths =
169 std::vector<std::string>(),
170 const std::vector<std::string> &prior_selection_ids =
171 std::vector<std::string>(),
172 const std::vector<HOM_Selection *> &prior_selections =
173 std::vector<HOM_Selection *>()) = 0;
174
175 SWIGOUT(%newobject selectPositions;)
176 SWIGOUT(%kwargs selectPositions;)
177 virtual std::vector<HOM_ElemPtr<HOM_Vector3> > selectPositions(
178 const char *prompt = "Click to specify a position",
179 int number_of_positions = 1,
180 bool connect_positions = true,
181 bool show_coordinates = true,
182 const HOM_BoundingBox &bbox = HOM_BoundingBox(),
183 HOM_EnumValue &position_type = HOM_positionType::WorldSpace,
184 const char *icon = NULL,
185 const char *label = NULL) = 0;
186
187 SWIGOUT(%newobject currentGeometrySelection;)
188 virtual HOM_GeometrySelection *currentGeometrySelection() = 0;
189
190 virtual void setCurrentGeometrySelection(
191 HOM_EnumValue &geometry_type,
192 const std::vector<HOM_Node *> &nodes,
193 const std::vector<HOM_Selection *> &selections) = 0;
194
195 // Snapping control
196 virtual HOM_EnumValue &snappingMode() = 0;
197 virtual void setSnappingMode(HOM_EnumValue &snapping_mode) = 0;
198
199 virtual bool isSnappingToTemplates() = 0;
200 virtual void setSnapToTemplates(bool on) = 0;
201
202 virtual bool isSnappingToOtherObjects() = 0;
203 virtual void setSnapToOtherObjects(bool on) = 0;
204
205 virtual bool isDepthSnapping() = 0;
206 virtual void setDepthSnapping(bool on) = 0;
207
208 virtual bool isOrientingOnSnap() = 0;
209 virtual void setOrientOnSnap(bool on) = 0;
210
211 // Selection control
212 virtual bool isPickingVisibleGeometry() = 0;
213 virtual void setPickingVisibleGeometry(bool on) = 0;
214
215 virtual bool isPickingContainedGeometry() = 0;
216 virtual void setPickingContainedGeometry(bool on) = 0;
217
218 virtual bool isGroupPicking() = 0;
219 virtual void setGroupPicking(bool on) = 0;
220
221 virtual bool isWholeGeometryPicking() = 0;
222 virtual void setWholeGeometryPicking(bool on) = 0;
223
224 virtual bool isSecureSelection() = 0;
225 virtual void setSecureSelection(bool on) = 0;
226
227 virtual bool isPickingCurrentNode() = 0;
228 virtual void setPickingCurrentNode(bool on) = 0;
229
230 virtual HOM_EnumValue &pickGeometryType() = 0;
231 virtual void setPickGeometryType(HOM_EnumValue &geometry_type) = 0;
232
233 virtual HOM_EnumValue &selectionMode() = 0;
234 virtual void setSelectionMode(HOM_EnumValue &style) = 0;
235
236 virtual HOM_EnumValue &pickStyle() = 0;
237 virtual void setPickStyle(HOM_EnumValue &style) = 0;
238
239 virtual HOM_EnumValue &pickModifier() = 0;
240 virtual void setPickModifier(HOM_EnumValue &modifier) = 0;
241
242 virtual HOM_EnumValue &defaultPickModifier() = 0;
243 virtual void setDefaultPickModifier(HOM_EnumValue &modifier) = 0;
244
245 virtual HOM_EnumValue &pickFacing() = 0;
246 virtual void setPickFacing(HOM_EnumValue &facing) = 0;
247
248 // Group list control
249 virtual bool isGroupListVisible() = 0;
250 virtual void setGroupListVisible(bool on) = 0;
251
252 virtual bool isGroupListColoringGeometry() = 0;
253 virtual void setGroupListColoringGeometry(bool on) = 0;
254
255 virtual bool isGroupListShowingEmptyGroups() = 0;
256 virtual void setGroupListShowingEmptyGroups(bool on) = 0;
257
258 virtual bool isGroupListShowingOnlyPreSelectedGroups() = 0;
259 virtual void setGroupListShowingOnlyPreSelectedGroups(bool on) = 0;
260
261 virtual bool isGroupListCondensingPathHierarchies() = 0;
262 virtual void setGroupListCondensingPathHierarchies(bool on) = 0;
263
264 virtual HOM_Vector2 *groupListSize() = 0;
265 virtual void setGroupListSize(double width, double height) = 0;
266
267 virtual HOM_EnumValue &groupListType() = 0;
268 virtual void setGroupListType(HOM_EnumValue &group_list_type) = 0;
269
270 virtual std::string groupListMask() = 0;
271 virtual void setGroupListMask(const char *mask) = 0;
272
273 // Construction plane access
274 SWIGOUT(%newobject constructionPlane;)
275 virtual HOM_ConstructionPlane *constructionPlane() = 0;
276
277 SWIGOUT(%newobject flipbookSettings;)
278 virtual HOM_FlipbookSettings *flipbookSettings() = 0;
279
280 SWIGOUT(%kwargs flipbook;)
281 virtual void flipbook(HOM_GeometryViewport *viewport = NULL,
282 HOM_FlipbookSettings *settings = NULL,
283 bool open_dialog = false) = 0;
284
285 virtual void runShelfTool(const char *tool_name) = 0;
286
287 virtual void displayRadialMenu(const std::string &name) = 0;
288 };
289
290 #endif
#define HOM_DESTRUCT_OBJECT(pointer)
Definition: HOM_Module.h:983
GLuint GLsizei const GLchar * label
Definition: glcorearb.h:2544
GLsizei const GLchar *const * string
Definition: glcorearb.h:813
#define SWIGOUT(x)
Definition: HOM_Defines.h:24
GLint GLuint mask
Definition: glcorearb.h:123
GLint GLsizei width
Definition: glcorearb.h:102
virtual std::string __repr__()=0
#define HOM_API
Definition: HOM_API.h:13
#define HOM_CONSTRUCT_OBJECT(pointer)
Definition: HOM_Module.h:982
GLuint const GLchar * name
Definition: glcorearb.h:785
HOM_SceneViewer(const HOM_SceneViewer &pane)
GLint GLsizei GLsizei height
Definition: glcorearb.h:102
virtual ~HOM_SceneViewer()
|
__label__pos
| 0.999447 |
/* $OpenBSD: init_main.c,v 1.315 2022/02/22 01:15:01 guenther Exp $ */ /* $NetBSD: init_main.c,v 1.84.4.1 1996/06/02 09:08:06 mrg Exp $ */ /* * Copyright (c) 1995 Christopher G. Demetriou. All rights reserved. * Copyright (c) 1982, 1986, 1989, 1991, 1992, 1993 * The Regents of the University of California. All rights reserved. * (c) UNIX System Laboratories, Inc. * All or some portions of this file are derived from material licensed * to the University of California by American Telephone and Telegraph * Co. or Unix System Laboratories, Inc. and are reproduced herein with * the permission of UNIX System Laboratories, Inc. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * 3. Neither the name of the University nor the names of its contributors * may be used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE REGENTS AND CONTRIBUTORS ``AS IS'' AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE * ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS * OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) * HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY * OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF * SUCH DAMAGE. * * @(#)init_main.c 8.9 (Berkeley) 1/21/94 */ #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #ifdef SYSVSHM #include #endif #ifdef SYSVSEM #include #endif #ifdef SYSVMSG #include #endif #include #include #include #include #include #include #include #include #include #include #include #include #include #include #include #if defined(CRYPTO) #include #include #endif #if defined(KUBSAN) extern void kubsan_init(void); #endif #if defined(NFSSERVER) || defined(NFSCLIENT) extern void nfs_init(void); #endif #include "stoeplitz.h" #if NSTOEPLITZ > 0 extern void stoeplitz_init(void); #endif #include "mpath.h" #include "vscsi.h" #include "softraid.h" const char copyright[] = "Copyright (c) 1982, 1986, 1989, 1991, 1993\n" "\tThe Regents of the University of California. All rights reserved.\n" "Copyright (c) 1995-2022 OpenBSD. All rights reserved. https://www.OpenBSD.org\n"; /* Components of the first process -- never freed. */ struct session session0; struct pgrp pgrp0; struct proc proc0; struct process process0; struct plimit limit0; struct vmspace vmspace0; struct sigacts sigacts0; struct process *initprocess; struct proc *reaperproc; extern struct user *proc0paddr; struct vnode *rootvp, *swapdev_vp; int boothowto; int db_active = 0; int ncpus = 1; int ncpusfound = 1; /* number of cpus we find */ volatile int start_init_exec; /* semaphore for start_init() */ #if !defined(NO_PROPOLICE) long __guard_local __attribute__((section(".openbsd.randomdata"))); #endif /* XXX return int so gcc -Werror won't complain */ int main(void *); void check_console(struct proc *); void start_init(void *); void db_ctf_init(void); void prof_init(void); void init_exec(void); void futex_init(void); void taskq_init(void); void timeout_proc_init(void); void pool_gc_pages(void *); void percpu_init(void); #ifdef DIAGNOSTIC int pdevinit_done = 0; #endif /* * System startup; initialize the world, create process 0, mount root * filesystem, and fork to create init and pagedaemon. Most of the * hard work is done in the lower-level initialization routines including * startup(), which does memory initialization and autoconfiguration. */ /* XXX return int, so gcc -Werror won't complain */ int main(void *framep) { struct proc *p; struct process *pr; struct pdevinit *pdev; extern struct pdevinit pdevinit[]; extern void disk_init(void); /* * Initialize the current process pointer (curproc) before * any possible traps/probes to simplify trap processing. */ curproc = p = &proc0; p->p_cpu = curcpu(); /* * Initialize timeouts. */ timeout_startup(); /* * Attempt to find console and initialize * in case of early panic or other messages. */ config_init(); /* init autoconfiguration data structures */ consinit(); printf("%s\n", copyright); #ifdef KUBSAN /* Initialize kubsan. */ kubsan_init(); #endif WITNESS_INITIALIZE(); KERNEL_LOCK_INIT(); SCHED_LOCK_INIT(); rw_obj_init(); uvm_init(); disk_init(); /* must come before autoconfiguration */ tty_init(); /* initialise tty's */ cpu_startup(); random_start(boothowto & RB_GOODRANDOM); /* Start the flow */ /* * Initialize mbuf's. Do this now because we might attempt to * allocate mbufs or mbuf clusters during autoconfiguration. */ mbinit(); #if NSTOEPLITZ > 0 stoeplitz_init(); #endif /* Initialize sockets. */ soinit(); /* Initialize SRP subsystem. */ srp_startup(); /* Initialize SMR subsystem. */ smr_startup(); /* * Initialize process and pgrp structures. */ procinit(); /* Initialize file locking. */ lf_init(); /* * Initialize filedescriptors. */ filedesc_init(); /* * Initialize pipes. */ pipe_init(); /* * Initialize kqueues. */ kqueue_init(); /* * Initialize futexes. */ futex_init(); /* Create credentials. */ p->p_ucred = crget(); p->p_ucred->cr_ngroups = 1; /* group 0 */ /* * Create process 0 (the swapper). */ pr = &process0; process_initialize(pr, p); LIST_INSERT_HEAD(&allprocess, pr, ps_list); LIST_INSERT_HEAD(PIDHASH(0), pr, ps_hash); atomic_setbits_int(&pr->ps_flags, PS_SYSTEM); /* Set the default routing table/domain. */ process0.ps_rtableid = 0; LIST_INSERT_HEAD(&allproc, p, p_list); pr->ps_pgrp = &pgrp0; LIST_INSERT_HEAD(TIDHASH(0), p, p_hash); LIST_INSERT_HEAD(PGRPHASH(0), &pgrp0, pg_hash); LIST_INIT(&pgrp0.pg_members); LIST_INSERT_HEAD(&pgrp0.pg_members, pr, ps_pglist); pgrp0.pg_session = &session0; session0.s_count = 1; session0.s_leader = pr; atomic_setbits_int(&p->p_flag, P_SYSTEM); p->p_stat = SONPROC; pr->ps_nice = NZERO; strlcpy(pr->ps_comm, "swapper", sizeof(pr->ps_comm)); /* Init timeouts. */ timeout_set(&p->p_sleep_to, endtsleep, p); /* Initialize signal state for process 0. */ signal_init(); siginit(&sigacts0); pr->ps_sigacts = &sigacts0; /* Create the file descriptor table. */ p->p_fd = pr->ps_fd = fdinit(); /* Create the limits structures. */ lim_startup(&limit0); pr->ps_limit = &limit0; /* Allocate a prototype map so we have something to fork. */ uvmspace_init(&vmspace0, pmap_kernel(), round_page(VM_MIN_ADDRESS), trunc_page(VM_MAX_ADDRESS), TRUE, TRUE); p->p_vmspace = pr->ps_vmspace = &vmspace0; p->p_addr = proc0paddr; /* XXX */ /* * Charge root for one process. */ (void)chgproccnt(0, 1); /* Initialize run queues */ sched_init_runqueues(); sleep_queue_init(); sched_init_cpu(curcpu()); p->p_cpu->ci_randseed = (arc4random() & 0x7fffffff) + 1; /* Initialize timeouts in process context. */ timeout_proc_init(); /* Initialize task queues */ taskq_init(); /* Initialize the interface/address trees */ ifinit(); /* Lock the kernel on behalf of proc0. */ KERNEL_LOCK(); #if NMPATH > 0 /* Attach mpath before hardware */ config_rootfound("mpath", NULL); #endif /* Configure the devices */ cpu_configure(); /* Configure virtual memory system, set vm rlimits. */ uvm_init_limits(&limit0); /* Per CPU memory allocation */ percpu_init(); /* Initialize the file systems. */ #if defined(NFSSERVER) || defined(NFSCLIENT) nfs_init(); /* initialize server/shared data */ #endif vfsinit(); /* Start real time and statistics clocks. */ initclocks(); #ifdef SYSVSHM /* Initialize System V style shared memory. */ shminit(); #endif #ifdef SYSVSEM /* Initialize System V style semaphores. */ seminit(); #endif #ifdef SYSVMSG /* Initialize System V style message queues. */ msginit(); #endif /* Create default routing table before attaching lo0. */ rtable_init(); /* Attach pseudo-devices. */ for (pdev = pdevinit; pdev->pdev_attach != NULL; pdev++) if (pdev->pdev_count > 0) (*pdev->pdev_attach)(pdev->pdev_count); #ifdef DIAGNOSTIC pdevinit_done = 1; #endif #ifdef CRYPTO crypto_init(); swcr_init(); #endif /* CRYPTO */ /* * Initialize protocols. */ domaininit(); initconsbuf(); #if defined(GPROF) || defined(DDBPROF) /* Initialize kernel profiling. */ prof_init(); #endif /* Enable per-CPU data. */ mbcpuinit(); kqueue_init_percpu(); uvm_init_percpu(); /* init exec */ init_exec(); /* Start the scheduler */ scheduler_start(); /* * Create process 1 (init(8)). We do this now, as Unix has * historically had init be process 1, and changing this would * probably upset a lot of people. * * Note that process 1 won't immediately exec init(8), but will * wait for us to inform it that the root file system has been * mounted. */ { struct proc *initproc; if (fork1(p, FORK_FORK, start_init, NULL, NULL, &initproc)) panic("fork init"); initprocess = initproc->p_p; } randompid = 1; /* * Create any kernel threads whose creation was deferred because * initprocess had not yet been created. */ kthread_run_deferred_queue(); /* * Now that device driver threads have been created, wait for * them to finish any deferred autoconfiguration. Note we don't * need to lock this semaphore, since we haven't booted any * secondary processors, yet. */ while (config_pending) tsleep_nsec(&config_pending, PWAIT, "cfpend", INFSLP); dostartuphooks(); #if NVSCSI > 0 config_rootfound("vscsi", NULL); #endif #if NSOFTRAID > 0 config_rootfound("softraid", NULL); #endif /* Configure root/swap devices */ diskconf(); #ifdef DDB /* Make debug symbols available in ddb. */ db_ctf_init(); #endif if (mountroot == NULL || ((*mountroot)() != 0)) panic("cannot mount root"); TAILQ_FIRST(&mountlist)->mnt_flag |= MNT_ROOTFS; /* Get the vnode for '/'. Set p->p_fd->fd_cdir to reference it. */ if (VFS_ROOT(TAILQ_FIRST(&mountlist), &rootvnode)) panic("cannot find root vnode"); p->p_fd->fd_cdir = rootvnode; vref(p->p_fd->fd_cdir); VOP_UNLOCK(rootvnode); p->p_fd->fd_rdir = NULL; /* * Now that root is mounted, we can fixup initprocess's CWD * info. All other processes are kthreads, which merely * share proc0's CWD info. */ initprocess->ps_fd->fd_cdir = rootvnode; vref(initprocess->ps_fd->fd_cdir); initprocess->ps_fd->fd_rdir = NULL; /* * Now can look at time, having had a chance to verify the time * from the file system. Reset p->p_rtime as it may have been * munched in mi_switch() after the time got set. */ LIST_FOREACH(pr, &allprocess, ps_list) { nanouptime(&pr->ps_start); TAILQ_FOREACH(p, &pr->ps_threads, p_thr_link) { nanouptime(&p->p_cpu->ci_schedstate.spc_runtime); timespecclear(&p->p_rtime); } } uvm_swap_init(); /* Create the pageout daemon kernel thread. */ if (kthread_create(uvm_pageout, NULL, NULL, "pagedaemon")) panic("fork pagedaemon"); /* Create the reaper daemon kernel thread. */ if (kthread_create(reaper, NULL, &reaperproc, "reaper")) panic("fork reaper"); /* Create the cleaner daemon kernel thread. */ if (kthread_create(buf_daemon, NULL, &cleanerproc, "cleaner")) panic("fork cleaner"); /* Create the update daemon kernel thread. */ if (kthread_create(syncer_thread, NULL, &syncerproc, "update")) panic("fork update"); /* Create the aiodone daemon kernel thread. */ if (kthread_create(uvm_aiodone_daemon, NULL, NULL, "aiodoned")) panic("fork aiodoned"); #if !defined(__hppa__) /* Create the page zeroing kernel thread. */ if (kthread_create(uvm_pagezero_thread, NULL, NULL, "zerothread")) panic("fork zerothread"); #endif #if defined(MULTIPROCESSOR) /* Boot the secondary processors. */ cpu_boot_secondary_processors(); #endif /* Now that all CPUs partake in scheduling, start SMR thread. */ smr_startup_thread(); config_process_deferred_mountroot(); /* * Okay, now we can let init(8) exec! It's off to userland! */ start_init_exec = 1; wakeup((void *)&start_init_exec); /* * Start the idle pool page garbage collector */ #if !(defined(__m88k__) && defined(MULTIPROCESSOR)) /* XXX */ pool_gc_pages(NULL); #endif start_periodic_resettodr(); /* * proc0: nothing to do, back to sleep */ while (1) tsleep_nsec(&proc0, PVM, "scheduler", INFSLP); /* NOTREACHED */ } /* * List of paths to try when searching for "init". */ static char *initpaths[] = { "/sbin/init", "/sbin/oinit", "/sbin/init.bak", NULL, }; void check_console(struct proc *p) { struct nameidata nd; int error; NDINIT(&nd, LOOKUP, FOLLOW, UIO_SYSSPACE, "/dev/console", p); error = namei(&nd); if (error) { if (error == ENOENT) printf("warning: /dev/console does not exist\n"); else printf("warning: /dev/console error %d\n", error); } else vrele(nd.ni_vp); } /* * Start the initial user process; try exec'ing each pathname in "initpaths". * The program is invoked with one argument containing the boot flags. */ void start_init(void *arg) { struct proc *p = arg; vaddr_t addr; struct sys_execve_args /* { syscallarg(const char *) path; syscallarg(char *const *) argp; syscallarg(char *const *) envp; } */ args; int options, error; long i; register_t retval[2]; char flags[4], *flagsp; char **pathp, *path, *ucp, **uap, *arg0, *arg1 = NULL; /* * Now in process 1. */ /* * Wait for main() to tell us that it's safe to exec. */ while (start_init_exec == 0) tsleep_nsec(&start_init_exec, PWAIT, "initexec", INFSLP); check_console(p); /* process 0 ignores SIGCHLD, but we can't */ p->p_p->ps_sigacts->ps_sigflags = 0; /* * Need just enough stack to hold the faked-up "execve()" arguments. */ #ifdef MACHINE_STACK_GROWS_UP addr = USRSTACK; #else addr = USRSTACK - PAGE_SIZE; #endif p->p_vmspace->vm_maxsaddr = (caddr_t)addr; p->p_vmspace->vm_minsaddr = (caddr_t)(addr + PAGE_SIZE); if (uvm_map(&p->p_vmspace->vm_map, &addr, PAGE_SIZE, NULL, UVM_UNKNOWN_OFFSET, 0, UVM_MAPFLAG(PROT_READ | PROT_WRITE, PROT_MASK, MAP_INHERIT_COPY, MADV_NORMAL, UVM_FLAG_FIXED|UVM_FLAG_OVERLAY|UVM_FLAG_COPYONW|UVM_FLAG_STACK|UVM_FLAG_SYSCALL))) panic("init: couldn't allocate argument space"); for (pathp = &initpaths[0]; (path = *pathp) != NULL; pathp++) { #ifdef MACHINE_STACK_GROWS_UP ucp = (char *)addr; #else ucp = (char *)(addr + PAGE_SIZE); #endif /* * Construct the boot flag argument. */ flagsp = flags; *flagsp++ = '-'; options = 0; if (boothowto & RB_SINGLE) { *flagsp++ = 's'; options = 1; } #ifdef notyet if (boothowto & RB_FASTBOOT) { *flagsp++ = 'f'; options = 1; } #endif /* * Move out the flags (arg 1), if necessary. */ if (options != 0) { *flagsp++ = '\0'; i = flagsp - flags; #ifdef DEBUG printf("init: copying out flags `%s' %ld\n", flags, i); #endif #ifdef MACHINE_STACK_GROWS_UP arg1 = ucp; (void)copyout((caddr_t)flags, (caddr_t)ucp, i); ucp += i; #else (void)copyout((caddr_t)flags, (caddr_t)(ucp -= i), i); arg1 = ucp; #endif } /* * Move out the file name (also arg 0). */ i = strlen(path) + 1; #ifdef DEBUG printf("init: copying out path `%s' %ld\n", path, i); #endif #ifdef MACHINE_STACK_GROWS_UP arg0 = ucp; (void)copyout((caddr_t)path, (caddr_t)ucp, i); ucp += i; ucp = (caddr_t)ALIGN((u_long)ucp); uap = (char **)ucp + 3; #else (void)copyout((caddr_t)path, (caddr_t)(ucp -= i), i); arg0 = ucp; uap = (char **)((u_long)ucp & ~ALIGNBYTES); #endif /* * Move out the arg pointers. */ i = 0; copyout(&i, (caddr_t)--uap, sizeof(register_t)); /* terminator */ if (options != 0) copyout(&arg1, (caddr_t)--uap, sizeof(register_t)); copyout(&arg0, (caddr_t)--uap, sizeof(register_t)); /* * Point at the arguments. */ SCARG(&args, path) = arg0; SCARG(&args, argp) = uap; SCARG(&args, envp) = NULL; /* * Now try to exec the program. If can't for any reason * other than it doesn't exist, complain. */ if ((error = sys_execve(p, &args, retval)) == 0) { KERNEL_UNLOCK(); return; } if (error != ENOENT) printf("exec %s: error %d\n", path, error); } printf("init: not found\n"); panic("no init"); }
|
__label__pos
| 0.99502 |
Health
A Look Into the Symptoms of Night Blindness
There are 93 million adults in the United States who are at high risk of serious vision loss. Some of the more prevalent eye conditions include dry eye, glaucoma, and cataracts. And there’s one less known condition called night blindness.
