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[Wegener's granulomatosis diagnosed by orbital-meningeal presentation: a case report]. | Wegener's granulomatosis is a necrotizing granulomatous vasculitis with a strong affinity for the upper respiratory tract, lung and kidney. The ophthalmologic manifestation most often presents as inflammatory orbital pseudotumor or scleritis. We report a case of a 27-year-old woman with an orbital-meningeal presentation leading to a diagnosis of Wegener's granulomatosis. |
A Comparison of Common Users across Instagram and Ask.fm to Better Understand Cyberbullying | This paper examines users who are common to two popular online social networks, Instagram and Ask.fm, That are often used for cyber bullying. An analysis of the negativity and positivity of word usage in posts by common users of these two social networks is performed. These results are normalized in comparison to a sample of typical users in both networks. We also examine the posting activity of common user profiles and consider its correlation with negativity. Within the Ask.fm social network, which allows anonymous posts, the relationship between anonymity and negativity is further explored. |
Treatment Enhances Ultradian Rhythms of CSF Monoamine Metabolites in Patients with Major Depressive Episodes | Unipolar and bipolar depressions show abnormal behavioral manifestations of ultradian (less than 24 h) rhythms, but abnormal rhythms of the central neurotransmitters thought to be important for depression pathophysiology (eg dopamine (DA) and serotonin (5-HT)) have not been shown in this time frame. Since antidepressant treatments normalize disrupted rhythms in depression (eg rapid-eye-movement sleep and hormonal rhythms), we hypothesized that depression-related changes in ultradian oscillations of DA and 5-HT might be revealed during antidepressant treatment. Cerebrospinal fluid (CSF) samples collected q10 min for 24 h in 13 patients experiencing major depressive episodes (MDE) before and after treatment for 5 weeks with sertraline or bupropion were assayed for levels of homovanillic acid (HVA) and 5-hydroxyindoleacetic acid (5-HIAA), and their ratio was calculated. Data were analyzed in the frequency domain using Fourier transforms and multivariate permutation testing. Antidepressant treatments were associated with decreased variance for 5-HIAA, increased variance for HVA, and markedly increased variance for the HVA : 5-HIAA ratio (p<0.05, p<0.02, and p<0.003, respectively). With treatment, the correlations between 5-HIAA and HVA weakened (p=0.06). Power spectral density (PSD—the Fourier magnitude squared) of the 5-HIAA signals at periods of 1.75 and 3.7 h (both p<0.05) decreased, while circadian cycling of HVA levels (p<0.05) and of the ratio (p<0.005) increased after treatment. The PSD of the full-length HVA : 5-HIAA ratio series after treatment increased in rapid variability (20–103 min periods, p<0.05). Spectrographic windowing demonstrated a focal span of enhanced HVA : 5-HIAA ratio variability following antidepressant treatment, in an approximately 84-min period through the evening (p<0.05). Periodic neurotransmitter relationships in depressed patients were altered by treatment in this analysis of a small data set. This may represent a baseline abnormality in the regulation of periodic functions involved in the depression pathophysiology, but it could also be due to an unrelated antidepressant effect. Further studies including comparisons with healthy subject data are in progress. |
Outsourcing transportation infrastructure maintenance : a theoretical approach with application to JR East | In transportation agencies, how to reduce maintenance and operation cost is one of the biggest and most common concerns, because their revenue is not expected to increase drastically in the future. One of the solutions undertaken nowadays is contracting out and utilizing contractors' efficiency for cost cutting and performance improvements. Actually, highway agencies in the US have already tried several pilot programs, employing performance-based contract, aiming at reducing their cost of maintenance and rehabilitation of their assets. It has been reported that these agencies achieved huge cost-reduction and performance improvement at the same time by implementing these strategies. Railway infrastructure maintenance is not outsourced as much as highway maintenance in the US. However, a theoretical discussion about outsourcing and contracting shows that railway track maintenance can be outsourced to enhance operating efficiency. Exploring the cases in several railway organizations and highway agencies, fixed-price contract with incentive schemes turn out to be mainly utilized. Evaluating maintenance contractor's performance by several comprehensive performance metrics is also a useful tool to manage and control the contractor's performance, which is linked to reward or penalty payments. Considering the lessons learned in the discussions above, applications for railway maintenance in JR East is discussed. Its maintenance contract structure is in the midst of transition, but still imbues a traditional style. Instead, a long-term, performance-based contract with incentive scheme is suggested to improve the efficiency of infrastructure maintenance and adjust the future environmental changes JR East faces. Thesis Supervisor: Joseph Sussman Title: JR East Professor Professor of Civil and Environmental Engineering and Engineering Systems |
Concept Mapping as a Form of Student Assessment and Instruction in the Domain of Bioengineering | As part of a concerted effort to improve Biomedical Engineering (BME) education, the Vanderbilt-Northwestern-Texas-Harvard/MIT Engineering Research Center (VaNTH ERC) is investigating alternative methods for assessing students’ conceptual knowledge, and integrating an array of diverse competencies into the curriculum. One potentially useful tool for achieving these goals is concept mapping or the spatial representation of concepts and their interrelationships. This paper describes three studies investigating this potential. In Study One, three groups (i.e., BME undergraduates, graduate students and faculty) constructed concept maps in response to the question, “What are the 10-20 most important concepts in BME?” Group differences were consistent with expert-novice distinctions in structural knowledge. Faculty generated dense networks of higher-order principles (e.g., “the synthesis of engineering and medicine”) and their applications (e.g., “interdisciplinary communication”) while students generated fewer connections among concepts pertaining largely to domain content (e.g., “biotechnology,” “physiology”). Study 2 conducted longitudinal and cross-sectional examinations of the development of expertise. Undergraduates in a yearlong design course responded at two different time points to the question, “What is your current conceptual understanding of what is involved in the BME design process?” Analyses revealed that, relative to maps constructed at the beginning of the course, end of the semester maps used more precise vocabulary, were more coherently constructed, and contained a greater number of connections among concepts. Student maps were also compared to a criterion map created by the course instructor. Study Three will investigate concept mapping as a form of instruction. Learning outcomes of students receiving traditional (i.e., taxonomy-driven presentation of concepts) and innovative (i.e., use of concept mapping as an advance organizer) instruction are being compared. Findings are discussed in terms of their implications for the role of concept mapping as a form of student assessment and instruction, and ultimately, a means to promoting lifelong learning. Introduction P ge 722.1 |
Gender difference in the response to valsartan/amlodipine single-pill combination in essential hypertension (China Status II): An observational study | BACKGROUND
The China STATUS II is a prospective, multicentre, open-label, post-marketing, observational study including Chinese adults (aged ⩾ 18 years) with essential hypertension who were prescribed once-daily valsartan/amlodipine (Val/Aml 80/5 mg) single-pill combination. In order to examine gender differences in treatment response to Val/Aml, we further analysed data from the China STATUS II study.
METHODS
A total of 11,312 patients (6456 (57%) men and 4856 (43%) women) received the Val/Aml treatment for 8 weeks. After the treatment, we compared the proportion of patients not achieving the target systolic blood pressure (SBP: < 140 mm Hg) or diastolic blood pressure (DBP: < 90 mm Hg) in different age groups (by Fisher exact probability test) and estimated the changes in blood pressure (BP) according to age and gender, using a mixed model.
RESULTS
At enrolment, mean SBP was higher in the female versus the male patients (160.0 ± 12.71 versus 159.3 ± 12.31 mm Hg; p = 0.003), whereas the mean DBP was higher in the male versus the female patients (96.4 ± 10.65 versus 94.5 ± 10.72 mm Hg; p < 0.001). The overall proportion of women not achieving the target BP was less than that of men (57.41% versus 59.59%; p < 0.05) at 4 weeks and (22.22% versus 23.78%; p < 0.05) at 8 weeks after the Val/Aml treatment. Among both men and women, the proportion of patients not achieving the target SBP increased with age; however, the proportion not achieving the target DBP decreased with age. The mixed-model analysis showed that the changes in SBP were closely related to gender, indicating that the SBP-lowering effect after Val/Aml treatment might be better in women. In addition, the changes in DBP were closely related to age.
