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Simultaneous pharmacogenetics-based population pharmacokinetic analysis of darunavir and ritonavir in HIV-infected patients. | BACKGROUND
Darunavir is a potent protease inhibitor of HIV. To enhance its pharmacokinetic profile, darunavir must be co-administered with ritonavir. There is wide inter-patient variability in darunavir pharmacokinetics among HIV-infected individuals, however. Darunavir is a known substrate for influx transporters, such as the 1A2 and the 1B1 members of the solute carrier organic anion transporter family (SLCO1A2, SLCO1B1), as well as for efflux transporters such as the multi-drug resistance protein 1 (MRP1).
OBJECTIVE
The aim of this study was to develop a semi-mechanistic population pharmacokinetic model for darunavir and ritonavir administered in HIV-infected adults. The desired model would incorporate patient characteristics and pharmacogenetic data contributing to variability in drug concentrations and also take into account the interaction between the two compounds.
METHODS
A population pharmacokinetic analysis was performed with 705 plasma samples from 75 Caucasian individuals receiving darunavir/ritonavir (600/100 mg twice daily) for at least 4 weeks. At least one full pharmacokinetic profile was obtained for each participant, and darunavir and ritonavir concentrations in plasma were determined by high performance liquid chromatography. Genotyping for 148 polymorphisms in genes coding for transporters or metabolizing enzymes was conducted by two methods: MALDI-TOF mass spectrometry and real-time polymerase chain reaction-based allelic discrimination. A population pharmacokinetic model was developed for darunavir and for ritonavir. The effect of single nucleotide polymorphisms on the post hoc individual pharmacokinetic parameters was first explored using graphic methods and regression analysis. Those covariates related to changes in darunavir or ritonavir pharmacokinetic parameters were then further evaluated using non-linear mixed effects modeling (NONMEM version VII).
RESULTS
Darunavir and ritonavir pharmacokinetics were best described by a two- and one-compartment model, respectively, both with first-order absorption and elimination. The darunavir peripheral volume of distribution decreased as α1-acid glycoprotein concentrations increased. Darunavir clearance was 12 % lower in patients with SLCO3A1 rs8027174 GT/TT genotypes, while homozygosity for the rs4294800 A allele was associated with 2.5-fold higher central volume of distribution. Body weight influenced ritonavir clearance. Ritonavir inhibited darunavir clearance following a maximum-effect model.
CONCLUSION
A population pharmacokinetic model to simultaneously describe the pharmacokinetics of darunavir and ritonavir was developed in HIV-infected patients. The model provides better understanding of the interaction between darunavir and ritonavir and suggests an association between SLCO3A1 polymorphisms and darunavir pharmacokinetics. Bayesian estimates of individual darunavir parameters and ritonavir may be useful to predict darunavir exposure. |
Online Speed Adaptation Using Supervised Learning for High-Speed, Off-Road Autonomous Driving | The mobile robotics community has traditionally addressed motion planning and navigation in terms of steering decisions. However, selecting the best speed is also important – beyond its relationship to stopping distance and lateral maneuverability. Consider a high-speed (35 mph) autonomous vehicle driving off-road through challenging desert terrain. The vehicle should drive slowly on terrain that poses substantial risk. However, it should not dawdle on safe terrain. In this paper we address one aspect of risk – shock to the vehicle. We present an algorithm for trading-off shock and speed in realtime and without human intervention. The trade-off is optimized using supervised learning to match human driving. The learning process is essential due to the discontinuous and spatially correlated nature of the control problem – classical techniques do not directly apply. We evaluate performance over hundreds of miles of autonomous driving, including performance during the 2005 DARPA Grand Challenge. This approach was the deciding factor in our vehicle’s speed for nearly 20% of the DARPA competition – more than any other constraint except the DARPA-imposed speed limits – and resulted in the fastest finishing time. |
A new fitness estimation strategy for particle swarm optimization | 24 25 26 27 28 29 30 31 32 33 34 35 Article history: Received 22 June 2011 Received in revised form 5 September 2012 Accepted 20 September 2012 Available online xxxx |
DeepNIS: Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering | Nonlinear electromagnetic (EM) inverse scattering is a quantitative and super-resolution imaging technique, in which more realistic interactions between the internal structure of scene and EM wavefield are taken into account in the imaging procedure, in contrast to conventional tomography. However, it poses important challenges arising from its intrinsic strong nonlinearity, ill-posedness, and expensive computational costs. To tackle these difficulties, we, for the first time to our best knowledge, exploit a connection between the deep neural network (DNN) architecture and the iterative method of nonlinear EM inverse scattering. This enables the development of a novel DNN-based methodology for nonlinear EM inverse problems (termed here DeepNIS). The proposed DeepNIS consists of a cascade of multilayer complex-valued residual convolutional neural network modules. We numerically and experimentally demonstrate that the DeepNIS outperforms remarkably conventional nonlinear inverse scattering methods in terms of both the image quality and computational time. We show that DeepNIS can learn a general model approximating the underlying EM inverse scattering system. It is expected that the DeepNIS will serve as powerful tool in treating highly nonlinear EM inverse scattering problems over different frequency bands, which are extremely hard and impractical to solve using conventional inverse scattering methods. |
DEEP-SEE: Joint Object Detection, Tracking and Recognition with Application to Visually Impaired Navigational Assistance | In this paper, we introduce the so-called DEEP-SEE framework that jointly exploits computer vision algorithms and deep convolutional neural networks (CNNs) to detect, track and recognize in real time objects encountered during navigation in the outdoor environment. A first feature concerns an object detection technique designed to localize both static and dynamic objects without any a priori knowledge about their position, type or shape. The methodological core of the proposed approach relies on a novel object tracking method based on two convolutional neural networks trained offline. The key principle consists of alternating between tracking using motion information and predicting the object location in time based on visual similarity. The validation of the tracking technique is performed on standard benchmark VOT datasets, and shows that the proposed approach returns state-of-the-art results while minimizing the computational complexity. Then, the DEEP-SEE framework is integrated into a novel assistive device, designed to improve cognition of VI people and to increase their safety when navigating in crowded urban scenes. The validation of our assistive device is performed on a video dataset with 30 elements acquired with the help of VI users. The proposed system shows high accuracy (>90%) and robustness (>90%) scores regardless on the scene dynamics. |
The role of strategic leadership in effective strategy implementation : Perceptions of South African strategic leaders | In the light of the identified problem, the primary objective of this study was to investigate the perceived role of strategic leadership in strategy implementation in South African organisations. The conclusion is that strategic leadership positively contributes to effective strategy implementation in South African organisations. |
Influence of Chemical Conditions on the Nanoporous Structure of Silicate Aerogels | Silica or various silicate aerogels can be characterized by highly porous, open cell, low density structures. The synthesis parameters influence the three-dimensional porous structures by modifying the kinetics and mechanism of hydrolysis and condensation processes. Numerous investigations have shown that the structure of porous materials can be tailored by variations in synthesis conditions (e.g., the type of precursors, catalyst, and surfactants; the ratio of water/precursor; the concentrations; the medium pH; and the solvent). The objectives of this review are to summarize and elucidate the effects of chemical conditions on the nanoporous structure of sol-gel derived silicate aerogels. |
Are Random Forests Better than Support Vector Machines for Microarray-Based Cancer Classification? | Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate decision support algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to-date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work however found that random forest classifiers outperform support vector machines. In the present paper we point to several biases of this prior work and conduct a new unbiased evaluation of the two algorithms. Our experiments using 18 diagnostic and prognostic datasets show that support vector machines outperform random forests often by a large margin. |
Hospital-based surveillance to estimate the burden of rotavirus gastroenteritis among European children younger than 5 years of age. | OBJECTIVES
Rotavirus is the leading cause of acute gastroenteritis requiring hospitalization in young children. Data on the burden of rotavirus gastroenteritis are needed to guide recommendations for rotavirus vaccine use. This study was undertaken to estimate the burden of rotavirus gastroenteritis in European children <5 years of age.
METHODS
This prospective, study was conducted in 12 hospitals in France, Germany, Italy, Spain, and the United Kingdom. A sample of all children aged <5 years presenting to emergency departments or hospitalized because of community-acquired acute gastroenteritis was enrolled for parental interview and stool collection. Acute gastroenteritis was defined as diarrhea (>/=3 loose stools per 24 hours) for <14 days. Rotavirus was detected by enzyme-linked immunosorbent assay and typed by reverse-transcriptase polymerase chain reaction.
RESULTS
Between February 2005 and August 2006, 3734 children with community-acquired acute gastroenteritis were recruited and retained for analysis (55.9% via the emergency department, 41.8% hospitalized). Of the 2928 community-acquired acute gastroenteritis cases for which stool samples were available, 43.4% were rotavirus-positive by enzyme-linked immunosorbent assay (32.8% emergency department, 56.2% hospitalized). Of these rotavirus gastroenteritis cases 80.9% occurred in children aged <2 years and 15.9% among infants aged <6 months. Acute gastroenteritis was more severe in rotavirus-positive subjects (Vesikari score >/= 11 in 53.3% compared with 31.0% of rotavirus-negative subjects). All 1271 rotavirus-positive strains were genotyped (G1P[8]: 40.3%; G9P[8]: 31.2%; G4P[8]: 13.5%; G3P[8]: 7.1%).
CONCLUSIONS
Rotavirus gastroenteritis places high demands on European health care systems, accounting for 56.2% of hospitalizations and 32.8% of emergency department visits because of community-acquired acute gastroenteritis in children aged <5 years. Most community-acquired rotavirus gastroenteritis occurs in children aged <2 years, and a high proportion occurs in infants aged <6 months. Cases were also observed among very young infants <2 months of age. Rotavirus vaccination is expected to have a major impact in reducing morbidity and the pressure on hospital services in Europe. |
Smartphone App Use Among Medical Providers in ACGME Training Programs | The past decade has witnessed the advent of the smartphone, a device armed with computing power, mobility and downloadable “apps,” that has become commonplace within the medical field as both a personal and professional tool. The popularity of medically-related apps suggests that physicians use mobile technology to assist with clinical decision making, yet usage patterns have never been quantified. A digital survey examining smartphone and associated app usage was administered via email to all ACGME training programs. Data regarding respondent specialty, level of training, use of smartphones, use of smartphone apps, desired apps, and commonly used apps were collected and analyzed. Greater than 85% of respondents used a smartphone, of which the iPhone was the most popular (56%). Over half of the respondents reported using apps in their clinical practice; the most commonly used app types were drug guides (79%), medical calculators (18%), coding and billing apps (4%) and pregnancy wheels (4%). The most frequently requested app types were textbook/reference materials (average response: 55%), classification/treatment algorithms (46%) and general medical knowledge (43%). The clinical use of smartphones and apps will likely continue to increase, and we have demonstrated an absence of high-quality and popular apps despite a strong desire among physicians and trainees. This information should be used to guide the development of future healthcare delivery systems; expanded app functionality is almost certain but reliability and ease of use will likely remain major factors in determining the successful integration of apps into clinical practice. |
Integrating context-awareness and multi-criteria decision making in educational learning | Recommender system is a well-known information system which can capture user tastes and produce item recommendations to the end users. Context-aware recommender systems (CARS) additionally take contexts (e.g., location, time, weather, etc) into consideration, and multi-criteria recommender systems (MCRS) utilize user preferences in multiple criteria to better generate recommendations. Both CARS and MCRS have been widely applied in the real-world applications, such as tourism, movies, music and dining. However, there are no existing research which exploits the methods to integrate them together, not to mention the contributions in the area of educational learning. In this paper, we make the first attempt to integrate context-awareness and multi-criteria decision making in the recommender systems by using the educational data as a case study. Our experimental results reveal that it is able to help produce more accurate recommendations by taking advantage of these two recommendation strategies. We also perform experiments on a tourism data set to demonstrate that the proposed methods can also be generalized to other domains. |
Diagnostic accuracy of the electromyography parameters associated with anterior knee pain in the diagnosis of patellofemoral pain syndrome. | OBJECTIVE
To assess the diagnostic accuracy of the surface electromyography (sEMG) parameters associated with referred anterior knee pain in diagnosing patellofemoral pain syndrome (PFPS).
DESIGN
Sensitivity and specificity analysis.
SETTING
Physical rehabilitation center and laboratory of biomechanics and motor control.
PARTICIPANTS
Pain-free subjects (n=29) and participants with PFPS (n=22) selected by convenience.
INTERVENTIONS
Not applicable.
MAIN OUTCOME MEASURE
The diagnostic accuracy was calculated for sEMG parameters' reliability, precision, and ability to differentiate participants with and without PFPS. The selected sEMG parameter associated with anterior knee pain was considered as an index test and was compared with the reference standard for the diagnosis of PFPS. Intraclass correlation coefficient, SEM, independent t tests, sensitivity, specificity, negative and positive likelihood ratios, and negative and positive predictive values were used for the statistical analysis.
RESULTS
The medium-frequency band (B2) parameter was reliable (intraclass correlation coefficient=.80-.90), precise (SEM=2.71-3.87 normalized unit), and able to differentiate participants with and without PFPS (P<.05). The association of B2 with anterior knee pain showed positive diagnostic accuracy values (specificity, .87; sensitivity, .70; negative likelihood ratio, .33; positive likelihood ratio, 5.63; negative predictive value, .72; and positive predictive value, .86).