Although night blindness is not a serious eye condition, it can hinder your ability to perform during the day. But what are the symptoms of night blindness?
In this article, we provide a breakdown of everything you need to know about the condition. Continue reading to learn more.
Trouble Seeing in Low Light
Night blindness, or nyctalopia, is a condition where sufferers have poor vision in low light or at night. This can make it difficult to drive at night or to read in dimly lit rooms.
It can also cause difficulty seeing clearly when there is a sudden change from bright to the dark light, such as when you walk from a sunny room into a dark movie theater. You may also find that you need more light than other people when you are reading or doing other close work.
Nearsightedness or Farsightedness
Night blindness symptoms relate back to either nearsightedness or farsightedness. If you are nearsighted, you may have trouble seeing objects that are far away.
On the other hand, if you are farsighted, you may have trouble seeing objects that are close up. This can make it difficult to read in low light or to see things in the dark.
Night blindness can also be a sign of other underlying health conditions. It’s important to talk to your doctor if you’re experiencing any of these symptoms.
Watery Eyes
When someone has watery eyes, it means that their tears are not draining properly. This is because the pupils are not able to constrict properly in low light, causing them to become irritated.
When your eyes are unable to produce enough tears, they become dry. This can cause your eyes to water in an attempt to lubricate them.
Headaches
Symptoms of night blindness headaches can include a throbbing sensation, pain behind the eyes, and sensitivity to light. The headaches may be caused by eyestrain from staring at objects in the dark. The pain may worsen with eye movement, and bright lights can make it worse.
Fatigue
When you can’t see well at night, your body expends extra energy to try to see. This can lead to fatigue during the day.
Night blindness is not a disease, but it can be a sign of an underlying problem with the eye or its nervous system. It is important to understand what causes night blindness to determine the best course of treatment. In most cases, night blindness can be corrected with glasses, contact lenses, or surgery.
Knowing the Symptoms of Night Blindness
There are many different symptoms of night blindness, but the most common symptom is difficulty seeing in low light or at night. Other symptoms can include light sensitivity, difficulty adjusting to changes in light, and trouble seeing in bright sunlight. If you think you might have night blindness, it’s important to see an eye doctor get a diagnosis and treatment.
For more helpful articles full of useful information and advice, please take a look at the rest of our blog site.
Talha
Link builder, Marketing Advertising specialist at SEO, done work on many site through guest posting. Have 5 year of experience in Guest posting. Email: [email protected] Whatsapp: +923421747707
Related Articles
Back to top button
|
__label__pos
| 0.521926 |
Laravel 路由：自定义模型绑定 1 个改进
路由模型绑定
当向路由或控制器行为注入模型 ID 时，就需要查询这个 ID 对应的模型。Laravel 为路由模型绑定提供了一个直接自动将模型实例注入到路由中的方法。例如，你可以注入与给定 ID 匹配的整个 User 模型实例，而不是注入用户的 ID。
隐式绑定
Laravel 会自动解析定义在路由或控制器行为中与类型提示的变量名匹配的路由段名称的 Eloquent 模型。例如：
Route::get('api/users/{user}', function (App\User $user) {
return $user->email;
});
在这个例子中，由于 $user 变量被类型提示为 Eloquent 模型 App\User，变量名称又与 URI 中的 {user} 匹配，因此，Laravel 会自动注入与请求 URI 中传入的 ID 匹配的用户模型实例。如果在数据库中找不到对应的模型实例，将会自动生成 404 异常。
自定义键名
如果你想要模型绑定在检索给定的模型类时使用除 id 之外的数据库字段，你可以在 Eloquent 模型上重写 getRouteKeyName 方法：
/**
* 获取该模型的路由的自定义键名。
*
* @return string
*/
public function getRouteKeyName()
{
return 'slug';
}
显式绑定
要注册显式绑定，使用路由器的 model 方法来为给定参数指定类。在 RouteServiceProvider 类中的 boot方法内定义这些显式模型绑定：
public function boot()
{
parent::boot();
Route::model('user', App\User::class);
}
接着，定义一个包含 {user} 参数的路由:
Route::get('profile/{user}', function (App\User $user) {
//
});
因为我们已经将所有 {user} 参数绑定至 App\User 模型，所以 User 实例将被注入该路由。例如，profile/1 的请求会注入数据库中 ID 为 1 的 User 实例。
如果在数据库中找不到匹配的模型实例，就会自动抛出一个 404 异常。
自定义逻辑解析
如果你想要使用自定义的解析逻辑，就使用 Route::bind 方法。传递到 bind 方法的 闭包 会接受 URI 中大括号对应的值，并且返回你想要在该路由中注入的类的实例：
/**
* 启动应用服务。
*
* @return void
*/
public function boot()
{
parent::boot();
Route::bind('user', function ($value) {
return App\User::where('name', $value)->first() ?? abort(404);
});
}
或者，您可以重写 Eloquent 模型上的 resolveRouteBinding 方法。 此方法会接受 URI 中大括号对应的值，并且返回你想要在该路由中注入的类的实例：
/**
* 检索绑定值的模型。
*
* @param mixed $value
* @return \Illuminate\Database\Eloquent\Model|null
*/
public function resolveRouteBinding($value)
{
return $this->where('name', $value)->first() ?? abort(404);
}
本文为 Wiki 文章，邀您参与纠错、纰漏和优化
讨论数量: 1
elesos
已阅
2年前 评论
讨论应以学习和精进为目的。请勿发布不友善或者负能量的内容，与人为善，比聪明更重要！
|
__label__pos
| 0.826728 |
CA1 pyramidal neuron (Combe et al 2018)
Download zip file
Help downloading and running models
Accession:244416
"Gamma oscillations are thought to play a role in learning and memory. Two distinct bands, slow (25-50 Hz) and fast (65-100 Hz) gamma, have been identified in area CA1 of the rodent hippocampus. Slow gamma is phase-locked to activity in area CA3 and presumably driven by the Schaffer collaterals. We used a combination of computational modeling and in vitro electrophysiology in hippocampal slices of male rats to test whether CA1 neurons responded to Schaffer collateral stimulation selectively at slow gamma frequencies, and to identify the mechanisms involved. Both approaches demonstrated that in response to temporally precise input at Schaffer collaterals, CA1 pyramidal neurons fire preferentially in the slow gamma range regardless of whether the input is at fast or slow gamma frequencies, suggesting frequency selectivity in CA1 output with respect to CA3 input. In addition, phase-locking, assessed by the vector strength, was more precise for slow gamma than fast gamma input. ..."
Reference:
1 . Combe CL, Canavier CC, Gasparini S (2018) Intrinsic Mechanisms of Frequency Selectivity in the Proximal Dendrites of CA1 Pyramidal Neurons. J Neurosci 38:8110-8127 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Gamma oscillations;
Implementer(s): Canavier, CC;
Search NeuronDB for information about: Hippocampus CA1 pyramidal GLU cell; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium;
/
CombeEtAl2018
experiment
lib
pc2b
template
readme.html
cad.mod
cagk.mod
cal.mod *
calH.mod
car.mod
cat.mod
d3.mod *
exp2i.mod *
h.mod
kadist.mod
kaprox.mod
kca.mod
kcasimple.mod
kdr.mod
km.mod
na3.mod
na3dend.mod
na3notrunk.mod
nap.mod
nax.mod
netstims.mod
nmdanet.mod
somacar.mod
stim2.mod *
cell-setup.hoc
fixnseg.hoc
init.hoc
mosinit.hoc *
multisyn.hoc
print.ses
screenshot1.png
screenshot2.png
screenshot3.png
screenshot4.png
simplestim.hoc
trunk.ses
TITLE K-A channel from Klee Ficker and Heinemann
: modified to account for Dax A Current --- M.Migliore Jun 1997
: modified to be used with cvode M.Migliore 2001
UNITS {
(mA) = (milliamp)
(mV) = (millivolt)
}
PARAMETER {
v (mV)
celsius (degC)
gkabar=.008 (mho/cm2)
vhalfn=11 (mV)
vhalfl=-56 (mV)
a0l=0.05 (/ms)
a0n=0.05 (/ms)
zetan=-1.5 (1)
zetal=3 (1)
gmn=0.55 (1)
gml=1 (1)
lmin=2 (mS)
nmin=0.1 (mS)
pw=-1 (1)
tq=-40
qq=5
q10=5
qtl=1
ek
}
NEURON {
SUFFIX kap
USEION k READ ek WRITE ik
RANGE gkabar,gka,vhalfn,vhalfl,i
GLOBAL ninf,linf,taul,taun,lmin
}
STATE {
n
l
}
ASSIGNED {
ik (mA/cm2)
i (mA/cm2)
ninf
linf
taul
taun
gka
}
INITIAL {
rates(v)
n=ninf
l=linf
}
BREAKPOINT {
SOLVE states METHOD cnexp
gka = gkabar*n*l
i = gka*(v-ek)
ik = i
}
FUNCTION alpn(v(mV)) {
LOCAL zeta
zeta=zetan+pw/(1+exp((v-tq)/qq))
alpn = exp(1.e-3*zeta*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius)))
}
FUNCTION betn(v(mV)) {
LOCAL zeta
zeta=zetan+pw/(1+exp((v-tq)/qq))
betn = exp(1.e-3*zeta*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius)))
}
FUNCTION alpl(v(mV)) {
alpl = exp(1.e-3*zetal*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius)))
}
FUNCTION betl(v(mV)) {
betl = exp(1.e-3*zetal*gml*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius)))
}
DERIVATIVE states { : exact when v held constant; integrates over dt step
rates(v)
n' = (ninf - n)/taun
l' = (linf - l)/taul
}
PROCEDURE rates(v (mV)) { :callable from hoc
LOCAL a,qt
qt=q10^((celsius-24)/10)
a = alpn(v)
ninf = 1/(1 + a)
taun = betn(v)/(qt*a0n*(1+a))
if (taun<nmin) {taun=nmin}
a = alpl(v)
linf = 1/(1+ a)
taul = 0.26*(v+50)/qtl
if (taul<lmin/qtl) {taul=lmin/qtl}
}
Loading data, please wait...
|
__label__pos
| 0.947241 |
Shoulder Bursitis, A Shoulder Physio Approach
Shoulder Bursitis, A Shoulder Physio Approach
Impingement as a cause of shoulder pain
Pain in the shoulder can arise from many different structures within and around the shoulder, and the neck. A common source of shoulder pain are the many bursa that exist around the joint. This can lead to conditions like shoulder bursitis and sub-acromial impingement. These conditions are particularly prevalent in overhead athletes (throwing sports), and swimmers.
What is a bursa?
Bursae are fluid-filled sacs that are generally located around our joints. They act to cushion areas that are likely to be compressed. Bursae also act to decrease friction between different tissues to allow tendons and bones to slide past each other. In a joint such as the shoulder, the bursae play a key role to allow movement to happen smoothly.
Process of shoulder impingement and shoulder bursitis
Bursitis is a condition where a bursa becomes inflamed. This can happen after an acute incident such as a fall. Or it can happen after small, repetitive irritations – such as with swimming and repetitive overhead use. In the shoulder, the most common site for this bursal inflammation is in the sub-acromial space. This is a narrow arch above the shoulder through which some of the rotator cuff tendons pass. When the arm is repeatedly moved above shoulder height, the tendons need to pass under a bony prominence. If the rotator cuff is tight, or there is an imbalance in the musculature – the tendons and bursa can be impinged between the bony prominences of the shoulder. In a fall or acute incident, impingement and inflammation of the bursa can be very painful and block movement. This is particularly noticeable with movements of the arm out to the side and above shoulder height. In more chronic cases of bursal irritation the movement can still be blocked. Most frequently movement is painful through an arc of movement between 80-120degrees of abduction. We call this the “painful arc”. This is the most common sign of shoulder bursitis that we see. Thorough shoulder physio assessment can help determine the causes, and other involved structures.
Physio for shoulder pain from shoulder bursitis
Often the first step of rehab for shoulder bursitis is to unload the bursa from irritating positions and movements. This will likely involve rest from movements above shoulder height. Overhead pressing, and pushing movements in the gym (bench press) often need to be avoided as the inflamed bursa settles. In less extreme cases, this rest can be relative – and involve a decrease in volume over overhead activity. Stretches to improve range of motion can commence in early rehab. Rather than pushing into overhead positions, early stretches often work on stretching the posterior cuff and the chest. If range of motion and pain allows, strengthening can commence. The role of strengthening is to build up strength and stability around the shoulder blade and rotator cuff. If there is a tear or strain in the rotator cuff, then this needs to be taken into account before any strength rehab can commence.
Shoulder strengthening rehab
While boring, the physio exercises for rotator cuff strengthening are an important part of the process. First, strengthening must focus on establishing adequate scapular stability. Once this is sound, strengthening for the rotator cuff in pain-free range of motion can commence. As irritation of the bursa allows, and as range of motion improves, the strengthening can progress into great range. Exercises we like to use in shoulder bursitis rehab programs
• Theraband rowing exercises
• Seated row
• Band pull-aparts
• One-arm row
• Theraband external rotation
• Hand behind back stretching
• Pec stretching against wall
Timeframes for this strengthening vary. As pain, strength and range allows, a return to normal activities can begin. There often isn’t a singular moment when all activities can resume as pre-injury. The process often involves a very graded return. This is due to the need for the muscles around the shoulder to be strong and fit enough to perform repetitive overhead activity. This can make it hard to predict a complete return to sports such as swimming and surfing, as return often requires shorter intervals such as 2-3 bouts of 10-20minutes of exercise with rest periods in between. Too much work while the bursa is irritated or while the muscles are tight or weak, can result in repetitive compression of the bursa, and possible re-irritation. For this reason, any return to sport should be done in a graded manner; and with special care to address any lingering or returning strength or range deficits.
What if your shoulder bursitis is lingering?
There are further options to investigate and to manage bursitis and sub-acromial impingement if it isn’t settling in the initial 2-3 months. Imaging (MRI, X-ray and Ultrasound) can be performed to better elucidate the problem. If the imaging shows a continuing bursal inflammation, then in consultation with your GP and radiologist, a cortisone injection, or course of anti-inflammatories may be indicated. If the imaging shows bony abnormalities then a consultation with an orthopaedic surgeon may be necessary to discuss ongoing management and possible surgical solutions.
Movement Centre for your shoulder physio needs
Come and see our team at Movement Centre in Randwick if you are having shoulder problems. Our team is highly experienced in managing shoulder injuries, and we have a fully equipped gym for all your rehab needs.
Disclaimer: The Movement Centre provides this information as an educational service. The information contained on this website and in this blog is not intended to serve as or replace actual medical advice. Anyone seeking specific advice or assistance should consult their local Randwick Physio, general practitioner, medical specialist, or otherwise appropriately skilled practitioner.
|
__label__pos
| 0.904964 |
Microsoft Office Tutorials and References
In Depth Information
Removing Items from the Context Menu
Removing Items from the Context Menu
Over time, your context menus can become cluttered with program entries from
old programs that you may not use anymore. You might experience programs that
take over all your context menus. Compression apps such as WinZip, WinRAR,
or Picozip always end up adding program entries to all the context menus. I have
Picozip installed on my computer and every time I right-click any file or folder,
I see five entries from Picozip giving me different compression options. This
can be a convenient feature, but if you don’t compress and extract zip files very
often, you might not need the added convenience. Instead, you could remove
these entries from your context menu, which will give your system a cleaner
interface as well as a small performance boost if you have a lot of extra entries
in your context menu.
Removing these programs from your context menus can be a little tricky
because they can be spread in different places in the registry. The only way to
remove these types of entries is to edit the registry directly. Follow these steps:
1. Open the Start screen, type regedit and then press Enter.
2. When the Registry Editor appears, expand the HKEY_CLASSES_ROOT folder.
A list of the file types set up on your computer displays.
3. If the entry that you want to remove from the context menu appears in
all context menus, such as the preceding Picozip example, you have to
expand the * folder. Otherwise, expand the folder with the file extension
you want to modify.
4. After expanding the correct folder, expand the ShellEx and ContextMenuHandlers
folders. Your registry path should be HKEY_CLASSES_ROOT\*\ShellEx\
ContextMenuHandlers.
5. Look through the list until you find the entry that you want to remove.
Right-click the entry and select Delete. Identifying some of the programs
is easy. For example, WinRAR is labeled WinRAR, as shown in Figure 9-5.
However, you may run into some items that are listed using their
application/class ID or a vague name. For those, do a registry search of the
class ID (Ctrl+F), which is formatted as {XXXXXXXX-XXXX-XXXX-XXXX-
XXXXXXXXXXXX} , to find other references that give you clues to what the
ID belongs to. If that does not work, try doing a search on Google to see
whether that turns up anything.
6. After you are finished removing all the entries from your context menus,
close Registry Editor and you are finished. Your changes will be in effect
immediately.
Search JabSto ::
Custom Search
|
__label__pos
| 0.692251 |
recent story
Synthesis and properties evaluation of quaternized polyurethanes as antibacterial adhesives
P. Hu, A. Greiner, S. Agarwal
J. Polym. Sci. Part A: Polym. Chem., 2019, doi:10.1002/pola.29321
antibacterial_adhesive
We present new side‐chain quaternized polyurethanes as antibacterial adhesives made by polyaddition polymerization followed by quaternization for different time intervals. The degree of quaternization of N‐diol units in the polymer is changed from 13.6 to 99.0 mol % (almost complete) for tuning the antibacterial action (leaching/contact type) and studying effect on adhesive strength. The degree of quaternization of about 26 mol % provided the nonleaching antibacterial effect with adhesive strength more than 60 N cm−2 on aluminum and glass substrates. The increase in the degree of quaternization enhanced polymer polarity shifting nonleaching (contact type) antibacterial behavior to the leaching type but maintaining the high adhesive strengths.
more
selected papers
selected reviews
New Review by S. Agarwal, S. Jiang, Y. Chen published in Macromol. Mater.
S. Agarwal, S. Jiang, Y. Chen
Macromol. Mater. Eng., 2018, 1800548
Review_Polymer_Actuators
Welcome to Macromolecular Chemistry II
Spruch der Woche
Perfektion ist erreicht, nicht, wenn sich nichts mehr hinzufügen lässt, sondern, wenn man nichts mehr wegnehmen kann. (Antoine de Saint-Exupery) (Perfection is achieved, not when nothing more can be added, but when nothing more can be taken away (Antoine de Saint-Exupery))
"Die reinste Form des Wahnsinns ist es, alles beim Alten zu lassen und gleichzeitig zu hoffen, dass sich etwas ändert. (The sheerest madness is to leave everything the way it is and to simultaneously hope that something will change)" Albert Einstein
"The fate of genius is to be misunderstood, but not everything is a misunderstood genius" Ralp Waldo Emmerson (1803-1882)
"Facts do not cease to exist because they are ignored” (Aldous Huxley, author of Brave New World)
"Die Ablehnung Unwichtiges zu tun, ist eine entscheidende Voraussetzung für den Erfolg“ Sir Alexander MacKenzie
"An idea that is not dangerous is unworthy of being called an idea at all“ von Oscar Wilde (Eine Idee, die nicht gewagt ist, verdient es nicht, überhaupt eine Idee genannt zu werden)
Gruppenfoto
News 16.01.2019
Controlled-Release LCST‐Type Nonwoven Depots via Squeezing-Out Thermal Response
F. Käfer, R. Vilensky, G. Vasilyev, E. Zussman, S. Agarwal
Macromol. Mater. Eng. 2018, 1800606.
LCST_Florian
A novel thermoresponsive fibrous matrix as controlled release depots upon heating is described. The matrix is composed of electrospun fibers of a lower critical solution temperature (LCST)‐type poly(methacrylamide‐co‐N‐tert‐butylacrylamide‐co‐4‐acryloylbenzophenone) P(MAAm‐NtbAAm‐ABP) copolymer. Spherical particles, simulating depots of drugs, are embedded with liquid‐filled inter‐fiber spaces (pores). On heating above 25 °C up to 45 °C, the nanofibers undergo a contraction of about 40%. This solid deformation is attributed to the LCST transition. Fibrous matrix contraction drives expulsion of depots and water solution stored in the pores of the matrix, as evidenced by in situ observations. The liquid flow in the deformable porous medium demonstrates liquid drainage from the matrix as a function of temperature. Experimental results reveal that 70% of the particles are expelled from the matrix upon heating to 45 °C from room temperature. The presented particles encapsulation and release model system using LCST‐type fibrous matrix can be used as a transdermal patch.
more news
Universität Bayreuth -
|
__label__pos
| 0.767236 |
Manmade Global Weather Last updated on 2018/2562 10 24, a full moon day;
kuru kuru of lights ... ;
Manmade Global Weather; Weather; WORMHOLE;
jinko chino Artificial Intelligence to do good weather conditions globally ... ;
Time (now), Space (Internet Domain Name: " " , Nation Name: " "), Action (in addition to DEE, using this DOMAIN (Satellite_DNS_Domain) 1 meter gravity spots to reduce the bad weather condition (storm name: " " (pressure hPa, wind gust kph, wind speed kph))) ... ;
earthquake prediction e.g.
on ZCS, C Sequence Number (BF2) endpoints (72, 90, 180), doko WHERE listening low frequency earthquake;
on ZCS, C Sequence Number (BF2) endpoints (72, 90, 180), doko WHERE listening low frequency tremor;
earthquake prediction;
HOW to avoid earthquakes (defined regions), also see: Monbusho level knowledge enhancement 3, idea ♯ 273, HOW to avoid earthquakes;
Manmade Global Weather
, , , , ;
nation name , video , audio , data , Number ;
numerological ; number (linear) ... ; noCOOKIE browser based internal address ; Keyword ; purpose ;
1 ; 7954552 ; 0.121.96.120 ; prevent : for preventing ;
7 ; 7962532 ; 0.121.127.164 ; protect ; for protecting ;
2 ; 954335 ; 0.14.143.223 ; reduce ; for reducing ;
Also see :
Address
;
, ,
for each Time Zone ,
for each domain ,
using
Gravity Dimension Computer (
DEE ,
Schematic Dimensional Directional Gravity Pressure ,
Gravity Spot s ,
Moon Wave ,
Sound _ Beam ,
Sound Pressure Level
) ... ;
to do good weather conditions globally ...
using more than 8+ methods ... e.g. 1m gravity spots as method; Rainbow Method; light as zero curvature method; wormhole way LASER (multi long length neutrino) as Method; ... ;
summer; Radical954;
as result e.g.