CONCLUSIONS
Gender might be a factor for consideration in the decision-making process of individualised antihypertensive therapy, in the future. |
Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks | Financial market dynamics forecasting has long been a focus of economic research. A stochastic time effective function neural network (STNN) with principal component analysis (PCA) developed for financial time series prediction is presented in the present work. In the training modeling, we first use the approach of PCA to extract the principal components from the input data, then integrate the STNN model to perform the financial price series prediction. By taking the proposed model compared with the traditional backpropagation neural network (BPNN), PCA-BPNN and STNN, the empirical analysis shows that the forecasting results of the proposed neural network display a better performance in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, HS300, S&P500 and DJIA in the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. & 2015 Elsevier B.V. All rights reserved. |
A 0.35 /spl mu/m CMOS comparator circuit for high-speed ADC applications | A high-speed differential clocked comparator circuit is presented. The comparator consists of a preamplifier and a latch stage followed by a dynamic latch that operates as an output sampler. The output sampler circuit consists of a full transmission gate (TG) and two inverters. The use of this sampling stage results in a reduction in the power consumption of this high-speed comparator. Simulations show that charge injection of the TG adds constructively to the sampled signal value, therefore amplifying the sampled signal with a modest gain of 1.15. Combined with the high gain of the inverters, the sampled signals are amplified toward the rail voltages. This comparator is designed and fabricated in a 0.35 /spl mu/m standard digital CMOS technology. Measurement results show a sampling frequency of 1 GHz with 16 mV resolution for a 1 V input signal range and 2 mW power consumption from a 3.3 V supply. The architecture can be scaled down to smaller feature sizes and lower supply voltages. |
Detection of Unauthorized IoT Devices Using Machine Learning Techniques | Security experts have demonstrated numerous risks imposed by Internet of Things (IoT) devices on organizations. Due to the widespread adoption of such devices, their diversity, standardization obstacles, and inherent mobility, organizations require an intelligent mechanism capable of automatically detecting suspicious IoT devices connected to their networks. In particular, devices not included in a white list of trustworthy IoT device types (allowed to be used within the organizational premises) should be detected. In this research, Random Forest, a supervised machine learning algorithm, was applied to features extracted from network traffic data with the aim of accurately identifying IoT device types from the white list. To train and evaluate multi-class classifiers, we collected and manually labeled network traffic data from 17 distinct IoT devices, representing nine types of IoT devices. Based on the classification of 20 consecutive sessions and the use of majority rule, IoT device types that are not on the white list were correctly detected as unknown in 96% of test cases (on average), and white listed device types were correctly classified by their actual types in 99% of cases. Some IoT device types were identified quicker than others (e.g., sockets and thermostats were successfully detected within five TCP sessions of connecting to the network). Perfect detection of unauthorized IoT device types was achieved upon analyzing 110 consecutive sessions; perfect classification of white listed types required 346 consecutive sessions, 110 of which resulted in 99.49% accuracy. Further experiments demonstrated the successful applicability of classifiers trained in one location and tested on another. In addition, a discussion is provided regarding the resilience of our machine learning-based IoT white listing method to adversarial attacks. |
A four channel 24-GHz FMCW radar sensor with two-dimensional target localization capabilities | The measurement of different target parameters using radar systems has been an active research area for the last decades. Particularly target angle measurement is a very demanding topic, because obtaining good measurement results often goes hand in hand with extensive hardware effort. Especially for sensors used in the mass market, e.g. in automotive applications like adaptive cruise control this may be prohibitive. Therefore we address target localization using a compact frequency-modulated continuous-wave (FMCW) radar sensor. The angular measurement results are improved compared to standard beamforming methods using an adaptive beamforming approach. This approach will be applied to the FMCW principle in a way that allows the use of well known methods for the determination of other target parameters like range or velocity. The applicability of the developed theory will be shown on different measurement scenarios using a 24-GHz prototype radar system. |
Simulation on a Fuzzy-PID Position Controller of the CNC Servo System | Variation of the system parameters and external disturbances always happen in the CNC servo system. With a traditional PID controller, it will cause large overshoot or poor stability. In this paper, a fuzzy-PID controller is proposed in order to improve the performance of the servo system. The proposed controller incorporates the advantages of PID control which can eliminate the steady-state error, and the advantages of fuzzy logic such as simple design, no need of an accurate mathematical model and some adaptability to nonlinearity and time-variation. The fuzzy-PID controller accepts the error (e) and error change(ec) as inputs ,while the parameters kp, ki, kd as outputs. Control rules of the controller are established based on experience so that self-regulation of the values of PID parameters is achieved. A simulation model of position servo system is constructed in Matlab/Simulink module based on a high-speed milling machine researched in our institute. By comparing the traditional PID controller and the fuzzy-PID controller, the simulation results show that the system has stronger robustness and disturbance rejection capability with the latter controller which can meet the performance requirements of the CNC position servo system better |
A master-slave blockchain paradigm and application in digital rights management | Upon flaws of current blockchain platforms of heavyweight, large capacity of ledger, and time-consuming of synchronization of data, in this paper, we proposed a new paradigm of master-slave blockchain scheme (MSB) for pervasive computing that suitable for general PC, mobile device such as smart phones or PADs to participants in the working of mining and verification, in which we separated traditional blockchain model in 2 layer defined as master node layer and a series of slavery agents layer, then we proposed 2 approaches for partially computing model(P-CM) and non-computing of model(NCM) in the MSB blockchain, Finally large amounts of simulations manifest the proposed master-slave blockchain scheme is feasible, extendible and suitable for pervasive computing especially in the 5G generation environment, and can apply in the DRM-related applications. |
A scored AUC Metric for Classifier Evaluation and Selection | The area under the ROC (Receiver Operating Characteristic) curve, or simply AUC, has been widely used to measure model performance for binary classification tasks. It can be estimated under parametric, semiparametric and nonparametric assumptions. The non-parametric estimate of the AUC, which is calculated from the ranks of predicted scores of instances, does not always sufficiently take advantage of the predicted scores. This problem is tackled in this paper. On the basis of the ranks and the original values of the predicted scores, we introduce a new metric, called a scored AUC or sAUC. Experimental results on 20 UCI data sets empirically demonstrate the validity of the new metric for classifier evaluation and selection. |
Fabrication of silver nanoparticles from leaf extract of Butea monosperma (Flame of Forest) and their inhibitory effect on bloom-forming cyanobacteria | Background: Silver nanoparticles (SNPs) are used extensively in areas such as medicine, catalysis, electronics, environmental science, and biotechnology. Therefore, facile synthesis of SNPs from an eco-friendly, inexpensive source is a prerequisite. In the present study, fabrication of SNPs from the leaf extract of Butea monosperma (Flame of Forest) has been performed. SNPs were synthesized from 1% leaf extract solution and characterized by ultraviolet-visible (UV-vis) spectroscopy and transmission electron microscopy (TEM). The mechanism of SNP formation was studied by Fourier transform infrared (FTIR), and anti-algal properties of SNPs on selected toxic cyanobacteria were evaluated. Results: TEM analysis indicated that size distribution of SNPs was under 5 to 30 nm. FTIR analysis indicated the role of amide I and II linkages present in protein in the reduction of silver ions. SNPs showed potent anti-algal properties on two cyanobacteria, namely, Anabaena spp. and Cylindrospermum spp. At a concentration of 800 μg/ml of SNPs, maximum anti-algal activity was observed in both cyanobacteria. Conclusions: This study clearly demonstrates that small-sized, stable SNPs can be synthesized from the leaf extract of B. monosperma. SNPs can be effectively employed for removal of toxic cyanobacteria. |
Reducing Duplicate Filters in Deep Neural Networks | This paper investigates the presence of duplicate neurons or filters in neural networks. This phenomenon is prevalent in networks and increases with the number of filters in a layer. We observe the emergence of duplicate filters over training iterations, study the factors that affect their concentration and compare existing network reducing operations. We validate our findings using convolutional and fully-connected networks on the CIFAR-10 dataset. |
Assessing and conceptualizing orgasm after a spinal cord injury. | OBJECTIVES
To provide a questionnaire for assessing the sensations characterizing orgasm. To test the hypothesis that orgasm is related to autonomic hyperreflexia (AHR) in individuals with a spinal cord injury (SCI).
SUBJECTS AND METHODS
A total of 97 men with SCI, of whom 50 showed AHR at ejaculation and 39 showed no AHR, were compared. Ejaculation was obtained through natural stimulation, vibrostimulation or vibrostimulation combined with midodrine (5-25 mg). Cardiovascular measures were recorded before, at, and after each test. Responses to the questionnaire were divided into four categories: cardiovascular, muscular, autonomic and dysreflexic sensations.
RESULTS
Significantly more sensations were described at ejaculation than with sexual stimulation alone. Men with SCI who experienced AHR at ejaculation reported significantly more cardiovascular, muscular, autonomic and dysreflexic responses than those who did not. There was no difference between men with complete and those with incomplete lesions.
CONCLUSIONS
The findings show that the questionnaire is a useful tool to assess orgasm and to guide patients in identifying the bodily sensations that accompany or build up to orgasm. The findings also support the hypothesis that orgasm may be related to the presence of AHR in individuals with SCI. Data from able-bodied men also suggest that AHR could be related to orgasm, as increases in blood pressure are observed at ejaculation along with cardiovascular, autonomic and muscular sensations. |
Beauveria bassiana yeast phase on agar medium and its pathogenicity against Diatraea saccharalis (Lepidoptera: Crambidae) and Tetranychus urticae (Acari: Tetranychidae). | Beauveria bassiana colonizes insect hosts initially through a yeast phase, which is common in some artificial liquid cultures, but not reported on artificial solid media. We describe a yeast-like phase for B. bassiana isolate 447 (ATCC 20872) on MacConkey agar and its virulence toward Diatraea saccharalis and Tetranychus urticae. The yeast-like cells of B. bassiana developed by budding from germinating conidia after 24-h incubation. Cells were typically 5-10 microm and fungal colonies were initially circular and mucoid, but later were covered with mycelia and conidia. Ability to produce yeast-like cells on MacConkey medium was relatively common among different B. bassiana isolates, but growth rate and timing of yeast-like cell production also varied. Metarhizium anisopliae and Paecilomyces spp. isolates did not grow as yeast-like cells on MacConkey medium. Yeast-like cells of B. bassiana 447 were more virulent against D. saccharalis than conidia when 10(7)cells/ml were used. At 10(8)cells/ml, the estimated mean survival time was 5.4 days for the yeast suspension and 7.7 days for the conidial suspension, perhaps due to faster germination. The LC(50) was also lower for yeast than conidial suspensions. Yeast-like cells and conidia had similar virulence against T. urticae; the average mortalities with yeast-like cells and conidia were, respectively, 42.8 and 45.0%, with 10(7)cells/ml, and 77.8 and 74.4%, with 10(8)cells/ml. The estimated mean survival times were 3.6 and 3.9 for yeast and conidial suspensions, respectively. The bioassay results demonstrate the yeast-like structures produced on MacConkey agar are effective as inoculum for B. bassiana applications against arthropod pests, and possibly superior to conidia against some species. Obtaining well-defined yeast phase cultures of entomopathogenic hyphomycetes may be an important step in studies of the biology and nutrition, pathogenesis, and the genetic manipulation of these fungi. |
Workload-aware database monitoring and consolidation | In most enterprises, databases are deployed on dedicated database servers. Often, these servers are underutilized much of the time. For example, in traces from almost 200 production servers from different organizations, we see an average CPU utilization of less than 4%. This unused capacity can be potentially harnessed to consolidate multiple databases on fewer machines, reducing hardware and operational costs. Virtual machine (VM) technology is one popular way to approach this problem. However, as we demonstrate in this paper, VMs fail to adequately support database consolidation, because databases place a unique and challenging set of demands on hardware resources, which are not well-suited to the assumptions made by VM-based consolidation.
Instead, our system for database consolidation, named Kairos, uses novel techniques to measure the hardware requirements of database workloads, as well as models to predict the combined resource utilization of those workloads. We formalize the consolidation problem as a non-linear optimization program, aiming to minimize the number of servers and balance load, while achieving near-zero performance degradation. We compare Kairos against virtual machines, showing up to a factor of 12× higher throughput on a TPC-C-like benchmark. We also tested the effectiveness of our approach on real-world data collected from production servers at Wikia.com, Wikipedia, Second Life, and MIT CSAIL, showing absolute consolidation ratios ranging between 5.5:1 and 17:1. |
Combined Phase-Shift and Frequency Modulation of a Dual-Active-Bridge AC–DC Converter With PFC | This paper presents a combined phase-shift and frequency modulation scheme of a dual-active-bridge (DAB) ac- dc converter with power factor correction (PFC) to achieve zero voltage switching (ZVS) over the full range of the ac mains voltage. The DAB consists of a half bridge with bidirectional switches on the ac side and a full bridge on the dc side of the isolation transformer to accomplish single-stage power conversion. The modulation scheme is described by means of analytical formulas, which are used in an optimization procedure to determine the optimal control variables for minimum switch commutation currents. Furthermore, an ac current controller suitable for the proposed modulation scheme is described. A loss model and measurements on a 3.3-kW electric vehicle battery charger to connect to the 230 Vrms / 50-Hz mains considering a battery voltage range of 280-420 V validate the theoretical analysis. |
Optimal pilot beam pattern design for massive MIMO systems | In this paper, channel estimation for massive multiple-input multiple-output (MIMO) systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation under the assumption of Gauss-Markov channel processes is proposed. The proposed algorithm designs the optimal pilot beam pattern sequentially by exploiting the statistics of the channel, antenna correlation, and temporal correlation. The algorithm provides a sequentially optimal sequence of pilot beam patterns for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm. |
A Compact Multiband Monopole Antenna With a Defected Ground Plane | A compact multiband antenna is proposed that consists of a printed circular disc monopole antenna with an L-shaped slot cut out of the ground, forming a defected ground plane. Analysis of the current distribution on the antenna reveals that at low frequencies the addition of the slot creates two orthogonal current paths, which are responsible for two additional resonances in the response of the antenna. By virtue of the orthogonality of these modes the antenna exhibits orthogonal pattern diversity, while enabling the adjacent resonances to be merged, forming a wideband low-frequency response and maintaining the inherent wideband high-frequency response of the monopole. The antenna exhibits a measured -10 dB S 11 bandwidth of 600 MHz from 2.68 to 3.28 GHz, and a bandwidth of 4.84 GHz from 4.74 to 9.58 GHz, while the total size of the antenna is only 24 times 28.3 mm. The efficiency is measured using a modified Wheeler cap method and is verified using the gain comparison method to be approximately 90% at both 2.7 and 5.5 GHz. |
Triage systems: a review of the literature with reference to Saudi Arabia. | This review evaluates some of the international literature on triage in order to provide evidence-based data for the medical community in Saudi Arabia specifically and the Eastern Mediterranean Region in general. The aim is to encourage national health planners and decision-makers to apply formal triage systems in the emergency departments of general and specialist hospitals and other relevant health settings, including primary and psychiatric care. Research and training on triage is extremely limited in Saudi Arabia and the Region and this review highlights the need for more research on triage systems and for the inclusion of training on triage in medical education programmes. |
BioIE: extracting informative sentences from the biomedical literature | SUMMARY
BioIE is a rule-based system that extracts informative sentences relating to protein families, their structures, functions and diseases from the biomedical literaturE. Based on manual definition of templates and rules, it aims at precise sentence extraction rather than wide recall. After uploading source text or retrieving abstracts from MEDLINE, users can extract sentences based on predefined or user-defined template categories. BioIE also provides a brief insight into the syntactic and semantic context of the source-text by looking at word, N-gram and MeSH-term distributions. Important Applications of BioIE are in, for example, annotation of microarray data and of protein databases.