CONCLUSIONS
The results provide evidence to support the use of EMG signals (B2-frequency band of 45-96 Hz) of the vastus lateralis and vastus medialis muscles with referred anterior knee pain in the diagnosis of PFPS. |
Variable Time Step Control for Six-Step Operation in Surface-Mounted Permanent Magnet Machine Drives | The six-step operation of surface-mounted permanent magnet machine drives in a flux weakening region has many advantages compared to the pulse width modulation mode, such as the reduced switching loss and fully utilized inverter output voltage. However, if the ratio of the sampling frequency to the fundamental frequency is low in fixed sampling system, the low-frequency oscillation in the current can be incurred in the six-step operation. The low-frequency current causes a system stability problem and reduces system efficiency due to an excessive heat and high power loss. Therefore, this paper proposes the variable time step controller for six-step operation. By updating an output voltage, sampling phase currents, and executing the digital controller synchronized with the variable sampling time, the turn on and off switch signals for six-step operation can be generated at the exact moment. As a result, the low-frequency oscillation in the phase current can be eliminated. In addition, the system transfer function of the proposed control method is discussed for the system stability and system dynamic analysis. The effectiveness of the proposed method is verified by the comparative simulation and experimental results. |
A Thesis for the Degree of Master Consumer Attitudes toward Location-based Advertising via Mobile Devices : An Empirical Study | Mobile advertising is evolving rapidly and becoming the key mobile data and revenue drivers of the mobile contents market. More powerful mobile devices have made possible the creation of better and richer mobile advertising. Moreover, the integration of location-aware technologies such as Cell Identification and GPS (Global Positioning Systems) into mobile devices has inspired the development of location-based advertising (LBA). As location-based services (LBS) have the potential to become the first realizable example of ubiquitous computing, business opportunities from these appear quite feasible. LBA can provide relevant, targeted, and timely advertising information to consumers at the point of need. The purpose of this study is to investigate consumer attitudes toward LBA, and the |
Training Neural Network Language Models on Very Large Corpora | During the last years there has been growing interest in using neural networks for language modeling. In contrast to the well known back-offn-gram language models, the neural network approach attempts to overcome the data sparseness problem by performing the estimation in a continuous space. This type of language model was mostly used for tasks for which only a very limited amount of in-domain training data is available. In this paper we present new algorithms to train a neural network language model on very large text corpora. This makes possible the use of the approach in domains where several hundreds of millions words of texts are available. The neural network language model is evaluated in a state-ofthe-art real-time continuous speech recognizer for French Broadcast News. Word error reductions of 0.5% absolute are reported using only a very limited amount of additional processing time. |
Learning with Local and Global Consistency | We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised learning is to design a classifying function which is sufficiently smooth with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. We present a simple algorithm to obtain such a smooth solution. Our method yields encouraging experimental results on a number of classification problems and demonstrates effective use of unlabeled data. |
Automatic text summarization of Wikipedia articles | The main objective of a text summarization system is to identify the most important information from the given text and present it to the end users. In this paper, Wikipedia articles are given as input to system and extractive text summarization is presented by identifying text features and scoring the sentences accordingly. The text is first pre-processed to tokenize the sentences and perform stemming operations. We then score the sentences using the different text features. Two novel approaches implemented are using the citations present in the text and identifying synonyms. These features along with the traditional methods are used to score the sentences. The scores are used to classify the sentence to be in the summary text or not with the help of a neural network. The user can provide what percentage of the original text should be in the summary. It is found that scoring the sentences based on citations gives the best results. |
Busbar design for SiC-based H-bridge PEBB using 1.7 kV, 400 a SiC MOSFETs operating at 100 kHz | This paper presents a systematic study of the busbar design and optimization for SiC-based H-bridge power electronics building block (PEBB) used in high-frequency and high-power applications. Step-by-step guidelines are presented in which the design considerations and analysis are given. This paper presents a double-sided busbar concept to create a compact PEBB design with improved thermal and switching performance, which result from having double-side cooling and symmetric minimized current commutation loop inductances, respectively. The proposed concept is verified experimentally by evaluating the high-speed switching performance of the PEBB up to 400 A. |
Clarification of the Essential of Life Cycle Cost upon Decision-Making Process: An Empirical Study in Building Projects | Life Cycle Cost (LCC) is one of the goals and key pillars of the construction management science because it comprises many of the functions and processes necessary, which assist organisations and agencies to achieve their goals. It has therefore become important to design and control assets during their whole life cycle, from the design and planning phase through to disposal phase. LCCA is aimed to improve the decision making system in the ownership of assets by taking into account all the cost elements including to the asset throughout its life. Current application of LCC approach is impractical during misunderstanding of the advantages of LCC. This main objective of this research is to show a different relationship between capital cost and long-term running costs. One hundred and thirty eight actual building projects in United Kingdom (UK) were used in order to achieve and measure the above-mentioned objective of the study. The result shown that LCC is one of the most significant tools should be considered on the decision making process. Keywords—Building projects, Capital cost, Life cycle cost, Maintenance costs, Operation costs. |
Sentiment-Specific Representation Learning for Document-Level Sentiment Analysis | In this paper, we propose a representation learning research framework for document-level sentiment analysis. Given a document as the input, document-level sentiment analysis aims to automatically classify its sentiment/opinion (such as thumbs up or thumbs down) based on the textural information. Despite the success of feature engineering in many previous studies, the hand-coded features do not well capture the semantics of texts. In this research, we argue that learning sentiment-specific semantic representations of documents is crucial for document-level sentiment analysis. We decompose the document semantics into four cascaded constitutes: (1) word representation, (2) sentence structure, (3) sentence composition and (4) document composition. Specifically, we learn sentiment-specific word representations, which simultaneously encode the contexts of words and the sentiment supervisions of texts into the continuous representation space. According to the principle of compositionality, we learn sentiment-specific sentence structures and sentence-level composition functions to produce the representation of each sentence based on the representations of the words it contains. The semantic representations of documents are obtained through document composition, which leverages the sentiment-sensitive discourse relations and sentence representations. |
Chapter 2 A Survey of Commodity Markets and Structural Models for Electricity Prices | The goal of this survey is to review the major idiosyncrasies of the commodity markets and the methods which have been proposed to handle them in spot and forward price models. We devote special attention to the most idiosyncratic of all: electricity markets. Following a discussion of traded instruments, market features, historical perspectives, recent developments and various modelling approaches, we focus on the important role of other energy prices and fundamental factors in setting the power price. In doing so, we present a detailed analysis of the structural approach for electricity, arguing for its merits over traditional reduced-form models. Building on several recent articles, we advocate a broad and flexible structural framework for spot prices, incorporating demand, capacity and fuel prices in several ways, while calculating closed-form forward prices throughout. |
Bonding effectiveness to different chemically pre-treated dental zirconia | The objective of this study was to evaluate the effect of different chemical pre-treatments on the bond durability to dental zirconia. Fully sintered IPS e.max ZirCAD (Ivoclar Vivadent) blocks were subjected to tribochemical silica sandblasting (CoJet, 3M ESPE). The zirconia samples were additionally pre-treated using one of four zirconia primers/adhesives (Clearfil Ceramic Primer, Kuraray Noritake; Monobond Plus, Ivoclar Vivadent; Scotchbond Universal, 3M ESPE; Z-PRIME Plus, Bisco). Finally, two identically pre-treated zirconia blocks were bonded together using composite cement (RelyX Ultimate, 3M ESPE). The specimens were trimmed at the interface to a cylindrical hourglass and stored in distilled water (7 days, 37 °C), after which they were randomly tested as is or subjected to mechanical ageing involving cyclic tensile stress (10 N, 10 Hz, 10,000 cycles). Subsequently, the micro-tensile bond strength was determined, and SEM fractographic analysis performed. Weibull analysis revealed the highest Weibull scale and shape parameters for the ‘Clearfil Ceramic Primer/mechanical ageing’ combination. Chemical pre-treatment of CoJet (3M ESPE) sandblasted zirconia using Clearfil Ceramic Primer (Kuraray Noritake) and Monobond Plus (Ivoclar Vivadent) revealed a significantly higher bond strength than when Scotchbond Universal (3M ESPE) and Z-PRIME Plus (Bisco) were used. After ageing, Clearfil Ceramic Primer (Kuraray Noritake) revealed the most stable bond durability. Combined mechanical/chemical pre-treatment, the latter with either Clearfil Ceramic Primer (Kuraray Noritake) or Monobond Plus (Ivoclar Vivadent), resulted in the most durable bond to zirconia. As a standard procedure to durably bond zirconia to tooth tissue, the application of a combined 10-methacryloyloxydecyl dihydrogen phosphate/silane ceramic primer to zirconia is clinically highly recommended. |
Lubrication oil condition monitoring and remaining useful life prediction with particle filtering | In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as the gearbox and means for lubrication oil condition monitoring and degradation detection. The wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil condition monitoring and remaining useful life prediction using particle filtering technique and commercially available online sensors. It first introduces the lubrication oil condition monitoring and degradation detection for wind turbines. Viscosity and dielectric constant are selected as the performance parameters to model the degradation of lubricants. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation study based on lab verified models is provided to demonstrate the effectiveness of the developed technique. |
RaBit EscAPE: a board game for computational thinking | Computational thinking (CT) is increasingly seen as a core literacy skill for the modern world on par with the longestablished skills of reading, writing, and arithmetic. To promote the learning of CT at a young age we capitalized on children's interest in play. We designed RabBit EscApe, a board game that challenges children, ages 610, to orient tangible, magnetized manipulatives to complete or create paths. We also ran an informal study to investigate the effectiveness of the game in fostering children's problemsolving capacity during collaborative game play. We used the results to inform our instructional interaction design that we think will better support the learning activities and help children hone the involved CT skills. Overall, we believe in the power of such games to challenge children to grow their understanding of CT in a focused and engaging activity. |
Pro Unity Game Development with C# | Unity am e Deelopm nt w ith C# Alan Thorn In Pro Unity Game Development with C#, Alan Thorn, author of Learn Unity for 2D` Game Development and experienced game developer, takes you through the complete C# workflow for developing a cross-platform first person shooter in Unity. C# is the most popular programming language for experienced Unity developers, helping them get the most out of what Unity offers. If you’re already using C# with Unity and you want to take the next step in becoming an experienced, professional-level game developer, this is the book you need. Whether you are a student, an indie developer, or a seasoned game dev professional, you’ll find helpful C# examples of how to build intelligent enemies, create event systems and GUIs, develop save-game states, and lots more. You’ll understand and apply powerful programming concepts such as singleton classes, component based design, resolution independence, delegates, and event driven programming. |
Application of Rhizobacteria for Induced Resistance | This article provides a review of experiments conducted over a six-year period to develop a biological control system for insect-transmitted diseases in vegetables based on induced systemic resistance (ISR) mediated by plant growth-promoting rhizobacteria (PGPR). Initial experiments investigated the factors involved in treatment with PGPR led to ISR to bacterial wilt disease in cucumber caused by Erwinia tracheiphila. Results demonstrated that PGPR-ISR against bacterial wilt and feeding by the cucumber beetle vectors of E. trachiphiela were associated with reduced concentrations of cucurbitacin, a secondary plant metabolite and powerful beetle feeding stimulant. In other experiments, PGPR induced resistance against bacterial wilt in the absence of the beetle vectors, suggesting that PGPR-ISR protects cucumber against bacterial wilt not only by reducing beetle feeding and transmission of the pathogen, but also through the induction of other plant defense mechanisms after the pathogen has been introduced into the plant. Additional greenhouse and field experiments are described in which PGPR strains were selected for ISR against cucumber mosaic virus (CMV) and tomato mottle virus (ToMoV). Although results varied from year to year, field-grown tomatoes treated with PGPR demonstrated a reduction in the development of disease symptoms, and often a reduction in the incidence of viral infection and an increase in tomato yield. Recent efforts on commercial development of PGPR are described in which biological preparations containing industrial formulated spores of PGPR plus chitosan were formulated and evaluated for use in a transplant soil mix system for developing plants that can withstand disease attack after transplanting in the field. |
Early detection of radiographic knee osteoarthritis using computer-aided analysis. | OBJECTIVE
To determine whether computer-based analysis can detect features predictive of osteoarthritis (OA) development in radiographically normal knees.
METHOD
A systematic computer-aided image analysis method weighted neighbor distances using a compound hierarchy of algorithms representing morphology (WND-CHARM) was used to analyze pairs of weight-bearing knee X-rays. Initial X-rays were all scored as normal Kellgren-Lawrence (KL) grade 0, and on follow-up approximately 20 years later either developed OA (defined as KL grade=2) or remained normal.
RESULTS
The computer-aided method predicted whether a knee would change from KL grade 0 to grade 3 with 72% accuracy (P<0.00001), and to grade 2 with 62% accuracy (P<0.01). Although a large part of the predictive signal comes from the image tiles that contained the joint, the region adjacent to the tibial spines provided the strongest predictive signal.