- 0.14.143.223, reduce category 4 storm in our earth;
- 0.14.143.223, reduce earthquake in Japan;
- 0.14.143.223, reduce excessive rainfall in Japan;
- 0.14.143.223, reduce forest fire in California, USA;
- 0.14.143.223, reduce heat wave in summer;
- 0.14.143.223, reduce PM2.5 air pollution above cities' sky in China;
- 0.14.143.223, reduce regional drought in defined nation name;
- 0.14.143.223, reduce regional flood in Thailand;
- 0.14.143.223, reduce tsunami in Japan;
- 0.14.143.223, reduce volcanic eruption in Japan;
Weather can be manmade. rescuing defined regional environment e.g. (( domain name), (International Domains), ( nation name, , , , number));
idea ♯ 266; Radio Specification of Computer System; Also see: Monbusho level knowledge enhancement 3;
idea ♯ 238; reducing volcanic eruption in Japan; Also see: Monbusho level knowledge enhancement 2;
DEE FMD _ Our Earth; HOW Nested Theory of Eastern Civilization (Directional Gravity Pressure, directions of STRING), also see: 5dComputer; 5fComputer; therefore, 0.14.143.223, reduce earthquake in the defined region, 0.14.143.223, reduce volcanic eruption in the defined region;
Anti Heat Wave; Heat Wave; also see: Schematic Dimensional;
chain; connection; Radical819;
for each human beings livable moon:
IFF summer, using "aqua" color to reduce excessive heat;
IFF winter, using "maroon" color to seal heat i.e. to avoid excessive snowing;
our earth 's normal Yellowish1, also see: Schematic Dimensional;
(0.14.143.223, 954335, 2) reduce a.k.a. reduce, reduced, reducing;
(0.14.143.223, 954335, 2) reduce bad ones;
e.g. reduce bad ones (i.e. good, goodwill);
e.g. reduce cancers (i.e. abnormal, disease and disorder); Also see: Gene Therapy System;
e.g. reduce price, as opposed to increase price; Also see: Biz; Business; (bargain, discount, sales);
e.g. reduce speed, as opposed to increase speed; Also see: Automotive; Processor;
reduce air pollution (e.g. PM2.5 air pollution above cities);
reduce bad weather conditions;
reduce category 4 storm;
reduce coastal erosion;
reduce cyclone;
reduce drought;
reduce earthquake;
reduce excessive heat;
reduce excessive rainfall;
reduce flood;
reduce forest fire;
reduce hazard;
reduce hurricane;
reduce risk;
reduce seismic hazard;
reduce tornado;
reduce tsunami;
reduce typhoon;
reduce unhealthy environments;
reduce volcanic eruption;
(0.14.143.223, 954335, 2) reduce a.k.a. reduce, reduced, reducing;
(0.14.143.223, 954335, 2) reduce bad ones;
Remark: 0.14.143.223 is IPv4 address; 954335 is numerological numbers; 2 is logical induction logic number;
Remark: (Reduce, Reuse, Recycle), originally invented by NEC (slogan, usage) ... ;
(Seismic Hazard Map, Seismic Hazard Map) IFF seismic hazard map color (code, coding), using (jinko chino Artificial Intelligence) to (0.14.143.223, 954335, 2) reduce risk probability color (code, coding) ; Remark: high risk color e.g. red; rather high risk color e.g. orange;
March 22, 2018/2561 NHK news; since March 22, 2018/2561, Japan (a.k.a. NIPPON) nationwide earthquake alert system has started;
the nationwide (i.e. NIS based) earthquake alert system (earthquake definition)
e.g. can detect center of earthquake,
e.g. can measure shock waves' radius,
e.g. its timestamp is second based,
e.g. seismology and scales;
e.g. via ( TV, radio, smart phone), the nationwide (i.e. NIS based) earthquake alert system's info can be ... ;
Also see: this DOMAIN 's IoT via NFC, e.g. (computer) connected to Internet;
Also see: www.jma.go.jp; Japan Meteorological Agency;
Also see: www.jnto.go.jp; Japan National Tourism Organization;
Up
my apologies if natural disaster happens naturally; Naturally Weather Log;
|
__label__pos
| 0.862679 |
Explore: Relationship Counseling Near Cuyahoga Falls Ohio – a customized therapist match
conventional in-person therapy, Relationship Counseling Near Cuyahoga Falls Ohio including cost, convenience, and therapist selection. While there are other online treatment platforms offered, BetterHelp stands apart for its big network of therapists and affordable pricing plans. Eventually, the choice in between online treatment and conventional in-person therapy comes down to personal preference and specific requirements.
Treatment can be beneficial for a wide range of psychological health conditions. In this post, we’ll explore 10 various conditions that people may have and how therapy can help.
Depression is a typical psychological health condition that impacts countless individuals worldwide. Therapy can help by offering a safe area to discuss your feelings and feelings. A therapist can help you recognize negative idea patterns and behaviors and deal with you to establish coping strategies and positive habits.
Stress and anxiety is another typical psychological health condition that can be incapacitating. Therapy can help by teaching you relaxation strategies, such as deep breathing and mindfulness, and dealing with you to develop coping techniques to handle anxiety triggers.
PTSD, or post-traumatic stress disorder, is a psychological health condition that can establish after experiencing or experiencing a traumatic occasion. Therapy can assist by supplying a safe area to process the trauma and develop coping methods to manage the signs of PTSD.
OCD, or obsessive-compulsive condition, is a mental health condition defined by invasive thoughts and compulsive behaviors. Therapy can help by teaching you how to recognize and manage these habits and thoughts, in addition to establish coping strategies to handle the symptoms of OCD. Relationship Counseling Near Cuyahoga Falls Ohio
Bipolar affective disorder
Bipolar illness is a psychological health condition characterized by severe mood swings, varying from depressive episodes to manic episodes. Therapy can assist by providing support and assistance in handling these mood swings, establishing coping techniques, and enhancing communication abilities.
Eating disorders
Eating disorders, such as anorexia and bulimia, are psychological health conditions that can have severe physical repercussions. Therapy can help by addressing the underlying emotional and mental problems that contribute to the eating disorder, in addition to developing techniques to manage the physical signs.
Substance abuse
Substance abuse can be a difficult habit to break, but treatment can be a reliable tool in handling dependency. Therapy can help by addressing the underlying psychological and mental problems that contribute to drug abuse, along with establishing methods to manage cravings and triggers.
Relationship problems
Relationship problems, such as communication problems and dispute, can have a substantial effect on mental health. Treatment can help by offering a safe space to talk about these concerns and develop methods to improve communication and deal with dispute.
Grief and loss can be a hard experience to navigate, however treatment can assist by supplying support and assistance through the mourning process. A therapist can assist you identify and handle the feelings related to sorrow and loss, along with establish coping methods to move on.
Tension management
Stress is a typical experience for many people, but it can have unfavorable impacts on mental health. Therapy can assist by teaching relaxation techniques and establishing coping techniques to manage tension, in addition to determining and resolving the underlying psychological and psychological issues that contribute to tension.
In conclusion, treatment can be an efficient tool in handling a large range of psychological health conditions, from depression and anxiety to drug abuse and relationship concerns. Consider seeking the support and assistance of a certified therapist if you are struggling with your mental health.
Seeing a therapist can have many benefits for a person’s mental health and wellness. Here are a few of the benefits of seeing a therapist from a psychological point of view:
Increased self-awareness
One of the main advantages of seeing a therapist is increased self-awareness. A therapist can assist you determine patterns in your thoughts, feelings, and habits, as well as the underlying beliefs and values that drive them. By ending up being more familiar with these patterns, you can gain a deeper understanding of yourself and your inspirations, which can result in individual growth and development.
Enhanced psychological guideline
Emotional policy is the ability to manage and control one’s feelings in a healthy and adaptive way. Seeing a therapist can assist individuals learn and practice emotional policy methods, such as deep breathing and mindfulness, that can be helpful in managing difficult feelings and reducing stress.
Better interpersonal relationships
Social relationships are a vital element of psychological health and wellbeing. Seeing a therapist can assist people improve their communication abilities, assertiveness, and compassion, which can result in much healthier and more fulfilling relationships with others.
Increased problem-solving skills
Therapy can likewise assist individuals develop problem-solving abilities. By working with a therapist, individuals can discover to method problems in a more organized and reliable way, identify prospective solutions, and make decisions that are aligned with their goals and worths.
Enhanced self-confidence
Self-esteem refers to an individual’s sense of self-worth and value. Seeing a therapist can help individuals determine and challenge unfavorable self-talk and beliefs that can contribute to low self-confidence. Through treatment, individuals can find out to develop a more positive and reasonable self-image, which can cause increased self-esteem and self-worth.
Boosted coping skills
Coping skills are strategies and strategies that individuals use to handle tension and misfortune. Seeing a therapist can help people establish and practice coping abilities that are customized to their particular requirements and preferences. Coping abilities can consist of mindfulness, relaxation techniques, analytical, and social support, among others.
Lowered symptoms of mental disorder
Therapy can likewise be effective in decreasing symptoms of mental illness, such as anxiety, anxiety, and trauma (PTSD). Therapists use evidence-based treatments, such as cognitive-behavioral therapy (CBT), dialectical behavior modification (DBT), and eye motion desensitization and reprocessing (EMDR), to help people manage symptoms and enhance their general quality of life.
|
__label__pos
| 0.900425 |
Skip to main content
CosmWasm
What is CosmWasm?
A smart contracting platform called CosmWasm was created for the Cosmos ecosystem. Simply described, it uses WebAssembly (Wasm) in the Cosmos (Cosm) fashion, thus the name.
The Cosmos SDK can accept modules that have been created for CosmWasm. Thus, anybody presently developing a blockchain using the Cosmos SDK may quickly and simply add CosmWasm smart contracting capabilities to their chain without changing the existing logic.
|
__label__pos
| 0.998673 |
MFCS 2023: 48TH INTERNATIONAL SYMPOSIUM ON MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE
PROGRAM FOR WEDNESDAY, AUGUST 30TH
Days:
previous day
next day
all days
View: session overviewtalk overview
08:30-09:00Coffee Break
09:00-10:00 Session 11
Invited Talk
Location: Amphi F
09:00
Some Algorithmic Problems on Temporal Graphs
ABSTRACT. Research on Temporal Graphs has greatly expanded in the last few years.
The majority of the results
till now , address problems related to the notion of Temporal Paths.
In this talk, we focus , instead , on some selected problems whose main topic is not on Temporal Paths.
In particular, we will discuss Temporal Vertex Covers , the notion of Temporal Transitivity , and also
issues and models of stochastic temporal graphs. We discuss the concept of a sliding time window in temporal graphs.
The talk aims to motivate new research towards lifting more topics of algorithmic
graph theory to the temporal case.
10:00-10:30Coffee Break
10:30-12:10 Session 12A: Computational and Dynamic Complexity
Location: Amphi F
10:30
A characterization of functions computable in polynomial time and space over the reals with discrete ordinary differential equations. Simulation of Turing machines with analytic discrete ordinary differential equations.
PRESENTER: Manon Blanc
ABSTRACT. We prove that functions over the reals computable in polynomial time can be characterized using discrete ordinary differential equations (ODE), also known as finite differences. We also provide a characterization of functions computable in polynomial space over the reals.
In particular, this covers space complexity, while existing characterizations were only able to cover time complexity, and were restricted to functions over the integers, and we prove that no artificial sign or test function is needed even for time complexity.
At a technical level, this is obtained by proving that Turing machines can be simulated with analytic discrete ordinary differential equations. We believe this result opens the way to many applications, as it opens the possibility of programming with ODEs, with an underlying well-understood time and space complexity.
10:55
Effective Continued Fraction Dimension versus Effective Hausdorff Dimension of Reals
PRESENTER: Akhil S
ABSTRACT. We establish that constructive continued fraction dimension originally defined using s-gales is robust, but surprisingly, that the effective continued fraction dimension and effective (base-b) Hausdorff dimension of the same real can be unequal in general.
We initially provide an equivalent characterization of continued fraction dimension using Kolmogorov complexity. In the process, we provide the construction of an optimal lower semicomputable s-gale for continued fractions. We also prove new bounds on the Lebesgue measure of continued fraction cylinders, which may be of independent interest.
We apply these bounds to reveal an unexpected behavior of continued fraction dimension. It is known that feasible dimension is invariant with respect to base conversion. We also know that Martin-Lof randomness and computable randomness are invariant not only with respect to base conversion, but also with respect to the continued fraction representation. In contrast, for any 0 < epsilon < 0.5, we prove the existence of a real whose effective Hausdorff dimension is less than epsilon, but whose effective continued fraction dimension is greater than or equal to 0.5. This phenomenon is related to the "non-faithfulness" of certain families of covers, investigated by Peres and Torbin and by Albeverio, Ivanenko, Lebid and Torbin .
We also establish that for any real, the constructive Hausdorff dimension is at most its effective continued fraction dimension.
11:20
Upward Translation of Optimal and P-Optimal Proof Systems in the Boolean Hierarchy over NP
PRESENTER: Martin Herold
ABSTRACT. We study the existence of optimal and p-optimal proof systems for classes in the Boolean hierarchy over NP. Our main results concern DP, i.e., the second level of this hierarchy:
If all sets in DP have p-optimal proof systems, then all sets in coDP have p-optimal proof systems. The analogous implication for optimal proof systems fails relative to an oracle.
As a consequence, we clarify such implications for all classes C and D in the Boolean hierarchy over NP: either we can prove the implication or show that it fails relative to an oracle.
Furthermore, we show that the sets SAT and TAUT have p-optimal proof systems, if and only if all sets in the Boolean hierarchy over NP have p-optimal proof systems which is a new characterization of a conjecture studied by Pudlák.
11:45
On the work of dynamic constant-time parallel algorithms for regular tree languages and context-free languages
ABSTRACT. Previous work on Dynamic Complexity has established that there exist dynamic constant-time parallel algorithms for regular tree languages and context-free languages under label or symbol changes. However, these algorithms were not developed with the goal to minimise work (or equivantly, the number of processors). In fact, their inspection yields the work bounds O(n^2) and O(n^7) per change operation, respectively. In this paper, dynamic algorithms for regular tree languages are proposed that generalise the previous algorithms in that they allow unbounded node rank and leaf insertions, while improving the work bound from O(n^2) to O(n^ϵ), for arbitrary ϵ > 0. For context-free languages algorithms with better work bounds (compared with O(n^7)) for restricted classes are proposed: for every ϵ > 0 there are such algorithms for deterministic context-free languages with work bound O(n^(3+ϵ)) and for visibly pushdown languages with work bound O(n^(2+ϵ)).
10:30-12:10 Session 12B: Games 1
Location: Amphi G
10:30
Rational Verification for Nash and Subgame-perfect Equilibria in Graph Games
PRESENTER: Léonard Brice
ABSTRACT. We study a natural problem about rational behaviors in multiplayer non-zero-sum sequential infinite duration games played on graphs: rational verification, that consists in deciding whether all the rational answers to a given strategy satisfy some specification.
We give the complexities of that problem for two major concepts of rationality: Nash equilibria and subgame-perfect equilibria, and for three major classes of payoff functions: energy, discounted-sum, and mean-payoff.
10:55
Solving irreducible stochastic mean-payoff games and entropy games by relative Krasnoselskii-Mann iteration
ABSTRACT. We analyse an algorithm solving stochastic mean-payoff games, combining the ideas of relative value iteration and of Krasnoselskii-Mann damping. We derive parameterized complexity bounds for several classes of games satisfying irreducibility conditions. We show in particular that an $\epsilon$-approximation of the value of an irreducible concurrent stochastic game can be computed in a number of iterations in $O(|\log\epsilon|)$ where the constant in the $O(\cdot)$ is explicit, depending on the smallest non-zero transition probabilities. This should be compared with a bound in $O(|\epsilon|^{-1}|\log(\epsilon)|)$ obtained by Chatterjee and Ibsen-Jensen (ICALP 2014) for the same class of games, and to a $O(|\epsilon|^{-1})$ bound by Allamigeon, Gaubert, Katz and Skomra (ICALP 2022) for turn-based games. We also establish parameterized complexity bounds for entropy games, a class of matrix multiplication games introduced by Asarin, Cervelle, Degorre, Dima, Horn and Kozyakin. We derive these results by methods of variational analysis, establishing contraction properties of the relative Krasnoselskii-Mann iteration with respect to Hilbert's
11:20
Relaxed core stability for hedonic games with size-dependent utilities
PRESENTER: Jannik Peters
ABSTRACT. We study relationships between different relaxed notions of core stability in hedonic games. In particular, we study (i) q-size core stable outcomes in which no deviating coalition of size at most $q$ exists and (ii) k-improvement core stable outcomes in which no coalition can improve by a factor of more than k. For a large class of hedonic games, including fractional and additively separable hedonic games, we derive upper bounds on the maximum factor by which a coalition of a certain size can improve in a q-size core stable outcome. We further provide asymptotically tight lower bounds for a large class of hedonic games. Finally, our bounds allow us to confirm two conjectures by Fanelli et al. [IJCAI'21] for symmetric fractional hedonic games (S-FHGs): (i) every q-size core stable outcome in an S-FHG is also (q/(q-1))-improvement core stable and (ii) the price of anarchy of q-size stability in S-FHGs is precisely (2q)/(q-1).
11:45
Recontamination helps a lot to hunt a rabbit
ABSTRACT. The \textsc{Hunters and Rabbit} game is played on a graph $G$ where the Hunter player shoots at $k$ vertices in every round while the Rabbit player occupies an unknown vertex and, if it is not shot, must move to a neighbouring vertex after each round. The Rabbit player wins if it can ensure that its position is never shot. The Hunter player wins otherwise. The hunter number $h(G)$ of a graph $G$ is the minimum integer $k$ such that the Hunter player has a winning strategy (i.e., allowing him to win whatever be the strategy of the Rabbit player). This game has been studied in several graph classes, in particular in bipartite graphs (grids, trees, hypercubes...), but the computational complexity of computing $h(G)$ remains open in general graphs and even in more restricted graph classes such as trees. To progress further in this study, we propose a notion of monotonicity (a well-studied and useful property in classical pursuit-evasion games such as Graph Searching games) for the \textsc{Hunters and Rabbit} game imposing that, roughly, a vertex that has already been shot ``must not host the rabbit anymore''. This allows us to obtain new results in various graph classes.
More precisely, let the monotone hunter number $mh(G)$ of a graph $G$ be the minimum integer $k$ such that the Hunter player has a monotone winning strategy. We show that $pw(G) \leq mh(G) \leq pw(G)+1$ for any graph $G$ with pathwidth $pw(G)$, which implies that computing $mh(G)$, or even approximating $mh(G)$ up to an additive constant, is \textsf{NP}-hard. Then, we show that $mh(G)$ can be computed in polynomial time in split graphs, interval graphs, cographs and trees. These results go through structural characterisations which allow us to relate the monotone hunter number with the pathwidth in some of these graph classes. In all cases, this allows us to specify the hunter number or to show that there may be an arbitrary gap between $h$ and $mh$, i.e., that monotonicity does not help. In particular, we show that, for every $k\geq 3$, there exists a tree $T$ with $h(T)=2$ and $mh(T)=k$. We conclude by proving that computing $h$ (resp., $mh$) is \FPT~parameterised by the minimum size of a vertex cover.
12:10-14:00Lunch Break
17:00-19:00 Cité du Vin (Bordeaux Wine City)
The social event takes place on Wednesday afternoon. It will start at "Cité du Vin » (Bordeaux Wine City) at 17h00, we will meet at this place before the visit. This place is directly accessible from Talence using Tram B, stop « Cité du Vin ». The museum visit lasts for about 2 hours, including tasting a glass of wine, more details there.
20:00-22:00 Diner at restaurant "Le café du port"
We will go to the restaurant « Le café du port », there. The dinner will start at 20h00. The restaurant is accessible from the museum by walking (40 minutes of a gentle walk by the quays) or by Tramway B, bus 91 or even by boat « Batcub 3 ».
|
__label__pos
| 0.857832 |
Configuration Management / Attribute Requestlegacyexternalstorage Set
AndroidMobile App
Description
Attribute requestLegacyExternalStorage set is a Configuration Management vulnerability, which usually occurs in Android and mobile applications. It is defined in the Common Weakness Enumeration (CWE) directory as "CWE-732: Incorrect Permission Assignment for Critical Resource". This means that the application does not assign the correct permissions to sensitive or critical resources, allowing malicious actors to modify or steal data. The Open Web Application Security Project (OWASP) Testing Guide also identifies this vulnerability as a key security issue.
Risk
The risk associated with this vulnerability is high due to the potential for malicious actors to gain access to sensitive information. If the incorrect permissions are assigned, attackers could potentially gain access to a user's personal information, such as banking details, passwords, or other sensitive data. This could lead to identity theft, financial losses, or other damages.
Solution
To mitigate the risk associated with the vulnerability, it is important to ensure that the correct permissions are assigned to the application. This can be done by using a secure coding approach and following secure coding best practices. Additionally, it is important to regularly audit the application to ensure that the correct permissions are in place.
Example
Below is an example of code with the incorrect permission assignment for a critical resource, taken from the Common Vulnerabilities and Exposures (CVE) directory:
android:requestLegacyExternalStorage="true"
This code assigns the incorrect permission to a critical resource, allowing malicious actors to potentially access sensitive data.
Curious? Convinced? Interested?
Arrange a no-obligation consultation with one of our product experts today.
|
__label__pos
| 0.964006 |
OBSESSIVE COMPULSIVE DISORDER (OCD)
50825
page-template-default,page,page-id-50825,cabin-core-1.0.2,select-child-theme-ver-1.0.0,select-theme-ver-3.2,ajax_fade,page_not_loaded,,wpb-js-composer js-comp-ver-6.0.5,vc_responsive
OBSESSIVE COMPULSIVE DISORDER (OCD)
An introduction to obsessive-compulsive disorder (OCD)
What is it like to have OCD?
My obsessive thoughts irrationally promised me that I was dangerous, or in danger, or some combination. I felt that if I can’t trust my thoughts anymore, I can still trust my actions, and I can trust that I’m touching this doorknob 64 times. I initially settled on 8 as the acceptable quantity of touch that would absolve me from guilt over something I’d never done, or prove to me that I wasn’t destined for some catastrophic fate. Then 8 started to feel too easy, so I moved to 64 (8×8). Inevitably, something would go wrong on the 63rd touch of a faucet or tug of an earring. And so I’d start over again. Meanwhile, disturbing images and sounds played across my mind—people I love dying, my own death, my body riddled with disease—all somehow my fault.”
– Lived experience of a woman with OCD, age 24
What is OCD?
Obsessive-compulsive disorder (OCD) is a mental health condition that occurs when a person is overwhelmed by intrusive thoughts or feelings that cause anxiety or distress, compelling them to engage in certain repeated behaviors or routines. These ritualistic actions briefly relieve the anxiety—until the unwanted thoughts return, and the cycle begins again.