AVAILABILITY
http://umber.sbs.man.ac.uk/dbbrowser/bioie/ |
Photographic Text-to-Image Synthesis with a Hierarchically-Nested Adversarial Network | This paper presents a novel method to deal with the challenging task of generating photographic images conditioned on semantic image descriptions. Our method introduces accompanying hierarchical-nested adversarial objectives inside the network hierarchies, which regularize mid-level representations and assist generator training to capture the complex image statistics. We present an extensile single-stream generator architecture to better adapt the jointed discriminators and push generated images up to high resolutions. We adopt a multi-purpose adversarial loss to encourage more effective image and text information usage in order to improve the semantic consistency and image fidelity simultaneously. Furthermore, we introduce a new visual-semantic similarity measure to evaluate the semantic consistency of generated images. With extensive experimental validation on three public datasets, our method significantly improves previous state of the arts on all datasets over different evaluation metrics. |
Meanings of blood, bleeding and blood donations in Pakistan: implications for national vs global safe blood supply policies | Contemporary public policy, supported by international arbitrators of blood policy such as the World Health Organization and the International Federation of the Red Cross, asserts that the safest blood is that donated by voluntary, non-remunerated donors from low-risk groups of the population. These policies promote anonymous donation and discourage kin-based or replacement donation. However, there is reason to question whether these policies, based largely on Western research and beliefs, are the most appropriate for ensuring an adequate safe blood supply in many other parts of the world. This research explored the various and complex meanings embedded in blood using empirical ethnographic data from Pakistan, with the intent of informing development of a national blood policy in that country. Using a focused ethnographic approach, data were collected in 26 in-depth interviews, 6 focus group discussions, 12 key informant interviews and 25 hours of observations in blood banks and maternity and surgical wards. The key finding was that notions of caste-based purity of blood, together with the belief that donors and recipients are symbolically knitted in a kin relationship, place a preference on kin-blood. The anonymity inherent in current systems of blood extraction, storage and use as embedded in contemporary policy discourse and practice was problematic as it blurred distinctions that were important within this society. The article highlights the importance-to ensuring a safe blood supply-of basing blood procurement policies on local, context-specific belief systems rather than relying on uniform, one-size-fits-all global policies. Drawing on our empirical findings and the literature, it is argued that the practice of kin-donated blood remains a feasible alternative to the global ideal of voluntary, anonymous donations. There is a need to focus on developing context-sensitive strategies for promoting blood safety, and critically revisit the assumptions underlying contemporary global blood procurement policies. |
Effect of a smartphone application incorporating personalized health-related imagery on adherence to antiretroviral therapy: a randomized clinical trial. | Poor adherence to combination antiretroviral therapy (ART) is a major global challenge. In this study we examined the efficacy of a smartphone application incorporating personalized health-related visual imagery that provided real-time information about the level of medication and the patient's level of immunoprotection, in order to improve adherence to ART. We randomized 28 people on ART to either a standard or augmented version of the smartphone application. The augmented version contained components that illustrated participants' current estimated plasma concentrations of antiretroviral drugs and the immune protection provided by ART. Adherence to ART was assessed at baseline and at 3 months using self-reported adherence, pharmacy dispensing records, and HIV viral load. Information was also collected on illness and medication beliefs and use of the application. Participants who received the augmented application showed a significantly higher level of self-reported adherence to ART at 3 months (p=0.03) and decreased viral load (p=0.023) as compared to individuals using the standard version. Greater usage of the extra components of the augmented application was associated with greater perceived understanding of HIV infection and increased perceived necessity for ART. Smartphone applications that incorporate personalized health-related visual imagery may have potential to improve adherence to ART. |
Profile View Lip Reading | In this paper, we introduce profile view (PV) lip reading, a scheme for speaker-dependent isolated word speech recognition. We provide historic motivation for PV from the importance of profile images in facial animation for lip reading, and we present feature extraction schemes for PV as well as for the traditional frontal view (FV) approach. We compare lip reading results for PV and FV, which demonstrate a significant improvement for PV over FV. We show improvement in speech recognition with the integration of audio and visual features. We also found it advantageous to process the visual features over a longer duration than the duration marked by the endpoints of the speech utterance. |
Variation of seizure frequency with ovulatory status of menstrual cycles. | PURPOSE
To determine if seizure frequency differs between anovulatory and ovulatory cycles.
METHODS
The data came from the 3-month baseline phase of an investigation of progesterone therapy for intractable focal onset seizures. Of 462 women who enrolled, 281 completed the 3-month baseline phase and 92 had both anovulatory and ovulatory cycles during the baseline phase. Midluteal progesterone levels ≥5 ng/ml were used to designate cycles as ovulatory. Among the 92 women, average daily seizure frequency (ADSF) for all seizures combined and each type of seizure considered separately (secondary generalized tonic-clonic seizures - 2°GTCS, complex partial seizures - CPS, simple partial seizures - SPS) were compared between anovulatory and ovulatory cycles using paired t-tests. A relationship between the proportional differences in ADSF and estradiol/progesterone (EP) serum level ratios between anovulatory and ovulatory cycles was determined using bivariate correlational analysis.
KEY FINDINGS
ADSF was 29.5% greater for 2°GTCS during anovulatory than during ovulatory cycles. ADSF did not differ significantly for CPS or SPS or for all seizures combined. Proportional differences in anovulatory/ovulatory 2°GTCS ADSF ratios correlated significantly with differences in anovulatory/ovulatory EP ratios. Among the 281 women, the three seizure types did not differ in ovulatory rates, but EP ratios were greater for cycles with 2°GTCS than partial seizures only.
SIGNIFICANCE
Seizure frequency is significantly greater for 2°GTCS, but not CPS or SPS, during anovulatory cycles than ovulatory cycles. Because the proportional increases in 2°GTCS frequency during anovulatory cycles correlate with the proportional increases in EP level ratios, these findings support a possible role for reproductive steroids in 2°GTCS occurrence. |
Life-world, modernity and critique : paths between Heidegger and the Frankfurt School | Ontology and critique Adorno and Heidegger critical theory and reconciliation Kant and critical theory Habermas and rationality Heidegger and Marxism psychoanalysis and critical theory - a Lacanian perspective Heidegger and psychotherapy. |
Improving Ontology-Based User Profiles | Personalized Web browsing and search hope to provide Web information that matches a user’s personal interests and thus provide more effective and efficient information access. A key feature in developing successful personalized Web applications is to build user profiles that accurately represent a user’ s interests. The main goal of this research is to investigate techniques that implicitly build ontology-based user profiles. We build the profiles without user interaction, automatically monitoring the user’s browsing habits. After building the initial profile from visited Web pages, we investigate techniques to improve the accuracy of the user profile. In particular, we focus on how quickly we can achieve profile stability, how to identify the most important concepts, the effect of depth in the concept-hierarchy on the importance of a concept, and how many levels from the hierarchy should be used to represent the user. Our major findings are that ranking the concepts in the profiles by number of documents assigned to them rather than by accumulated weights provides better profile accuracy. We are also able to identify stable concepts in the profile, thus allowing us to detect long-term user interests. We found that the accuracy of concept detection decreases as we descend them in the concept hierarchy, however this loss of accuracy must be balanced against the detailed view of the user available only through the inclusion of lower-level concepts. |
A Structured Model For Action Detection | A dominant paradigm for learning-based approaches in computer vision is training generic models, such as ResNet for image recognition, or I3D for video understanding, on large datasets and allowing them to discover the optimal representation for the problem at hand. While this is an obviously attractive approach, it is not applicable in all scenarios. We claim that action detection is one such challenging problem the models that need to be trained are large, and the labeled data is expensive to obtain. To address this limitation, we propose to incorporate domain knowledge into the structure of the model to simplify optimization. In particular, we augment a standard I3D network with a tracking module to aggregate long term motion patterns, and use a graph convolutional network to reason about interactions between actors and objects. Evaluated on the challenging AVA dataset, the proposed approach improves over the I3D baseline by 5.5% mAP and over the state-ofthe-art by 4.8% mAP. |
Measuring the Cost of Cybercrime | In this paper we present what we believe to be the first systematic study of the costs of cybercrime. It was prepared in response to a request from the UK Ministry of Defence following scepticism that previous studies had hyped the problem. For each of the main categories of cybercrime we set out what is and is not known of the direct costs, indirect costs and defence costs – both to the UK and to the world as a whole. We distinguish carefully between traditional crimes that are now ‘cyber’ because they are conducted online (such as tax and welfare fraud); transitional crimes whose modus operandi has changed substantially as a result of the move online (such as credit card fraud); new crimes that owe their existence to the Internet; and what we might call platform crimes such as the provision of botnets which facilitate other crimes rather than being used to extract money from victims directly. As far as direct costs are concerned, we find that traditional offences such as tax and welfare fraud cost the typical citizen in the low hundreds of pounds/Euros/dollars a year; transitional frauds cost a few pounds/Euros/dollars; while the new computer crimes cost in the tens of pence/cents. However, the indirect costs and defence costs are much higher for transitional and new crimes. For the former they may be roughly comparable to what the criminals earn, while for the latter they may be an order of magnitude more. As a striking example, the botnet behind a third of the spam sent in 2010 earned its owners around US$2.7m, while worldwide expenditures on spam prevention probably exceeded a billion dollars. We are extremely inefficient at fighting cybercrime; or to put it another way, cybercrooks are like terrorists or metal thieves in that their activities impose disproportionate costs on society. Some of the reasons for this are well-known: cybercrimes are global and have strong externalities, while traditional crimes such as burglary and car theft are local, and the associated equilibria have emerged after many years of optimisation. As for the more direct question of what should be done, our figures suggest that we should spend less in anticipation of cybercrime (on antivirus, firewalls, etc.) and more in response – that is, on the prosaic business of hunting down cyber-criminals and throwing them in jail. Computer Laboratory, University of Cambridge, JJ Thomson Ave, Cambridge, CB3 0FD, UK. [email protected] UK. [email protected] University of Münster, Department of Information Systems, Leonardo-Campus 3, 48149 Münster, Germany. [email protected] Computer Laboratory, University of Cambridge, JJ Thomson Ave, Cambridge, CB3 0FD, UK. [email protected] Faculty of Technology, Policy and Management, Delft University of Technology, Jaffalaan 5, 2628 BX, Delft, Netherlands. [email protected] School of Social Sciences, Cardiff University, Cardiff, CF10 3XQ, UK. [email protected] Department of Computer Science and Engineering, Southern Methodist University, Dallas, TX 75275, USA. [email protected] Department of Computer Science and Engineering, University of California, San Diego, CA 92093, USA. [email protected] |
Shape from shading: a well-posed problem? | Shape from shading is known to be an ill-posed problem. We show in this paper that if we model the problem in a different way than it is usually done, more precisely by taking into account the 1/r/sup 2/ attenuation term of the illumination, shape from shading becomes completely well-posed. Thus the shading allows to recover (almost) any surface from only one image (of this surface) without any additional data (in particular, without the knowledge of the heights of the solution at the local intensity "minima", contrary to [P. Dupuis et al. (1994), E. Prados et al. (2004), B. Horn (1986), E. Rouy et al. (1992), R. Kimmel et al. (2001)]) and without regularity assumptions (contrary to [J. Oliensis et al. (1993), R. Kimmel et al. (1995)], for example). More precisely, we formulate the problem as that of solving a new partial differential equation (PDE), we develop a complete mathematical study of this equation and we design a new provably convergent numerical method. Finally, we present results of our new shape from shading method on various synthetic and real images. |