CONCLUSION
Radiographic features detectable using a computer-aided image analysis method can predict the future development of radiographic knee OA. |
The World-Wide Web: Quagmire or Gold Mine? | Skeptics believe the Web is too unstructured for Web mining to succeed. Indeed, data mining has been applied traditionally to databases, yet much of the information on the Web lies buried in documents designed for human consumption such as home pages or product catalogs. Furthermore, much of the information on the Web is presented in natural-language text with no machine-readable semantics; HTML annotations structure the display of Web pages, but provide little insight into their content. Some have advocated transforming the Web into a massive layered database to facilitate data mining [12], but the Web is too dynamic and chaotic to be tamed in this manner. Others have attempted to hand code site-specific “wrappers” that facilitate the extraction of information from individual Web resources (e.g., [8]). Hand coding is convenient but cannot keep up with the explosive growth of the Web. As an alternative, this article argues for the structured Web hypothesis: Information on the Web is sufficiently structured to facilitate effective Web mining. Examples of Web structure include linguistic and typographic conventions, HTML annotations (e.g., <title>), classes of semi-structured documents (e.g., product catalogs), Web indices and directories, and much more. To support the structured Web hypothesis, this article will survey preliminary Web mining successes and suggest directions for future work. Web mining may be organized into the following subtasks: |
VARIATION OF INDIVIDUALISM AND COLLECTIVISM WITHIN AND BETWEEN 20 COUNTRIES A Typological Analysis | With data from a 20-nation study (N = 2,533), the authors investigated how individual patterns of endorsement of individualist and collectivist attitudes are distributed within and across national contexts. A cluster analysis performed on individual scores of self-reliance (individualist dimension), group-oriented interdependence (collectivist dimension), and competitiveness (individualist or collectivist dimension) yielded a typology of four constrained combinations of these dimensions. Despite the prevalence of a typology group within a given country, variability was observed in all countries. Self-reliant non-competitors and interdependent non-competitors were prevalent among participants from Western nations, whereas self-reliant competitors and interdependent competitors were more common in non-Western countries. These findings emphasize the benefits for cross-cultural research of a typological approach based on combinations of individualist and collectivist dimensions. |
Digital Image Security : Fusion of Encryption , Steganography and Watermarking | Digital images are widely communicated over the internet. The security of digital images is an essential and challenging task on shared communication channel. Various techniques are used to secure the digital image, such as encryption, steganography and watermarking. These are the methods for the security of digital images to achieve security goals, i.e. confidentiality, integrity and availability (CIA). Individually, these procedures are not quite sufficient for the security of digital images. This paper presents a blended security technique using encryption, steganography and watermarking. It comprises of three key components: (1) the original image has been encrypted using large secret key by rotating pixel bits to right through XOR operation, (2) for steganography, encrypted image has been altered by least significant bits (LSBs) of the cover image and obtained stego image, then (3) stego image has been watermarked in the time domain and frequency domain to ensure the ownership. The proposed approach is efficient, simpler and secured; it provides significant security against threats and attacks. Keywords—Image security; Encryption; Steganography; Watermarking |
LSB: A Lightweight Scalable BlockChain for IoT Security and Privacy | BlockChain (BC) has attracted tremendous attention due to its immutable nature and the associated security and privacy benefits. BC has the potential to overcome security and privacy challenges of Internet of Things (IoT). However, BC is computationally expensive, has limited scalability and incurs significant bandwidth overheads and delays which are not suited to the IoT context. We propose a tiered Lightweight Scalable BC (LSB) that is optimized for IoT requirements. We explore LSB in a smart home setting as a representative example for broader IoT applications. Low resource devices in a smart home benefit from a centralized manager that establishes shared keys for communication and processes all incoming and outgoing requests. LSB achieves decentralization by forming an overlay network where high resource devices jointly manage a public BC that ensures end-to-end privacy and security. The overlay is organized as distinct clusters to reduce overheads and the cluster heads are responsible for managing the public BC. LSB incorporates several optimizations which include algorithms for lightweight consensus, distributed trust and throughput management. Qualitative arguments demonstrate that LSB is resilient to several security attacks. Extensive simulations show that LSB decreases packet overhead and delay and increases BC scalability compared to relevant baselines. |
Researching Assessment as Social Practice: Implications for Research Methodology. | Abstract Recent educational journals on both sides of the Atlantic have seen a resurgence of debate about the nature of educational research. As a contribution to these debates, this paper draws on theoretical and methodological ‘thinking tools’ of French sociologist Pierre Bourdieu. Specifically, the paper explores what Jenkins [Jenkins, R. (2002). Pierre Bourdieu . London: Routledge and Falmer] refers to as Bourdieu's “reflexive epistemological pluralism” and its implications for research into higher education, with a particular focus on assessment as social practice. This particular theoretical and methodological understanding is used to critically reflect on a study conducted in 2005 on the impact of a policy on anonymous examination marking which was implemented at the University of Cape Town in 2004. The study collected both quantitative data of student examination performance pre- and post-policy implementation, as well as interviews with course conveners. The paper argues that when viewed interdependently the data offers insight into some of the “principles of vision and division” [Bourdieu, P. (1996). The state nobility: Elite schools in the field of power . Cambridge: Polity Press] at work in assessors’ judgment-making process. The assessors’ deliberations expose ideological tensions between the dual challenges of equity and excellence in the context of a historically white liberal university under transformation. |
‘Every Catholic Child in a Catholic School’: Historical Resistance to State Schooling, Contemporary Private Competition and Student Achievement across Countries*: EVERY CATHOLIC CHILD IN A CATHOLIC SCHOOL | Nineteenth-Century Catholic doctrine strongly opposed state schooling. We show that countries with larger shares of Catholics in 1900 (but without a Catholic state religion) tend to have larger shares of privately operated schools even today. We use this historical pattern as a natural experiment to estimate the causal effect of contemporary private competition on student achievement in cross-country student-level analyses. Our results show that larger shares of privately operated schools lead to better student achievement in mathematics, science, and reading and to lower total education spending, even after controlling for current Catholic shares. JEL Code: I20, L33, N30, Z12. |
Image encryption using chaotic logistic map | In recent years, the chaos based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques. In this communication,wepropose a newapproach for image encryption basedon chaotic logisticmaps in order tomeet the requirements of the secure image transfer. In the proposed image encryption scheme, an external secret key of 80-bit and two chaotic logistic maps are employed. The initial conditions for the both logistic maps are derived using the external secret key by providing different weightage to all its bits. Further, in the proposed encryption process, eight different types of operations are used to encrypt the pixels of an image and which one of them will be used for a particular pixel is decided by the outcome of the logistic map. To make the cipher more robust against any attack, the secret key is modified after encrypting each block of sixteen pixels of the image. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for real-time image encryption and transmission. q 2006 Elsevier B.V. All rights reserved. |
M-invariance: towards privacy preserving re-publication of dynamic datasets | The previous literature of privacy preserving data publication has focused on performing "one-time" releases. Specifically, none of the existing solutions supports re-publication of the microdata, after it has been updated with insertions <u>and</u> deletions. This is a serious drawback, because currently a publisher cannot provide researchers with the most recent dataset continuously.
This paper remedies the drawback. First, we reveal the characteristics of the re-publication problem that invalidate the conventional approaches leveraging k-anonymity and l-diversity. Based on rigorous theoretical analysis, we develop a new generalization principle m-invariance that effectively limits the risk of privacy disclosure in re-publication. We accompany the principle with an algorithm, which computes privacy-guarded relations that permit retrieval of accurate aggregate information about the original microdata. Our theoretical results are confirmed by extensive experiments with real data. |
Design of a Reflection-Type Phase Shifter With Wide Relative Phase Shift and Constant Insertion Loss | reflection-type phase shifter with constant insertion loss over a wide relative phase-shift range is presented. This important feature is attributed to the salient integration of an impedance-transforming quadrature coupler with equalized series-resonated varactors. The impedance-transforming quadrature coupler is used to increase the maximal relative phase shift for a given varactor with a limited capacitance range. When the phase is tuned, the typical large insertion-loss variation of the phase shifter due to the varactor parasitic effect is minimized by shunting the series-resonated varactor with a resistor Rp. A set of closed-form equations for predicting the relative phase shift, insertion loss, and insertion-loss variation with respect to the quadrature coupler and varactor parameters is derived. Three phase shifters were implemented with a silicon varactor of a restricted capacitance range of Cv,min = 1.4 pF and Cv,max = 8 pF, wherein the parasitic resistance is close to 2 Omega. The measured insertion-loss variation is 0.1 dB over the relative phase-shift tuning range of 237deg at 2 GHz and the return losses are better than 20 dB, excellently agreeing with the theoretical and simulated results. |
Development and initial validation of a short three-dimensional inventory of character strengths | Character strength is described as a positive and organized pattern of emotions, thoughts, and behaviors. It serves as a schema that organizes categories of information toward the self, others, and the world, and provides the self-aware knowledge that facilitates the pursuit of goals, values, and ethical principles. Recent research has suggested that three reliable factors emerge from the measures of character strengths: caring, inquisitiveness, and self-control. The goal of this paper is to develop a psychometrically sound short measure of character strength. The questions were addressed in two studies using two independent samples: a cross-cultural (i.e., 518 Asians and 556 Westerners) sample, and a cross-population (i.e., 175 community participants and 171 inpatients) sample in China. Findings from the exploratory and confirmatory factor analysis suggested a cross-cultural three-factor model of character strength that could be measured by the Three-dimensional Inventory of Character Strengths (TICS). A multigroup confirmatory factor analysis further indicated that the number of factors and factor loadings was invariant in the medical and community samples. This result indicated that the brief inventory could be applied to a medical context. Internal reliability, content validity, and predictive validity were good, although the predictive validity of the three character strengths for psychological symptoms in the medical sample was more modest than that in the community sample. TICS is expected to be used for screening populations at risk, and a tool to aid mental health professionals in group-based treatment/intervention planning. It also should be noted that this short inventory should be used with caution for individual decision making. |
Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis | The frequently changing user preferences and/or item profiles have put essential importance on the dynamic modeling of users and items in personalized recommender systems. However, due to the insufficiency of per user/item records when splitting the already sparse data across time dimension, previous methods have to restrict the drifting purchasing patterns to pre-assumed distributions, and were hardly able to model them rather directly with, for example, time series analysis. Integrating content information helps to alleviate the problem in practical systems, but the domain-dependent content knowledge is expensive to obtain due to the large amount of manual efforts.
In this paper, we make use of the large volume of textual reviews for the automatic extraction of domain knowledge, namely, the explicit features/aspects in a specific product domain. We thus degrade the product-level modeling of user preferences, which suffers from the lack of data, to the feature-level modeling, which not only grants us the ability to predict user preferences through direct time series analysis, but also allows us to know the essence under the surface of product-level changes in purchasing patterns. Besides, the expanded feature space also helps to make cold-start recommendations for users with few purchasing records.