According to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), a comprehensive guide that mental health professionals use to understand and diagnose mental health conditions, people with OCD spend at least one hour per day engaging in these repetitive behaviors. The considerable amount of time a person with OCD spends on these routines—in additional to the psychological burden of living with intrusive, distressing thoughts—can take a significant toll on a person’s health, happiness, and overall quality of life.
What isn’t OCD?
In recent years, phrases like “I’m so OCD!” have become a trendy way to describe a personal preference for tidiness, cleanliness, or organization. And while some individuals with OCD do experience thoughts and routines related to cleaning or organizing, these behaviors aren’t a personality quirk—they are part of a maladaptive behavior pattern, and they typically interfere with daily life. Clinicians and OCD sufferers alike implore the general public not to make light of the condition, urging them to consider the very real, devastating impact of OCD on the millions of Americans who live with the disorder.
Why is it called “obsessive-compulsive disorder”?
OCD is named for the two primary components of the disorder: obsessions and compulsions.
Obsessions refer to the intrusive, relentless thoughts, feelings, impulses, or mental images that cause emotional distress or discomfort. While most people experience the occasional unpleasant thought or feeling, those who have OCD fixate on these constant obsessions and may be unable to control or suppress them. Even if a person with OCD recognizes that their obsessions are excessive or irrational, they still might feel powerless to control these persistent, unwanted thoughts. In some cases, this internal conflict amplifies the anxiety associated with their obsessions.
Compulsions are the repeated actions that temporarily alleviate the distress caused by obsessions. These behaviors are often rigid and routine, and they must be performed in a certain sequence or a certain number of times in order to soothe the anxiety associated with obsessive thoughts. Many people are familiar with the relatively common, visible compulsions that a person with OCD might repeat, including hand-washing, neatly arranging objects, or checking (such as ensuring that the door is locked). Other compulsions may be entirely mental, such as silently counting or internally repeating certain words or phrases. Unfortunately, compulsions typically provide a brief reprieve from anxiety before the obsession returns, causing an endless cycle of obsessive-compulsive behavior.
To an outside observer, a person’s obsessions and compulsions may be invisible or may appear to be normal, innocuous behaviors. Yet to a person living with OCD, obsessions and compulsions can be all-consuming and may prevent healthy participation in school, employment, hobbies, and relationships.
What are the signs and symptoms of OCD?
Although every person’s OCD is different, the most common types of obsessions and compulsions can be grouped into broad categories. Understanding how a person’s OCD corresponds to these categories may help health care professionals and people with OCD to identify, understand, and address obsession and compulsions when they occur.
Common obsessions include:
• Losing control. A person with OCD may have intrusive thoughts about acting on an impulse to harm oneself or others, about engaging in socially inappropriate acts (such as using profanity), or about stealing.
• Perhaps the most stereotyped form of OCD, a person with contamination obsessions may be excessively afraid of coming in contact with substances they perceive to be unclean, including dirt, germs, and body fluids.
• A person with harm-related obsessions may fear that harm will occur as a result of their actions; for example, they might fear that leaving the stove on will cause a fatal house fire.
• A person with perfectionistic OCD may fixate on exactness or symmetry. They may be afraid to forget information or memories, to throw away objects that will be needed later (which may lead to hoarding behaviors), or to lose important objects.
• Unwanted sexual or taboo thoughts. Sexual OCD may cause intrusive, perverse sexual thoughts, images, or impulses, often related to others around them. Many people with unwanted sexual obsessions fear acting on these impulses or engaging in sexually harmful behavior, including pedophilia, incest, or assault. An estimated 1 in 10 people with OCD may experience obsessions related to their sexual orientation.
• Religion (also called scrupulosity). A person with scrupulosity OCD may experience obsessions about committing sins, offending God or other sacred figures, or committing blasphemy. They may be excessively concerned with “perfect” moral behavior.
Common compulsions include:
• A person with cleanliness compulsions may excessively or repetitively bathe, groom, wash their hands, or clean items in an effort to remove contaminants.
• A person may repeat tasks, activities, or body movements (such as blinking or tapping) to relieve their anxiety, often in multiples of a preferred number.
• A person may repetitively check on real or imagined conditions, such as excessively checking that loved ones are safe, checking that certain tasks were completed (such as locking the door), or checking the body (often to look for signs of illness or disfiguration).
• Mental compulsions. A person with OCD may internally count in multiples of a preferred number, excessively pray to oneself, or review past events (often to ensure that tasks were completed properly to prevent a perceived harm to oneself or others).
How is OCD diagnosed?
The DSM-5 provides guidelines for determining that a person has OCD. To be diagnosed with OCD, a person’s behaviors must meet the following criteria:
Behaviors qualify as obsessions when a person
• Experiences recurrent, persistent, intrusive thoughts that cause anxiety or distress.
• Attempts to suppress these thoughts by engaging in a compulsive behavior.
Behaviors qualify as compulsions when a person…
• Feels driven to repetitively, excessively, or rigidly perform a task in response to an obsession.
• Engages in these behaviors to relieve distress, even though the actions are not rationally connected with the events they are intended to prevent (e.g., hand-washing does not actually prevent a loved one from having a car accident).
• Spends at least one hour per day engaging in compulsive behaviors, or experiences significant impairments in important areas of their life as a result of compulsive behaviors.
How many people have OCD?
Millions of people in the United States live with OCD. Researchers estimate that:
Who’s at risk for OCD?
Any person can develop OCD at any point in their lifetime. However, certain groups of people are more likely to develop OCD than others.
How does OCD affect a person’s life?
Most people with OCD are either severely (50.6% of sufferers) or moderately (34.8%) impacted by their illness. For those with moderate to severe OCD, the hours they spend engaging in compulsions can significantly interfere with their ability to work, study, sleep, maintain social relationships, and enjoy leisure activities. Many people with OCD experience additional emotional distress because they are aware that their behavior is irrational and detrimental to their quality of life, but they feel powerless to stop.
Individuals with OCD are also more likely to develop other mental disorders. While some people may be generally predisposed to experiencing mental illness, the distress of living OCD can directly cause other debilitating conditions that can further reduce quality of life. An estimated 40-80% of people with OCD also experience major depressive disorder. Additionally, more than 1 in 4 people with OCD meet criteria for a substance use disorder, often using drugs or alcohol to cope with the anxiety and distress of OCD. When seeking treatment for OCD, it is critical to address any other co-occurring mental health concerns to ensure that OCD recovery is not complicated or inhibited by the presence of other disorders.
What’s happening in the brain?
Neuroscientists have used brain imaging techniques to determine that people with OCD may have structural differences in certain areas of the brain, such as the prefrontal cortex, which is responsible for decision making, personality, impulse control, and planning. Some scientists suspect that OCD symptoms are the result of communication errors between multiple areas of the brain called the cortico-striatal-thalamic-cortical (CTSC) circuit, which works together to regulate cognition, reward seeking and motivation, behavior, sensation, motor function, and other important brain functions. When these specific areas of the brain fail to properly send certain signals among each other, a person may experience OCD symptoms.
Scientists also know that neurotransmitters, or brain chemicals that perform important functions, are involved in OCD. Specifically, they have found that people with OCD may release too much or too little of four specific neurotransmitters (serotonin, dopamine, glutamate, and GABA), all of which are found in the CTSC circuit. The resulting chemical imbalance may cause OCD.
Despite these observations, scientists have not discovered a predictable pattern of brain structure or behavior that can definitively indicate that a person has OCD. Researchers are still working to advance our understanding of the neuroscience basis for this disorder.
How is OCD treated?
Many treatment options are available to people seeking relief from OCD. Treatment usually involves a combination of medication and therapy, but other cutting-edge options may offer a solution for the 30% of individuals who do not respond to traditional treatment.
Selective serotonin reuptake inhibitors (SSRIs), which are considered a first-line treatment for OCD, help the brain regulate and create a healthy balance of neurotransmitters. These medications can also help to treat other mental disorders (especially depression), making them an desirable option for people who suffer from certain co-occurring conditions in addition to OCD.
Many clinicians recommend that people with OCD should seek psychotherapy, which can be effective alone or in combination with medication. One popular therapeutic approach, called cognitive behavioral therapy (CBT), may help people reduce their OCD symptoms by providing them with coping skills that can help them unlearn patterns of harmful behavior.
Although medication and therapy generally are considered successful treatments for OCD, research suggests that only 7 in 10 people with OCD will benefit from these treatments, and they typically only see a partial reduction in their symptoms, rather than full remission.
Fortunately, innovative techniques may offer relief where traditional treatments fail. Transcranial magnetic stimulation (TMS), a non-invasive therapy that uses small electrical impulses to stimulate areas of the brain, received FDA approval in 2018 as a safe, effective treatment for OCD. Research indicates that 38.1% of people with treatment-resistant OCD showed at least a 30% reduction in their OCD symptoms after receiving TMS, indicating that the technique is a promising way to alleviate stubborn OCD and offer a renewed quality of life to those who live with the condition.
We are happy to offer this evidence based, cutting-edge OCD treatment, TMS Therapy, at our clinic, TMS Program. Please give us a call at 856.350.5555 to schedule a free consultation.
|
__label__pos
| 0.976816 |
What's pulmonary diseases ? Here are causes, signs and symptoms that should be wary
In addition to common causes of the pulmonary diseases that we know such as Pleurisy, Asthma , pulmonary Embolism, Pneumothorax, pneumonia, Hyperventilation, lung Cancer, Costochondritis and Tuberculosis, there are 2 types of other pulmonary diseases that you should be aware, that is Pulmonary embolism and pulmonary hypertension .
What is the difference pulmonary hypertension and Pulmonary embolism ? Pulmonary embolism is a blockage that occurs in one of the arteries of Your lungs.
In many cases, pulmonary embolism caused by a lot of congealed blood flowing to the lungs from the legs, or more rarely from other parts of the body (deep vein thrombosis).
While Pulmonary hypertension is one type of high blood pressure that is specific for blood vessels the arteries in the lungs and the right side of the heart.
Pulmonary hypertension occurs when the small arteries in the lungs are called the arterioles of the pulmonary vessels and the capillaries are narrowed, clogged, or damaged.
What's pulmonary diseases ? Here are causes signs and symptoms that should be wary
Signs and symptoms most typical of pulmonary embolism:
• Short breath
• Pain in the chest, this condition can take place in a matter of minutes to hours
• Bloody cough
• Rapid heart rate
Other symptoms include:
• Nausea or vomiting
• Dizziness or headaches
• Low blood pressure
• Fainting
• Sweating
• Sound when breathing
• Sweating hands
• The skin is bluish
There still may be other symptoms not listed above. If You have concerns about specific symptoms, consult your doctor.
The causes of pulmonary embolism
In many cases, a pulmonary embolism occurs when a blood clot occurs in the arteries of Your lungs. A blood clot is most often derived from the blood vessels of the inner leg, known as deep vein thrombosis. Sometimes, a blockage in the blood vessels can also be caused by other substances in addition to blood clotting, such as:
• Fat from sumsung broken bones
• Air bubbles
• Part of the tumor cells
• Collagen or other tissue
Signs and symptoms of hypertension pulmonary
Shortness of breath or dizziness during the day is the initial symptoms. The heart to beat fast (palpitations). Over time, the symptoms appear when doing light activity or even when you are resting. Other symptoms namely:
• The leg and wrist swelling
• Bluish color of the lips or skin (cyanosis)
• Chest pain like to be pressed, usually in the front of the
• Dizziness and even fainting
• Fatigue
• The increase in the size of the stomach
• Limp bodies
Likely there are symptoms and other signs not mentioned above. If You have any concerns regarding the symptoms of this disease, please consult with Your doctor.
Reacd more : 11 Symptoms diseases of the heart should be aware, immediate consultation to the doctor!
The causes of pulmonary hypertension
The right side of the heart to pump blood through the lungs, where blood picks up oxygen. The blood returns to the left side of the heart, and is pumped to the entire body. When the small arteries (blood vessels) of the lungs become narrow, they can not bring a lot of blood. When this happens, the blood accumulates and presses the walls of blood vessels.
This is called pulmonary hypertension. Pulmonary hypertension idiopathic heritable hereditary and is rare compared with secondary pulmonary hypertension. The genes of people with pulmonary hypertension idiopathic make the blood vessels constrict so the blood becomes more difficult to flow.
Secondary pulmonary hypertension is caused by arteries and capillaries in the lungs narrowing, which causes the heart to work harder to pump blood through the lungs.Pulmonary hypertension can be caused by:
• Autoimmune diseases that damage the lungs, such as scleroderma and rheumatoid arthritis
• Heart defects since birth
• Blood clots in the lungs (pulmonary embolism)
• Heart failure
• Disorders of the heart valves
• HIV infection
• The Level of low oxygen in the blood and has been prolonged (chronic)
• Lung diseases, such as COPD or pulmonary fibrosis
• Drugs (eg, drug a specific diet)
• Sleep apnea obstructive
Share this
|
__label__pos
| 0.977897 |
x
Out of memory loading between levels
Howdy Unity gurus!!!
I get out of memory errors now and then just before loading scene "y" from secene "x". Scene"x" is moderate size, not tiny. Scene "y" only has two objects. One with a 1024 texture.
I'm trying the following:
Resources.UnloadUnusedAssets()
just before loading scene"y" but I'm not using any resource bundles. Would this have any effect? I'm assuming it would dump some memory.
Thx for any tips in advance on this issue.
more ▼
asked Jan 25, 2012 at 04:37 PM
avatar image
peter
381 101 77 80
Have you tracked the memory usage on Unity profiler or on the Windows taskmanager?
Jan 25, 2012 at 05:44 PM luizgpa
Thx for your comment! On closer inspection, scene"y" has several object. about 15 simple planes, (billboards) and two guitext. Two boned skinned meshes. I looked at the profiler. Below is what is reported for memory. Does it look like enough to crash 4th gen iOS devices? I get occassional crashes that are stopped by cold start of device, but it's not a valid fix IMO.... Thx for any tips! scene"x" memory textures: 964 / 18 mb meshes 92 / 4.4mb total object count 14683
scene"y" textures: 959 / 10.3 mb meshes 41 / 285 kb total object count 2797
Jan 25, 2012 at 06:06 PM peter
I'm sorry but I don't have much experience with iOS devices, so I will just throw some generic questions that came to my mind:
Does it crash if start your game loading scene "y" before "x"? Do you use LoadLevelAdditive or LoadLevelAsync? Do you have many static objects (like static var obj : GameObject) or objects using DontDestroyOnLoad?
Jan 25, 2012 at 09:14 PM luizgpa
(comments are locked)
10|3000 characters needed characters left
1 answer: sort voted first
You can profile your memory usage using Instruments through XCode. Simply select Product > Profile from the menu bar, which will compile your app, put it on the device, and automatically open up Instruments (using XCode4, might be the same in XCode3). If you then select "Activity Monitor," you'll get a lot of data on the amount of memory you are using. Depending on your testing device, the acceptable amount of RAM varies.
iPhone3 (128MB total RAM): less than 40MB
iPad1 or iPhone3GS (256MB total RAM): less than 80MB
iPhone4, iPhone4S, iPad2 (512MB total RAM): less than 160MB
Another thing you might want to do is watch your XCode log and see if you are receiving memory warnings. Memory warnings are a pretty good indicator that you are using too much memory and the OS might shut you down.
Then, I've found the following code pretty useful to see everything that is loaded in memory at a given time. It will slow down your build a little bit because it uses UnityGUI, so use it for debugging only, not in production builds:
public class DetectLeaks : MonoBehaviour
{
private static DetectLeaks instance;
void Awake()
{
if(instance == null)
{
instance = this;
}
else
{
Destroy(this);
}
}
void Start()
{
DontDestroyOnLoad(gameObject);
}
void OnGUI()
{
if(GUILayout.Button("Unload Unused Assets"))
{
Resources.UnloadUnusedAssets();
}
if(GUILayout.Button("Mono Garbage Collect"))
{
System.GC.Collect();
}
if(GUILayout.Button("List Loaded Textures"))
{
ListLoadedTextures();
}
if(GUILayout.Button("List Loaded Sounds"))
{
ListLoadedAudio();
}
if(GUILayout.Button("List Loaded GameObjects"))
{
ListLoadedGameObjects();
}
}
private void ListLoadedTextures()
{
Object[] textures = Resources.FindObjectsOfTypeAll(typeof(Texture));
string list = string.Empty;
for(int i = 0; i < textures.Length; i++)
{
if(textures[i].name == string.Empty)
{
continue;
}
list += (i.ToString() + ". " + textures[i].name + "\n");
if(i == 500)
{
Debug.Log(list);
list = string.Empty;
}
}
Debug.Log(list);
}
private void ListLoadedAudio()
{
Object[] sounds = Resources.FindObjectsOfTypeAll(typeof(AudioClip));
string list = string.Empty;
for(int i = 0; i < sounds.Length; i++)
{
if(sounds[i].name == string.Empty)
{
continue;
}
list += (i.ToString() + ". " + sounds[i].name + "\n");
}
Debug.Log(list);
}
private void ListLoadedGameObjects()
{
Object[] gos = Resources.FindObjectsOfTypeAll(typeof(GameObject));
string list = string.Empty;
for(int i = 0; i < gos.Length; i++)
{
if(gos[i].name == string.Empty)
{
continue;
}
list += (i.ToString() + ". " + gos[i].name + "\n");
}
Debug.Log(list);
}
}
Finally, Resources.UnloadUnusedAssets() will only work if the asset is truly unused - that is, if there is no remaining script reference to the asset. If any Monobehavior is holding a reference, or if you have a link to a prefab that contains the asset, it will probably not be unloaded as a result of calling this. It is tricky to manage sometimes.
Hope this helps, and good luck!
more ▼
answered Jan 25, 2012 at 09:39 PM
avatar image
kromenak
2.7k 160 80 114
Thx so much! Very helpful tips!
Feb 02, 2012 at 12:44 AM peter
Useful post - where do you get the numbers from for acceptable RAM?
Aug 23, 2012 at 07:44 AM Bovine
Those RAM values aren't from an authoritative source; just my own observations/forum research and then extrapolating for newer devices. I probably got the most data with ipad1, where we were constantly battling memory crashes.
In my idealized world, "too much memory" is receiving memory warnings from the os. In practice, I've occosionally had to let it slip ;).
Aug 23, 2012 at 08:10 AM kromenak
Thanks for the detail - that's fine, observations are as valid as anything and we're seeing some signal 9 issues and running at about 80MB I think. The trouble I am having at present is that the various metrics available give wildly different figures as to how much physical RAM is being used.
Our problem, I suspect, is that we have a memory intensive operation (compressing level data to save it between scenes) that allocates a lot of RAM during a blocking operation. I wonder if the application's main loop were allowed to run, whether Unity would handle the request more elegantly...
Aug 23, 2012 at 08:57 AM Bovine
Yeah, I agree that the metrics given by the Unity profiler vs. the XCode profiler vs. a custom solution make it very hard to get an accurate picture of where your memory is going. I think this may be in part because Unity is pretty complicated, and it is storing things on the native heap vs. the mono heap. I've usually put more faith in the XCode profiler just because it is telling me what iOS is seeing, and iOS is the authority on whether my app gets terminated or not.
I wrote a blog post on this awhile back which, frankly, could probably be expanded a bit more with info on profiling. If you're interested though, there may be some helpful info: http://supersegfault.com/?p=43
Aug 23, 2012 at 03:58 PM kromenak
(comments are locked)
10|3000 characters needed characters left
Your answer
toggle preview:
Up to 2 attachments (including images) can be used with a maximum of 524.3 kB each and 1.0 MB total.
Follow this question
By Email:
Once you sign in you will be able to subscribe for any updates here
By RSS:
Answers
Answers and Comments
Topics:
x1158
x560
x13
asked: Jan 25, 2012 at 04:37 PM
Seen: 9593 times
Last Updated: Aug 23, 2012 at 03:58 PM
|
__label__pos
| 0.651899 |
Phantom Matrix
From Ascension Glossary
Jump to: navigation, search
The Phantom Matrix: A fallen region of lower-dimensional spectrum originally from our Universal Time Matrix. It became a slowly degenerating black-hole reality and contains a fallen parallel Earth that the Bible refers to as the bottomless pit, Hades or Hell. Nevertheless if one fell into this, say, via the Falcon or Phoenix Grid wormholes on the basis of frequency affiliation one wouldn't necessarily encounter sheer misery and torment; there would be upper portions of this reality which initially might be indistinguishable from Earth as it is today, though one would soon realize the control and suppression was greater and from an ET government; also that it was an astral frequency dimension with no death of the body, except that one would slowly die in an imperceptibly imploding black-hole system (capable of lasting some hundreds of millions of years without external and internal sustenance.[1]
Over the last 5,500 years our planet has been operating on a “closed” bi-wave, reversal polarity system (see the Ages of Humanity chart). This means the Trinity wave of the Christos nor Cosmic Mother Arc were existing or accessible from within this planetary field during that timeline. A closed system means “finite energy supply”. With finite energy supply, consuming others energies and parasitic relationships multiplied into massive proportions. These “feedlines” have clustered creating multiple infections of Dead Energy and Miasma in the Universe and all through the Planetary Time Matrix. These “infections” are called “phantom matrix” or dead spaces. These dead spaces have to feed on someone or something in order to exist. Or they are just like piles of infectious dead waste and pollution piled in a corner, just like massive trash dumps and plastic bottles littering the land and oceans of the Earth. It is the phantom or dead spaces that the NAA Controller Forces siphon our planetary energy into. They do this by manipulation of the bi-wave polarity fields and rotation of the electron particle by forcing the energy flow in disproportionate channels that feed their intended source. Usually the feedline is directed by and through the Alpha Draconis/Orion Group controllers.[2]
AI Timelines of Fallen Earth
We are providing a summation of the most common Historical Timeline Trigger Events that were generated during the Great Galactic War histories, in order to give greater context and meaning to the memory associations that occur throughout the remembering process. When we start to remember what has happened, this supports the reclamation of soul fragments and the returning of consciousness memories that were being manipulated by the AI version of the 3D timelines. (This is the Phantom Earth timelines). The NAA have used dimensional blending experiments and alien technology to eliminate certain historical timeline records and to manipulate the perception of important figures throughout human history, in order to control or eradicate these memories from the physical 3D matrix of human perception. This is intended to lure the human soul into the Phantom Earth powered up by AI technology and false timelines.
In order to be freed from the control of the AI reality, one must see it as false. The artificial reality is based on maintaining deceptions and manipulations that keep us ignorant of the larger truth of what has really happened to humanity. [3]
Hibernation Zones
Additional phantom area pockets or zones were created during the Atlantian Cataclysm through reversal electron or Light reversals made in sections of the earths field that were intended to inhabit by the NAA and intruding races to enslave the planet and humanity. This connects with the NETs that turned earth into a prison planet.