A friction differential and cable transmission design for a 3-DOF haptic device with spherical kinematics | We present a new mechanical design for a 3-DOF haptic device with spherical kinematics (pitch, yaw, and prismatic radial). All motors are grounded in the base to decrease inertia and increase compactness near the user's hand. An aluminum-aluminum friction differential allows for actuation of pitch and yaw with mechanical robustness while allowing a cable transmission to route through its center. This novel cabling system provides simple, compact, and high-performance actuation of the radial DOF independent of motions in pitch and yaw. We show that the device's capabilities are suitable for general haptic rendering, as well as specialized applications of spherical kinematics such as laparoscopic surgery simulation. |
Compressing deep convolutional neural networks in visual emotion recognition | In this paper, we consider the problem of insufficient runtime and memory-space complexities of deep convolutional neural networks for visual emotion recognition. A survey of recent compression methods and efficient neural networks architectures is provided. We experimentally compare the computational speed and memory consumption during the training and the inference stages of such methods as the weights matrix decomposition, binarization and hashing. It is shown that the most efficient optimization can be achieved with the matrices decomposition and hashing. Finally, we explore the possibility to distill the knowledge from the large neural network, if only large unlabeled sample of facial images is available. |
HCCI combustion timing control with Variable Valve Timing | Homogeneous Charge Compression Ignition (HCCI) is a promising concept for combustion engines to reduce both emissions and fuel consumption. In HCCI engines, a homogeneous air-fuel mixture auto-ignites due to compression, which is unlike traditional spark ignition or diesel engines where ignition is started with either a spark or fuel injection. HCCI combustion control is a challenging issue because there is no direct initiator of combustion in these engines. Variable Valve Timing (VVT) is one effective way to control the combustion timing in HCCI engines. VVT changes the amount of trapped residual gas and the effective compression ratio both of which have a strong effect on combustion timing. In order to control HCCI combustion, a physics based control oriented model is developed that includes the effect of trapped residual gas on combustion timing. The control oriented model is obtained by model order reduction of complex chemical kinetic reaction mechanisms. This method allows different fuels to be incorporated using a standard methodology and fills the gap between complex models with highly detailed chemical kinetics and simple black box models that have been used in model based control. The control oriented model is used to develop ignition timing PI control using simulation. The PI control modulates the trapped residual gas using variable valve timing as the actuator. The results indicate that the controller can track step changes in HCCI combustion timing. |
Dynamic Input Structure and Network Assembly for Few-Shot Learning | The ability to learn from a small number of examples has been a difficult problem in machine learning since its inception. While methods have succeeded with large amounts of training data, research has been underway in how to accomplish similar performance with fewer examples, known as one-shot or more generally few-shot learning. This technique has been shown to have promising performance, but in practice requires fixed-size inputs making it impractical for production systems where class sizes can vary. This impedes training and the final utility of few-shot learning systems. This paper describes an approach to constructing and training a network that can handle arbitrary example sizes dynamically as the system is used. |
Nonlinear Pedagogy: An Effective Approach to Cater for Individual Differences in Learning a Sports Skill | Learning a sports skill is a complex process in which practitioners are challenged to cater for individual differences. The main purpose of this study was to explore the effectiveness of a Nonlinear Pedagogy approach for learning a sports skill. Twenty-four 10-year-old females participated in a 4-week intervention involving either a Nonlinear Pedagogy (i.e.,manipulation of task constraints including equipment and rules) or a Linear Pedagogy (i.e., prescriptive, repetitive drills) approach to learn a tennis forehand stroke. Performance accuracy scores, movement criterion scores and kinematic data were measured during pre-intervention, post-intervention and retention tests. While both groups showed improvements in performance accuracy scores over time, the Nonlinear Pedagogy group displayed a greater number of movement clusters at post-test indicating the presence of degeneracy (i.e., many ways to achieve the same outcome). The results suggest that degeneracy is effective for learning a sports skill facilitated by a Nonlinear Pedagogy approach. These findings challenge the common misconception that there must be only one ideal movement solution for a task and thus have implications for coaches and educators when designing instructions for skill acquisition. |
Efficient DTW-Based Speech Recognition System for Isolated Words of Arabic Language | Despite the fact that Arabic language is currently one of the most common languages worldwide, there has been only a little research on Arabic speech recognition relative to other languages such as English and Japanese. Generally, digital speech processing and voice recognition algorithms are of special importance for designing efficient, accurate, as well as fast automatic speech recognition systems. However, the speech recognition process carried out in this paper is divided into three stages as follows: firstly, the signal is preprocessed to reduce noise effects. After that, the signal is digitized and hearingized. Consequently, the voice activity regions are segmented using voice activity detection (VAD) algorithm. Secondly, features are extracted from the speech signal using Mel-frequency cepstral coefficients (MFCC) algorithm. Moreover, delta and acceleration (delta-delta) coefficients have been added for the reason of improving the recognition accuracy. Finally, each test word’s features are compared to the training database using dynamic time warping (DTW) algorithm. Utilizing the best set up made for all affected parameters to the aforementioned techniques, the proposed system achieved a recognition rate of about 98.5% which outperformed other HMM and ANN-based approaches available in the literature. Keywords—Arabic speech recognition, MFCC, DTW, VAD. |
Functional characterization of human coronary artery smooth muscle cells under cyclic mechanical strain in a degradable polyurethane scaffold. | There are few synthetic elastomeric biomaterials that simultaneously provide the required biological conditioning and the ability to translate biomechanical stimuli to vascular smooth muscle cells (VSMCs). Biomechanical stresses are important physiological elements that regulate VSMC function, and polyurethane elastomers are a class of materials capable of facilitating the translation of stress induced biomechanics. In this study, human coronary artery smooth muscle cells (hCASMCs), which were seeded into a porous degradable polar/hydrophobic/ionic (D-PHI) polyurethane scaffold, were subjected to uniaxial cyclic mechanical strain (CMS) over a span of four weeks using a customized bioreactor. The distribution, proliferation and contractile protein expression of hCASMCs in the scaffold were then analyzed and compared to those grown under static conditions. Four weeks of CMS, applied to the elastomeric scaffold, resulted in statistically greater DNA mass, more cell area coverage and a better distribution of cells deeper within the scaffold construct. Furthermore, CMS samples demonstrated improved tensile mechanical properties following four weeks of culture, suggesting the generation of more extracellular matrix within the polyurethane constructs. The expression of smooth muscle α-actin, calponin and smooth muscle myosin heavy chain and the absence of Ki-67+ cells in both static and CMS cultures, throughout the 4 weeks, suggest that hCASMCs retained their contractile character on these biomaterials. The study highlights the importance of implementing physiologically-relevant biomechanical stimuli in the development of synthetic elastomeric tissue engineering scaffolds. |
The Past, Present, and Future for Software Architecture | It's been 10 years since David Garlan and Mary Shaw wrote their seminal book Software Architecture Perspective on an Emerging Discipline, since Maarten Boasson edited a special issue of IEEE Software on software architecture, and since the first International Software Architecture Workshop took place. What has happened over these 10 years? What have we learned? Where do we look for information? What's the community around this discipline? And where are we going from here?This article is part of a focus section on software architecture. |
Reverse engineering: a roadmap | By the early 1990s the need for reengineering legacy systems was already acute, but recently the demand has increased significantly with the shift toward web-based user interfaces. The demand by all business sectors to adapt their information systems to the Web has created a tremendous need for methods, tools, and infrastructures to evolve and exploit existing applications efficiently and cost-effectively. Reverse engineering has been heralded as one of the most promising technologies to combat this legacy systems problem. This paper presents a roadmap for reverse engineering research for the first decade of the new millennium, building on the program comprehension theories of the 1980s and the reverse engineering technology of the 1990s. |
I Sensed It Was You: Authenticating Mobile Users with Sensor-Enhanced Keystroke Dynamics | Mobile devices have become an important part of our everyday life, harvesting more and more confidential user information. Their portable nature and the great exposure to security attacks, however, call out for stronger authentication mechanisms than simple password-based identification. Biometric authentication techniques have shown potential in this context. Unfortunately, prior approaches are either excessively prone to forgery or have too low accuracy to foster widespread adoption. In this paper, we propose sensor-enhanced keystroke dynamics, a new biometric mechanism to authenticate users typing on mobile devices. The key idea is to characterize the typing behavior of the user via unique sensor features and rely on standard machine learning techniques to perform user authentication. To demonstrate the effectiveness of our approach, we implemented an Android prototype system termed Unagi. Our implementation supports several feature extraction and detection algorithms for evaluation and comparison purposes. Experimental results demonstrate that sensor-enhanced keystroke dynamics can improve the accuracy of recent gestured-based authentication mechanisms (i.e., EER>0.5%) by one order of magnitude, and the accuracy of traditional keystroke dynamics (i.e., EER>7%) by two orders of magnitude. |
Additive Margin Softmax for Face Verification | In this letter, we propose a conceptually simple and intuitive learning objective function, i.e., additive margin softmax, for face verification. In general, face verification tasks can be viewed as metric learning problems, even though lots of face verification models are trained in classification schemes. It is possible when a large-margin strategy is introduced into the classification model to encourage intraclass variance minimization. As one alternative, angular softmax has been proposed to incorporate the margin. In this letter, we introduce another kind of margin to the softmax loss function, which is more intuitive and interpretable. Experiments on LFW and MegaFace show that our algorithm performs better when the evaluation criteria are designed for very low false alarm rate. |
AI for Dynamic Difficulty Adjustment in Games | Video Games are boring when they are too easy and frustrating when they are too hard. While most singleplayer games allow players to adjust basic difficulty (easy, medium, hard, insane), their overall level of challenge is often static in the face of individual player input. This lack of flexibility can lead to mismatches between player ability and overall game difficulty. In this paper, we explore the computational and design requirements for a dynamic difficulty adjustment system. We present a probabilistic method (drawn predominantly from Inventory Theory) for representing and reasoning about uncertainty in games. We describe the implementation of these techniques, and discuss how the resulting system can be applied to create flexible interactive experiences that adjust on the fly. Introduction Video games are designed to generate engaging experiences: suspenseful horrors, whimsical amusements, fantastic adventures. But unlike films, books, or televised media which often have similar experiential goals video games are interactive. Players create meaning by interacting with the games internal systems. One such system is inventory the stock of items that a player collects and carries throughout the game world. The relative abundance or scarcity of inventory items has a direct impact on the players experience. As such, games are explicitly designed to manipulate the exchange of resources between world and player. [Simpson, 2001] This network of producer-consumer relationships can be viewed as an economy or more broadly, as a dynamic system [Castronova, 2000, Luenberger, 79]. 1 Inventory items for first-person shooters include health, weapons, ammunition and power-ups like shielding or temporary invincibility. 2 A surplus of ammunition affords experimentation and shoot first tactics, while limited access to recovery items (like health packs) will promote a more cautious approach to threatening situations. Game developers iteratively refine these systems based on play testing feedback tweaking behaviors and settings until the game is balanced. While balancing, they often analyze systems intuitively by tracking specific identifiable patterns or types of dynamic activity. It is a difficult and time consuming process [Rollings and Adams, 2003]. While game balancing and tuning cant be automated, directed mathematical analysis can reveal deeper structures and relationships within a game system. With the right tools, researchers and developers can calculate relationships in less time, with greater accuracy. In this paper, we describe a first step towards such tools. Hamlet is a Dynamic Difficulty Adjustment (DDA) system built using Valves Half Life game engine. Using techniques drawn from Inventory Theory and Operations Research, Hamlet analyzes and adjust the supply and demand of game inventory in order to control overall game difficulty. |