Technically, we develop the Fourier-assisted Auto-Regressive Integrated Moving Average (FARIMA) process to tackle with the year-long seasonal period of purchasing data to achieve daily-aware preference predictions, and we leverage the conditional opportunity models for daily-aware personalized recommendation. Extensive experimental results on real-world cosmetic purchasing data from a major e-commerce website (JD.com) in China verified both the effectiveness and efficiency of our approach. |
Comparison of patient and partner quality of life and health outcomes in the first year after an implantable cardioverter defibrillator (ICD) | Recovery following an implantable cardioverter defibrillator (ICD) impacts both the patient and partner, often in divergent ways. Patients may have had a cardiac arrest or cardiac arrhythmias, whereas partners may have to perform CPR and manage the ongoing challenges of heart disease therapy. Currently, support for post-ICD care focuses primarily on restoring patient functioning with few interventions available to partners who serve as primary support. This descriptive study examined and compared patterns of change for both patients and partners during the first year post-ICD implantation. For this longitudinal study, the sample included 42 of 55 (76.4 %) patient–partner dyads who participated in the ‘usual care’ group of a larger intervention RCT with patients following ICD implant for secondary prevention of cardiac arrest. Measures taken at across five time points (at hospital discharge and at 1, 3, 6 and 12 months follow up) tracked physical function (SF-12 PCS, symptoms); psychological adjustment (SF-12 MCS; State-Trait Anxiety Inventory; CES-D); relationship impact (Family Functioning, DOII; Mutuality and Interpersonal Sensitivity, MIS); and healthcare utilization (ED visits, outpatient visits, hospitalizations). Repeated measures analysis of variance was used to characterize and compare outcome trends for patients and partners across the first 12 months of recovery. Patients were 66.5 ± 11.3 (mean + SD) years old, predominately Caucasian male (91 %), with Charlson co-morbidities of 4.4 ± 2.4. Partners were 62.5 ± 11.1 years old, predominantly female (91 %) with Charlson co-morbidities of 2.9 ± 3.0. Patient versus partner differences were observed in the pattern of physical health (F = 10.8, p < 0.0001); patient physical health improved while partner health showed few changes. For partners compared to patients, anxiety, depression, and illness demands on family functioning tended to be higher. Patient mutuality was stable, while partner mutuality increased steadily (F = 2.5, p = 0.05). Patient sensitivity was highest at discharge and declined; partner sensitivity increased (F = 10.2, p < 0.0001) across the 12-month recovery. Outpatient visits for patients versus partners differed (F = 5.0, p = 0.008) due most likely to the number of required patient ICD visits. Total hospitalizations and ED visits were higher for patients versus partners, but not significantly. The findings highlight the potential reciprocal influences of patient and partner responses to the ICD experience on health outcomes. Warranted are new, sound and feasible strategies to counterbalance partner needs while simultaneously optimizing patient recovery outcomes. |
The Runner -- Recommender System of Workout and Nutrition for Runners | Recommender systems have been gaining popularity and appreciation over the past few years and they kept growing towards a semantic web. Internet users search for more and more facilities to get information and recommendations based on their preferences, experience and expectations. Nowadays, there are many recommender systems on the web for music, movies, diets, products, etc. Some of them use very efficient recommending techniques (ex. Amazon), while others are very simple, based on algorithms that do not always provide relevant or interesting recommendations. The solution we propose is a recommender system for running professionals and amateurs, which is able to provide information to users regarding the workout and the diet that best suits them, based on their profile information, preferences and declared purpose. The solution mixes a social dimension derived from an expanding community with expert knowledge defined within an ontology. Moreover, our model addresses adaptability in terms of personal profile, professional results and unfortunate events that might occur during workouts. |
Cross Sentence Inference for Process Knowledge | For AI systems to reason about real world situations, they need to recognize which processes are at play and which entities play key roles in them. Our goal is to extract this kind of rolebased knowledge about processes, from multiple sentence-level descriptions. This knowledge is hard to acquire; while semantic role labeling (SRL) systems can extract sentence level role information about individual mentions of a process, their results are often noisy and they do not attempt create a globally consistent characterization of a process. To overcome this, we extend standard within sentence joint inference to inference across multiple sentences. This cross sentence inference promotes role assignments that are compatible across different descriptions of the same process. When formulated as an Integer Linear Program, this leads to improvements over within-sentence inference by nearly 3% in F1. The resulting role-based knowledge is of high quality (with a F1 of nearly 82). |
Special issue on climate change impacts and mitigation on water quality and ecological health in aquatic systems. | The increase of carbon dioxide (CO2) and other greenhouse gases in the atmosphere is projected to cause climate change and global warming. The understanding of climate change impacts on water quality in aquatic systems (lakes, streams, reservoirs, and estuaries) is fundamental in providing better environmental strategies and mitigation methods to protect ecological health of aquatic systems. Water quality is a critical issue due to its direct influence on public health, biological integrity of natural resources, and the economy. The climate change leads to possible changes in local and global weather conditions, such as higher air temperatures and variable precipitation (both intensity and magnitude). Climate conditions affect hydrology in watersheds and then water quality conditions in aquatic systems. To make the projection on future climate, various General Circulation Models (GCMs) of the earth’s atmosphere have been developed. These GCM models simulate time series of climate parameters that can be used to create future climate scenarios for hydrological and water quality studies in watersheds and aquatic systems. |
Fostering User Engagement: Rhetorical Devices for Applause Generation Learnt from TED Talks | One problem that every presenter faces when delivering a public discourse is how to hold the listeners’ attentions or to keep them involved. Therefore, many studies in conversation analysis work on this issue and suggest qualitatively constructions that can effectively lead to audience’s applause. To investigate these proposals quantitatively, in this study we analyze the transcripts of 2,135 TED Talks, with a particular focus on the rhetorical devices that are used by the presenters for applause elicitation. Through conducting regression analysis, we identify and interpret 24 rhetorical devices as triggers of audience applauding. We further build models that can recognize applause-evoking sentences and conclude this work with potential implications. Introduction and Motivation Many academic studies have been devoted to the tasks of user engagement characterization. However, applause, as the most direct audience reaction, has till now not been fully investigated and understood. The audience do not just clap whenever they like, they do so only at certain points and are continuously looking for appropriate times when applause can possibly occur (Kuo, 2001). Having a deep understanding of audience’s applause is important because it will help the speakers to better design their speech with recognizable calls for conjoined response, and to make their presentation more appealing and engageable. Despite its importance, to date relatively limited work have been conducted on the topic of applause generation, except a few qualitative studies done by social psychologists. Atkinson (1984) first claimed that applause is closely synchronized with a number of actions on the part of the speakers, which he referred to as “rhetorical devices”. He identified three rhetorical devices that are effective in evoking applauses, including: contrasts, three-part lists, and projection of names. Heritage and Greatbatch (1986) found five other basic rhetorical devices, including: puzzlesolution, headline-punchline, combination, position taking This is a pre-print of an article appearing at ICWSM 2017. and pursuit. In addition, new categories were also identified in many recent studies, such as greetings, expressing appreciations, etc. (Bull and Feldman, 2011). To date, research on applause generation has been limited to the analysis of political speeches only. Besides, all of the aforementioned work were conducted using qualitative methods. Many critical questions, such as, What triggers the audience’s applause?, When do audience applaud?, etc., remain unanswered. To address these gaps, this work aims to identify the rhetorical devices for applause elicitation using data-driven methods. To this end, we propose two research questions: RQ1: What are the rhetorical devices that cause the audiences to applaud during a specific part of a speech? RQ2: To what extent the hypothesized rhetorical devices can be used to predict applause generation? To answer both questions, we crawl 2,135 TED talk transcripts and conduct quantitative analysis to investigate the factors that could trigger audience’s applause. We find that factors such as, gratitude expressions, phonetic structure, projection of names, emotion, etc., have significant effects on applause generation. These identified factors are later used to build machine learning models that can automatically identify applause-evoking segments. |
KidCAD: digitally remixing toys through tangible tools | Children have great facility in the physical world, and can skillfully model in clay and draw expressive illustrations. Traditional digital modeling tools have focused on mouse, keyboard and stylus input. These tools may be complicated and difficult for young users to easily and quickly create exciting designs. We seek to bring physical interaction to digital modeling, to allow users to use existing physical objects as tangible building blocks for new designs. We introduce KidCAD a digital clay interface for children to remix toys. KidCAD allows children to imprint 2.5D shapes from physical objects into their digital models by deforming a malleable gel input device, deForm. Users can mashup existing objects, edit and sculpt or draw new designs on a 2.5D canvas using physical objects, hands and tools as well as 2D touch gestures. We report on a preliminary user study with 13 children, ages 7 to 10, which provides feedback for our design and helps guide future work in tangible modeling for children. |
Improved Stochastic Gradient Descent Algorithm for SVM | In order to improve the efficiency and classification ability of Support vector machines (SVM) based on stochastic gradient descent algorithm, three algorithms of improved stochastic gradient descent (SGD) are used to solve support vector machine, which are Momentum, Nesterov accelerated gradient (NAG), RMSprop. The experimental results show that the algorithm based on RMSprop for solving the linear support vector machine has faster convergence speed and higher testing precision on five datasets (Alpha, Gamma, Delta, Mnist, Usps). |
Sex and the Workplace. | "With this clearly-written, thorough, and well-organized book, Gutek has provided a how-tomanual for managers and others who want to eliminate sexual harassment in the workplace."--Choice |
Epigram and the Theater | The entire Hellenistic vogue for epigrams on great literary gures of the past shares, as has been aptly remarked, “a common impulse with the great contemporary projects of literary classi cation, such as the Pinakes of Callimachus: namely the wish, on the one hand, to engage the past . . ., but also the need to assert control, to master a past that was viewed as unattainably, at times oppressively distinguished. That mastery, however, often involves wholesale abridgement, truncation, even evisceration.”1 Both aspects of this controlling relationship constitute forms of appropriation. Even the most sympathetic forms of epigrammatic re-enactment of literary history in miniaturized “pen-portraits” challenged the monumental sepulchral portraits that, in most cases, the pseudo-epitaphs on poets affected to describe; they also challenged the complexity of the deceased author’s achievements through the reductio ad unum of a pithy appraisal, adapting to the brevity of epigram a literary judgment of the sort that might otherwise be realized as an expanded essay. Needless to say, however, abridgement, truncation, and evisceration were forms of more invasive, and even deforming, mastery. At least three of the most important epigrammatists of the third and second centuries, Callimachus, Asclepiades and Dioscorides, dealt with dramatic authors (whether contemporary or of generations past), as well as theatrical activity in general, in a way that primarily stresses their self-asserting mastery. Other epigrammatists broach the topic with the gentle tone of admiration and celebration that most often characterized epigrams written for other poets of the past—for the third century B.C. we have at least ten epigrams of this kind celebrating dramatic authors.2 Drama, though, was certainly not the genre most |
neuralnet: Training of Neural Networks | Artificial neural networks are applied in many situations. neuralnet is built to train multi-layer perceptrons in the context of regression analyses, i.e. to approximate functional relationships between covariates and response variables. Thus, neural networks are used as extensions of generalized linear models. neuralnet is a very flexible package. The backpropagation algorithm and three versions of resilient backpropagation are implemented and it provides a custom-choice of activation and error function. An arbitrary number of covariates and response variables as well as of hidden layers can theoretically be included. The paper gives a brief introduction to multilayer perceptrons and resilient backpropagation and demonstrates the application of neuralnet using the data set infert, which is contained in the R distribution. |
Automatic Detection of Malware-Generated Domains with Recurrent Neural Models | Modern malware families often rely on domain-generation algorithms (DGAs) to determine rendezvous points to their command-and-control server. Traditional defence strategies (such as blacklisting domains or IP addresses) are inadequate against such techniques due to the large and continuously changing list of domains produced by these algorithms. This paper demonstrates that a machine learning approach based on recurrent neural networks is able to detect domain names generated by DGAs with high precision. The neural models are estimated on a large training set of domains generated by various malwares. Experimental results show that this data-driven approach can detect malware-generated domain names with a F1 score of 0.971. To put it differently, the model can automatically detect 93 % of malware-generated domain names for a false positive rate of 1:100. |
Integration and evaluation of intrusion detection for CoAP in smart city applications | The Constrained Application Protocol (CoAP) is a promising candidate for future smart city applications that run on resource-constrained devices. However, additional security means are mandatory to cope with the high security requirements of smart city applications. We present a framework to evaluate lightweight intrusion detection techniques for CoAP applications. This framework combines an OMNeT++ simulation with C/C++ application code that also runs on real hardware. As the result of our work, we used our framework to evaluate intrusion detection techniques for a smart public transport application that uses CoAP. Our first evaluations indicate that a hybrid IDS approach is a favorable choice for smart city applications. |
NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter | This paper describes our NIHRIO system for SemEval-2018 Task 3 “Irony detection in English tweets.” We propose to use a simple neural network architecture of Multilayer Perceptron with various types of input features including: lexical, syntactic, semantic and polarity features. Our system achieves very high performance in both subtasks of binary and multi-class irony detection in tweets. In particular, we rank third using the accuracy metric and fifth using the F1 metric. Our code is available at: https://github.com/ NIHRIO/IronyDetectionInTwitter. |
Unsupervised Extraction of Attributes and Their Values from Product Description | This paper describes an unsupervised method for extracting product attributes and their values from an e-commerce product page. Previously, distant supervision has been applied for this task, but it is not applicable in domains where no reliable knowledge base (KB) is available. Instead, the proposed method automatically creates a KB from tables and itemizations embedded in the product’s pages. This KB is applied to annotate the pages automatically and the annotated corpus is used to train a model for the extraction. Because of the incompleteness of the KB, the annotated corpus is not as accurate as a manually annotated one. Our method tries to filter out sentences that are likely to include problematic annotations based on statistical measures and morpheme patterns induced from the entries in the KB. The experimental results show that the performance of our method achieves an average F score of approximately 58.2 points and that filters can improve the performance. |
CAD of Waveguide Low-Pass Filters for Satellite Applications | Corrugated-waveguide low-pass filters are analysed by successive reflection coefficient transformations. The discontinuities are modelled by waveguide equivalent circuits, including interaction of higher order modes. The filter response is determined by TEm0-transfer functions (m=1,2...) each of which can be calculated independently. Implementing this method in an optimization routine allows complete computer-aided design according to given specifications. |
W-band sub-harmonic mixer in hybrid technology | A sub-harmonic mixer in hybrid technology is reported in this paper. Flip chip Schottky diode pairs are used as nonlinear elements. A novel solutions with split stubs is used for improving both W-band and LO signals' confinement near diode terminals. The design is validated with mixer structures of good dynamic range and similar conversion loss over 90–100 GHz band. |
Analysis and Design of Energy Regenerative Snubber for Transformer Isolated Converters | An energy regenerative passive snubber for transformer isolated converters is proposed. The snubber is implemented on the transformer's primary and secondary windings. The proposed snubber significantly reduces the voltage spike across the switch caused by the transformer's primary inductance upon switch turn-off and facilitates the fast ramping up of the transformer secondary current. In addition, the proposed snubber provides lossless zero voltage turn off and zero current turn on conditions for the power switch. Experimental example of a flyback converter has shown measured efficiency exceeding 90%. This paper describes the principle of operation and presents approximate theoretical analysis and design guidelines of the proposed snubber. Simulation and experimental results are also reported. The proposed energy regenerating snubber is best suited for flyback and SEPIC converters and can also be adapted to other transformer isolated topologies. |
Short circuit current comparison of DFIG during symmetrical faults with different wind speeds | The short-circuit current calculation of any equipment in the power system is very important for selection of appropriate relay characteristics and circuit breaker for the protection of the system. The power system is undergoing changes because of large scale penetration of renewable energy sources in the conventional system. Major renewable sources which are included in the power system are wind energy and solar energy sources. The wind energy is supplied by wind turbine generators of various types. Type III generators i.e. Doubly Fed Induction Generator (DFIG) is the most common types of generator employed offering different behavior compared to conventionally employed synchronous generators. In this paper; the short circuit current contribution of DFIG is calculated analytically and the same is validated by PSCAD/EMTDC software under various wind speeds and by considering certain voltage drops of the generator output. |
Friedreich's ataxia and scoliosis: the experience at two institutions. | PURPOSE
Friedreich's ataxia is a genetically transmitted, progressive spinocerebellar degenerative disease characterized by ataxia. The purpose of this study is to evaluate the demographics, progression, nonoperative, and operative treatment of spinal deformities in patients with Friedreich's ataxia at 2 tertiary pediatric orthopaedic hospitals.
METHODS
After institutional review board approval, chart review of Friedreich's ataxia patients identified those having scoliosis. Demographic data, length of follow-up, brace treatment, operative treatment, and complications were determined. Radiographic review was also performed.