5D Earth, Tara
The 5D planet Tara exploded millions of years ago and as a result, was sucked into a reversal black hole which fragmented the entire fifth dimensional planetary blueprint into 12 planetary bodies in our current third dimensional Solar System. This includes the 3D version of Earth we inhabit in this Time Vector of the Universal Time Matrix. We exist in a lower dimension of Phantom Matrix created by the reversal black hole, which is the 3D earth timelines. These 12 planets are Mercury, Venus, Earth, Mars, Maldek, Jupiter, Uranus, Neptune, Pluto, Nibiru and then the Sun star. Current science recognizes only seven planets of the twelve in our Solar System, along with dwarf planets. [4]
Tara and Tiamat aspects were companions in a Binary Star system in the higher dimensions. Binary Star Systems are common for ascending planets with advanced races. Tiamats explosion and destruction in the 5D universe, along with the planetary cataclysm of Tara, is the reason our planet earth descended into the Phantom Matrix and has an artificial satellite which is the Moon.
Tiamat as Phantom Matrix
This collision with Nibiru happened millenniums ago with a 5D planet that was between Jupiter and Mars referred to as the female principle Stellar body Tiamat. This collision was catastrophic and severed the consciousness units of Tiamat and her Moon consort (Apsu,then son Kingu) which were strewn into pieces of an asteroid belt. This asteroid belt changed the orbits of the inner planets and outer planets of our Solar System. The severed bodies and consciousness of the planet were absorbed into a Phantom Matrix and its physical remains plummeted into a descending orbit into the 3D density we now exist. It is a part of this 3D earth planet that we now exist upon.
References
1. January 2008 Newsletter
2. February 2011 Newsletter
3. Historical Timeline Triggers
4. List of gravitationally rounded objects of the Solar System
Term first found: Page 56, HGS Manual
See Also
False Timelines
Tiamat
Beast Machine
|
__label__pos
| 0.96579 |
2
$\begingroup$
I am writing a custom framework and in it I'm trying to train a simple network to predict the addition function.
The network:
• 1 hidden layer of 3 Neurons
• 1 output layer
• cost function used is Squared error, (Not MSE to avoid precision problems)
• Identity transfer function to make things simple at first
• no specal updaters, just the step size
• no learning rate decay
• no regularization
The training set:
• ~500 samples
• inputs: [n1][n2]; labels: [n1 + n2]
• Every element is between 0 and 1. e.g.: [0.5][0.3] => [0.8]
The algorithm I'm using to optimize:
• samples 64 elements for an epoch
• for each sample: it evaluates the error
• then propagates the error back
• and then based on the error values calculates the gradients
• the gradients for each elements are added up into one vector, then normalized by dividing by the number of samples evaluated
• After the gradients are calculated a step size of 1e-2 is used to modify the weights.
• The training stops when the sum of the errors for the 500 data elements are below 1e-2
I don't have a test dataset yet, as first I'd like to overfit to a training set, to see if it could even do that. Withouot bias the training converges to an optimum in about ~4k epochs.
When I include the tuning of bias into the training, it seems to have a much worse performance, the network is not converging to the optimum, instead the biases and the weights oscillate next to one another..
Is this a normal effect of introducing a bias?
Here is a chart abuot the weight values throughout the training: enter image description here
$\endgroup$
2 Answers 2
0
$\begingroup$
Bias takes care of variables which are latent for i.e you did not include it in the training set.
So you are trying to overfitt on training set, but now you introduce pertrubance. Ofcourse it will have worse performance.
$\endgroup$
4
• $\begingroup$ Thank you for your answer! How would you say I can improve upon this? $\endgroup$ Mar 10, 2020 at 12:18
• $\begingroup$ Depends on your goal. You wanna generalise? introduce bias. You wanna overfit train- dont. In general overfitting train tells you nothing. We already know that NN can approximate arbitrary functions... $\endgroup$
– Noah Weber
Mar 10, 2020 at 12:32
• $\begingroup$ So a good next step would be to introduce an evaluation training set, then. But what I don't understand is that how could adding a different evaluation metric affect the training itself, i.e. : how should the gradients be affected? To the best of my knowledge introducing a validation set does not change the input for the training set.. $\endgroup$ Mar 10, 2020 at 12:39
• $\begingroup$ Maybe I'm not understanding "bias" correctly. It is a learnable parameter, so I update that along with the parameters inside the training set. What I mean under bias is a value which is stored inside the Neuron, which offsets its output activation. It is something to be learned just like the parameters are, so why does calculating the gradient for it, and updating it just like the parameters worsen the performance? $\endgroup$ Mar 10, 2020 at 14:51
0
$\begingroup$
It should not decrease performance that badly (as shown in the question). Biases help in generalizing and learning it adds complexity to the training, but it doesn't add much in this example.
Here the problem was with the implementation. After ~weeks of drooling above it, I finally got to the point where I started to use ancient methods ( pen + paper ) to verify the gradients, and therein I found a bug in the cost function:
some network outputs were compared to the wrong label values, hence the gradient calculation was faulty.
After the bug was fixed the network now converges as it should:
enter image description here
$\endgroup$
Your Answer
By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.
Not the answer you're looking for? Browse other questions tagged or ask your own question.
|
__label__pos
| 0.840471 |
Dashboards & Visualizations
Highlighted
Is it possible to customize a dashboard to have statistics and a graph in one panel?
Communicator
Hi Splunkers,
Is it possible to customize a dashboard having the statistics and graph in one panel?
Thanks,
0 Karma
Highlighted
Re: Is it possible to customize a dashboard to have statistics and a graph in one panel?
Builder
Yes, it's... Create your table and chart and arrange them side by side. After that click on "Edit Source" and you'll see something similar to it:
<option name="charting.layout.splitSeries">0</option>
<option name="charting.legend.labelStyle.overflowMode">ellipsisMiddle</option>
<option name="charting.legend.placement">right</option>
<option name="drilldown">row</option>
</table>
</panel>
<panel>
<chart>
<searchString>some search</searchString>
<earliestTime>$inputTime.earliest$</earliestTime>
<latestTime>$inputTime.latest$</latestTime>
<option name="charting.axisLabelsX.majorLabelStyle.overflowMode">ellipsisNone</option>
<option name="charting.axisLabelsX.majorLabelStyle.rotation">0</option>
This is basically the end of a table and start of a chart... just remove the 2 lines:
</panel>
<panel>
And both will appear on the same panel.
View solution in original post
Highlighted
Re: Is it possible to customize a dashboard to have statistics and a graph in one panel?
Communicator
Hi musskopf,
Thanks for quick help. It works.
Thanks,
0 Karma
|
__label__pos
| 0.958806 |
M2Lens: Visualizing and Explaining Multimodal Models for Sentiment Analysis
17 Jul 2021 · Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu ·
Multimodal sentiment analysis aims to recognize people's attitudes from multiple communication channels such as verbal content (i.e., text), voice, and facial expressions. It has become a vibrant and important research topic in natural language processing. Much research focuses on modeling the complex intra- and inter-modal interactions between different communication channels. However, current multimodal models with strong performance are often deep-learning-based techniques and work like black boxes. It is not clear how models utilize multimodal information for sentiment predictions. Despite recent advances in techniques for enhancing the explainability of machine learning models, they often target unimodal scenarios (e.g., images, sentences), and little research has been done on explaining multimodal models. In this paper, we present an interactive visual analytics system, M2Lens, to visualize and explain multimodal models for sentiment analysis. M2Lens provides explanations on intra- and inter-modal interactions at the global, subset, and local levels. Specifically, it summarizes the influence of three typical interaction types (i.e., dominance, complement, and conflict) on the model predictions. Moreover, M2Lens identifies frequent and influential multimodal features and supports the multi-faceted exploration of model behaviors from language, acoustic, and visual modalities. Through two case studies and expert interviews, we demonstrate our system can help users gain deep insights into the multimodal models for sentiment analysis.
PDF Abstract
Datasets
Results from the Paper
Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.
Methods
No methods listed for this paper. Add relevant methods here
|
__label__pos
| 0.998811 |
Visible to the public Biblio
Filters: Author is Wang, XiaoFeng [Clear All Filters]
2022-02-24
Liu, Weijie, Wang, Wenhao, Chen, Hongbo, Wang, XiaoFeng, Lu, Yaosong, Chen, Kai, Wang, Xinyu, Shen, Qintao, Chen, Yi, Tang, Haixu. 2021. Practical and Efficient In-Enclave Verification of Privacy Compliance. 2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). :413–425.
A trusted execution environment (TEE) such as Intel Software Guard Extension (SGX) runs attestation to prove to a data owner the integrity of the initial state of an enclave, including the program to operate on her data. For this purpose, the data-processing program is supposed to be open to the owner or a trusted third party, so its functionality can be evaluated before trust being established. In the real world, however, increasingly there are application scenarios in which the program itself needs to be protected (e.g., proprietary algorithm). So its compliance with privacy policies as expected by the data owner should be verified without exposing its code.To this end, this paper presents DEFLECTION, a new model for TEE-based delegated and flexible in-enclave code verification. Given that the conventional solutions do not work well under the resource-limited and TCB-frugal TEE, we come up with a new design inspired by Proof-Carrying Code. Our design strategically moves most of the workload to the code generator, which is responsible for producing easy-to-check code, while keeping the consumer simple. Also, the whole consumer can be made public and verified through a conventional attestation. We implemented this model on Intel SGX and demonstrate that it introduces a very small part of TCB. We also thoroughly evaluated its performance on micro-and macro-benchmarks and real-world applications, showing that the design only incurs a small overhead when enforcing several categories of security policies.
2021-05-05
Zhu, Jianping, HOU, RUI, Wang, XiaoFeng, Wang, Wenhao, Cao, Jiangfeng, Zhao, Boyan, Wang, Zhongpu, Zhang, Yuhui, Ying, Jiameng, Zhang, Lixin et al.. 2020. Enabling Rack-scale Confidential Computing using Heterogeneous Trusted Execution Environment. 2020 IEEE Symposium on Security and Privacy (SP). :1450—1465.
With its huge real-world demands, large-scale confidential computing still cannot be supported by today's Trusted Execution Environment (TEE), due to the lack of scalable and effective protection of high-throughput accelerators like GPUs, FPGAs, and TPUs etc. Although attempts have been made recently to extend the CPU-like enclave to GPUs, these solutions require change to the CPU or GPU chips, may introduce new security risks due to the side-channel leaks in CPU-GPU communication and are still under the resource constraint of today's CPU TEE.To address these problems, we present the first Heterogeneous TEE design that can truly support large-scale compute or data intensive (CDI) computing, without any chip-level change. Our approach, called HETEE, is a device for centralized management of all computing units (e.g., GPUs and other accelerators) of a server rack. It is uniquely designed to work with today's data centres and clouds, leveraging modern resource pooling technologies to dynamically compartmentalize computing tasks, and enforce strong isolation and reduce TCB through hardware support. More specifically, HETEE utilizes the PCIe ExpressFabric to allocate its accelerators to the server node on the same rack for a non-sensitive CDI task, and move them back into a secure enclave in response to the demand for confidential computing. Our design runs a thin TCB stack for security management on a security controller (SC), while leaving a large set of software (e.g., AI runtime, GPU driver, etc.) to the integrated microservers that operate enclaves. An enclaves is physically isolated from others through hardware and verified by the SC at its inception. Its microserver and computing units are restored to a secure state upon termination.We implemented HETEE on a real hardware system, and evaluated it with popular neural network inference and training tasks. Our evaluations show that HETEE can easily support the CDI tasks on the real-world scale and incurred a maximal throughput overhead of 2.17% for inference and 0.95% for training on ResNet152.
2020-07-10
Mi, Xianghang, Feng, Xuan, Liao, Xiaojing, Liu, Baojun, Wang, XiaoFeng, Qian, Feng, Li, Zhou, Alrwais, Sumayah, Sun, Limin, Liu, Ying. 2019. Resident Evil: Understanding Residential IP Proxy as a Dark Service. 2019 IEEE Symposium on Security and Privacy (SP). :1185—1201.
An emerging Internet business is residential proxy (RESIP) as a service, in which a provider utilizes the hosts within residential networks (in contrast to those running in a datacenter) to relay their customers' traffic, in an attempt to avoid server- side blocking and detection. With the prominent roles the services could play in the underground business world, little has been done to understand whether they are indeed involved in Cybercrimes and how they operate, due to the challenges in identifying their RESIPs, not to mention any in-depth analysis on them. In this paper, we report the first study on RESIPs, which sheds light on the behaviors and the ecosystem of these elusive gray services. Our research employed an infiltration framework, including our clients for RESIP services and the servers they visited, to detect 6 million RESIP IPs across 230+ countries and 52K+ ISPs. The observed addresses were analyzed and the hosts behind them were further fingerprinted using a new profiling system. Our effort led to several surprising findings about the RESIP services unknown before. Surprisingly, despite the providers' claim that the proxy hosts are willingly joined, many proxies run on likely compromised hosts including IoT devices. Through cross-matching the hosts we discovered and labeled PUP (potentially unwanted programs) logs provided by a leading IT company, we uncovered various illicit operations RESIP hosts performed, including illegal promotion, Fast fluxing, phishing, malware hosting, and others. We also reverse engi- neered RESIP services' internal infrastructures, uncovered their potential rebranding and reselling behaviors. Our research takes the first step toward understanding this new Internet service, contributing to the effective control of their security risks.
2018-05-30
Chen, Yi, You, Wei, Lee, Yeonjoon, Chen, Kai, Wang, XiaoFeng, Zou, Wei. 2017. Mass Discovery of Android Traffic Imprints Through Instantiated Partial Execution. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :815–828.
Monitoring network behaviors of mobile applications, controlling their resource access and detecting potentially harmful apps are becoming increasingly important for the security protection within today's organizational, ISP and carriers. For this purpose, apps need to be identified from their communication, based upon their individual traffic signatures (called imprints in our research). Creating imprints for a large number of apps is nontrivial, due to the challenges in comprehensively analyzing their network activities at a large scale, for millions of apps on today's rapidly-growing app marketplaces. Prior research relies on automatic exploration of an app's user interfaces (UIs) to trigger its network activities, which is less likely to scale given the cost of the operation (at least 5 minutes per app) and its effectiveness (limited coverage of an app's behaviors). In this paper, we present Tiger (Traffic Imprint Generator), a novel technique that makes comprehensive app imprint generation possible in a massive scale. At the center of Tiger is a unique instantiated slicing technique, which aggressively prunes the program slice extracted from the app's network-related code by evaluating each variable's impact on possible network invariants, and removing those unlikely to contribute through assigning them concrete values. In this way, Tiger avoids exploring a large number of program paths unrelated to the app's identifiable traffic, thereby reducing the cost of the code analysis by more than one order of magnitude, in comparison with the conventional slicing and execution approach. Our experiments show that Tiger is capable of recovering an app's full network activities within 18 seconds, achieving over 98% coverage of its identifiable packets and 0.742% false detection rate on app identification. Further running the technique on over 200,000 real-world Android apps (including 78.23% potentially harmful apps) leads to the discovery of surprising new types of traffic invariants, including fake device information, hardcoded time values, session IDs and credentials, as well as complicated trigger conditions for an app's network activities, such as human involvement, Intent trigger and server-side instructions. Our findings demonstrate that many network activities cannot easily be invoked through automatic UI exploration and code-analysis based approaches present a promising alternative.
2018-04-11
Wang, Wenhao, Chen, Guoxing, Pan, Xiaorui, Zhang, Yinqian, Wang, XiaoFeng, Bindschaedler, Vincent, Tang, Haixu, Gunter, Carl A.. 2017. Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2421–2434.
Side-channel risks of Intel SGX have recently attracted great attention. Under the spotlight is the newly discovered page-fault attack, in which an OS-level adversary induces page faults to observe the page-level access patterns of a protected process running in an SGX enclave. With almost all proposed defense focusing on this attack, little is known about whether such efforts indeed raise the bar for the adversary, whether a simple variation of the attack renders all protection ineffective, not to mention an in-depth understanding of other attack surfaces in the SGX system. In the paper, we report the first step toward systematic analyses of side-channel threats that SGX faces, focusing on the risks associated with its memory management. Our research identifies 8 potential attack vectors, ranging from TLB to DRAM modules. More importantly, we highlight the common misunderstandings about SGX memory side channels, demonstrating that high frequent AEXs can be avoided when recovering EdDSA secret key through a new page channel and fine-grained monitoring of enclave programs (at the level of 64B) can be done through combining both cache and cross-enclave DRAM channels. Our findings reveal the gap between the ongoing security research on SGX and its side-channel weaknesses, redefine the side-channel threat model for secure enclaves, and can provoke a discussion on when to use such a system and how to use it securely.
2018-03-26
You, Wei, Zong, Peiyuan, Chen, Kai, Wang, XiaoFeng, Liao, Xiaojing, Bian, Pan, Liang, Bin. 2017. SemFuzz: Semantics-Based Automatic Generation of Proof-of-Concept Exploits. Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. :2139–2154.
Patches and related information about software vulnerabilities are often made available to the public, aiming to facilitate timely fixes. Unfortunately, the slow paces of system updates (30 days on average) often present to the attackers enough time to recover hidden bugs for attacking the unpatched systems. Making things worse is the potential to automatically generate exploits on input-validation flaws through reverse-engineering patches, even though such vulnerabilities are relatively rare (e.g., 5% among all Linux kernel vulnerabilities in last few years). Less understood, however, are the implications of other bug-related information (e.g., bug descriptions in CVE), particularly whether utilization of such information can facilitate exploit generation, even on other vulnerability types that have never been automatically attacked. In this paper, we seek to use such information to generate proof-of-concept (PoC) exploits for the vulnerability types never automatically attacked. Unlike an input validation flaw that is often patched by adding missing sanitization checks, fixing other vulnerability types is more complicated, usually involving replacement of the whole chunk of code. Without understanding of the code changed, automatic exploit becomes less likely. To address this challenge, we present SemFuzz, a novel technique leveraging vulnerability-related text (e.g., CVE reports and Linux git logs) to guide automatic generation of PoC exploits. Such an end-to-end approach is made possible by natural-language processing (NLP) based information extraction and a semantics-based fuzzing process guided by such information. Running over 112 Linux kernel flaws reported in the past five years, SemFuzz successfully triggered 18 of them, and further discovered one zero-day and one undisclosed vulnerabilities. These flaws include use-after-free, memory corruption, information leak, etc., indicating that more complicated flaws can also be automatically attacked. This finding calls into question the way vulnerability-related information is shared today.
2018-02-28
Demetriou, Soteris, Zhang, Nan, Lee, Yeonjoon, Wang, XiaoFeng, Gunter, Carl A., Zhou, Xiaoyong, Grace, Michael. 2017. HanGuard: SDN-driven Protection of Smart Home WiFi Devices from Malicious Mobile Apps. Proceedings of the 10th ACM Conference on Security and Privacy in Wireless and Mobile Networks. :122–133.
A new development of smart-home systems is to use mobile apps to control IoT devices across a Home Area Network (HAN). As verified in our study, those systems tend to rely on the Wi-Fi router to authenticate other devices. This treatment exposes them to the attack from malicious apps, particularly those running on authorized phones, which the router does not have information to control. Mitigating this threat cannot solely rely on IoT manufacturers, which may need to change the hardware on the devices to support encryption, increasing the cost of the device, or software developers who we need to trust to implement security correctly. In this work, we present a new technique to control the communication between the IoT devices and their apps in a unified, backward-compatible way. Our approach, called HanGuard, does not require any changes to the IoT devices themselves, the IoT apps or the OS of the participating phones. HanGuard uses an SDN-like approach to offer fine-grained protection: each phone runs a non-system userspace Monitor app to identify the party that attempts to access the protected IoT device and inform the router through a control plane of its access decision; the router enforces the decision on the data plane after verifying whether the phone should be allowed to talk to the device. We implemented our design over both Android and iOS (\textbackslashtextgreater 95% of mobile OS market share) and a popular router. Our study shows that HanGuard is both efficient and effective in practice.
2018-01-23
Wang, Shuai, Wang, Wenhao, Bao, Qinkun, Wang, Pei, Wang, XiaoFeng, Wu, Dinghao. 2017. Binary Code Retrofitting and Hardening Using SGX. Proceedings of the 2017 Workshop on Forming an Ecosystem Around Software Transformation. :43–49.
Trusted Execution Environment (TEE) is designed to deliver a safe execution environment for software systems. Intel Software Guard Extensions (SGX) provides isolated memory regions (i.e., SGX enclaves) to protect code and data from adversaries in the untrusted world. While existing research has proposed techniques to execute entire executable files inside enclave instances by providing rich sets of OS facilities, one notable limitation of these techniques is the unavoidably large size of Trusted Computing Base (TCB), which can potentially break the principle of least privilege. In this work, we describe techniques that provide practical and efficient protection of security sensitive code components in legacy binary code. Our technique dissects input binaries into multiple components which are further built into SGX enclave instances. We also leverage deliberately-designed binary editing techniques to retrofit the input binary code and preserve the original program semantics. Our tentative evaluations on hardening AES encryption and decryption procedures demonstrate the practicability and efficiency of the proposed technique.
2017-09-26
Liao, Xiaojing, Alrwais, Sumayah, Yuan, Kan, Xing, Luyi, Wang, XiaoFeng, Hao, Shuang, Beyah, Raheem. 2016. Lurking Malice in the Cloud: Understanding and Detecting Cloud Repository As a Malicious Service. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :1541–1552.
The popularity of cloud hosting services also brings in new security challenges: it has been reported that these services are increasingly utilized by miscreants for their malicious online activities. Mitigating this emerging threat, posed by such "bad repositories" (simply Bar), is challenging due to the different hosting strategy to traditional hosting service, the lack of direct observations of the repositories by those outside the cloud, the reluctance of the cloud provider to scan its customers' repositories without their consent, and the unique evasion strategies employed by the adversary. In this paper, we took the first step toward understanding and detecting this emerging threat. Using a small set of "seeds" (i.e., confirmed Bars), we identified a set of collective features from the websites they serve (e.g., attempts to hide Bars), which uniquely characterize the Bars. These features were utilized to build a scanner that detected over 600 Bars on leading cloud platforms like Amazon, Google, and 150K sites, including popular ones like groupon.com, using them. Highlights of our study include the pivotal roles played by these repositories on malicious infrastructures and other important discoveries include how the adversary exploited legitimate cloud repositories and why the adversary uses Bars in the first place that has never been reported. These findings bring such malicious services to the spotlight and contribute to a better understanding and ultimately eliminating this new threat.
2017-09-15
Liao, Xiaojing, Yuan, Kan, Wang, XiaoFeng, Li, Zhou, Xing, Luyi, Beyah, Raheem. 2016. Acing the IOC Game: Toward Automatic Discovery and Analysis of Open-Source Cyber Threat Intelligence. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :755–766.