Real-Time Through-Wall Situation Awareness Using a Microwave Doppler Radar Sensor | This paper deals with the development of a short-range radar suitable for the detection of humans behind visually opaque structures such as building walls. The system consists in a continuous wave Doppler radar operating in the S-band of the electromagnetic spectrum in order to ensure an adequate signal penetration through the walls. Based on the interaction of the electromagnetic waves with human targets, a phase modulation of the radar signal arises due to their movements and tiny periodic chest displacements associated with the respiratory activity. A simple and effective radar data processing algorithm is proposed to detect, in real-time, the presence of one or several human subjects in the through-wall scene. Such an algorithm automatically provides also an indication on whether the subjects are static or moving in the environment. As shown by experimental tests carried out in an indoor scenario, the proposed sensing device and related signal processing yields prompt and reliable information about the scene thus confirming its practical value. |
Neural Trojans | While neural networks demonstrate stronger capabilities in pattern recognition nowadays, they are also becoming larger and deeper. As a result, the effort needed to train a network also increases dramatically. In many cases, it is more practical to use a neural network intellectual property (IP) that an IP vendor has already trained. As we do not know about the training process, there can be security threats in the neural IP: the IP vendor (attacker) may embed hidden malicious functionality, i.e neural Trojans, into the neural IP. We show that this is an effective attack and provide three mitigation techniques: input anomaly detection, re-training, and input preprocessing. All the techniques are proven effective. The input anomaly detection approach is able to detect 99.8% of Trojan triggers although with 12.2% false positive. The re-training approach is able to prevent 94.1% of Trojan triggers from triggering the Trojan although it requires that the neural IP be reconfigurable. In the input preprocessing approach, 90.2% of Trojan triggers are rendered ineffective and no assumption about the neural IP is needed. |
Pictorial Representation of Illness and Self Measure (PRISM): A novel visual instrument to measure quality of life in dermatological inpatients. | OBJECTIVES
To validate the PRISM (Pictorial Representation of Illness and Self Measure) tool, a novel visual instrument, for the assessment of health-related quality of life in dermatological inpatients compared with the Dermatology Life Quality Index (DLQI) and the Skindex-29 questionnaires and to report qualitative information on PRISM.
DESIGN
In an open longitudinal study, PRISM and Skindex-29 and DLQI questionnaires were completed and HRQOL measurements compared.
SETTING
Academic dermatological inpatient ward.
PARTICIPANTS
The study population comprised 227 sequential dermatological inpatients on admission.
INTERVENTION
Patients completed the PRISM tool and the Skindex-29 and DLQI questionnaires at admission and discharge.
MAIN OUTCOME MEASURES
PRISM Self-Illness Separation (SIS) score; Skindex-29 and DLQI scores; and qualitative PRISM information by Mayring inductive qualitative context analysis.
RESULTS
The PRISM scores correlated well with those from the Skindex-29 (rho = 0.426; P < .001) and DLQI (rho = 0.304; P < .001) questionnaires. Between PRISM and Skindex-29 scores, the highest correlations were for dermatitis (rho = 0.614) and leg ulcer (rho = 0.554), and between PRISM and DLQI scores, the highest correlations were for psoriasis (rho = 0.418) and tumor (rho = 0.399). The PRISM tool showed comparable or higher sensitivity than quality of life questionnaires to assess changes in the burden of suffering during hospitalization. Inductive qualitative context analysis revealed impairment of adjustment and self-image as major aspects. Patients overall expected symptomatic and functional improvement. In patients with psoriasis and leg ulcers, many expected no treatment benefit.
CONCLUSIONS
The PRISM tool proved to be convenient and reliable for health-related quality of life assessment, applicable for a wide range of skin diseases, and correlated with DLQI and Skindex-29 scores. With the PRISM tool, free-text answers allow for the assessment of individual information and potentially customized therapeutic approaches. |
Action unit selective feature maps in deep networks for facial expression recognition | Facial expression recognizers based on handcrafted features have achieved satisfactory performance on many databases. Recently, deep neural networks, e. g. deep convolutional neural networks (CNNs) have been shown to boost performance on vision tasks. However, the mechanisms exploited by CNNs are not well established. In this paper, we establish the existence and utility of feature maps selective to action units in a deep CNN trained by transfer learning. We transfer a network pre-trained on the Image-Net dataset to the facial expression recognition task using the Karolinska Directed Emotional Faces (KDEF), Radboud Faces Database(RaFD) and extended Cohn-Kanade (CK+) database. We demonstrate that higher convolutional layers of the deep CNN trained on generic images are selective to facial action units. We also show that feature selection is critical in achieving robustness, with action unit selective feature maps being more critical in the facial expression recognition task. These results support the hypothesis that both human and deeply learned CNNs use similar mechanisms for recognizing facial expressions. |
VizDeck: Streamlining exploratory visual analytics of scientific data | As research becomes increasingly data-intensive, scientists are relying on visualization very early in the data analysis cycle. We find that existing tools assume a “one-at-a-time” workflow for creating visualizations and impose a steep learning curve that makes it difficult to rapidly create and review visualizations. At the same time, scientists are becoming more cognitively overloaded, spending an increasing proportion of time on data “handling” tasks rather than scientific analysis. In response, we present VizDeck, a web-based visual analytics tool for relational data that automatically recommends a set of appropriate visualizations based on the statistical properties of the data and adopts a card game metaphor to present the results to the user. We describe the design of VizDeck and discuss the results of a usability evaluation comparing VizDeck with three other popular visualization tools. We then discuss design considerations for visualization tools focused on rapid analysis based on observed sensemaking processes. |
Virtual reality-augmented rehabilitation for patients in subacute phase post stroke : a feasibility study | Upper extremity (UE) rehabilitation is of utmost importance to the achievement of full inclusion and functional independence. Traditionally presented as well as technology-based therapeutic interventions have produced measurable changes in motor function and motor control but fall short of major reductions in disability. Animal models of stroke suggest that the first two weeks to one month post stroke may be a critical time period of increased brain plasticity. This study shows the feasibility of adding one hour of intensive robotic/virtual reality (VR) therapy to on-going rehabilitation in the acute phase of recovery post-stroke. All five of the subjects made substantial improvements in Upper Extremity Fugl-Meyer Assessment (UEFMA) scores (mean improvement = 6 points (SD=2)) as well as improvements in Wolf Motor Function Test (WMFT) time (average decrease = 41% (SD=35) after training with more consistent changes in the proximal arm portions of the WMFT and the UEFMA as well as in upper arm kinematics. Maps of cortical excitability indicate an increase in both the area of activation and the volume of activation of the first dorsal interosseous (FDI) muscle after a two-week training period. |
Reproducibility of heart rate and blood pressure variability in patients with chronic obstructive pulmonary disease | Wide variations in respiratory rate and hypoxic stimulation of chemoreceptors may produce unreliable autonomic results in patients with COPD. We studied the reproducibility of two consecutive measurements of heart rate variability (HRV) and blood pressure variability (BPV) by time frequency analysis in patients with COPD while controlling respiratory rate and oxygen hemoglobin saturation (SaO2). Reproducibility was assessed by paired t-tests and correlation analyses between repeated measures. Correlation analyses of the log transformed low (LF) and high frequency (HF) HRV were x̄ 11.5 ± 1.1 in measurement A and x̄ 11.5 ± 1.0 in measurement B (r = 0.89, p < 0.0001), and x̄ 10.5 ± 1.1 in measurement A and x̄ 10.6 ± 1.1 in measurement B (r = 0.89, p < 0.0001) respectively. The log transformed LF and HF BPV were x̄ 4.9 ± 1.3 in measurement A and x̄ 5.3 ± 0.9 in measurement B (r = 0.70, p < 0.0002), and x̄ 6.4 ± 1.3 in measurement A and 6.6 ± 1.2 in measurement B (R = 0.71 p < 0.0001) respectively. In conclusion, time frequency analysis of HRV and BPV is reproducible and reliable in patients with COPD while controlling their respiratory rate and oxygen hemoglobin saturation. Reproducibility of these measurements may allow for a non-invasive evaluation of autonomic tone in response to treatments in COPD patients. |
Quadcopter – Obstacle Detection and Collision Avoidance | A simple approach for obstacle detection and collision avoidance of an autonomous flying quadcopter using low-cost ultrasonic sensors and simple data fusion is presented here. The approach has been implemented and tested in a self-developed quadcopter and its evaluation shows the general realizability as well as the drawbacks of this approach. In this paper, we propose a complete MICRO-UNMANNED AERIAL VEHICLE (MUAV) platform including hardware setup and processing pipeline-that is able to perceive obstacles in (almost) all directions in its surrounding. In this paper, we propose a complete micro aerial vehicle platform—including hardware setup and processing pipeline—that is able to perceive obstacles in (almost) all directions in its surrounding. Quadcopter is equipped with ultrasonic sensor. All signals from sensors are processed by Arduino microcontroller board. [5] Output from Arduino microcontroller board used to control Quadcopter propellers. [5] Keywords— Obstacle Detection, Collision Avoidance, PID controller programming, components. |
PMSG fault diagnosis in marine application | This paper presents a fault diagnosis (FD) method for on line monitoring of stator winding partial inter-turn fault and severe faults, in permanent magnet synchronous generator (PMSG) used in shaft generator system in marine applications. The faulty machine is represented in state space model based on the dq-frame transformation. The Extended Kalman Filter (EKF) parameters estimation technique is used to estimate the value of stator winding short-circuit parameters of the machine. The proposed technique has been simulated for different fault scenarios using Matlab®/Simulink®. Simulation results show that the proposed technique is robust and effective. Moreover it can be applied at different operating conditions to prevent development of complete failure. |
Generalization Error in Deep Learning | Deep learning models have lately shown great performance in various fields such as computer vision, speech recognition, speech translation, and natural language processing. However, alongside their state-of-the-art performance, it is still generally unclear what is the source of their generalization ability. Thus, an important question is what makes deep neural networks able to generalize well from the training set to new data. In this article, we provide an overview of the existing theory and bounds for the characterization of the generalization error of deep neural networks, combining both classical and more recent theoretical and empirical results. |
Behavior-Based Control: Main Properties and Implications | In addition to its computational and sensory hardware , the architecture of an autonomous robot determines how that robot will behave by imposing key constraints on the way it can sense, reason, and act in order to achieve its task. In this paper we deene the basic types of control architectures: purely reac-tive, behavior-based, and planner-based. We clarify the fundamental diierences between the rst two approaches , which are commonly confused in the literature. Next we describe the properties of behavior-based systems in detail and compare them to the two alternative approaches. Finally, we describe the application of the behavior-based paradigm in two very diierent domains. |