RESULTS
Seventy-seven patients were identified as having Friedreich's ataxia, of which 49 (63%) were diagnosed with scoliosis. Twenty-seven were male; 22 were female. Mean age at diagnosis of scoliosis was 12.8 years (4.9-20 years). Mean follow-up was 3.7 years (0-13 years). There were 16 (33%) double major curves, with 8 (22%) of the thoracic curves being left sided. Hyperkyphosis was present in 12 (24.5%).Twenty-four (49%) of patients progressed > or =6 degrees. Using a chi-square analysis, there was no association, with a curve magnitude of 10 degrees before the age of 10 years and progression of the curve (P = 0.4386). Ten (20%) patients were treated in braces, with average progression in brace of 15 (0-44) degrees. Sixteen (33%) patients were treated with spinal fusion (15 posterior spinal fusion and 1 anterior spinal fusion). Thirteen (81%) of 16 patients who underwent operative intervention were wheelchair dependent. Somatosensory evoked potentials monitoring was attempted in 11 patients but was effective in only 1. Immediate postoperative correction averaged 49% in the thoracic spine (24%-87%) and 51% in the lumbar spine (26%-82%). This correction decreased to 39% in the thoracic (-22% to 85 %) and 30% in the lumbar spine (-35% to 82%) at final follow-up. The average postoperative follow-up was 3.6 years (2-6.5). One patient (6.2%) developed an infection and was the only patient who underwent reoperation.
CONCLUSIONS
Scoliosis in Friedreich's ataxia is common (63%). Curve patterns are variable and do not necessarily resemble idiopathic curves. Although few patients were braced, results were poor. Fusion using modern segmental constructs was effective in creating substantial intraoperative correction and maintaining correction postoperatively. SSEP monitoring was usually ineffective, so preparation for a wake-up test is recommended.
SIGNIFICANCE
Patients with Friedreich's ataxia need to be carefully screened for scoliosis and counseled about the high rate of surgical fusion. Using modern implants, correction can be achieved and maintained. |
Effects of leucine and its metabolite β-hydroxy-β-methylbutyrate on human skeletal muscle protein metabolism | Maintenance of skeletal muscle mass is contingent upon the dynamic equilibrium (fasted losses-fed gains) in protein turnover. Of all nutrients, the single amino acid leucine (Leu) possesses the most marked anabolic characteristics in acting as a trigger element for the initiation of protein synthesis. While the mechanisms by which Leu is 'sensed' have been the subject of great scrutiny, as a branched-chain amino acid, Leu can be catabolized within muscle, thus posing the possibility that metabolites of Leu could be involved in mediating the anabolic effect(s) of Leu. Our objective was to measure muscle protein anabolism in response to Leu and its metabolite HMB. Using [1,2-(13)C2]Leu and [(2)H5]phenylalanine tracers, and GC-MS/GC-C-IRMS we studied the effect of HMB or Leu alone on MPS (by tracer incorporation into myofibrils), and for HMB we also measured muscle proteolysis (by arteriovenous (A-V) dilution). Orally consumed 3.42 g free-acid (FA-HMB) HMB (providing 2.42 g of pure HMB) exhibited rapid bioavailability in plasma and muscle and, similarly to 3.42 g Leu, stimulated muscle protein synthesis (MPS; HMB +70% vs. Leu +110%). While HMB and Leu both increased anabolic signalling (mechanistic target of rapamycin; mTOR), this was more pronounced with Leu (i.e. p70S6K1 signalling 90 min vs. 30 min for HMB). HMB consumption also attenuated muscle protein breakdown (MPB; -57%) in an insulin-independent manner. We conclude that exogenous HMB induces acute muscle anabolism (increased MPS and reduced MPB) albeit perhaps via distinct, and/or additional mechanism(s) to Leu. |
Knowledge exchange processes in organizations and policy arenas: a narrative systematic review of the literature. | CONTEXT
This article presents the main results from a large-scale analytical systematic review on knowledge exchange interventions at the organizational and policymaking levels. The review integrated two broad traditions, one roughly focused on the use of social science research results and the other focused on policymaking and lobbying processes.
METHODS
Data collection was done using systematic snowball sampling. First, we used prospective snowballing to identify all documents citing any of a set of thirty-three seminal papers. This process identified 4,102 documents, 102 of which were retained for in-depth analysis. The bibliographies of these 102 documents were merged and used to identify retrospectively all articles cited five times or more and all books cited seven times or more. All together, 205 documents were analyzed. To develop an integrated model, the data were synthesized using an analytical approach.
FINDINGS
This article developed integrated conceptualizations of the forms of collective knowledge exchange systems, the nature of the knowledge exchanged, and the definition of collective-level use. This literature synthesis is organized around three dimensions of context: level of polarization (politics), cost-sharing equilibrium (economics), and institutionalized structures of communication (social structuring).
CONCLUSIONS
The model developed here suggests that research is unlikely to provide context-independent evidence for the intrinsic efficacy of knowledge exchange strategies. To design a knowledge exchange intervention to maximize knowledge use, a detailed analysis of the context could use the kind of framework developed here. |
Breast cancer sentinel lymph node mapping using near-infrared guided indocyanine green in comparison with blue dye | Near-infrared (NIR) fluorescence imaging using indocyanine green (ICG) was considered to have the potential to improve sentinel lymph node (SLN) mapping in breast cancer. Herein, we performed a randomized clinical trial to evaluate the effectiveness of ICG fluorescence imaging compared with blue dye imaging in SLN navigation surgery. We also analyzed lymph drainage pathways to identify targets for sentinel lymph node biopsy (SLNB). Finally, 68 consecutive patients diagnosed with breast cancer and who underwent SLNB between November 2010 and September 2012 were enrolled in the study. The cases were randomly grouped into either the ICG fluorescence or blue dye group, with 36 in the ICG fluorescence group and 32 in the blue dye group. Levels I and II axillary dissection was performed in all cases after SLNB. A single lymph drainage pathway was detected in 21 of 36 (58.3 %) patients, and multiple lymph drainage pathways were detected in 15 of 36 (41.7 %) cases. The detection rate of SLNB was higher by ICG fluorescence than by blue dye (97.2 vs. 81.3 %, p < 0.05), as 3.6 SLNs were detected on average in the ICG fluorescence group compared to 2.1 in the blue dye group. However, the sensitivity and false-negative rate were similar in the two groups. In conclusion, ICG fluorescence was superior to blue dye for the identification of the SLN. |
Salinity of deep groundwater in California: Water quantity, quality, and protection. | Deep groundwater aquifers are poorly characterized but could yield important sources of water in California and elsewhere. Deep aquifers have been developed for oil and gas extraction, and this activity has created both valuable data and risks to groundwater quality. Assessing groundwater quantity and quality requires baseline data and a monitoring framework for evaluating impacts. We analyze 938 chemical, geological, and depth data points from 360 oil/gas fields across eight counties in California and depth data from 34,392 oil and gas wells. By expanding previous groundwater volume estimates from depths of 305 m to 3,000 m in California's Central Valley, an important agricultural region with growing groundwater demands, fresh [<3,000 ppm total dissolved solids (TDS)] groundwater volume is almost tripled to 2,700 km(3), most of it found shallower than 1,000 m. The 3,000-m depth zone also provides 3,900 km(3) of fresh and saline water, not previously estimated, that can be categorized as underground sources of drinking water (USDWs; <10,000 ppm TDS). Up to 19% and 35% of oil/gas activities have occurred directly in freshwater zones and USDWs, respectively, in the eight counties. Deeper activities, such as wastewater injection, may also pose a potential threat to groundwater, especially USDWs. Our findings indicate that California's Central Valley alone has close to three times the volume of fresh groundwater and four times the volume of USDWs than previous estimates suggest. Therefore, efforts to monitor and protect deeper, saline groundwater resources are needed in California and beyond. |
Honey Bee Behavior Based Load Balancing of Tasks in Cloud Computing | Cloud computing has recently emerging technology getting popular day by day having wide scope in future. Cloud computing is defined as a large scale distributed computing paradigm that is driven by economics of scale in which a pool of abstracted virtualized energetically. The number of users in cloud computing is growing exponentially. Large number of user requests tries to designate the resources for many applications which along with to high load not far afield off from cloud server. Whenever certain VMs are overloaded then no more tasks should be send to overloaded virtual machine if under loaded virtual machines are available. For optimize solution and better response time the load has to be balanced among overloaded and under loaded virtual machines. In this paper, an algorithm is proposed named honey bee behavior based load balancing (HBB-LB), which targets to achieve well balanced load across virtual machine. The experimental results show that the algorithm has many advantages over existing algorithms. There is improvement in average execution time and reduction in waiting time of tasks. The paper also describes briefly about other existing load balancing approaches. |
Galois groups of Schubert problems via homotopy computation | Numerical homotopy continuation of solutions to polynomial equations is the foundation for numerical algebraic geometry, whose development has been driven by applications of mathematics. We use numerical homotopy continuation to investigate the problem in pure mathematics of determining Galois groups in the Schubert calculus. For example, we show by direct computation that the Galois group of the Schubert problem of 3-planes in C^8 meeting 15 fixed 5-planes non-trivially is the full symmetric group S_6006. |
Person-centered therapy and solution-focused brief therapy: An integration of present and future awareness. | The authors propose an integration of person-centered therapy, with its focus on the here and now of client awareness of self, and solution-focused therapy, with its future-oriented techniques that also raise awareness of client potentials. Although the two theories hold different assumptions regarding the therapist's role in facilitating client change, it is suggested that solution-focused techniques are often compatible for use within a person-centered approach. Further, solution-focused activities may facilitate the journey of becoming self-aware within the person-centered tradition. This article reviews the two theories, clarifying the similarities and differences. To illustrate the potential integration of the approaches, several types of solution-focused strategies are offered through a clinical example. (PsycINFO Database Record (c) 2011 APA, all rights reserved). |
SANE: System for Fine Grained Named Entity Typing on Textual Data | Assignment of fine-grained types to named entities is gaining popularity as one of the major Information Extraction tasks due to its applications in several areas of Natural Language Processing. Existing systems use huge knowledge bases to improve the accuracy of the fine-grained types. We designed and developed SANE, a system that uses Wikipedia categories to fine grain the type of the named entities recognized in the textual data. The main contribution of this work is building a named entity typing system without the use of knowledge bases. Through our experiments, 1) we establish the usefulness of Wikipedia categories to Named Entity Typing and 2) we show that SANE’s performance is on par with the state-ofthe-art. |
Variants of travelling salesman problem: A survey | The Travelling Salesman Problem (TSP) is a well-known NP-hard problem exceedingly studied in the fields of operations research and computer science. In TSP, a salesman wants to visit each of a set of cities exactly once and return to the starting city with minimal distance travelled. The significance of the TSP is that it can be pertained on many practical applications in real life scenario. But, it is not always possible to apply TSP for all the real world applications because of different constraints and also variations of TSP might be desired in such real-life scenarios. Therefore, several variants of TSP have been proposed to manage with the application specific constraints. In this work, a comprehensive study on various categories of TSP variants such as Profit Based, Time Windows based, Maximal Based and Kinetic Based has been studied with respect to the problem formulation and applications. |
Correlation between radiographic severity of knee osteoarthritis and future disease progression. Results from a 3-year prospective, placebo-controlled study evaluating the effect of glucosamine sulfate. | OBJECTIVE
To investigate the relationship between baseline radiographic severity of knee osteoarthritis (OA) and the importance of long-term joint space narrowing.
DESIGN
Sub-analysis from a three-year randomized, placebo-controlled, prospective study, of 212 patients with knee OA, recruited in an osteoarthritic outpatient clinic and having been part of a study evaluating the effect of glucosamine sulfate on symptom and structure modification in knee OA.
MATERIAL AND METHODS
Measurements of mean joint space width (JSW), assessed by a computer-assisted method, were performed at baseline and after 3 years, on weightbearing anteroposterior knee radiographs.
RESULTS
In the placebo group, baseline JSW was significantly and negatively correlated with the joint space narrowing observed after 3 years (r=-0.34, P=0.003). In the lowest quartile of baseline mean JSW (<4.5mm), the JSW increased after 3 years by (mean (S.D.)) 3.8% (23.8) in the placebo group and 6.2% (17.5) in the glucosamine sulfate group. The difference between the two groups in these patients with the most severe OA at baseline was not statistically significant (P=0.70). In the highest quartile of baseline mean JSW (>6.2mm), a joint space narrowing of 14.9% (17.9) occurred in the placebo group after 3 years while patients from the glucosamine sulfate group only experienced a narrowing of 6.0% (15.1). Patients with the most severe OA at baseline had a RR of 0.42 (0.17-1.01) to experience a 0.5mm joint space narrowing over 3 years, compared to those with the less affected joint. In patients with mild OA, i.e. in the highest quartile of baseline mean JSW, glucosamine sulfate use was associated with a trend (P=0.10) towards a significant reduction in joint space narrowing.