To adapt to the rapidly evolving landscape of cyber threats, security professionals are actively exchanging Indicators of Compromise (IOC) (e.g., malware signatures, botnet IPs) through public sources (e.g. blogs, forums, tweets, etc.). Such information, often presented in articles, posts, white papers etc., can be converted into a machine-readable OpenIOC format for automatic analysis and quick deployment to various security mechanisms like an intrusion detection system. With hundreds of thousands of sources in the wild, the IOC data are produced at a high volume and velocity today, which becomes increasingly hard to manage by humans. Efforts to automatically gather such information from unstructured text, however, is impeded by the limitations of today's Natural Language Processing (NLP) techniques, which cannot meet the high standard (in terms of accuracy and coverage) expected from the IOCs that could serve as direct input to a defense system. In this paper, we present iACE, an innovation solution for fully automated IOC extraction. Our approach is based upon the observation that the IOCs in technical articles are often described in a predictable way: being connected to a set of context terms (e.g., "download") through stable grammatical relations. Leveraging this observation, iACE is designed to automatically locate a putative IOC token (e.g., a zip file) and its context (e.g., "malware", "download") within the sentences in a technical article, and further analyze their relations through a novel application of graph mining techniques. Once the grammatical connection between the tokens is found to be in line with the way that the IOC is commonly presented, these tokens are extracted to generate an OpenIOC item that describes not only the indicator (e.g., a malicious zip file) but also its context (e.g., download from an external source). Running on 71,000 articles collected from 45 leading technical blogs, this new approach demonstrates a remarkable performance: it generated 900K OpenIOC items with a precision of 95% and a coverage over 90%, which is way beyond what the state-of-the-art NLP technique and industry IOC tool can achieve, at a speed of thousands of articles per hour. Further, by correlating the IOCs mined from the articles published over a 13-year span, our study sheds new light on the links across hundreds of seemingly unrelated attack instances, particularly their shared infrastructure resources, as well as the impacts of such open-source threat intelligence on security protection and evolution of attack strategies.
2017-07-24
Liao, Xiaojing, Yuan, Kan, Wang, XiaoFeng, Li, Zhou, Xing, Luyi, Beyah, Raheem. 2016. Acing the IOC Game: Toward Automatic Discovery and Analysis of Open-Source Cyber Threat Intelligence. Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. :755–766.
To adapt to the rapidly evolving landscape of cyber threats, security professionals are actively exchanging Indicators of Compromise (IOC) (e.g., malware signatures, botnet IPs) through public sources (e.g. blogs, forums, tweets, etc.). Such information, often presented in articles, posts, white papers etc., can be converted into a machine-readable OpenIOC format for automatic analysis and quick deployment to various security mechanisms like an intrusion detection system. With hundreds of thousands of sources in the wild, the IOC data are produced at a high volume and velocity today, which becomes increasingly hard to manage by humans. Efforts to automatically gather such information from unstructured text, however, is impeded by the limitations of today's Natural Language Processing (NLP) techniques, which cannot meet the high standard (in terms of accuracy and coverage) expected from the IOCs that could serve as direct input to a defense system. In this paper, we present iACE, an innovation solution for fully automated IOC extraction. Our approach is based upon the observation that the IOCs in technical articles are often described in a predictable way: being connected to a set of context terms (e.g., "download") through stable grammatical relations. Leveraging this observation, iACE is designed to automatically locate a putative IOC token (e.g., a zip file) and its context (e.g., "malware", "download") within the sentences in a technical article, and further analyze their relations through a novel application of graph mining techniques. Once the grammatical connection between the tokens is found to be in line with the way that the IOC is commonly presented, these tokens are extracted to generate an OpenIOC item that describes not only the indicator (e.g., a malicious zip file) but also its context (e.g., download from an external source). Running on 71,000 articles collected from 45 leading technical blogs, this new approach demonstrates a remarkable performance: it generated 900K OpenIOC items with a precision of 95% and a coverage over 90%, which is way beyond what the state-of-the-art NLP technique and industry IOC tool can achieve, at a speed of thousands of articles per hour. Further, by correlating the IOCs mined from the articles published over a 13-year span, our study sheds new light on the links across hundreds of seemingly unrelated attack instances, particularly their shared infrastructure resources, as well as the impacts of such open-source threat intelligence on security protection and evolution of attack strategies.
2017-05-22
Alrwais, Sumayah, Yuan, Kan, Alowaisheq, Eihal, Liao, Xiaojing, Oprea, Alina, Wang, XiaoFeng, Li, Zhou. 2016. Catching Predators at Watering Holes: Finding and Understanding Strategically Compromised Websites. Proceedings of the 32Nd Annual Conference on Computer Security Applications. :153–166.
Unlike a random, run-of-the-mill website infection, in a strategic web attack, the adversary carefully chooses the target frequently visited by an organization or a group of individuals to compromise, for the purpose of gaining a step closer to the organization or collecting information from the group. This type of attacks, called "watering hole", have been increasingly utilized by APT actors to get into the internal networks of big companies and government agencies or monitor politically oriented groups. With its importance, little has been done so far to understand how the attack works, not to mention any concrete step to counter this threat. In this paper, we report our first step toward better understanding this emerging threat, through systematically discovering and analyzing new watering hole instances and attack campaigns. This was made possible by a carefully designed methodology, which repeatedly monitors a large number potential watering hole targets to detect unusual changes that could be indicative of strategic compromises. Running this system on the HTTP traffic generated from visits to 61K websites for over 5 years, we are able to discover and confirm 17 watering holes and 6 campaigns never reported before. Given so far there are merely 29 watering holes reported by blogs and technical reports, the findings we made contribute to the research on this attack vector, by adding 59% more attack instances and information about how they work to the public knowledge. Analyzing the new watering holes allows us to gain deeper understanding of these attacks, such as repeated compromises of political websites, their long lifetimes, unique evasion strategy (leveraging other compromised sites to serve attack payloads) and new exploit techniques (no malware delivery, web only information gathering). Also, our study brings to light interesting new observations, including the discovery of a recent JSONP attack on an NGO website that has been widely reported and apparently forced the attack to stop.
|
__label__pos
| 0.616511 |
DPDK logo
Elixir Cross Referencer
/* SPDX-License-Identifier: (BSD-3-Clause OR GPL-2.0)
*
* Copyright 2013-2016 Freescale Semiconductor Inc.
* Copyright 2016-2017 NXP
*
*/
#ifndef __FSL_DPSECI_H
#define __FSL_DPSECI_H
/* Data Path SEC Interface API
* Contains initialization APIs and runtime control APIs for DPSECI
*/
struct fsl_mc_io;
/**
* General DPSECI macros
*/
/**
* Maximum number of Tx/Rx priorities per DPSECI object
*/
#define DPSECI_PRIO_NUM 8
/**
* All queues considered; see dpseci_set_rx_queue()
*/
#define DPSECI_ALL_QUEUES (uint8_t)(-1)
int dpseci_open(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
int dpseci_id,
uint16_t *token);
int dpseci_close(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token);
/**
* Enable the Congestion Group support
*/
#define DPSECI_OPT_HAS_CG 0x000020
/**
* struct dpseci_cfg - Structure representing DPSECI configuration
* @options: Any combination of the following options:
* DPSECI_OPT_HAS_CG
* DPSECI_OPT_HAS_OPR
* DPSECI_OPT_OPR_SHARED
* @num_tx_queues: num of queues towards the SEC
* @num_rx_queues: num of queues back from the SEC
* @priorities: Priorities for the SEC hardware processing;
* each place in the array is the priority of the tx queue
* towards the SEC,
* valid priorities are configured with values 1-8;
*/
struct dpseci_cfg {
uint32_t options;
uint8_t num_tx_queues;
uint8_t num_rx_queues;
uint8_t priorities[DPSECI_PRIO_NUM];
};
int dpseci_create(struct fsl_mc_io *mc_io,
uint16_t dprc_token,
uint32_t cmd_flags,
const struct dpseci_cfg *cfg,
uint32_t *obj_id);
int dpseci_destroy(struct fsl_mc_io *mc_io,
uint16_t dprc_token,
uint32_t cmd_flags,
uint32_t object_id);
int dpseci_enable(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token);
int dpseci_disable(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token);
int dpseci_is_enabled(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
int *en);
int dpseci_reset(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token);
/**
* struct dpseci_attr - Structure representing DPSECI attributes
* @id: DPSECI object ID
* @num_tx_queues: number of queues towards the SEC
* @num_rx_queues: number of queues back from the SEC
* @options: Any combination of the following options:
* DPSECI_OPT_HAS_CG
* DPSECI_OPT_HAS_OPR
* DPSECI_OPT_OPR_SHARED
*/
struct dpseci_attr {
int id;
uint8_t num_tx_queues;
uint8_t num_rx_queues;
uint32_t options;
};
int dpseci_get_attributes(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
struct dpseci_attr *attr);
/**
* enum dpseci_dest - DPSECI destination types
* @DPSECI_DEST_NONE: Unassigned destination; The queue is set in parked mode
* and does not generate FQDAN notifications; user is expected to
* dequeue from the queue based on polling or other user-defined
* method
* @DPSECI_DEST_DPIO: The queue is set in schedule mode and generates FQDAN
* notifications to the specified DPIO; user is expected to dequeue
* from the queue only after notification is received
* @DPSECI_DEST_DPCON: The queue is set in schedule mode and does not generate
* FQDAN notifications, but is connected to the specified DPCON
* object; user is expected to dequeue from the DPCON channel
*/
enum dpseci_dest {
DPSECI_DEST_NONE = 0,
DPSECI_DEST_DPIO = 1,
DPSECI_DEST_DPCON = 2
};
/**
* struct dpseci_dest_cfg - Structure representing DPSECI destination parameters
* @dest_type: Destination type
* @dest_id: Either DPIO ID or DPCON ID, depending on the destination type
* @priority: Priority selection within the DPIO or DPCON channel; valid values
* are 0-1 or 0-7, depending on the number of priorities in that
* channel; not relevant for 'DPSECI_DEST_NONE' option
*/
struct dpseci_dest_cfg {
enum dpseci_dest dest_type;
int dest_id;
uint8_t priority;
};
/**
* DPSECI queue modification options
*/
/**
* Select to modify the user's context associated with the queue
*/
#define DPSECI_QUEUE_OPT_USER_CTX 0x00000001
/**
* Select to modify the queue's destination
*/
#define DPSECI_QUEUE_OPT_DEST 0x00000002
/**
* Select to modify the queue's order preservation
*/
#define DPSECI_QUEUE_OPT_ORDER_PRESERVATION 0x00000004
/**
* struct dpseci_rx_queue_cfg - DPSECI RX queue configuration
* @options: Flags representing the suggested modifications to the queue;
* Use any combination of 'DPSECI_QUEUE_OPT_<X>' flags
* @order_preservation_en: order preservation configuration for the rx queue
* valid only if 'DPSECI_QUEUE_OPT_ORDER_PRESERVATION' is contained in 'options'
* @user_ctx: User context value provided in the frame descriptor of each
* dequeued frame;
* valid only if 'DPSECI_QUEUE_OPT_USER_CTX' is contained in 'options'
* @dest_cfg: Queue destination parameters;
* valid only if 'DPSECI_QUEUE_OPT_DEST' is contained in 'options'
*/
struct dpseci_rx_queue_cfg {
uint32_t options;
int order_preservation_en;
uint64_t user_ctx;
struct dpseci_dest_cfg dest_cfg;
};
int dpseci_set_rx_queue(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
uint8_t queue,
const struct dpseci_rx_queue_cfg *cfg);
/**
* struct dpseci_rx_queue_attr - Structure representing attributes of Rx queues
* @user_ctx: User context value provided in the frame descriptor of each
* dequeued frame
* @order_preservation_en: Status of the order preservation configuration
* on the queue
* @dest_cfg: Queue destination configuration
* @fqid: Virtual FQID value to be used for dequeue operations
*/
struct dpseci_rx_queue_attr {
uint64_t user_ctx;
int order_preservation_en;
struct dpseci_dest_cfg dest_cfg;
uint32_t fqid;
};
int dpseci_get_rx_queue(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
uint8_t queue,
struct dpseci_rx_queue_attr *attr);
/**
* struct dpseci_tx_queue_attr - Structure representing attributes of Tx queues
* @fqid: Virtual FQID to be used for sending frames to SEC hardware
* @priority: SEC hardware processing priority for the queue
*/
struct dpseci_tx_queue_attr {
uint32_t fqid;
uint8_t priority;
};
int dpseci_get_tx_queue(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
uint8_t queue,
struct dpseci_tx_queue_attr *attr);
/**
* struct dpseci_sec_attr - Structure representing attributes of the SEC
* hardware accelerator
* @ip_id: ID for SEC.
* @major_rev: Major revision number for SEC.
* @minor_rev: Minor revision number for SEC.
* @era: SEC Era.
* @deco_num: The number of copies of the DECO that are implemented
* in this version of SEC.
* @zuc_auth_acc_num: The number of copies of ZUCA that are implemented
* in this version of SEC.
* @zuc_enc_acc_num: The number of copies of ZUCE that are implemented
* in this version of SEC.
* @snow_f8_acc_num: The number of copies of the SNOW-f8 module that are
* implemented in this version of SEC.
* @snow_f9_acc_num: The number of copies of the SNOW-f9 module that are
* implemented in this version of SEC.
* @crc_acc_num: The number of copies of the CRC module that are
* implemented in this version of SEC.
* @pk_acc_num: The number of copies of the Public Key module that are
* implemented in this version of SEC.
* @kasumi_acc_num: The number of copies of the Kasumi module that are
* implemented in this version of SEC.
* @rng_acc_num: The number of copies of the Random Number Generator that
* are implemented in this version of SEC.
* @md_acc_num: The number of copies of the MDHA (Hashing module) that
* are implemented in this version of SEC.
* @arc4_acc_num: The number of copies of the ARC4 module that are
* implemented in this version of SEC.
* @des_acc_num: The number of copies of the DES module that are
* implemented in this version of SEC.
* @aes_acc_num: The number of copies of the AES module that are
* implemented in this version of SEC.
**/
struct dpseci_sec_attr {
uint16_t ip_id;
uint8_t major_rev;
uint8_t minor_rev;
uint8_t era;
uint8_t deco_num;
uint8_t zuc_auth_acc_num;
uint8_t zuc_enc_acc_num;
uint8_t snow_f8_acc_num;
uint8_t snow_f9_acc_num;
uint8_t crc_acc_num;
uint8_t pk_acc_num;
uint8_t kasumi_acc_num;
uint8_t rng_acc_num;
uint8_t md_acc_num;
uint8_t arc4_acc_num;
uint8_t des_acc_num;
uint8_t aes_acc_num;
};
int dpseci_get_sec_attr(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
struct dpseci_sec_attr *attr);
/**
* struct dpseci_sec_counters - Structure representing global SEC counters and
* not per dpseci counters
* @dequeued_requests: Number of Requests Dequeued
* @ob_enc_requests: Number of Outbound Encrypt Requests
* @ib_dec_requests: Number of Inbound Decrypt Requests
* @ob_enc_bytes: Number of Outbound Bytes Encrypted
* @ob_prot_bytes: Number of Outbound Bytes Protected
* @ib_dec_bytes: Number of Inbound Bytes Decrypted
* @ib_valid_bytes: Number of Inbound Bytes Validated
*/
struct dpseci_sec_counters {
uint64_t dequeued_requests;
uint64_t ob_enc_requests;
uint64_t ib_dec_requests;
uint64_t ob_enc_bytes;
uint64_t ob_prot_bytes;
uint64_t ib_dec_bytes;
uint64_t ib_valid_bytes;
};
int dpseci_get_sec_counters(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
struct dpseci_sec_counters *counters);
int dpseci_get_api_version(struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t *major_ver,
uint16_t *minor_ver);
/**
* enum dpseci_congestion_unit - DPSECI congestion units
* @DPSECI_CONGESTION_UNIT_BYTES: bytes units
* @DPSECI_CONGESTION_UNIT_FRAMES: frames units
*/
enum dpseci_congestion_unit {
DPSECI_CONGESTION_UNIT_BYTES = 0,
DPSECI_CONGESTION_UNIT_FRAMES
};
/**
* CSCN message is written to message_iova once entering a
* congestion state (see 'threshold_entry')
*/
#define DPSECI_CGN_MODE_WRITE_MEM_ON_ENTER 0x00000001
/**
* CSCN message is written to message_iova once exiting a
* congestion state (see 'threshold_exit')
*/
#define DPSECI_CGN_MODE_WRITE_MEM_ON_EXIT 0x00000002
/**
* CSCN write will attempt to allocate into a cache (coherent write);
* valid only if 'DPSECI_CGN_MODE_WRITE_MEM_<X>' is selected
*/
#define DPSECI_CGN_MODE_COHERENT_WRITE 0x00000004
/**
* if 'dpseci_dest_cfg.dest_type != DPSECI_DEST_NONE' CSCN message is sent to
* DPIO/DPCON's WQ channel once entering a congestion state
* (see 'threshold_entry')
*/
#define DPSECI_CGN_MODE_NOTIFY_DEST_ON_ENTER 0x00000008
/**
* if 'dpseci_dest_cfg.dest_type != DPSECI_DEST_NONE' CSCN message is sent to
* DPIO/DPCON's WQ channel once exiting a congestion state
* (see 'threshold_exit')
*/
#define DPSECI_CGN_MODE_NOTIFY_DEST_ON_EXIT 0x00000010
/**
* if 'dpseci_dest_cfg.dest_type != DPSECI_DEST_NONE' when the CSCN is written
* to the sw-portal's DQRR, the DQRI interrupt is asserted immediately
* (if enabled)
*/
#define DPSECI_CGN_MODE_INTR_COALESCING_DISABLED 0x00000020
/**
* struct dpseci_congestion_notification_cfg - congestion notification
* configuration
* @units: units type
* @threshold_entry: above this threshold we enter a congestion state.
* set it to '0' to disable it
* @threshold_exit: below this threshold we exit the congestion state.
* @message_ctx: The context that will be part of the CSCN message
* @message_iova: I/O virtual address (must be in DMA-able memory),
* must be 16B aligned;
* @dest_cfg: CSCN can be send to either DPIO or DPCON WQ channel
* @notification_mode: Mask of available options; use 'DPSECI_CGN_MODE_<X>'
* values
*/
struct dpseci_congestion_notification_cfg {
enum dpseci_congestion_unit units;
uint32_t threshold_entry;
uint32_t threshold_exit;
uint64_t message_ctx;
uint64_t message_iova;
struct dpseci_dest_cfg dest_cfg;
uint16_t notification_mode;
};
int dpseci_set_congestion_notification(
struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
const struct dpseci_congestion_notification_cfg *cfg);
int dpseci_get_congestion_notification(
struct fsl_mc_io *mc_io,
uint32_t cmd_flags,
uint16_t token,
struct dpseci_congestion_notification_cfg *cfg);
#endif /* __FSL_DPSECI_H */
|
__label__pos
| 0.978761 |
Rethinking the Truly Unsupervised Image-to-Image Translation
Kyungjune Baek, Yunjey Choi, Youngjung Uh, Jaejun Yoo, Hyunjung Shim; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 14154-14163
Abstract
Every recent image-to-image translation model inherently requires either image-level (i.e. input-output pairs) or set-level (i.e. domain labels) supervision. However, even set-level supervision can be a severe bottleneck for data collection in practice. In this paper, we tackle image-to-image translation in a fully unsupervised setting, i.e., neither paired images nor domain labels. To this end, we propose a truly unsupervised image-to-image translation model (TUNIT) that simultaneously learns to separate image domains and translates input images into the estimated domains. Experimental results show that our model achieves comparable or even better performance than the set-level supervised model trained with full labels, generalizes well on various datasets, and is robust against the choice of hyperparameters (e.g. the preset number of pseudo domains). Furthermore, TUNIT can be easily extended to semi-supervised learning with a few labeled data.
Related Material
[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Baek_2021_ICCV, author = {Baek, Kyungjune and Choi, Yunjey and Uh, Youngjung and Yoo, Jaejun and Shim, Hyunjung}, title = {Rethinking the Truly Unsupervised Image-to-Image Translation}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2021}, pages = {14154-14163} }
|
__label__pos
| 0.98849 |
fbpx
With the breadth and depth of services AWS has to offer, it’s likely that you start off with a simple EC2 instance powering a website, and your architecture stack would look something like this:
Figure 1A simple WordPress website
And later, once you get used to working on AWS, and the website grows, the stack can gradually evolve into something like:
Figure 2: The first one on steroids
More services are used; the infrastructure can intelligently grow as traffic increases; there’s a CDN in place and; failsafe mechanisms are now provisioned.
For a geek, the transformation is brilliant, and the process of orchestrating it enthralling.
This involves learning how to set up multiple different services, understand how they talk to each other, make sure that every single component just works. You probably don’t want to do something that involved. You probably want the entire website with all its bells and whistles to work as simply as an EC2 started, with a few clicks of a mouse on a GUI.
Enter AWS CloudFormation
CloudFormation enables you to create and manage your infrastructure and application stack in a controlled and predictable way.
The CloudFormation service consists of:
1. Templates
A JSON text file which defines the resources and/or services which you need. Templates are also the place where dependencies, runtime parameters, and data flow sequences are defined. Once these are specified, the template is submitted to the CloudFormation service. The JSON contains the following fields:
1. Template format version (optional)—A value denoting the version of the current template. This is completely user—defined, and is usually a date value.
2. Description(optional)—A string describing what the template does.
3. Parameters(optional)
4. Resources(required)—A list of AWS services that the stack must include. This must conform to the following pattern
“Resources”:
{
“Logical_Identifier”:
{
“Type”: Type_of_Resource,
“Properties”:
{
}
}
}
Some resources require the resource field to be populated, and some don’t.
1. Outputs (Optional)—When you run the AWS CloudFormation describe command, the stuff specified in this field is what is returned.
2. Stacks
A running instance of a Template is called a Stack. Stacks are combinations of services and resources which run concurrently. Once a stack is up and running, services mentioned in the template driving it are launched.
So, the next time you require something as complex as “WordPress onto Amazon EC2 instances in an Auto Scaling group with a multi-AZ Amazon RDS database instance for storage,” don’t roll up your sleeves and start furiously typing away, investigate the CloudFormation sample templates page, because, probably “there’s a CloudFormation template for that”. Here it is, on the off chance that you were interested.
References:
[1]: https://aws.amazon.com/cloudformation/
[2]: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/sample-templates-applications-ap-south-1.html
Monali Ghosh
Monali Ghosh
Monali Ghosh is an active and passionate marketing professional with well-honed skills, a keen eye for subtle elements and enthusiasm to work smart. With a can-do attitude and zeal, she is allegedly wise to the ways of Content Marketing, PR, and Social Media.