Toward Personalized Relational Learning | Relational learning exploits relationships among instances manifested in a network to improve the predictive performance of many network mining tasks. Due to its empirical success, it has been widely applied in myriad domains. In many cases, individuals in a network are highly idiosyncratic. They not only connect to each other with a composite of factors but also are often described by some content information of high dimensionality specific to each individual. For example in social media, as user interests are quite diverse and personal; posts by different users could differ significantly. Moreover, social content of users is often of high dimensionality which may negatively degrade the learning performance. Therefore, it would be more appealing to tailor the prediction for each individual while alleviating the issue related to the curse of dimensionality. In this paper, we study a novel problem of Personalized Relational Learning and propose a principled framework PRL to personalize the prediction for each individual in a network. Specifically, we perform personalized feature selection and employ a small subset of discriminative features customized for each individual and some common features shared by all to build a predictive model. On this account, the proposed personalized model is more human interpretable. Experiments on realworld datasets show the superiority of the proposed PRL framework over traditional relational learning methods. |
Big data emerging technologies: A CaseStudy with analyzing twitter data using apache hive | These are the days of Growth and Innovation for a better future. Now-a-days companies are bound to realize need of Big Data to make decision over complex problem. Big Data is a term that refers to collection of large datasets containing massive amount of data whose size is in the range of Petabytes, Zettabytes, or with high rate of growth, and complexity that make them difficult to process and analyze using conventional database technologies. Big Data is generated from various sources such as social networking sites like Facebook, Twitter etc, and the data that is generated can be in various formats like structured, semi-structured or unstructured format. For extracting valuable information from this huge amount of Data, new tools and techniques is a need of time for the organizations to derive business benefits and to gain competitive advantage over the market. In this paper a comprehensive study of major Big Data emerging technologies by highlighting their important features and how they work, with a comparative study between them is presented. This paper also represents performance analysis of Apache Hive query for executing Twitter tweets in order to calculate Map Reduce CPU time spent and total time taken to finish the job. |
A study of age and gender seen through mobile phone usage patterns in Mexico | Mobile phone usage provides a wealth of information, which can be used to better understand the demographic structure of a population. In this paper we focus on the population of Mexican mobile phone users. Our first contribution is an observational study of mobile phone usage according to gender and age groups. We were able to detect significant differences in phone usage among different subgroups of the population. Our second contribution is to provide a novel methodology to predict demographic features (namely age and gender) of unlabeled users by leveraging individual calling patterns, as well as the structure of the communication graph. We provide details of the methodology and show experimental results on a real world dataset that involves millions of users. |
Adjuvant high-dose medroxyprogesterone acetate for early breast cancer: 13 years update in a multicentre randomized trial | The authors updated their report on a randomized trial initiated in 1982 comparing, in early breast cancer, high-dose IM Medroxyprogesterone acetate (HD-MPA) adjuvant hormonotherapy during 6 months with no hormonotherapy; node-positive patients also received 6 courses of IV CMF (day 1, day 8; q.4 weeks). 246 node-negative (NN) and 270 node-positive (NP) patients had been followed for a median duration of 13 years. Previous results were confirmed in this analysis on mature data. In NN patients, relapse-free survival (RFS) was improved in the adjuvant hormonotherapy arm, regardless of age while overall survival (OAS) was also increased in younger (less then 50 years) patients. In the whole group of NP patients, no difference was seen regarding RFS or OAS. However, an age-dependant opposite effect was observed: younger patients (< 50) experienced a worse and significant outcome of relapse-free and overall survivals when receiving adjuvant HD-MPA while older patients (> = 50) enjoyed a significant improvement of their relapse-free survival. For both NN and NP patients, differences in overall survivals observed in older women with a shorter follow-up, were no longer detected. © 2001 Cancer Research Campaign http://www.bjcancer.com |
Ad Exchanges: Research Issues | An emerging way to sell and buy display ads on the Internet is via ad exchanges. RightMedia [1], AdECN [2] and DoubleClick Ad Exchange [3] are examples of such real-time two-sided markets. We describe an abstraction of ad exchanges. Based on that abstraction, we present several research directions and discuss some insights. |
Depinning of three-dimensional drops from wettability defects | Substrate defects crucially influence the onset of sliding drop motion under lateral driving. A finite force is necessary to overcome the pinning influence even of microscale heterogeneities. The depinning dynamics of three-dimensional drops is studied for hydrophilic and hydrophobic wettability defects using a long-wave evolution equation for the film thickness profile. The model is studied employing effective algorithms for the parameter continuation of pinned steady drops and for the time simulation of the dynamics of sliding drops that perform a stick-slip motion. The discussion focuses on common features and significant differences of the depinning process for three-dimensional and two-dimensional drops. Copyright c © EPLA, 2009 Introduction. – Drops sliding along a solid substrate under the influence of a lateral force are a very common physical phenomenon. The force might be gravity for drops on an inclined or vertical wall, centrifugal forces for drops on a rotating disk or external shear for drops in an ambient flow. Note that lateral gradients in wettability, temperature or electrical fields can as well drive sliding motion. For smooth homogeneous substrates, an arbitrarily small driving force results in drops that move with constant velocity and shape [1–3]. Larger driving forces may lead to shape instabilities, e.g., trailing cusps may evolve that periodically emit small satellite drops [1,4]. Real substrates, however, are normally not smooth. They are rough or have local chemical or topographical defects. Even microscopic defects can have a strong influence on the drop dynamics. The heterogeneities may cause stick-slip motion [5,6] or roughening [7,8] of moving contact lines, and are thought to be responsible for contact angle hysteresis [9–12]. A local variation of the driving force (e.g., electrostatic field or temperature gradient) may play the same role as a substrate defect. The present paper focuses on the depinning of threedimensional (3d) drops from hydrophobic and hydrophilic line defects that pin them at their front and back, respectively: A hydrophobic defect is less wettable for the drop that therefore has to be forced to pass over it. On the contrary, a hydrophilic defect is more wettable and (a)E-mail: [email protected] the drop has to be forced to leave it as sketched in fig. 1. A recent theoretical study of the depinning dynamics of two-dimensional (2d) drops corresponding to 3d ridges with imposed transverse translational symmetry finds stick-slip motion beyond depinning [13,14]. The present work is based on a thin film evolution equation in long-wave approximation [15,16] that incorporates wettability in the form of a disjoining pressure [9]. It models the effective molecular interactions between the substrate and the free surface of the liquid, e.g., long-range apolar van der Waals interactions and short-range polar electrostatic or entropic interactions [17]. With the proper choice of terms, such a disjoining pressure describes drops of partially wetting liquid with a small equilibrium contact angle that coexist with an ultra-thin precursor film. An advantage of such a model is the absence of a contact line singularity. Incorporating wettability in such a way allows one to study the influence of chemical substrate heterogeneities or defects by a spatial modulation of the involved material parameters. Note, however, that they have to vary on length scales much larger than the film thickness to be consistent with the long-wave approximation [18]. The presented analysis of the behaviour of 3d drops is based on a study of i) steady drops and their stability and ii) the stick-slip motion of droplets beyond depinning. Both are based on recently developed effective algorithms for the continuation of pinned steady drops described by a partial differential equation and the time simulation of the dynamics of sliding drops [19]. |
In-vivo validation of a new clinical tool to quantify three-dimensional myocardial strain using ultrasound | Three-dimensional (3D) strain analysis based on real-time 3-D echocardiography (RT3DE) has emerged as a novel technique to quantify regional myocardial function. The goal of this study was to evaluate accuracy of a novel model-based 3D tracking tool (eSie Volume Mechanics, Siemens Ultrasound, Mountain View, CA, USA) using sonomicrometry as an independent measure of cardiac deformation. Thirteen sheep were instrumented with microcrystals sutured to the epi- and endocardium of the inferolateral left ventricular wall to trace myocardial deformation along its three directional axes of motion. Paired acquisitions of RT3DE and sonomicrometry were made at baseline, during inotropic modulation and during myocardial ischemia. Accuracy of 3D strain measurements was quantified and expressed as level of agreement with sonomicrometry using linear regression and Bland–Altman analysis. Correlations between 3D strain analysis and sonomicrometry were good for longitudinal and circumferential strain components (r = 0.78 and r = 0.71) but poor for radial strain (r = 0.30). Accordingly, agreement (bias ± 2SD) was −5 ± 6 % for longitudinal, −5 ± 7 % for circumferential, and 15 ± 19 % for radial strain. Intra-observer variability was low for all components (intra-class correlation coefficients (ICC) of respectively 0.89, 0.88 and 0.95) while inter-observer variability was higher, in particular for radial strain (ICC = 0.41). The present study shows that 3D strain analysis provided good estimates of circumferential and longitudinal strain, while estimates of radial strain were less accurate between observers. |
Dwarfism with gloomy face: a new syndrome with features of 3-M syndrome. | Nine children with primordial dwarfism are described and a new syndrome is delineated. The significant features of this syndrome include facial dysmorphism with gloomy face and very short stature, but no radiological abnormality or hormone deficiency. Mental development is normal. The mode of inheritance seems to be autosomal recessive because of consanguinity in three of the four sibships. Some overlap with the 3-M syndrome is discussed but the autonomy of the gloomy face syndrome seems to be real. |
Blob Analysis of the Head and Hands: A Method for Deception Detection | Behavioral indicators of deception and behavioral state are extremely difficult for humans to analyze. Blob analysis, a method for analyzing the movement of the head and hands based on the identification of skin color is presented. This method is validated with numerous skin tones. A proof-of-concept study is presented that uses blob analysis to explore behavioral state identification in the detection of deception. |
Quantum generalisation of feedforward neural networks | We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e. unitary. (The classical networks we generalise are called feedforward, and have step-function activation functions.) The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically. |
Active Magnetic Anomaly Detection Using Multiple Micro Aerial Vehicles | Magnetic anomaly detection (MAD) is an important problem in applications ranging from geological surveillance to military reconnaissance. MAD sensors detect local disturbances in the magnetic field, which can be used to detect the existence of and to estimate the position of buried, hidden, or submerged objects, such as ore deposits or mines. These sensors may experience false positive and false negative detections and, without prior knowledge of the targets, can only determine proximity to a target. The uncertainty in the sensors, coupled with a lack of knowledge of even the existence of targets, makes the estimation and control problems challenging. We utilize a hierarchical decomposition of the environment, coupled with an estimation algorithm based on random finite sets, to determine the number of and the locations of targets in the environment. The small team of robots follow the gradient of mutual information between the estimated set of targets and the future measurements, locally maximizing the rate of information gain. We present experimental results of a team of quadrotor micro aerial vehicles discovering and localizing an unknown number of permanent magnets. |
An updated natural history model of cervical cancer: derivation of model parameters. | Mathematical models of cervical cancer have been widely used to evaluate the comparative effectiveness and cost-effectiveness of preventive strategies. Major advances in the understanding of cervical carcinogenesis motivate the creation of a new disease paradigm in such models. To keep pace with the most recent evidence, we updated a previously developed microsimulation model of human papillomavirus (HPV) infection and cervical cancer to reflect 1) a shift towards health states based on HPV rather than poorly reproducible histological diagnoses and 2) HPV clearance and progression to precancer as a function of infection duration and genotype, as derived from the control arm of the Costa Rica Vaccine Trial (2004-2010). The model was calibrated leveraging empirical data from the New Mexico Surveillance, Epidemiology, and End Results Registry (1980-1999) and a state-of-the-art cervical cancer screening registry in New Mexico (2007-2009). The calibrated model had good correspondence with data on genotype- and age-specific HPV prevalence, genotype frequency in precancer and cancer, and age-specific cancer incidence. We present this model in response to a call for new natural history models of cervical cancer intended for decision analysis and economic evaluation at a time when global cervical cancer prevention policy continues to evolve and evidence of the long-term health effects of cervical interventions remains critical. |