CONCLUSION
These results suggest that patients with the less severe radiographic knee OA will experience, over 3 years, the most dramatic disease progression in terms of joint space narrowing. Such patients may be particularly responsive to structure-modifying drugs. |
Designing epoxy insulators in SF6-filled DC-GIL with simulations of ionic conduction and surface charging | The problem of surface charge accumulation on gas-insulator interface is one of the critical factors for the development of DC Gas Insulated transmission Lines (GIL). In order to solve this problem, researchers have proposed a variety of mathematical models in which the volume conductivity of SF6 was assumed to be constant for calculating the distribution of surface charge. However, the conductivity of SF6 was inconstant, affected by electric field strength. In this paper, a gas model is developed, taking into account the generation, recombination and motion of charge carriers in SF6 of DC-GIL. The surface charge density and the electric field distribution on the insulator surface under DC voltage were simulated. Afterwards, the electric conduction through the volume of the insulator was proved to be the dominating accumulation mechanism. In order to improve the insulation performance, the influence of practical insulator shape on the electric field distribution in DC-GIL was studied. Three different shapes of insulator which were disc insulator, conical insulator and obtuse conical insulator were introduced and compared. The simulation results indicate the obtuse conical insulator was the most suitable configuration for DC-GIL. |
Family functioning in the context of parental bipolar disorder: associations with offspring age, sex, and psychopathology. | Previous research has shown that families with a parent who has bipolar disorder (BD) may experience family functioning difficulties. However, the association between family functioning and psychopathology among offspring of parents with BD, and offspring characteristics that may moderate this association, remains poorly understood. This study examined the cross-sectional associations between family functioning (cohesion, expressiveness, and conflict) and psychopathology in 117 offspring (ages 5-18) of 75 parents with BD. We also examined whether age and sex differences moderated these associations. We measured offspring psychopathology by examining current dimensional symptoms and DSM-IV emotional and behavioral disorders. Correlational analyses indicated that higher family conflict and lower cohesion were associated with higher internalizing and externalizing symptoms in offspring. Lower family cohesion was also associated with current offspring mood disorders. Moderation analyses indicated, first, that the link between lower family cohesion and internalizing symptoms was stronger for younger offspring compared to older offspring. Second, higher family conflict and current mood disorder were associated in younger males but not in older males or in females. Results remained the same after controlling for parental anxiety or substance use disorder comorbidity. Our study highlights the importance of accounting for family functioning when working with offspring at risk for BD, while also recognizing that the connections between family functioning and offspring outcomes are complex and differ based on offspring sex and developmental stage. |
A longitudinal analysis of sex differences in math and spatial skills in primary school age children. | We report on a longitudinal study designed to assess possible sex differences in math achievement, math ability, and math-related tasks during the primary school age years. Participants included over 200 children from one public school district. Annual assessments included measures of math ability, math calculation achievement scores, rapid naming and decoding tasks, visual perception tests, visual motor tasks, and reading skills. During select years of the study we also administered tests of counting and math facts skills. We examined whether girls or boys were overrepresented among the bottom or top performers on any of these tasks, relative to their peers, and whether growth rates or predictors of math-related skills differed for boys and girls. Our findings support the notion that sex differences in math are minimal or nonexistent on standardized psychometric tests routinely given in assessments of primary school age children. There was no persistent finding suggesting a male or female advantage in math performance overall, during any single year of the study, or in any one area of math or spatial skills. Growth rates for all skills, and early correlates of later math performance, were comparable for boys and girls. The findings fail to support either persistent or emerging sex differences on non-specialized math ability measures during the primary school age years. |
Is FDG PET a better imaging tool than somatostatin receptor scintigraphy in patients with relapsing multiple myeloma? | PURPOSE
Osseous involvement defined by lytic bone lesions is shown by skeletal survey in multiple myeloma (MM). This technique has limitations because it detects only lesions with more than 30% trabecular bone loss. In addition, lesions persist after chemotherapy, thereby limiting its usefulness at relapsing disease. Alternative techniques to detect new bone lesions are somatostatin receptor scintigraphy (SRS) and 18F-fluordeoxyglucose (FDG) PET so far predominantly studied in patients with newly diagnosed MM. Malignant plasma cells can have a high expression of somatostatin receptors and an elevated metabolic activity. Therefore, these techniques might be useful in patients with relapsing MM because they are not hampered by preexisting skeletal defects. The purpose of this study was to demonstrate which technique is most optimal to detect skeletal lesions in patients with relapsing MM.
METHOD
In patients with relapsing MM (n = 21), 3 separate methods were used (skeletal survey, SRS, and FDG PET) for detecting new skeletal lesions.
RESULTS
Of all patients, 55% had new lesions on the skeletal survey [mean (SD), 1.45 (1.76); range, 0-5], 52% had new SRS lesions [mean (SD), 1.43 (0.38); range, 0-5], and 71% demonstrated new lesions on the FDG PET-scan [mean (SD), 4.05 (0.9); range, 0-12]. The lesions on skeletal survey and SRS corresponded with FDG PET. The number of lesions was higher with the FDG PET versus that with SRS (P = 0.01) and with FDG PET versus that with skeletal survey (P = 0.01).
CONCLUSIONS
The results demonstrate that FDG PET is more valuable than skeletal survey and SRS to detect disease activity in relapsing MM. |
Genetic variability and heritability of grain yield components and grain mineral concentration in India's pearl millet (Pennisetum glaucum (L) R. Br.) accessions | Pearl millet (Pennisetum glaucum (L.) R. Br.) is an important cereal in semi-arid tropics in Africa and India. Conventionally, millet has good amounts of grain minerals compared to other cereals. Estimation of genetic parameters would be useful in developing appropriate breeding and selection strategies. The present study was conducted to evaluate the local pearl millet accessions to assess the magnitude of variability and to understand the heritable component of variation present in the yield and nutritional characters. A field trial was laid under the complete randomized block design (RCBD) with three replications; observation were recorded on eight morphological and seven nutritional characters (as detailed in material and methods) including anti-nutritional properties such as phytate content among 61 genotypes collected from millet collection. The phenotypic co-efficient of variation (PCV) was greater than genotypic co-efficient of variation (GCV) for all the characters studied; this shows the influence of environmental factors on the characters. The phosphorus content had expressed the highest phenotypic and genotypic variances (845.30 and 772.08, respectively). The magnitudes of phenotypic and genotypic variances were low for the 100 grain weight (0.001 for both phenotypic and genotypic variance). High estimates of genetic co-efficient of variation, heritability and genetic advance were exhibited by iron and crude fat content. Heritability is a measure of possible genetic advancement under selection. High heritability was observed for all the traits under study except seed weight which had moderate heritability. High value of heritability coupled with high genetic advance as per cent of mean were recorded for number of productive tillers, crude protein, crude fat, phytate, phosphorus, calcium, iron and zinc content, indicating the important role of additive gene action for the expression of these characters. Therefore, selection based on these characters could bring about desired improvement in yield as well as nutritional quality of pearl millet cultivars. |
A comparison of carotenoids, retinoids, and tocopherols in the serum and buccal mucosa of chronic cigarette smokers versus nonsmokers. | BACKGROUND
Cigarette smoking, a major risk factor for oropharyngeal cancer, is reported to alter oral levels of carotenoids and tocopherols. Such effects may be important because these nutrients, as well as retinoids, are putative chemoprotective agents.
OBJECTIVES
To determine whether chronic smoking is associated with altered concentrations of these nutrients in serum and buccal mucosa; to distinguish whether such effects are ascribable to diet; and to determine whether oral concentrations of these nutrients correlate with a putative biomarker of oral cancer risk.
METHODS
Serum and buccal mucosal cells (BMC) were analyzed for these nutrients and for BMC micronuclei in smokers (n = 35) and nonsmokers (n = 21).
RESULTS
General linear regression with adjustments for dietary intake showed that smokers possess lower serum concentrations of beta- and alpha-carotene, cryptoxanthin, lutein, and zeaxanthin (P </= 0.01) and a significantly higher serum gamma-tocopherol (P = 0.03). In BMCs, smokers had significantly lower concentrations of beta- and alpha-carotene, lycopene, and alpha-tocopherol (P < 0.05) but significantly higher gamma-tocopherol (P < 0.01). Among nonsmokers, many serum carotenoid concentrations correlated with concentrations of the corresponding nutrient in BMCs whereas no such correlations existed among smokers. BMC micronuclei did not correlate with the oral concentration of any micronutrient.
CONCLUSIONS
Chronic cigarette smokers have lower concentrations of many dietary antioxidants in serum and BMCs compared with nonsmokers, an effect which is not entirely ascribable to diet. Nevertheless, the lack of concordance between oral concentrations of these nutrients and genetic damage in the BMCs of smokers does not support a protective role for these nutrients in oral carcinogenesis. |
Finite-Element-Based Multiobjective Design Optimization Procedure of Interior Permanent Magnet Synchronous Motors for Wide Constant-Power Region Operation | This paper proposes the design optimization procedure of three-phase interior permanent magnet (IPM) synchronous motors with minimum weight, maximum power output, and suitability for wide constant-power region operation. The particular rotor geometry of the IPM synchronous motor and the presence of several variables and constraints make the design problem very complicated. The authors propose to combine an accurate finite-element analysis with a multiobjective optimization procedure using a new algorithm belonging to the class of controlled random search algorithms. The optimization procedure has been employed to design two IPM motors for industrial application and a city electrical scooter. A prototype has been realized and tested. The comparison between the predicted and measured performances shows the reliability of the simulation results and the effectiveness, versatility, and robustness of the proposed procedure. |
CMOS Image Sensors With Multi-Bucket Pixels for Computational Photography | This paper presents new image sensors with multi- bucket pixels that enable time-multiplexed exposure, an alter- native imaging approach. This approach deals nicely with scene motion, and greatly improves high dynamic range imaging, structured light illumination, motion corrected photography, etc. To implement an in-pixel memory or a bucket, the new image sensors incorporate the virtual phase CCD concept into a standard 4-transistor CMOS imager pixel. This design allows us to create a multi-bucket pixel which is compact, scalable, and supports true correlated double sampling to cancel kTC noise. Two image sensors with dual and quad-bucket pixels have been designed and fabricated. The dual-bucket sensor consists of a 640H × 576V array of 5.0 μm pixel in 0.11 μm CMOS technology while the quad-bucket sensor comprises 640H × 512V array of 5.6 μm pixel in 0.13 μm CMOS technology. Some computational photography applications were implemented using the two sensors to demonstrate their values in eliminating artifacts that currently plague computational photography. |
Fear Conditioning in Humans The Influence of Awareness and Autonomic Arousal on Functional Neuroanatomy | The degree to which perceptual awareness of threat stimuli and bodily states of arousal modulates neural activity associated with fear conditioning is unknown. We used functional magnetic neuroimaging (fMRI) to study healthy subjects and patients with peripheral autonomic denervation to examine how the expression of conditioning-related activity is modulated by stimulus awareness and autonomic arousal. In controls, enhanced amygdala activity was evident during conditioning to both "seen" (unmasked) and "unseen" (backward masked) stimuli, whereas insula activity was modulated by perceptual awareness of a threat stimulus. Absent peripheral autonomic arousal, in patients with autonomic denervation, was associated with decreased conditioning-related activity in insula and amygdala. The findings indicate that the expression of conditioning-related neural activity is modulated by both awareness and representations of bodily states of autonomic arousal. |
A Robust Digital Image Watermarking Scheme Using Hybrid DWT-DCT-SVD Technique | Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. As watermarking is identified as a major technology to achieve copyright protection, the relevant literature includes several distinct approaches for embedding data into a multimedia element (primarily images, audio, and video). In this paper, we present a hybrid watermarking scheme based on Discrete Wavelet Transform – Discrete Cosine Transform – Singular Value Decomposition (DWT-DCT-SVD). Robustness is achieved by taking DCT of the DWT coefficients of the HL band of DWT. After applying DCT we map the DCT coefficients in a zig – zag order into four quadrants and apply the SVD to each quadrant. These four quadrants represent frequency bands from the lowest to the highest. The singular values in each quadrant are then modified by the singular values of the DWT-DCT transformed visual watermark. We show that embedding data in lowest frequencies is resistant to most of the attacks and some attacks are resistant to other frequency bands. |
Characteristics of knowledge, people engaged in knowledge transfer and knowledge stickiness: evidence from Chinese R&D team | Characteristics of knowledge, people engaged in knowledge transfer, and knowledge stickiness: evidence from Chinese R & D team Huang Huan, Ma Yongyuan, Zhang Sheng, Dou Qinchao, Article information: To cite this document: Huang Huan, Ma Yongyuan, Zhang Sheng, Dou Qinchao, "Characteristics of knowledge, people engaged in knowledge transfer, and knowledge stickiness: evidence from Chinese R & D team", Journal of Knowledge Management, https:// doi.org/10.1108/JKM-02-2017-0054 Permanent link to this document: https://doi.org/10.1108/JKM-02-2017-0054 |