Leave a Reply
|
__label__pos
| 0.530255 |
my python solution
• 0
G
# Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution(object):
def rotateRight(self, head, k):
"""
:type head: ListNode
:type k: int
:rtype: ListNode
"""
if not head or k == 0:
return head
length, p = 0, head
while p:
length += 1
p = p.next
k = k % length
if k == 0:
return head
fast, slow = head, head
while k:
fast = fast.next
k -= 1
while fast and fast.next:
fast = fast.next
slow = slow.next
new_head = slow.next
slow.next = None
fast.next = head
return new_head
Log in to reply
Looks like your connection to LeetCode Discuss was lost, please wait while we try to reconnect.
|
__label__pos
| 0.866132 |
15 Juni 2011
Testing dan Implemetasi Aplikasi Pembilang Dengan Metode Berbasis Path ( BAB 2 )
BAB II
PENGUJIAN PROGRAM
2. 1 Algoritma Program
keterangan …
1. inputkan angka
2. cek inputan.. Apakah berupa angka
3. cek inputan.. Apakah digit angka melebihi batasan
4. konversi angka ke bilangan
5. cek posisi digit
6. cetak bilangan
7. keluar program
8. bersihkan layar
9. selesai
Berikut ini adalah script lengkap dari aplikasi pembilang angka
Script
Fungsi
Private Sub txtAngka_KeyPress(KeyAscii As Integer)
If Not (KeyAscii >= Asc("0") And KeyAscii <= Asc("9") Or KeyAscii = vbKeyBack) Then
Beep
KeyAscii = 0
End If
End Sub
Mengecek inputan apakah berupa angka
Private Sub Image1_Click()
If txtAngka.Text > 999999999 Then
pesan = MsgBox("Angka yang dimasukkan terlalu besar" + Chr(13) + "Silahkan masukkan angka lagi", vdCritical, "Informasi")
txtAngka.Text = ""
Else
Label2.Caption = SayN(Val(txtAngka.Text))
End If
End Sub
Mengecek digit angka yang akan dikonversi, jika digit angka masih sesuai maka proses konversi akan dijalankan
Private Function Nama(a As String) As String
Select Case a
Case "1": Nama = "Satu "
Case "2": Nama = "Dua "
Case "3": Nama = "Tiga "
Case "4": Nama = "Empat "
Case "5": Nama = "Lima "
Case "6": Nama = "Enam "
Case "7": Nama = "Tujuh "
Case "8": Nama = "Delapan "
Case "9": Nama = "Sembilan "
Case "0": Nama = ""
End Select
End Function
Konversi angka ke bilangan
Private Function SayN(nNumber As Double) As String
Dim z, s, a, c, X
Dim ulang As Double
Dim i As Byte
Dim tampung(5) As String
Dim n As String
n = LTrim(RTrim(nNumber))
ulang = (Len(n) - 1) \ 3 + 1
For i = 1 To ulang
If Len(n) > 3 Then
c = Mid(n, Len(n) - 2, 3)
n = Mid(n, 1, Len(n) - 3)
tampung(i) = c
Else
tampung(i) = n
End If
Next i
z = ""
If n = "0" Then
z = "Nol "
Else
i = ulang
Do
a = ""
X = ""
s = tampung(i)
'menggenapkan tiga digit
While Len(s) < 3
s = "0" + s
Wend
'digit ratusan
If Mid(s, 1, 1) <> "0" Then
If Mid(s, 1, 1) = "1" Then
a = a + "Seratus "
Else
a = a + Nama(Mid(s, 1, 1)) + "Ratus "
End If
End If
'digit 11 - 19
If Mid(s, 2, 1) = "1" Then
If (Mid(s, 3, 1) <> "1") And _
(Mid(s, 3, 1) <> "0") _
Then a = a + Nama(Mid(s, 3, 1)) + "Belas "
If Mid(s, 3, 1) = "1" Then a = a + "Sebelas "
If Mid(s, 3, 1) = "0" Then a = a + "Sepuluh "
End If
'digit puluhan
If (Mid(s, 2, 1) <> "1") _
And (s <> "000") And _
(Mid(s, 2, 1) <> "0") Then
a = a + Nama(Mid(s, 2, 1)) + "Puluh "
End If
If (Mid(s, 3, 1) <> "0") And _
(Mid(s, 2, 1) <> "1") Then
a = a + Nama(Mid(s, 3, 1))
End If
'perkecualian untuk seribu
If (i = 2) Then
If s = "001" Then a = "Se"
End If
If s <> "000" Then
If i = 1 Then X = ""
If i = 2 Then X = "Ribu "
If i = 3 Then X = "Juta "
End If
If a = "Se" Then X = LCase(X)
z = z + a + X
i = i - 1
Loop Until i = 0
End If
SayN = z
End Function
Pengkonversian dengan memperhatikan digit
Private Sub Image3_Click()
txtAngka.Text = ""
Label2.Caption = ""
txtAngka.SetFocus
End Sub
Membersihkan tampilan layar
Private Sub Image2_Click()
Unload Me
End Sub
Keluar dari program
2. 1.1 Flow Graph
1. Diagram Flow Graph
1. Pembahasan
Jalur 1 : 1 – 7 – 9
Jalur 2 : 1 – 2 – 3 – 4 – 5 – 6 – 7 – 9
Jalur 3 : 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 1 – 7 – 9
Jalur 4 : 1 – 2 – 8 – 1 – 7 – 9
Jalur 5 : 1 – 2 – 3 – 8 – 1 – 7 – 9
2. 1.2 Cyclomatic Complexity
1. Pengertian
Cyclomatic Complexity adalah pengukuran software yang memberikan pengukuran kuantitatif dari kompleksitas logika program.
Pada konteks metode basis path testing, nilai yang dihitung bagi cyclomatic complexity menentukan jumlah jalur- jalur yang independen dalam kumpulan basis suatu program dan memberikan jumlah tes minimal yang harus dilakukan untuk memastikan bahwa semua pernyataan telah dieksekusi sekurangnya satu kali.
b. Pencarian Cyclomatic Complexity
1. Jumlah Region (R) : 5
2. [Region / Complexity] V(G) = E (edges) – N (nodes) + 2
= 12 – 9 + 2 = 5
3. [Complexity]V(G) = P (predicate node) + 1
= 4 + 1 = 5
Sehingga hasil dari Cyclomatic Complexity adalah 5
2. 1.1 Pengujian Jalur
Jalur 1 : 1 – 7 – 9
Hasil yang diharapkan : Keluar dari system
Jalur 2 : 1 – 2 – 3 – 4 – 5 – 6 – 7 – 9
Hasil yang diharapkan : Menampilkan hasil konversi kemudian keluar dari system
Jalur 3 : 1 – 2 – 3 – 4 – 5 – 6 – 7 – 8 – 1 – 7 – 9
Hasil yang diharapkan : Menampilkan hasil konversi kemudian system siap untuk menerima inputan kembali
Jalur 4 : 1 – 2 – 8 – 1 – 7 – 9
Hasil yang diharapkan : system tidak dapat menerima inputan selain angka
Jalur 5 : 1 – 2 – 3 – 8 – 1 – 7 – 9
Hasil yang diharapkan : system tidak dapat menerima inputan melebihi 9 digit (ratusan juta)
0 komentar:
Posting Komentar
Silahkan TInggalkan Komentar Anda di Blog Saya..
No SPAM and No PORN...
Terimakasih Telah meninggalkan Jejak Anda
Related Posts Plugin for WordPress, Blogger...
Award Pertama
Photobucket
Langganan Artikel Si Boersan :
Enter your email address:
Delivered by FeedBurner
Monggo Di Copy Linknya :
Text Link
Banner Link
Komunitas Blogger Indonesia Komunitas Blogwalking
|
__label__pos
| 0.997895 |
Reply
Contributor
Posts: 27
Registered: 07-19-2016
Should Journal nodes and Zookeeper nodes be on same host as the Namenodes in HA setup?
[ Edited ]
TLDR;
Should Journal nodes and Zookeeper nodes be on same host as the Namenodes in HA setup?
The point is that losing a NN+ZK+JN node will leave only two JK and JN in the cluster.
Are the remaining two ZKs and JNs enough for the promotion of the standby NN to active?
Long version:
We have a HA cluster that simplified looks like this:
master1: NN+JN+ZK
master2: NN+JN+ZK
mgmt1: CM+JN+ZK
Due to maintenence all three nodes lost connections between them which caused the following to happen:
Both Failover controllers got timeouts from 2 of the Zookeepers (majority) and shutsdown.
The active Namenode shutdown because it timedout while waiting for a quorum of Journal nodes to respond (only the local one did).
Since the failover controllers were down the standby NN never become active (it also got timeouts from a majority of JN by the way).
The Zookeepers threw generic error which seems to mean that there is only one ZK, there is even number of ZK or that it can't communicate with other ZKs.
1. Will it be correct to say that having all three nodes loose connection to each other is not a scenario in which the HA failover can occur?
2. Does the Failover Controller needs to be able to reach all three JN in order for it to trigger a failover? I am trying to figure out if moving the JN and the ZK to different hosts than the ones running NN would have helped.
3. Will it make sense to spread the two masters and the mgmt node in different datacenter in order to midiate the possibility of losing all at once if a datacenter goes down?
Highlighted
Expert Contributor
Posts: 152
Registered: 07-01-2015
Re: Should Journal nodes and Zookeeper nodes be on same host as the Namenodes in HA setup?
I am not an expert, but for the 1st question I know quite sure the answer.
HA is NOT handling the loss of connectivity in the cluster (each nodes). This of course brings down the services. HA is handling just the outage (loss of connectivity) of ONE server agains the rest.
This is my opinion..
Announcements
|
__label__pos
| 0.990423 |
John John - 1 year ago 67
C++ Question
finding the average of sums made in a loop in c++
Hello everyone I'm trying to find the average of a random amount of numbers that are input into a loop. For sum reason after the loop im able to print the right total, but when i try to find the average i get a weird answer. can anyone help me with this or direct to a thread on here that could help? I wasnt able to find anything on here.
here is my code for the program that isnt working.
#include <iostream>
#include <fstream>
#include <string>
using namespace std;
int main()
{
ifstream inData;
string golferFile;
string golfer;
int matches;
int score;
cout << endl;
cout << "Enter the golfer's filename: ";
cin >> golferFile;
inData.open(golferFile.c_str());
getline(inData, golfer);
inData >> matches;
cout << endl;
cout << "The golfer " << golfer << " has " << matches << " matches with scores"
" of" << endl;
cout << endl;
int count;
count = 1;
int matchNumber;
matchNumber = 1;
int sum;
while(count <= matches)
{
inData >> score;
cout << "Match " << matchNumber << ": " << score << endl;
matchNumber++;
count++;
sum = sum + score;
}
}
int mean;
mean = sum / matches;
cout << "The mean score is " << mean << endl;
return 0;
}
the output i receive is this for the mean
The mean score is 1399255
Answer Source
I found several error in your code.
• you forget to initialize your sum variable.
• in while loop an extra brace found.remove it
• you didn't write anything to stop your loop.that why your loop run infinite time.so initialize you loop also.
Recommended from our users: Dynamic Network Monitoring from WhatsUp Gold from IPSwitch. Free Download
|
__label__pos
| 0.961645 |
How to make better health and fitness decisions: A primer on Bayesian reasoning
Here’s something you won’t hear a lot of fitness pros admit: I’m not totally certain about all of the recommendations I give. To be honest, I’m not totally certain about most of them.
I’d say I have about 80-90% certainty about most of the stuff I tell you on here. Ten years from now, I’m sure I’ll have changed my mind about a few of those things.
This is radically different from how most people form their beliefs around health and fitness. Most people adopt one of two mentalities.
First, you have the absolutists. These people look at (some of) the evidence, pick a side, and then put all disconfirming evidence out of their minds. Once they’ve formed an opinion, these people are loathe to even admit any possibility they might be wrong.
This approach is encouraged by the media, which tends to report the latest study as though it both provides a definite answer and overrides all previous studies. New study proves that eggs will make you live longer!
There’s an obvious danger here of having a false sense of certainty- remember how many times the media has flip-flopped on eggs?
The second group is the relativists. These people look at the evidence, acknowledge that it is somewhat contradictory, and throw their hands up in the air and claim that the truth is unknowable, or possibly even unimportant.
At their worst, these people claim that the truth is literally relative- that what’s true for me isn’t necessarily true for you, and all opinions are equally valid. Just shoot me. Note: we’re talking about objective truth here. That’s different from individual variation, which we’ll talk about in a minute.
You shouldn’t be a relativist or an absolutist. Instead, you should become what’s known in statistical and philosophical circles as a Bayesian.
What is Bayesian Reasoning?
Some of you may have heard the term Bayesian from fitness writer and former statistician Menno Henselmans, whose website is called Bayesian Bodybuilding. Menno has said that Bayesian is essentially synonymous with “rational.” That’s close- Bayesian reasoning certainly is rational, but that’s not quite what it means. A more precise definition of Bayesian would be “probabilistic.”
The term comes from the name of the 18th century statistician, philosopher and minister Thomas Bayes, who created a formula (appropriately enough called Bayes’ Theorem) for estimating the likelihood of an event occurring. However, it was quickly realized that the same formula could be adapted to estimate the probability of a particular belief or hypothesis being true. This practice has evolved into the field that is now known as Bayesian probability.
To an absolutist, 70% certainty is the same as 100% certainty. To a relativist, it’s the same as 50% certainty. To a Bayesian, 70% certainty is just 70% certainty.
Now, you don’t actually need to learn Bayes’ Theorem, or any of the math behind this at all. I’m not a statistician, and you don’t need to be one either. What you do need to learn is what probabilistic reasoning looks like in action.
Probabilistic predictions are frequently used in the fields of finance and economics, and in particular for evaluating investments. One of the best examples of probabilistic thinking in action was the article Donald Trump is a tail-risk candidate, where author Josh Barro evaluates then-candidate Trump (this was written in early 2016) as if he were a stock that Josh was considering investing in.
First off, look at the graphic. Josh took everything that might happen if Trump gets elected, and plotted them along a bell curve-improbable bad outcomes on the left, likely outcomes in the middle, and improbable good outcomes on the right. Even though he’s strongly anti-Trump, he acknowledges a 10-15% possibility that Trump will surprise him and be a good president.
Second, read his argument for focusing on the left tail of that probability curve. Yes, nuclear war or global economic collapse are unlikely, but they would be catastrophic if they did happen. Therefore, he argues that voters should be conservative, in the sense of being risk-averse.
In applying Bayesian reasoning to your own decisions, you should be forming a rough mental probability graph similar to the one Josh drew, with the most likely outcome in the middle, below-expected outcomes on the left, and above-expected outcomes on the right. Also, like Josh did, you should give serious consideration to unlikely but catastrophic outcomes. In other words, don’t take drugs that have a 1% chance of killing you, even if the upside is good.
In a minute, I’ll show you a few examples of how I would graph out potential health and fitness choices. First though, you need to know what kind of data you’ll need to make these choices.
What to consider when making health and fitness choices
Okay, so now you have a basic idea of what your mental model should look like- a bell curve of the probable outcomes of any particular decision. Now the question becomes, how do you figure out how the bell curve is shaped, what goes on it, and where? In other words, how do you use this mental model to evaluate potential health and fitness choices?
First, you look at the evidence. Preferably scientific research- anecdotes have value, particularly if you’re asking a question that scientists haven’t studied very much, but research always takes precedence over anecdote.
Crucially, you need to look at the sum total of the research, not just the latest study. New studies build on old studies, but don’t replace them. The best way to get an overview of all the research on a topic is to look at meta-analyses and narrative reviews, two types of studies which synthesize the results of many prior studies on a given topic to figure out what the research as a whole says about a given question.
Once you’ve looked at the evidence, you ask yourself four questions:
First, what are the benefits? What are they and how big are they?
Second, what are the risks or drawbacks? Again, how big are they and how severe are they?
Third, how clear or certain is the evidence? Does it consistently say the same thing, or is it highly contradictory?
Fourth, how much inter-individual variability is there? This is really two questions. Does everybody respond the same way to whatever course of action you’re considering? And if not, do you have any way of knowing how you’ll respond?
I realize this is all really abstract and a bit confusing- as with most things, the best way to learn it is to see it in action, then do it yourself.
Five examples of Bayesian reasoning in action
Here are a few examples of this thought process in action. Since my aim here is mainly to demonstrate this thought process rather than to make definitive recommendations on any of these five things, these examples will be a little light on the citations.
Example 1: Anabolic steroids
Steroids are more popular than most people realize. We can only get very rough estimates on how many people use them, but it’s clear that at least several million Americans have tried them at some point.
Steroids are much more common among men than women, since they can cause women to essentially undergo a DIY sex change. Dosages also vary quite a lot. For the sake of this exercise, I’ll assume you’re a healthy young man considering trying a newbie-level steroid cycle of 400-600 mg/week of injectable testosterone for 10-16 weeks.
Benefits- High. You’ll gain muscle, and probably lose some fat. Your sex drive might also go up, and your skin might look a little better.
Risks- High. You could get acne, lose your sex drive, or start growing breast tissue, a condition called gynecomastia. You might suffer hair loss or anger issues. You will also suppress your body’s own testosterone production; it will recover, but it’s not clear how quickly or easily. Steroids can also cause heart problems, though probably not at this dosage.
Certainty- High. All of the risks and benefits I listed definitely happen, as confirmed b both studies and widespread anecdotal reports. Certainty is basically 100% for body composition effects- you’ll definitely put on muscle. The effects on libido and personality are less clear, and the odds of serious side effects are also less clear, but probably low at low doses.
Inter-individual variability- High. In both studies and anecdotes, different guys respond differently to steroids, both in terms of benefits and side effects. Hair loss is more common if you have a genetic predisposition for make-pattern baldness, and gyno is more common the higher your body fat percentage. The other effects are hard to predict, as they depend mostly on your androgen receptor density, which you don’t really know about.
Conclusion: effective but dangerous Steroids absolutely work, but they’re high risk, high reward. They also have some very severe side effects. I don’t use them and don’t think most people should. If you do want to try them, you should at least spend over a year learning about them, use a low dose to start with, get as lean as possible first to minimize the chance of gynecomastia, monitor your blood work before, during and after your cycle, and know how to help your body recover from steroid use.
Example 2: Meditation
Meditation is widely reported to lower stress and improve overall mental and physical health, as well as cognitive functioning. It can be as simple as sitting in silence with your eyes closed for 2 minutes at a time.
Benefits- Moderate to high. Meditation can reduce stress and increase quality of life, and has been suggested to have many other physical and mental benefits, like improved cognition and a stronger immune system.
Risks- low. I can’t see any way that meditation could go horribly wrong. Given its’ spiritual connotations, I suppose you might fall in with a creepy new-age crowd, but the only likely risk is that it won’t work, you’ll be frustrated and waste a little time.
Certainty- high. Meditation definitely works. The stress-reduction benefits are beyond dispute at this point. Other benefits have varying degrees of support- there’s probably something to improved cognition, while disease prevention and life extension are more speculative.
Inter-individual variability- moderate. It works better for some people than others, but most people who stick with it get some result.
Conclusion- try it. It doesn’t work for everyone, but given the substantial benefits and basically non-existent risks, there’s really no reason not to at least try meditation.
Related article: How to start meditating in just 2 minutes a day
Example 3: Branched-Chain Amino Acids
Branched-chain amino acids include the three amino acids leucine, isoleucine, and valine. BCAAs play a vital role in anabolic signaling, with leucine in particular having been shown to be absolutely necessary for muscle protein synthesis. Thus, it is widely believed that BCAA supplementation will help people build more muscle, preserve muscle while fasting, or reduce muscle catabolism during workouts.
Benefits- low. BCAAs have a strong theoretical foundation- you definitely do need them to build muscle. However, BCAA supplementation has generally failed to improve muscle protein synthesis in studies.
Risks- low. BCAAs don’t seem to have side effects. I seem to recall one study where they were shown to be actively counterproductive, but mostly they do nothing.
Certainty- moderate to high. Studies are pretty consistent about not finding results from BCAAs, at least if they’re well-designed. Of course, supplement companies can find ways to bias their studies- such as by having the group that takes BCAAs also consume more protein than the control group. Also, there’s always the argument that studies might not reflect real-world conditions all that well.
Inter-individual variability- low. Muscle protein breakdown and synthesis are fundamental biological processes that don’t vary a whole lot between people. Your diet may make a difference though- since vegetable protein has lower natural BCAA content, vegans might benefit somewhat from taking a couple of grams of BCAA with meals to boost the quality of the protein they eat.
Conclusion- waste of money. BCAAs don’t seem to work, nor do they seem to hurt anyone. They just waste your money. The one exception here being the aforementioned possible minor benefit to vegans. Menno Henselmans provides a good summary of the research here.
Example 4: Vegan Diet
I don’t think I need to explain what this is. Let’s assume your main goal is overall health, and you have no particular medical condition driving that decision.
Benefits- varies. This depends a lot on what your basis of comparison is. Vegan diets have consistently outperformed the standard American junk food diet, but then so does any other controlled diet. Compared to other diets like paleo, Atkins, or the Mediterranean diet, the vegan diet usually ends up coming pretty close- there’s not a totally clear winner, at least for fat loss. For lifespan, eating more unprocessed plant foods is good.
Risks and drawbacks- moderate. There’s the obvious problem of missing out on a lot of foods you like. Vegetable protein is also lower-quality than animal protein, so you need to eat more of it and even then you won’t gain muscle as easily as a meat-eater. Vegan diets also tend to lead to a few nutrient deficiencies, particularly iron, zinc, and B-vitamins.
It should be noted that these are long-term risks; there’s no major short-term risk to at least trying veganism. For weight loss and blood sugar control, several other diets have outperformed the vegan diet.
Certainty- high. The vegan diet has been very well-studied and we have a pretty clear picture of its effects. Well-controlled long-term experimental studies are still lacking, and of course it’s a heavily politicized topic, but overall we have a reasonably clear picture of the upsides and downsides.
Inter-individual variability- moderate. Some people do respond better to it than others, but not radically so. You might feel great or you might feel fatigued all the time, but you won’t die.
Conclusion- probably worth a try, but might be going too far. Going vegan for a month won’t kill you and might be interesting. That said, remember how I said that the best diet for longevity appears to be a primarily plant-based diet?
The benefits of the vegan diet may have more to do with adding fruits and vegetables than with subtracting meat, although that obviously depends somewhat on what kind of meat you were eating before. Meanwhile, the drawbacks primarily come from the lack of animal protein. You’ll likely be better off doing it halfway by eating vegan for some, but not all, of your meals.
Example 5: Crossfit
To paraphrase Wikipedia: Promoted as both a physical exercise philosophy and also as a competitive fitness sport, CrossFit workouts incorporate elements from high-intensity interval training, Olympic weightlifting, plyometrics, powerlifting, gymnastics, girevoy sport, calisthenics, strongman, and other exercises. Crossfit is practiced at special Crossfit gyms, which are called “boxes” instead of gyms for some reason.
Benefits- High. You can lose fat, build muscle, build cardiovascular endurance, and develop a well-rounded physique and athletic ability. Crossfit really does work for a lot of people, so long as they avoid injury. You can also make friends, as Crossfit does a great job of building an active and motivating social environment into its gyms.
Risks- Very high.
Also, exertional rhabdomyolysis. And you’ll be surrounded by people who see this as some kind of silly joke.
Certainty- moderate. Crossfit is somewhat well-researched, but for ethical reasons the workouts used in research are usually different (read: safer) than most real Crossfit workouts. As a result, we still have to rely partly on anecdotal evidence. It’s clear that Crossfit works for many, doesn’t work for others, and also injures a lot of people, but the anecdotes don’t provide numbers.