Non-fragile mixed H∞ and passive synchronization of Markov jump neural networks with mixed time-varying delays and randomly occurring controller gain fluctuation | This paper studies the non-fragile mixed H∞ and passive synchronization problem for Markov jump neural networks. The randomly occurring controller gain fluctuation phenomenon is investigated for non-fragile strategy. Moreover, the mixed time-varying delays composed of discrete and distributed delays are considered. By employing stochastic stability theory, synchronization criteria are developed for the Markov jump neural networks. On the basis of the derived criteria, the non-fragile synchronization controller is designed. Finally, an illustrative example is presented to demonstrate the validity of the control approach. |
Collusion Detection and Prevention with FIRE+ Trust and Reputation Model | Recently many decentralized methods for trust management have been proposed. FIRE trust and reputation model presents a modular approach to trust and reputation from different information sources, according to availability, interaction trust, role-based trust, witness reputation, and certified reputation. However, FIRE model does not consider malicious activity and possible collusive behavior in the network nodes and is therefore susceptible to collusion attacks. In this paper we present a trust management approach to detecting collusion in direct and witness interactions among nodes based on history of interactions among nodes. Various interaction policies are defined to detect and prevent collaborative behavior in colluding nodes. Finally a multidimensional trust model FIRE+ is proposed for avoiding collusion attacks in direct and witness based interactions. |
DCT-Based Iris Recognition | This paper presents a novel iris coding method based on differences of discrete cosine transform (DCT) coefficients of overlapped angular patches from normalized iris images. The feature extraction capabilities of the DCT are optimized on the two largest publicly available iris image data sets, 2,156 images of 308 eyes from the CASIA database and 2,955 images of 150 eyes from the Bath database. On this data, we achieve 100 percent correct recognition rate (CRR) and perfect receiver-operating characteristic (ROC) curves with no registered false accepts or rejects. Individual feature bit and patch position parameters are optimized for matching through a product-of-sum approach to Hamming distance calculation. For verification, a variable threshold is applied to the distance metric and the false acceptance rate (FAR) and false rejection rate (FRR) are recorded. A new worst-case metric is proposed for predicting practical system performance in the absence of matching failures, and the worst case theoretical equal error rate (EER) is predicted to be as low as 2.59 times 10-1 available data sets |
Frangi-Net: A Neural Network Approach to Vessel Segmentation | In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network (“Frangi-Net”), and illustrate that the Frangi-Net is equivalent to the original Frangi filter. Furthermore, we show that, as a neural network, Frangi-Net is trainable. We evaluate the proposed method on a set of 45 high resolution fundus images. After fine-tuning, we observe both qualitative and quantitative improvements in the segmentation quality compared to the original Frangi measure, with an increase up to 17% in F1 score. |
Finding Structure in Time | Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves; the internal representations which develop thus reflect task demands in the context of prior internal states. A set of simulations is reported which range from relatively simple problems (temporal version of XOR) to discovering syntactic/semantic features for words. The networks are able to learn interesting internal representations which incorporate task demands with memory demands; indeed, in this approach the notion of memory is inextricably bound up with task processing. These representations reveal a rich structure, which allows them to be highly context-dependent while also expressing generalizations across classes of items. These representations suggest a method for representing lexical categories and the type/token distinction. |
Skill-based Exception Handling and Error Recovery for Collaborative Industrial Robots | Gualzru’s path to the Advertisement World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Fernando Fernández, Moisés Mart́ınez, Ismael Garćıa-Varea, Jesús Mart́ınez-Gómez, Jose Pérez-Lorenzo, Raquel Viciana, Pablo Bustos, Luis J. Manso, Luis Calderita, Marco Antonio Gutiérrez Giraldo, Pedro Núñez, Antonio Bandera, Adrián Romero-Garcés, Juan Bandera and Rebeca Marfil |
A case study of open source software development: the Apache server | According to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. In order to begin investigating such claims, we examine the development process of a major open source application, the Apache web server. By using email archives of source code change history and problem reports we quantify aspects of developer participation, core team size, code ownership, productivity, defect density, and problem resolution interval for this OSS project. This analysis reveals a unique process, which performs well on important measures. We conclude that hybrid forms of development that borrow the most effective techniques from both the OSS and commercial worlds may lead to high performance software processes. |
Staying Cool when Things Get Hot: Emotion Regulation Modulates Neural Mechanisms of Memory Encoding | During times of emotional stress, individuals often engage in emotion regulation to reduce the experiential and physiological impact of negative emotions. Interestingly, emotion regulation strategies also influence memory encoding of the event. Cognitive reappraisal is associated with enhanced memory while expressive suppression is associated with impaired explicit memory of the emotional event. However, the mechanism by which these emotion regulation strategies affect memory is unclear. We used event-related fMRI to investigate the neural mechanisms that give rise to memory formation during emotion regulation. Twenty-five participants viewed negative pictures while alternately engaging in cognitive reappraisal, expressive suppression, or passive viewing. As part of the subsequent memory design, participants returned to the laboratory two weeks later for a surprise memory test. Behavioral results showed a reduction in negative affect and a retention advantage for reappraised stimuli relative to the other conditions. Imaging results showed that successful encoding during reappraisal was uniquely associated with greater co-activation of the left inferior frontal gyrus, amygdala, and hippocampus, suggesting a possible role for elaborative encoding of negative memories. This study provides neurobehavioral evidence that engaging in cognitive reappraisal is advantageous to both affective and mnemonic processes. |
Development of a brief ataxia rating scale (BARS) based on a modified form of the ICARS. | To develop a brief ataxia rating scale (BARS) for use by movement disorder specialists and general neurologists. Current ataxia rating scales are cumbersome and not designed for clinical practice. We first modified the International Cooperative Ataxia Rating Scale (ICARS) by adding seven ataxia tests (modified ICARS, or MICARS), and observed only minimally increased scores. We then used the statistics package R to find a five-test subset in MICARS that would correlate best with the total MICARS score. This was accomplished first without constraints and then with the clinical constraint requiring one test each of Gait, Kinetic Function-Arm, Kinetic Function-Leg, Speech, and Eye Movements. We validated these clinical constraints by factor analysis. We then validated the results in a second cohort of patients; evaluated inter-rater reliability in a third cohort; and used the same data set to compare BARS with the Scale for the Assessment and Rating of Ataxia (SARA). Correlation of ICARS with the seven additional tests that when added to ICARS form MICARS was 0.88. There were 31,481 five-test subtests (48% of possible combinations) that had a correlation with total MICARS score of > or =0.90. The strongest correlation of an unconstrained five-test subset was 0.963. The clinically constrained subtest validated by factor analysis, BARS, had a correlation with MICARS-minus-BARS of 0.952. Cronbach alpha for BARS and SARA was 0.90 and 0.92 respectively; and inter-rater reliability (intraclass correlation coefficient) was 0.91 and 0.93 respectively. BARS is valid, reliable, and sufficiently fast and accurate for clinical purposes. |
A Core Quantitative Coeffect Calculus | Linear logic is well known for its resource-awareness, which has inspired the design of several resource management mechanisms in programming language design. Its resource-awareness arises from the distinction between linear, single-use data and non-linear, reusable data. The latter is marked by the so-called exponential modality, which, from the categorical viewpoint, is a (monoidal) comonad. Monadic notions of computation are well-established mechanisms used to express effects in pure functional languages. Less well-established is the notion of comonadic computation. However, recent works have shown the usefulness of comonads to structure context dependent computations. In this work, we present a language `RPCF inspired by a generalized interpretation of the exponential modality. In `RPCF the exponential modality carries a label—an element of a semiring R—that provides additional information on how a program uses its context. This additional structure is used to express comonadic type analysis. |
Novel air blowing control for balancing a unicycle robot | This paper presents the implementation of a novel control method of using air for balancing the roll angle of a unicycle robot. The unicycle robot is designed and built. The roll angle of the unicycle robot is controlled by blowing air while the pitch angle is also controlled by DC motors. Successful balancing performances are demonstrated. |
What Is the Blockchain? | Blockchain is a new technology, based on hashing, which is at the foundation of the platforms for trading cryptocurrencies and executing smart contracts. This article reviews the basic ideas of this technology and provides a sample minimalist implementation in Python. |
Small Universal families of graphs on ℵω+ 1 | We prove that it is consistent that אω is strong limit, 2אω is large and the universality number for graphs on אω+1 is small. The proof uses Prikry forcing with interleaved collapsing. |
Cure of chronic prostatitis presumably due to Enterococcus spp and gram-negative bacteria | Chronic bacterial prostatitis is a therapeutic challenge since even long treatment courses result in clinical and bacteriological cure in only approximately one-third of cases [1]. This is related to the poor diffusion of many antimicrobial agents into the prostate [2], changes in the pH level of prostatic fluid associated with infection, and the presence of infected calculi. The treatment of chronic prostatitis caused by Enterococcus spp is especially difficult, since antibiotics such as amoxicillin and vancomycin do not reach sufficient levels in prostatic fluid. Cure of chronic enterococcal prostatitis has been reported once after treatment with a novel fluoroquinolone [3]. Here, we describe a case of a patient with chronic enterococcal prostatitis who was cured using a combined medical and surgical approach. A 45-year-old man with type I ‘brittle’ diabetes mellitus complicated by severe polyneuropathy had experienced recurrent episodes of prostatitis since 1996. In 1999, he underwent subtotal colectomy for neuropathic bowel motility disorder. Post-surgical complications necessitated a total colectomy with ileorectal anastomosis. The postoperative course was complicated by a severe hernia of the anterior abdominal wall and chronic diarrhea. Since 1999, the patient had suffered from chronic prostatitis presenting with perineal pain, dysuria, and difficulty emptying the bladder. Multiple courses of antibiotics had only a temporary effect. In 2004, surgical repair of the abdominal wall hernia was indicated, but implantation of foreign material was deemed unsafe unless the prostatitis was completely cured in advance. Prostate ultrasonography showed calcifications and minimal bladder residue after voiding. At least six different cultures of urine and ejaculate yielded Enterococcus faecalis (sensitive to amoxicillin, moxifloxacin and linezolid, but resistant to co-trimoxazole), Klebsiella pneumoniae and Proteus mirabilis (both susceptible to moxifloxacin and co-trimoxazole, but only K. pneumoniae sensitive to nitrofurantoin). However, no prostate-specific diagnostic specimens were obtained, so the diagnosis of chronic enterococcal and gram-negative bacterial prostatitis was presumed but not proven. In order to reduce the risk of residual infection associated with prostatic calculi, it was decided that a transurethral resection of the prostate should be performed during prolonged antibiotic treatment. Treatment with moxifloxacin was consequently started, since this agent has good activity against the cultured pathogens [4]. However, within 1 week of treatment initiation the patient developed severe Clostridium difficile-associated diarrhea, which necessitated the discontinuation of moxifloxacin. An alternative antibiotic regimen thus had to be considered. Although we could find no published reports of the use of linezolid for the treatment of chronic prostatitis, data showing that linezolid effectively enters the prostatic parenchyma are available [5, 6]. Treatment was thus restarted with a combination of co-trimoxazole (960 mg bid) plus folic acid (5 mg once daily) for the gram-negative bacteria, and linezolid (600 mg bid) aimed at the enterococci. Both antibiotics had to be administered intraveM. J. H. Pronk . S. M. Arend (*) Department of Infectious Diseases C5P-39, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands e-mail: [email protected] Tel.: +31-71-5262620 Fax: +31-71-5266758 |