Early sport specialisation, does it lead to long-term problems? | SPORT SPECIALISATION: FRIEND OR FOE? Sports participation is increasing in the USA (US population 313 million inhabitants) and in Icelandic (population 320 thousand inhabitants) adolescents, it is estimated that 35–45 million youth 6–18 years of age participate in some form of organised or recreational athletics. 2 However, sports specialisation including year-round sport-specific training, participation on multiple teams of the same sport and focused participation in a single sport is purported to be increasing in frequency in preadolescent children across the world. There are several factors that contribute to the desire of young athletes to specialise in a single sport including the pursuit of scholarships or professional contracts, being labelled as talented by parents or coaches, retailing industry and media reports. A 2006 New York Times article notes “A growing number of coaches, parents, and children believe that the best way to produce superior young athletes is to have them play only one sport from an early age, and to play it virtually year-round.” Despite this increase in global sports participation, physical fitness levels of children and adults are declining and more people around the globe are becoming obese and physically inactive. The efforts to specialise youth sports underlie the effects of reduced general opportunity for all children to participate in a diverse year-round sports season, and possibly leading to lost development of lifetime sports skills. These lost opportunities for ‘fun’ focused physical activity during youth likely contribute to deficits in current and long-term physical activity and health. Physical inactivity is a major factor in obesity and other comorbidities that are driving up healthcare costs. We hypothesise that sports specialisation in preadolescent children may lead to reduced overall comprehensive motor skill development, increased injury risk and therefore could contribute to reduced lifetime physical activity. Specialisation in a single sport was perceived to have begun in Eastern Europe with activities such as gymnastics, swimming, diving and figure skating. Most Olympic sports have selection processes that attempt to identify future champions and initiate specialised training-often before the prospect finishes elementary school. The relative success of these programmes has led to early talent identification and developmental programmes focusing on a single sport, globally. The glamour of a professional contract is too good to pass up and more athletes are turning professional at a younger age. Unfortunately, most athletes and their parents fail to realise that only 0.2–0.5% of USA high school athletes ever make it to the professional level. |
E-fashion Product Discovery via Deep Text Parsing | Transforming unstructured text into structured form is important for fashion e-commerce platforms that ingest tens of thousands of fashion products every day. While most of the e-commerce product extraction research focuses on extracting a single product from the product title using known keywords, little attention has been paid to discovering potentially multiple products present in the listing along with their respective relevant attributes, and leveraging the entire title and description text for this purpose. We fill this gap and propose a novel composition of sequence labeling and multi-task learning as an end-to-end trainable deep neural architecture. We systematically evaluate our approach on one of the largest tagged datasets in fashion e-commerce consisting of 25K listings labeled at word-level. Given 23 labels, we discover label-values with F1 score of 92.2%. When applied to 2M listings, we discovered 2.6M fashion items and 9.5M attribute values. |
The Neuroprotective Efficacy of Cell-Penetrating Peptides TAT, Penetratin, Arg-9, and Pep-1 in Glutamic Acid, Kainic Acid, and In Vitro Ischemia Injury Models Using Primary Cortical Neuronal Cultures | Cell-penetrating peptides (CPPs) are small peptides (typically 5–25 amino acids), which are used to facilitate the delivery of normally non-permeable cargos such as other peptides, proteins, nucleic acids, or drugs into cells. However, several recent studies have demonstrated that the TAT CPP has neuroprotective properties. Therefore, in this study, we assessed the TAT and three other CPPs (penetratin, Arg-9, Pep-1) for their neuroprotective properties in cortical neuronal cultures following exposure to glutamic acid, kainic acid, or in vitro ischemia (oxygen–glucose deprivation). Arg-9, penetratin, and TAT-D displayed consistent and high level neuroprotective activity in both the glutamic acid (IC50: 0.78, 3.4, 13.9 μM) and kainic acid (IC50: 0.81, 2.0, 6.2 μM) injury models, while Pep-1 was ineffective. The TAT-D isoform displayed similar efficacy to the TAT-L isoform in the glutamic acid model. Interestingly, Arg-9 was the only CPP that displayed efficacy when washed-out prior to glutamic acid exposure. Neuroprotection following in vitro ischemia was more variable with all peptides providing some level of neuroprotection (IC50; Arg-9: 6.0 μM, TAT-D: 7.1 μM, penetratin/Pep-1: >10 μM). The positive control peptides JNKI-1D-TAT (JNK inhibitory peptide) and/or PYC36L-TAT (AP-1 inhibitory peptide) were neuroprotective in all models. Finally, in a post-glutamic acid treatment experiment, Arg-9 was highly effective when added immediately after, and mildly effective when added 15 min post-insult, while the JNKI-1D-TAT control peptide was ineffective when added post-insult. These findings demonstrate that different CPPs have the ability to inhibit neurodamaging events/pathways associated with excitotoxic and ischemic injuries. More importantly, they highlight the need to interpret neuroprotection studies when using CPPs as delivery agents with caution. On a positive note, the cytoprotective properties of CPPs suggests they are ideal carrier molecules to deliver neuroprotective drugs to the CNS following injury and/or potential neuroprotectants in their own right. |
Study of Heritability and Genetic Variability among Different Plant and Fruit Characters of Tomato (Solanum lycopersicon L.) | Heritability, genetic advance, genetic advanced as percentage over mean and genetic variability among different plant and fruit characters of thirty tomato genotypes were studied at Hudeiba Research Station (ARC) during the winter of 200708. Analysis of variance showed significant variation among the genotypes for all tested characters. Fruit weight showed the highest genotypic and phenotypic variance (1642.9 and 1779.1) whereas fruit yield per plant showed the lowest ones (0.17 and 0.39). High genotypic variance was observed for most of the characters indicating more contribution of genetic component for the total variation. Genotypic coefficients of variations (GCV) and phenotypic coefficient of variation (PCV) were highest for fruit weight (0.4885 and 0.4905) whereas the lowest ones were for days to 50% flowering (0.0552 and 0.0665). Higher GCV and PVC were recorded for most of the characters indicating higher magnitude of variability for these characters. The highest heritability was recorded on plant height (97%), while the lowest was for fruit yield per plant (43%). High heritability (broad senses) estimates were observed for all the tested characters indicating that these characters are controlled by additive genes action which is very useful in selection. |
Incorporating Structural Alignment Biases into an Attentional Neural Translation Model | Neural encoder-decoder models of machine translation have achieved impressive results, rivalling traditional translation models. However their modelling formulation is overly simplistic, and omits several key inductive biases built into traditional models. In this paper we extend the attentional neural translation model to include structural biases from word based alignment models, including positional bias, Markov conditioning, fertility and agreement over translation directions. We show improvements over a baseline attentional model and standard phrase-based model over several language pairs, evaluating on difficult languages in a low resource setting. |
Change in condom and other barrier method use during and after an HIV prevention trial in Zimbabwe | BACKGROUND
We examined the use of male condoms and the diaphragm following completion of a clinical trial of the diaphragm's HIV prevention effectiveness. In the trial, called Methods for Improving Reproductive Health in Africa (MIRA), women were randomized to a diaphragm group (diaphragm, gel and condoms) or a condom-only control group. At trial exit, all women were offered the diaphragm and condoms.
METHODS
Our sample consisted of 801 Zimbabwean MIRA participants who completed one post-trial visit (median lapse: nine months; range two to 20 months). We assessed condom, diaphragm and any barrier method use at last sex act at enrolment, final MIRA and post-trial visits. We used multivariable random effects logistic regression to examine changes in method use between these three time points.
RESULTS AND DISCUSSION
In the condom group, condom use decreased from 86% at the final trial visit to 67% post trial (AOR = 0.20; 95% CI: 0.12 to 0.33). In the diaphragm group, condom use was 61% at the final trial visit, and did not decrease significantly post trial (AOR = 0.77; 95% CI: 0.55 to 1.09), while diaphragm use decreased from 79% to 50% post trial (AOR = 0.18; 95% CI: 0.12 to 0.28). Condom use significantly decreased between the enrolment and post-trial visits in both groups. Use of any barrier method was similar in both groups: it significantly decreased between the final trial and the post-trial visits, but did not change between enrolment and the post-trial visits.
CONCLUSIONS
High condom use levels achieved during the trial were not sustained post trial in the condom group. Post-trial diaphragm use remained relatively high in the diaphragm group (given its unknown effectiveness), but was very low in the condom group. Introducing "new" methods for HIV prevention may require time and user skills before they get adopted. Our findings underscore the potential benefit of providing a mix of methods to women as it may encourage more protected acts. |
Haemostatic and inflammatory responses to blood flow-restricted exercise in patients with ischaemic heart disease: a pilot study. | Low-intensity resistance exercise can effectively induce muscle hypertrophy and increases in strength when combined with moderate blood flow restriction (BFR). As this type of exercise does not require lifting heavy weights, it might be a feasible method of cardiac rehabilitation, in which resistance exercise has been recommended to be included. Although previous studies with healthy subjects showed relative safety of BFR exercise, we cannot exclude the possibility of unfavourable effects in patients with cardiovascular disease. We therefore aimed to investigate haemostatic and inflammatory responses to BFR exercise in patients with ischaemic heart disease (IHD). Nine stable patients with IHD who were not taking anticoagulant drugs performed four sets of knee extension exercise at an intensity of 20% one-repetition maximum (1RM) either with or without BFR. Blood samples were taken before, immediately after and 1 h after the exercise session and analysed for noradrenaline, D-dimer, fibrinogen/fibrin degradation products (FDP) and high-sensitive C-reactive protein (hsCRP). Plasma noradrenaline concentration increased after the exercise, and the increase was significantly larger after the exercise with BFR than without BFR. On the other hand, increases in concentrations of plasma D-dimer and serum hsCRP were independent of the condition. However, increases in D-dimer and hsCRP were no longer observed after plasma volume correction, suggesting that hemoconcentration was responsible for these increases. Plasma FDP concentration did not change after the exercise. These results suggest that applying BFR during low-intensity resistance exercise does not affect exercise-induced haemostatic and inflammatory responses in stable IHD patients. |
Neural Temporal Relation Extraction | We experiment with neural architectures for temporal relation extraction and establish a new state-of-the-art for several scenarios. We find that neural models with only tokens as input outperform state-ofthe-art hand-engineered feature-based models, that convolutional neural networks outperform LSTM models, and that encoding relation arguments with XML tags outperforms a traditional position-based encoding. |
Community Informatics and Sustainability: Why Social Capital Matters | This paper adopts a holistic approach to explain why social capital matters for effective implementation, widespread uptake, greater social inclusion, and the sustainability of CI initiatives. It describes a theoretical framework drawn from diffusion of innovation, community development and social capital theories. The framework emphasises the interplay between physical infrastructure (including hard technologies and their location in the community), soft technologies (including capacity building, education, training and awareness raising), social infrastructure (including local networks and community organisations) and social capital (including trust and reciprocity, strong sense of community, shared vision, and outcomes from participation in local and external networks). |
Wafer Resection of the Distal Ulna. | The wafer procedure is an effective treatment for ulnar impaction syndrome, which decompresses the ulnocarpal junction through a limited open or arthroscopic approach. In comparison with other common decompressive procedures, the wafer procedure does not require bone healing or internal fixation and also provides excellent exposure of the proximal surface of the triangular fibrocartilage complex. Results of the wafer procedure have been good and few complications have been reported. |
Wideband Circularly Polarized Antenna With Gain Improvement | A wideband circularly polarized antenna with coaxial balun feed, using a broadband 90° hybrid feed network, is proposed. By introducing a narrow patch connecting the pair of bowtie dipoles as an entity that increases the effective radiation area, the proposed antenna delivers a higher gain than that of the conventional dual-fed-type circularly polarized antenna. It can achieve a measured impedance bandwidth for VSWR ≤ 1.5 of 57% and a 3-dB axial-ratio bandwidth of 51.8%. Moreover, the antenna has stable peak circularly polarized gain better than 9.0 dBi ranging from 1.1 to 1.6 GHz. For the entire half-power beamwidth, the axial ratio can be kept below 3 dB. |
Parkinson's Disease Therapeutics: New Developments and Challenges Since the Introduction of Levodopa | The demonstration that dopamine loss is the key pathological feature of Parkinson's disease (PD), and the subsequent introduction of levodopa have revolutionalized the field of PD therapeutics. This review will discuss the significant progress that has been made in the development of new pharmacological and surgical tools to treat PD motor symptoms since this major breakthrough in the 1960s. However, we will also highlight some of the challenges the field of PD therapeutics has been struggling with during the past decades. The lack of neuroprotective therapies and the limited treatment strategies for the nonmotor symptoms of the disease (ie, cognitive impairments, autonomic dysfunctions, psychiatric disorders, etc.) are among the most pressing issues to be addressed in the years to come. It appears that the combination of early PD nonmotor symptoms with imaging of the nigrostriatal dopaminergic system offers a promising path toward the identification of PD biomarkers, which, once characterized, will set the stage for efficient use of neuroprotective agents that could slow down and alter the course of the disease. |
3D shape regression for real-time facial animation | We present a real-time performance-driven facial animation system based on 3D shape regression. In this system, the 3D positions of facial landmark points are inferred by a regressor from 2D video frames of an ordinary web camera. From these 3D points, the pose and expressions of the face are recovered by fitting a user-specific blendshape model to them. The main technical contribution of this work is the 3D regression algorithm that learns an accurate, user-specific face alignment model from an easily acquired set of training data, generated from images of the user performing a sequence of predefined facial poses and expressions. Experiments show that our system can accurately recover 3D face shapes even for fast motions, non-frontal faces, and exaggerated expressions. In addition, some capacity to handle partial occlusions and changing lighting conditions is demonstrated. |
Simulated Car Racing Championship: Competition Software Manual | This manual describes the competition software for the Simulated Car Racing Championship, an international competition held at major conferences in the field of Evolutionary Computation and in the field of Computational Intelligence and Games. It provides an overview of the architecture, the instructions to install the software and to run the simple drivers provided in the package, the description of the sensors and the actuators. |
The population genetics of the Jewish people | Adherents to the Jewish faith have resided in numerous geographic locations over the course of three millennia. Progressively more detailed population genetic analysis carried out independently by multiple research groups over the past two decades has revealed a pattern for the population genetic architecture of contemporary Jews descendant from globally dispersed Diaspora communities. This pattern is consistent with a major, but variable component of shared Near East ancestry, together with variable degrees of admixture and introgression from the corresponding host Diaspora populations. By combining analysis of monoallelic markers with recent genome-wide variation analysis of simple tandem repeats, copy number variations, and single-nucleotide polymorphisms at high density, it has been possible to determine the relative contribution of sex-specific migration and introgression to map founder events and to suggest demographic histories corresponding to western and eastern Diaspora migrations, as well as subsequent microevolutionary events. These patterns have been congruous with the inferences of many, but not of all historians using more traditional tools such as archeology, archival records, linguistics, comparative analysis of religious narrative, liturgy and practices. Importantly, the population genetic architecture of Jews helps to explain the observed patterns of health and disease-relevant mutations and phenotypes which continue to be carefully studied and catalogued, and represent an important resource for human medical genetics research. The current review attempts to provide a succinct update of the more recent developments in a historical and human health context. |