According to this study, 73% of Crossfitters get injured, with 7% being injured badly enough to require surgery. That’s much higher than traditional weightlifting, but lower than heavy contact sports like rugby. However, you’d get very different numbers depending on which gyms- excuse me, “boxes-“ you drew your subjects from.
Inter-individual variability- high. There’s substantial variability in how your body responds to different kinds of training. There’s also a lot of variability between gyms, with some being much safer than others.
Most important in my opinion is psychological variability. Some people will enjoy the social environment of Crossfit more than others, and some people will be better able to resist the urge to push themselves too hard and get injured.
Conclusion- effective but unnecessary and dangerous. I’d go with traditional weight training. Crossfit does work for some people though. My guess is, the people who do best at it would most likely be extroverts who enjoy the socializing that comes with Crossfit, and not very competitive, so they won’t be driven to overreach and get injured like the people in the video.
Related article: The most overrated everything in fitness (Crossfit combines at least 3 of them)
Level up your reasoning skills
If you’re not use to thinking in probabilistic terms, it can be a difficult skill to develop. The best way to start thinking that way is to read the works of other people who express their thoughts in probabilistic terms.
Such people are few and far between. Bayesian-style predictions and statements of confidence can sometimes be seen in political polling and sports reporting- particularly betting sites. They’re otherwise uncommon in media reporting.
By far the best resource I’ve found for instilling this kind of thinking into my mind has been FiveThirtyEight. They almost always express their predictions for the future in terms of probability, and even publish detailed projections of elections and sports tournaments. I actually sometimes read their sports section just to absorb their way of thinking, even though I don’t care about sports.
As for resources that are specifically about fitness, the two people who I’ve seen to most exemplify this mindset are Alan Aragon and Menno Henselmans. I highly recommend that everyone read Menno’s blog and subscribe to Alan’s monthly research review. Although they don’t typically say that they’re “x% sure” about their recommendations, both of them habitually speak in terms of “weight of evidence” rather than certainty.
Regardless of who you read, start thinking in terms of how certain you are, and how probable it is that you’re correct- it’s never 100%, although it can certainly get close in some cases. When making health decisions- deciding on a new diet, a style of workout, what supplements to buy, which toxins you need to avoid- remember to look at the weight of all available evidence, not individual studies and definitely not popular media articles.
Click here to join the discussion on Facebook
|
__label__pos
| 0.566269 |
Schwarz minimal surface
From Wikipedia, the free encyclopedia
Jump to: navigation, search
In differential geometry, the Schwarz minimal surfaces are periodic minimal surfaces originally described by Hermann Schwarz.
In the 1880s Schwarz and his student E. R. Neovius described periodic minimal surfaces.[1][2] They were later named by Alan Schoen in his seminal report that described the gyroid and other triply periodic minimal surfaces.[3]
The surfaces were generated using symmetry arguments: given a solution to Plateau's problem for a polygon, reflections of the surface across the boundary lines also produce valid minimal surfaces that can be continuously joined to the original solution. If a minimal surface meets a plane at right angles, then the mirror image in the plane can also be joined to the surface. Hence given a suitable initial polygon inscribed in a unit cell periodic surfaces can be constructed.[4]
The Schwarz surfaces have topological genus 3, the minimal genus of triply periodic minimal surfaces.[5]
They have been considered as models for periodic nanostructures in block copolymers, electrostatic equipotential surfaces in crystals.,[6] and hypothetical negatively curved graphite phases.[7]
Schwarz P ("Primitive")[edit]
Schwarz P surface
Schoen named this surface 'primitive' because it has two interwined congruent labyrinths, each with the shape of an inflated tubular version of the simple cubic lattice. While the standard P surface has cubic symmetry the unit cell can be any rectangular box, producing a family of minimal surfaces with the same topology.[8]
It can be approximated by the implicit surface
\cos(x) + \cos(y) + \cos(z) = 0 \ .[9]
The P surface has been considered for prototyping tissue scaffolds with a high surface-to-volume ratio and porosity.[10]
Schwarz D ("Diamond")[edit]
Schwarz D surface
Schoen named this surface 'diamond' because has two intertwined congruent labyrinths, each having the shape of an inflated tubular version of the diamond bond structure. It is sometimes called the F surface in the literature.
It can be approximated by the implicit surface
\sin(x)\sin(y)\sin(z) + \sin(x)\cos(y)\cos(z) + \cos(x)\sin(y)\cos(z) + \cos(x)\cos(y)\sin(z) = 0.\
An exact expression exists in terms of elliptic integrals, based on the Weierstrass representation.[11]
Schwarz H ("Hexagonal")[edit]
Schwarz H surface
The H surface is similar to a catenoid with a triangular boundary, allowing it to tile space.
Schwarz CLP ("Crossed layers of parallels")[edit]
Schwarz CLP surface
Illustrations[edit]
References[edit]
1. ^ H. A. Schwarz, Gesammelte Mathematische Abhandlungen, Springer, Berlin, 1933.
2. ^ E. R. Neovius, "Bestimmung zweier spezieller periodischer Minimal achen", Akad. Abhandlungen, Helsingfors, 1883.
3. ^ Alan H. Schoen, Infinite periodic minimal surfaces without self-intersections, NASA Technical Note TN D-5541 (1970)[1]
4. ^ Hermann Karcher, Konrad Polthier, "Construction of Triply Periodic Minimal Surfaces", Phil. Trans. R. Soc. Lond. A 16 September 1996 vol. 354 no. 1715 2077–2104
5. ^ http://schoengeometry.com/e-tpms.html
6. ^ Alan L. Mackay, "Periodic minimal surfaces", Physica B+C, Volume 131, Issues 1–3, August 1985, Pages 300–305
7. ^ H. Terrones and A. L. Mackay, "Negatively curved graphite and triply periodic minimal surfaces", Journal of Mathematical Chemistry, Volume 15, Number 1 (1994), 183–195, DOI:10.1007/BF01277558
8. ^ W. H. Meeks. The theory of triply-periodic minimal surfaces. Indiana University Math. Journal, 39 (3):877{936, 1990.
9. ^ http://archive.msri.org/about/sgp/jim/geom/level/library/triper/index.html
10. ^ Jaemin Shin, Sungki Kim, Darae Jeong, Hyun Geun Lee, Dongsun Lee, Joong Yeon Lim, and Junseok Kim, Finite Element Analysis of Schwarz P Surface Pore Geometries for Tissue-Engineered Scaffolds, Mathematical Problems in Engineering, Volume 2012, Article ID 694194, doi:10.1155/2012/694194
11. ^ Paul J.F. Gandy, Djurdje Cvijović, Alan L. Mackay, Jacek Klinowski, Exact computation of the triply periodic D (`diamond') minimal surface, Chemical Physics Letters, Volume 314, Issues 5–6, 10 December 1999, Pages 543–551
|
__label__pos
| 0.794471 |
Automobile
Difference Between Diesel Cars and Petrol Cars
Difference Between Diesel Cars and Petrol Cars
Written by Autofot
Sponsored Links
The difference between diesel cars and petrol cars! The world of automobiles has a lot to offer. There are hundreds of different car models and brands that you can choose from, but you can also get a feel for how each type of engine works. When it comes to diesel cars vs petrol cars, there are many similarities between these two types of engines. However, there are some key differences as well. In this article we will discuss these differences in detail so that we can help you make an informed decision about which car is better for your needs.
Diesel cars are not meant for the thrill seekers who like to drive down the highway fast.
The diesel cars are not meant for the thrill seekers who like to drive down the highway fast. The diesel car has a different kind of engine which is meant to provide a lot of power at low RPMs, which makes them ideal for heavy duty vehicles that need a lot of torque.
On the other hand, petrol cars are suitable for people who enjoy long drives and speed.
On the other hand, petrol cars are suitable for people who enjoy long drives and speed. Petrol cars are more powerful than diesel cars as they can attain higher speeds. On the other hand, diesel engines produce more torque than petrol engines which result in better pickup but at a slower pace.
A petrol engine can go up to 200 km per hour whereas a diesel engine can only go up to 160 km per hour. The cost of running a car also differs between these two types of vehicles; it is estimated that a petrol car costs about $0.47 per kilometre whereas a diesel car costs about $0.6 per kilometre to run it on an average day with light traffic conditions
Diesel cars are all about mileage.
Diesel cars are all about mileage. Diesel engines are more fuel efficient than petrol engines because they produce more torque at lower RPMs, which means you don’t have to rev them as much before you get moving. This is especially helpful in traffic and when trying to find a parking spot—you won’t waste so much time waiting for your car to accelerate. In addition, diesel vehicles are generally more efficient at lower speeds and on highways, meaning that though you may spend more money on fuel up front, your overall driving costs will be less than if you were using a gasoline-powered vehicle.
Also keep in mind that if you live somewhere cold or plan on driving long distances during winter months (or both), then it’s probably worth considering purchasing a diesel car since diesel engines can run well even when temperatures drop down into the single digits; plus there’s no need for antifreeze or coolant!
High mileage is the biggest advantage of purchasing a diesel car over a petrol car.
The main advantage of owning a diesel car is the high mileage. This fuel efficiency rate is much higher than petrol cars and the reason for this is that diesels have a higher compression ratio, which means more power from less fuel. The low temperature combustion of diesel engines also contributes to their greater efficiency compared to petrol engines.
A lot of people who own diesel cars use them for long drives because they can go for longer without having to refuel. As well as being more economical when it comes to running costs, there are also fewer maintenance issues associated with them than petrol-powered vehicles because they don’t require regular servicing as often as petrol cars do (usually every oil change).
Petrol cars have higher maintenance costs than diesel cars.
The maintenance costs of petrol cars are higher than diesel cars. This is because they require more frequent servicing to keep them running in tip-top shape. The more frequent servicing means more money has to be spent on it and the car owner will have to spend more money on parts and services than someone who owns a diesel vehicle.
Petrol cars also tend to be more expensive to insure than diesel vehicles, but not by much. Both types of cars have very similar insurance premiums when it comes down to it, so there’s no real difference between buying one or the other if you’re worried about insurance costs.
Diesel engines are generally considered cleaner than petrol engines, because they produce less CO2 and other pollutants when driving long distances over short periods of time (like highway driving). However, many people still don’t like having higher emissions around them all day long while they drive their car around town!
One of the drawbacks of diesel cars is that they burn more fuel than petrol cars at lower speeds.
Diesel cars are generally more fuel efficient than petrol cars at higher speeds. This is because they have a lower internal resistance (more torque) and a higher power output, so they can accelerate faster. However, diesel cars are more expensive to buy and maintain than petrol cars.
One of the drawbacks of diesel cars is that they burn more fuel at lower speeds. This means that when you’re going slow (like in traffic), your car uses more fuel than it would if you were going fast or on open roads where there isn’t much friction between the tyres and road surface.
Petrol and diesel engines work differently from each other.
The way in which a petrol engine and diesel engine produces power is different. In a petrol engine, the pistons are driven by an electric motor which is powered by an alternator. The fuel used to ignite the air/oxygen mixture inside the cylinders of this type of engine is ignited through spark plugs.
In contrast, diesel engines do not require spark plugs to ignite their fuel because they use compression instead. Diesel engines rely on air pressure alone to compress their air-fuel mixture enough so that it will ignite when injected into combustion chambers at high speeds during compression strokes.
Proper care must be taken to maintain a diesel engine as it is less tolerant than petrol engine.
Proper care must be taken to maintain a diesel engine as it is less tolerant than petrol engine.
• Diesel engines have a higher compression ratio and hence they need more refined fuel.
• Diesel engines are more sensitive to engine oil quality. Using poor quality oil will result in sludge formation, which may cause damage to the engine and its parts slowly.
• Proper maintenance of your car’s diesel engine will keep it in good condition for longer period of time. Oil should be changed regularly (every 3000 miles or 6 months), because dirty oil can lead to sludge formation inside the engine that may cause damage over time. You must clean your air filter before every trip so that there is no build-up of dirt on it, which can restrict air flow into the combustion chamber resulting in poor performance of your car’s diesel motor
Diesel fuel is cheaper in most states and countries as compared to petrol.
Diesel fuel is cheaper in most states and countries as compared to petrol. Diesel cars are more efficient than petrol cars as a result of their lower fuel consumption.
Diesel is less expensive to produce than petrol, so it costs less at the pump. It also contains more energy per unit volume than gasoline, which makes it more cost-effective for vehicles that need high performance or long driving range. Because diesel engines burn their fuel more completely than gasoline engines do, they require fewer emissions control devices like catalytic converters (which convert harmful gases into less harmful ones). This means that using less-efficient diesel engines can still result in lower operating costs over time because they do not require additional equipment to achieve equivalent emissions levels. Read Also : The Difference Between Kia Shortage VS Honda CRV
For those who want great fuel efficiency and don’t mind an expensive purchase price, shopping for a diesel car ca n be a good decision.
For those who want great fuel efficiency and don’t mind an expensive purchase price, shopping for a diesel car can be a good decision. Diesel cars are more efficient than petrol cars in several ways. They have better acceleration than petrol vehicles on the road, but their top speeds are usually lower. When it comes to gas mileage though, diesels often get much better results than their gasoline counterparts do.
In addition to being more fuel efficient than other types of engines available today, diesel engines tend to last longer and be less expensive overall when it comes time for service or repairs on your vehicle. This is because they’re made from higher quality materials that require less maintenance over time as well as fewer parts that need replacement during regular maintenance visits (like oil changes). Read Also: The Difference Between Kia Shortage VS Honda CRV
Conclusion
In conclusion, diesel cars are more economical and can save you a lot of money on gas. You can also expect to drive longer distances without needing to refill your tank. However, if you like fast speeds and high performance, then maybe petrol vehicles are better suited for you.
Sponsored Links
About the author
Autofot
Autofot is a website that blogs on the importance of taking good care of our automobiles. Little things that are ignored matter the most, hence we try to educate car owners and other different auto owners on how to go about taking care of their cars with little or no cost.
Leave a Reply
|
__label__pos
| 0.800173 |
Marital conflict, separation, dissolution and court proceedings can be stressful and even traumatic. The arguments, verbal attacks, grief and feelings of loss or betrayal can be devastating. The result of that trauma, if not resolved, is often anxiety, overt stress, and resistance to interactions with one’s former spouse that trigger extreme anxiety and defensiveness. When there are children involved, interacting with one’s ex is necessary, but can be the source of ongoing feelings of traumatization, stress and anxiety, in turn creating more conflict, further escalating the negative feelings. None of these feelings and behaviors are conducive to productive co-parenting or communication, not to mention personal health and wellbeing. However, EMDR treatment can help.
EMDR stands for Eye Movement Desensitization and Reprocessing. It is a well researched and established technique that combines imagery, mindfulness, and cognitive techniques to meet the client’s treatment needs. EMDR therapy is often used in trauma counseling, the treatment of anxiety, and in the treatment of a number of other issues. The process of doing EMDR involves focus on a traumatic or disturbing memory while doing back and forth eye movements, listening to alternating tones, and/or feeling alternating vibrations in your hands. This process enables the brain to resolve emotional trauma and gain insight into the circumstance in a way that is often more effective than traditional talk therapy.
What can EMDR mean for someone struggling with divorce or post-divorce conflict?
• It can help to facilitate trauma processing.
• It can reduce undesirable feelings and responses to the triggers of the anxiety.
• It can help to improve one’s ability to maintain a more rational, productive and un-emotional mindset when interacting with their former partner.
• It can help to reduce anxiety.
• It can help to improve an overall sense of well-being.
In a nutshell, the trauma and bad feelings resulting from divorce can fuel conflict and ongoing resentment. By treating the trauma with EMDR, there is tremendous potential to change the dynamic of the interactions between former partners, and to reclaim a life of peace and dignity following divorce.
Click here for more information on Anxiety Treatment.
Tamra Hughes, MA, LPC https://www.greenwoodcounselingcenter.com
|
__label__pos
| 0.915038 |
MATLAB Answers
Continuously overwriting plot in a loop
84 views (last 30 days)
Hans123
Hans123 on 9 Apr 2019
Edited: Peter Cook on 9 Apr 2019
Dear MATLAB Gods,
I have a plot in a loop that changes after each iteration, currently I have a hold on...hold off line which plots the graphs on the same figure, rather I need it to overwrite the current plot after each iteration and I need to visually see this too - i.e. see each figure before being updated(animated line)
How can I achieve this, and to see the plot being updated should I have a pause line?
This is what I have
-Another issue I have is the text I have writes over it after each iteration. How can I fix this issue. My code is pasted below
matlabissue.png
for k=1:length(Mean_step)
y1=Mean(k);
x1=Mean_step(k);
% yy=cap(cap>475 & cap<485);
% y1=min(yy);
y2=max_cap./10;
x2=0;
b=y2;
aaa=(x1*y1)+(y1)*(x2*y2-x1*y1)/(y1-y2);
bbb=(x2*y2-x1*y1)/(y1-y2);
dist=0:1/3:1600;
model=aaa./(dist + bbb);
plot(dist,model,'r-','Linewidth',1.5)
txt1 = ['Y = ' num2str(aaa) ' / (X + (' num2str(bbb) '))'];
text(580, 700, txt1,'FontSize',8);
end
Accepted Answer
Peter Cook
Peter Cook on 9 Apr 2019
Edited: Peter Cook on 9 Apr 2019
Since dist is the same for each loop iteration, and you are only updating model, you should return a handle to the line object before you start looping and just update the YData property. Similarly, you should just do the same for the text object.
y1 = Mean(1);
x1 = Mean_step(1);
y2 = max_cap./10;
x2 = 0;
b = y2;
aaa = (x1*y1)+(y1)*(x2*y2-x1*y1)/(y1-y2);
bbb = (x2*y2-x1*y1)/(y1-y2);
dist = 0:1/3:1600;
model = aaa./(dist + bbb);
hp = plot(dist, model, 'r-', 'Linewidth', 1.5);
txt1 = ['Y = ' num2str(aaa) ' / (X + (' num2str(bbb) '))'];
ht = text(580, 700, txt1, 'FontSize', 8);
for k = 2:length(Mean_step)
y1=Mean(k);
x1=Mean_step(k);
aaa=(x1*y1)+(y1)*(x2*y2-x1*y1)/(y1-y2);
bbb=(x2*y2-x1*y1)/(y1-y2);
model = aaa./(dist + bbb);
hp.YData = model;
txt1 = ['Y = ' num2str(aaa) ' / (X + (' num2str(bbb) '))'];
ht.String = txt1;
drawnow()
end
2 Comments
Peter Cook
Peter Cook on 9 Apr 2019
Oops It should be hp.YData & ht.String. I'll edit above to reflect that.
Sign in to comment.
More Answers (0)
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!
|
__label__pos
| 0.869722 |
Find. Buy. Drive
CAR FROM JAPAN - Find best deals of used cars from reliable Japanese sellers
How Fast Can the Slowest Car In the World Go?
“How fast it can go?” – this is what comes into the mind of most people when shopping for a car. We all are fond of speed and wish to be in the shoes of Frank Martin (played by Jason Statham, The Transporter) or Dominic Toretto (played by Vin Diesel, The Fast and the Furious) at least for a day. But, what about driving the slowest car in the world?
A relaxed drive behind the wheel of a low-power car has its own unique benefits. You will have time to retrospect amid a busy lifestyle. Also, think of better fuel economy, less carbon in the environment, and avoiding the inevitable speeding tickets!
There are a handful of slow automobiles in the market. But, what is the slowest car of the bunch?
What Is the Slowest Car on Earth?
The slowest car in the world is the Peel P50, manufactured by Peel Engineering. It’s so slow that it has become a part of the history. Holding the Guinness World Records for the smallest car that has been ever made, it also crowns the title of being the slowest.
what is the slowest car on earth
It’s also the smallest car in the world.
Can you predict how fast does the slowest car in the world go? Only 28mph. The speed of the electric vehicle is deliberately limited to that range because Peel’s slogan has always been – almost cheaper than walking.
SEE MORE
The Specs of Peel P50 – The Slowest Car in the World
The Peel P50 came into the market in 1962. With 54 inches in length, the three-wheeler was and still is the world’s smallest car. The company discontinued it in 1969 but it brought it back into production in 2010. Currently, it manufactures a petrol and an electric version of the car.
The original edition has one door on the left side, a single widescreen wiper, and a headlight. There was no reverse gear but a rear handle to lug the car around by hand when needed. It was easy to tow as the weight was only 130 pounds.
The new version keeps the physical features almost similar but brings changes in the drivetrain, suspension, and steering. It also has a fully-functioning reverse gear.
The top speed of both versions is 28mph. however, the original engine was a 49cc moped unit generating 4.2 hp. The new petrol-run version generates slightly less power, 3.35 hp, with a 49cc four-stroke engine. It comes with a modern CVT instead of the old one’s three-speed transmission. The EV edition yields the same power with a moped electric motor and gelled-electrolyte batteries.
how fast does the slowest car in the world go
P50’s top speed is 28mph.
>> Finding a cheap used car in good conditions here <<
Should You Buy a Peel P50?… Even Just for Fun?
Purchasing the slowest car in the world does not seem very practical or useful, especially when it costs almost $16,000. You will get plenty of choices with better amenities and secondhand versions of many mid-range cars.
Still, the P50 has some major advances over a standard automobile. It offers a surprising 118 mpg (35 mpg for the EV), which makes it cheaper and a better replacement than walking. Also, this is the only car that you can park in your living room!
Leave A Reply
Your email address will not be published.
|
__label__pos
| 0.53713 |
Uninstall Elastic Agents from edge hostsedit
Uninstall on macOS, Linux, and Windowsedit
To uninstall Elastic Agent, run the uninstall command from the directory where Elastic Agent is running:
You must run this command as the root user.
sudo /Library/Elastic/Agent/elastic-agent uninstall
Follow the prompts to confirm that you want to uninstall Elastic Agent. The command stops and uninstalls any managed programs, such as Beats and Elastic Endpoint, before it stops and uninstalls Elastic Agent.
If you run into problems, refer to Troubleshoot common problems.
If you are using DEB or RPM, you can use the package manager to remove the installed package.
Remove Elastic Agent files manuallyedit
You might need to remove Elastic Agent files manually if there’s a failure during installation.
To remove Elastic Agent manually from your system:
1. Unenroll the agent if it’s managed by Fleet.
2. For standalone agents, back up any configuration files you want to preserve.
3. On your host, stop the agent. If any Elastic Agent-related processes are still running, stop them too.
Search for these processes and stop them if they’re still running: filebeat, metricbeat, fleet-server, and elastic-endpoint.
4. Manually remove the Elastic Agent files from your system. For example, if you’re running Elastic Agent on macOS, delete /Library/Elastic/Agent/*. Not sure where the files are installed? Refer to Installation layout.
5. If you’ve configured the Elastic Endpoint integration, also remove the files installed for endpoint protection. The directory structure is similar to Elastic Agent, for example, /Library/Elastic/Endpoint/*.
When you remove the Elastic Endpoint integration from a macOS host (10.13, 10.14, or 10.15), the Endpoint System Extension is left on disk intentionally. If you want to remove the extension, refer to the documentation for your operating sytem.
|
__label__pos
| 0.707207 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.