Phase Repeatable Synthesizers as a New Harmonic Phase Standard for Nonlinear Network Analysis | In this paper, the synthesized phase reference standard is introduced as a new viable alternative to comb generator-based phase references for nonlinear vector network analyzer measurements. Emphasis is put on the achievable higher specific output power of a frequency picket of interest for a denser spacing in the reference frequency grid. Supporting calculations on network analyzer IF filter bandwidths and limits for a denser grid spacing for comb-based phase references are presented. The concept is evaluated with a reference prototype covering the frequency range of 54 MHz to 6.8 GHz requiring only a 10-MHz reference signal and no network analyzer generators for stimulus, thus enabling even 2-port network analyzers without direct receiver and generator access to perform nonlinear reflection measurements. Furthermore, a method for generating a low-jitter trigger signal for the oscilloscope in absence of the comb generator pulse is shown. The synthesized phase standard implementation and the characterization setup are described in high detail to facilitate reproducibility of the results. Characterization of the new phase standard is performed in a frequency hopping pattern for amplitude and phase values of the reference pickets with a sampling oscilloscope-based setup. Startup and steady state measurements are provided. A steady-state relative phase repeatability better than 2° over power cycles and drift of 0.089 °/h at 4 GHz referenced to a synthesized 1-GHz fundamental is achieved. |
Light-dependent leaf trait variation in 43 tropical dry forest tree species. | Our understanding of leaf acclimation in relation to irradiance of fully grown or juvenile trees is mainly based on research involving tropical wet forest species. We studied sun-shade plasticity of 24 leaf traits of 43 tree species in a Bolivian dry deciduous forest. Sampling was confined to small trees. For each species, leaves were taken from five of the most and five of the least illuminated crowns. Trees were selected based on the percentage of the hemisphere uncovered by other crowns. We examined leaf trait variation and the relation between trait plasticity and light demand, maximum adult stature, and ontogenetic changes in crown exposure of the species. Leaf trait variation was mainly related to differences among species and to a minor extent to differences in light availability. Traits related to the palisade layer, thickness of the outer cell wall, and N(area) and P(area) had the greatest plasticity, suggesting their importance for leaf function in different light environments. Short-lived pioneers had the highest trait plasticity. Overall plasticity was modest and rarely associated with juvenile light requirements, adult stature, or ontogenetic changes in crown exposure. Dry forest tree species had a lower light-related plasticity than wet forest species, probably because wet forests cast deeper shade. In dry forests light availability may be less limiting, and low water availability may constrain leaf trait plasticity in response to irradiance. |
Lightning impulse performances of grounding devices covered with low-resistivity materials | The low-resistivity material (LRM) is widely used to decrease the power-frequency grounding resistances of grounding devices for transmission lines in the regions with high soil resistivity. The study about the influence of the LRM on impulse performances of grounding devices cannot be found in literature. Experimental results of lightning impulse properties of grounding devices covered with LRM were presented in this paper. The influences of impulse current, geometrical dimensions of grounding devices, and soil resistivity on impulse grounding resistance and impulse coefficient of grounding devices with the LRM coverings are still the same with those without the LRM coverings. The impulse grounding resistance decreases from about 25% to 45% when the LRM covering is used. The fitting formulae to calculate the reducing ratio of impulse grounding resistance of different grounding devices are provided. On the other hand, the influence of LRM on the effective impulse length of grounding electrodes is discussed. |
ACR Appropriateness Criteria® Suspected upper extremity deep vein thrombosis. | Upper-extremity venous thrombosis often presents as unilateral arm swelling. The differential diagnosis includes lesions compressing the veins and causing a functional venous obstruction, venous stenosis, an infection causing edema, obstruction of previously functioning lymphatics, or the absence of sufficient lymphatic channels to ensure effective drainage. The following recommendations are made with the understanding that venous disease, specifically venous thrombosis, is the primary diagnosis to be excluded or confirmed in a patient presenting with unilateral upper-extremity swelling. Contrast venography remains the best reference-standard diagnostic test for suspected upper-extremity acute venous thrombosis and may be needed whenever other noninvasive strategies fail to adequately image the upper-extremity veins. Duplex, color flow, and compression ultrasound have also established a clear role in evaluation of the more peripheral veins that are accessible to sonography. Gadolinium contrast-enhanced MRI is routinely used to evaluate the status of the central veins. Delayed CT venography can often be used to confirm or exclude more central vein venous thrombi, although substantial contrast loads are required. The ACR Appropriateness Criteria(®) are evidence-based guidelines for specific clinical conditions that are reviewed every 2 years by a multidisciplinary expert panel. The guideline development and review include an extensive analysis of current medical literature from peer-reviewed journals and the application of a well-established consensus methodology (modified Delphi) to rate the appropriateness of imaging and treatment procedures by the panel. In those instances in which evidence is lacking or not definitive, expert opinion may be used to recommend imaging or treatment. |
AI Safety Gridworlds | We present a suite of reinforcement learning environments illustrating various safety properties of intelligent agents. These problems include safe interruptibility, avoiding side effects, absent supervisor, reward gaming, safe exploration, as well as robustness to self-modification, distributional shift, and adversaries. To measure compliance with the intended safe behavior, we equip each environment with a performance function that is hidden from the agent. This allows us to categorize AI safety problems into robustness and specification problems, depending on whether the performance function corresponds to the observed reward function. We evaluate A2C and Rainbow, two recent deep reinforcement learning agents, on our environments and show that they are not able to solve them satisfactorily. |
Mechanistic Insights into the Crystallization of Amorphous Calcium Carbonate (ACC) | Many organisms use amorphous calcium carbonate (ACC) during crystalline calcium carbonate biomineralization, as a means to control particle shape/size and phase stability. Here, we present an in situ smalland wide-angle X-ray scattering (SAXS/WAXS) study of the mechanisms and kinetics of ACC crystallization at rapid time scales (seconds). Combined with offline solid and solution characterization, we show that ACC crystallizes to vaterite via a threestage process. First, hydrated and disordered ACC forms, then rapidly transforms to more ordered and dehydrated ACC; in conjunction with this, vaterite forms via a spherulitic growth mechanism. Second, when the supersaturation of the solution with respect to vaterite decreases sufficiently, the mechanism changes to ACC dissolution and vaterite crystal growth. The third stage is controlled by Ostwald ripening of the vaterite particles. Combining this information with previous studies, allowed us to develop a mechanistic understanding of the abiotic crystallization process from ACC to vaterite and all the way to calcite. We propose this is the underlying abiotic mechanism for calcium carbonate biomineralization from ACC. This process is then augmented or altered by organisms (e.g., using organic compounds) to form intricate biominerals. This study also highlights the applicability of in situ time-resolved SAXS/WAXS to study rapid crystallization reactions. ■ INTRODUCTION The anhydrous crystalline calcium carbonate (CaCO3) polymorphs, which form under ambient conditions, are calcite, aragonite, and vaterite. Their crystallization in both abiotic and biotic systems is often preceded by the formation and subsequent transformation of amorphous calcium carbonate (ACC). Synthetic calcium carbonates with specific particle sizes, shapes, and structures can be produced using the ACC formation pathway. Large quantities are manufactured for many industrial applications (e.g., paper manufacture and pharmaceuticals); however, in some cases, their precipitation is highly undesirable (e.g., scale formation in oil pipes), which leads to high repair/replacement costs. Calcium carbonates also form in a wide variety of natural environments (e.g., soils and sediments) and are ubiquitous at the Earth’s surface. For example, calcium carbonate is the major component of ancient limestone deposits or modern marine reefs. Most modern, natural calcium carbonate phases are formed by organisms as biominerals, which fulfill a wide variety of functions (e.g., stability and protection). The most common and stable calcareous biominerals are calcite and aragonite. However, in some cases, less stable vaterite is biomineralized (e.g., in spicules of an ascidian and various fish otoliths). Despite their importance, a clear understanding of the fundamental processes controlling the crystallization of calcium carbonate is still lacking. Many biomineralizing organisms utilize the ACC pathway to precisely control the particle shape and crystalline polymorph during the formation of their shells or spines etc. For example, sea urchin larvae produce highly elongated single crystals of calcite by the controlled deposition and transformation of ACC within a biological membrane. Such natural biological processes have informed biomimetic studies of crystal growth and design and are now used to manipulate the shape and size of synthetic calcium carbonate particles. The structure and chemistry of ACC is complex with several forms of ACC classified according to their water content, local order, and mode of formation (e.g., abiotic vs biogenic). A key variable is the amount of structural water. Hydrated-ACC can contain up to ∼1.6 mol of water per mole of CaCO3, yet several less hydrated and even anhydrous forms of ACC have been described. For example, Radha et al. produced both disordered and less disordered ACC with different degrees of hydration. Observations by Politi et al. during sea urchin spicule formation showed that initially hydrated ACC forms, which transformed to anhydrous ACC before crystallizing to calcite via a secondary nucleation process. The enthalpies of the ACC phases in relation to the crystalline calcium carbonates show that energetically the sequence of increasing stability and possible crystallization pathway is as follows: disordered, hydrated ACC → less disordered, less hydrated ACC → anhydrous ACC → vaterite → aragonite → calcite. This sequence highlights that all ACC phases have higher formation Received: May 17, 2012 Published: May 21, 2012 Article pubs.acs.org/crystal © 2012 American Chemical Society 3806 dx.doi.org/10.1021/cg300676b | Cryst. Growth Des. 2012, 12, 3806−3814 enthalpies than the crystalline polymorphs; thus, ACC can act as a precursor to any of the anhydrous crystalline phases. However, in inorganic systems, the transformation of ACC to its crystalline counterparts is often extremely rapid (seconds to minutes), and because of their inherent instability, the ACC precursors are difficult to characterize using ex situ techniques (e.g., TEM and FTIR). Therefore the proposed sequence of polymorph formation has not yet been observed in full or quantified in detail. Abiotically synthesized ACC rapidly transforms to vaterite, calcite, or aragonite, with the polymorph formed dependent on a number of factors including time, fluid composition, presence of organic molecules, and temperature. In most cases, pure ACC will transform to calcite via a vaterite intermediate at low temperatures (<30 °C) and to aragonite via vaterite at higher temperatures (>60 °C). At low temperatures, the addition of magnesium tends to favor the direct formation of calcite from ACC, without a vaterite intermediate. In contrast, sulfate has been shown to increase the stability and persistence of vaterite significantly at low temperatures and may be key to understanding the stabilization of vaterite in biological and environmental systems. The mechanisms and kinetics of the later stages of the crystallization pathways have been shown to be controlled by the dissolution of vaterite and precipitation of calcite, with the rate controlled by the surface area of calcite. However, the mechanism of the ACC to vaterite transformation is still not clear, with several possible mechanisms proposed. Many studies have suggested that ACC dissolves and vaterite spheres formed via homogeneous nucleation of nanocrystalline vaterite particles, followed by fast aggregation to form micrometer sized polycrystalline spheres. A solid state mechanism for the ACC to vaterite crystallization has also been proposed, with the ACC particles dehydrating and recrystallizing to form vaterite. Finally, a recent study, based on imaging of inorganically precipitated vaterite, suggested that vaterite forms via ACC dissolution coupled to spherulitic growth. Resolving the mechanisms and kinetics of ACC crystallization in abiotic systems is key to developing a detailed understanding of how calcium carbonate phases form in both natural and synthetic processes. In particular, the mechanism of transformation between the individual phases forming as the system moves toward thermodynamic equilibrium from disordered hydrated ACC to fully crystalline calcite needs to be fully quantified. However, it should be noted that many biomineralization processes occur entirely within a biological membrane with little or no free water and in the presence of organic macromolecules. Therefore, any abiotic mechanism of ACC crystallization in solution may be altered or manipulated by the organism during biomineral formation. In this study, we performed in situ smalland wide-angle Xray scattering (SAXS/WAXS) experiments with a time resolution of 1 s to study the direct transformation of ACC to vaterite in solution and the effect of sulfate on this reaction. Combined with offline characterization of the solid phases and solution composition, we show that the crystallization of ACC to vaterite occurs in three distinct stages. First, the initial ACC phase dehydrates and vaterite forms via rapid spherulitic growth. This is followed by an intermediate stage where vaterite continues to form from the dissolving ACC, and finally, the vaterite particle grows via surface-controlled Oswald ripening. In addition, the presence of sulfate decreased the overall crystallization rate and reduced the particle growth rate during |
Harmonic mitigation by SRF theory based active power filter using adaptive hysteresis control | Power quality is an all-encompassing concept for a multitude of individual types of power system disturbances. The presence of harmonics in power supply network poses a severe power quality problem that results in greater power losses in the distribution system, interference problems in communication systems and, sometimes, in operation failures of electronic equipment. Shunt active power filters are employed to suppress the current harmonics and reduce the total harmonic distortion (THD). The voltage source inverter (VSI) is the core of an active power filter. The hysteresis current control is a method of controlling the VSI. Hysteresis control can be either of fixed band type or adaptive band type. In this paper, Synchronous Reference Frame (SRF) theory is implemented for the generation of reference current signals for the controller. This paper investigates the effectiveness of the proposed model in harmonics currents mitigation by simulating a model of a three-phase three-wire shunt active power filter based on adaptive hysteresis current control and SRF theory. Simulation results indicate that the proposed active power filter can restrain harmonics of electrical source current effectively. |
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