A Review of the Research on Internet Addiction | Research indicates that maladaptive patterns of Internet use constitute behavioral addiction. This article explores the research on the social effects of Internet addiction. There are four major sections. The Introduction section overviews the field and introduces definitions, terminology, and assessments. The second section reviews research findings and focuses on several key factors related to Internet addiction, including Internet use and time, identifiable problems, gender differences, psychosocial variables, and computer attitudes. The third section considers the addictive potential of the Internet in terms of the Internet, its users, and the interaction of the two. The fourth section addresses current and projected treatments of Internet addiction, suggests future research agendas, and provides implications for educational psychologists. |
Genetic manipulation of Neisseria gonorrhoeae. | The sexually-transmitted pathogen, Neisseria gonorrhoeae, undergoes natural transformation at high frequency. This property has led to the rapid dissemination of antibiotic resistance markers and to the panmictic structure of the gonococcal population. However, high frequency transformation also makes N. gonorrhoeae one of the easiest bacterial species to manipulate genetically in the laboratory. Techniques have been developed that result in transformation frequencies >50%, allowing the identification of mutants by screening and without selection. Constructs have been created to take advantage of this high frequency transformation, facilitating genetic mutation, complementation, and heterologous gene expression. Techniques are described for genetic manipulation of N. gonorrhoeae, as well as for growth of this fastidious organism. |
Contamination by arsenic and other trace elements of tube-well water along the Mekong River in Lao PDR. | Arsenic and other trace element concentrations were determined for tube-well water collected in the Lao PDR provinces of Attapeu, Bolikhamxai, Champasak, Savannakhet, Saravane, and Vientiane. Water samples, especially from floodplain areas of central and southern Laos, were significantly contaminated not only with As, but with B, Ba, Mn, U, and Fe as well. Total As concentrations ranged from <0.5 μg L(-1) to 278 μg L(-1), with over half exceeding the WHO guideline of 10 μg L(-1). 46% of samples, notably, were dominated by As(III). Samples from Vientiane, further north, were all acceptable except on pH, which was below drinking water limits. A principal component analysis found associations between general water characteristics, As, and other trace elements. Causes of elevated As concentrations in Lao tube wells were considered similar to those in other Mekong River countries, particularly Cambodia and Vietnam, where young alluvial aquifers give rise to reducing conditions. |
Covert channels using mobile device's magnetic field sensors | This paper presents a new covert channel using smartphone magnetic sensors. We show that modern smartphones are capable to detect the magnetic field changes induced by different computer components during I/O operations. In particular, we are able to create a covert channel between a laptop and a mobile device without any additional equipment, firmware modifications or privileged access on either of the devices. We present two encoding schemes for the covert channel communication and evaluate their effectiveness. |
NextPlace: A Spatio-temporal Prediction Framework for Pervasive Systems | Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, advertisement dissemination for mobile users, and recreational social networking tools for smart-phones. Existing techniques based on linear and probabilistic models are not able to provide accurate prediction of the location patterns from a spatio-temporal perspective, especially for long-term estimation. More specifically, they are able to only forecast the next location of a user, but not his/her arrival time and residence time, i.e., the interval of time spent in that location. Moreover, these techniques are often based on prediction models that are not able to extend predictions further in the future. In this paper we present NextPlace, a novel approach to location prediction based on nonlinear time series analysis of the arrival and residence times of users in relevant places. NextPlace focuses on the predictability of single users when they visit their most important places, rather than on the transitions between different locations. We report about our evaluation using four different datasets and we compare our forecasting results to those obtained by means of the prediction techniques proposed in the literature. We show how we achieve higher performance compared to other predictors and also more stability over time, with an overall prediction precision of up to 90% and a performance increment of at least 50% with respect to the state of the art. |
Wind and Tall Buildings – Negatives and Positives | Wind is often regarded as the foe of tall buildings since it tends to be the governing lateral load. Careful aerodynamic design of tall buildings through wind tunnel testing can greatly reduce wind loads and their affect on building motions. Various shaping strategies are discussed, aimed particularly at suppression of vortex shedding since it is frequently the cause of crosswind excitation. The use of supplementary damping systems is another approach that takes the energy out of building motions and reduces loads. Different applications of damping systems are described on several buildings, and an example of material savings and reduced carbon emissions is given. Wind also has some potential beneficial effects particular to tall buildings. One is that, since wind speeds are higher at the heights of tall buildings, the potential for extracting wind energy using wind turbines is significantly improved compared with ground level. The paper explores how much energy might be generated in this way relative to the building's energy usage. Other benefits are to be found in judicious use of natural ventilation, sometimes involving double layer wall systems, and, in hot climates, the combination of tailored wind and shade conditions to improve outdoor comfort near tall buildings and on balconies and terraces. |
Social Support and Health: A Review of Physiological Processes Potentially Underlying Links to Disease Outcomes | Social support has been reliably related to lower rates of morbidity and mortality. An important issue concerns the physiological mechanisms by which support influences such health endpoints. In this review, I examine evidence linking social support to changes in cardiovascular, neuroendocrine, and immune function. Consistent with epidemiological evidence, social support appears to be related to more positive “biological profiles” across these disease-relevant systems. Recent research on immune-mediated inflammatory processes is also starting to provide data on more integrative physiological mechanisms potentially linking social support to health. The implications of these links, along with future research directions are discussed. |
Model-based matching and hinting of fonts | In today's digital computers, phototypesetters and printers, typographic fonts are mainly given by their outline descriptions. Outline descriptions alone do not provide any information about character parts like stems serifs, shoulders, and bowls. But, in order to produce the best looking characters at a given size on a specific printer, non-linear operations must be applied to parts of the character shape. At low-resolution, grid-fitting of character outlines is required for generating nice and regular raster characters. For this reason, grid-fitting rules called hints are added to the character description. Grid-fitting rules require as parameters certain characteristic points within the shape outlines. In order to be able to detect these characteristic points in any given input font, a topological model representing the essence of the shapes found in typographic latin typefaces is proposed. This model includes sufficient information for matching existing non-fancy outline fonts to the model description. For automatic hint generation, a table of applicable hints is added into the topological model description. After matching a given input shape to the model, hints which can be applied to the shape of the given font are taken and added to its outline description. Furthermore, a structural description of individual letter shape parts using characteristic model points can be added to the model. Such a description provides knowledge about typographic structure elements like stems, serifs and bowls. |
Metaphor in Action in Political Discourse | More and more metaphors are employed in different patterns of discourses, especially in political discourses. Politics is inseparable with metaphors. This thesis makes an analysis of the functions of metaphors in political discourses from three aspects, namely, the stylistic function, the cognitive function and the social function. Vivid expression, succinct wording, clear meaning and easy understanding contribute to the stylistic function of metaphors in political discourses. For the cognitive function, metaphors have the function of guiding perception, structuralizing experience and creating new insight. The social function is that through the use of metaphors, a political discourse may easily inform people by stirring their emotions. Metaphors can serve as a persuasive device in political discourses and debates. Also, metaphors can create a sense of consolidation among people and thus mobilize people into the war. In addition, metaphors may deceive people by disguising or embellishing something. Metaphor and politics are closely interwoven. Graber once said that political communication is the "lifeblood or mother's milk of politics because communication is the essential activity that links the various parts of society together and allows them to function as an integrated whole" (Graber, 1993:305). As Edelman (1977) contended, at the core of political communication is the ability of the politician to use metaphor and symbols that awaken potential tendencies among the masses. |
Static race detection for device drivers: The Goblint approach | Device drivers rely on fine-grained locking to ensure safe access to shared data structures. For human testers, concurrency makes such code notoriously hard to debug; for automated reasoning, dynamically allocated memory and low-level pointer manipulation poses significant challenges. We present a flexible approach to data race analysis, implemented in the open source Goblint static analysis framework, that combines different pointer and value analyses in order to handle a wide range of locking idioms, including locks allocated dynamically as well as locks stored in arrays. To the best of our knowledge, this is the most ambitious effort, having lasted well over ten years, to create a fully automated static race detection tool that can deal with most of the intricate locking schemes found in Linux device drivers. Our evaluation shows that these analyses are sufficiently precise, but practical use of these techniques requires inferring environmental and domain-specific assumptions. |
Automating GUI testing for Android applications | Users increasingly rely on mobile applications for computational needs. Google Android is a popular mobile platform, hence the reliability of Android applications is becoming increasingly important. Many Android correctness issues, however, fall outside the scope of traditional verification techniques, as they are due to the novelty of the platform and its GUI-oriented application construction paradigm. In this paper we present an approach for automating the testing process for Android applications, with a focus on GUI bugs. We first conduct a bug mining study to understand the nature and frequency of bugs affecting Android applications; our study finds that GUI bugs are quite numerous. Next, we present techniques for detecting GUI bugs by automatic generation of test cases, feeding the application random events, instrumenting the VM, producing log/trace files and analyzing them post-run. We show how these techniques helped to re-discover existing bugs and find new bugs, and how they could be used to prevent certain bug categories. We believe our study and techniques have the potential to help developers increase the quality of Android applications. |
Ontology-Based Data Access for Extracting Event Logs from Legacy Data: The onprom Tool and Methodology | Process mining aims at discovering, monitoring, and improving business processes by extracting knowledge from event logs. In this respect, process mining can be applied only if there are proper event logs that are compatible with accepted standards, such as extensible event stream (XES). Unfortunately, in many real world set-ups, such event logs are not explicitly given, but instead are implicitly represented in legacy information systems. In this work, we exploit a framework and associated methodology for the extraction of XES event logs from relational data sources that we have recently introduced. Our approach is based on describing logs by means of suitable annotations of a conceptual model of the available data, and builds on the ontology-based data access (OBDA) paradigm for the actual log extraction. Making use of a realworld case study in the services domain, we compare our novel approach with a more traditional extract-transform-load based one, and are able to illustrate its added value. We also present a set of tools that we have developed and that support the OBDA-based log extraction framework. The tools are integrated as plugins of the ProM process mining suite. |
A Video Representation Using Temporal Superpixels | We develop a generative probabilistic model for temporally consistent super pixels in video sequences. In contrast to supermodel methods, object parts in different frames are tracked by the same temporal super pixel. We explicitly model flow between frames with a bilateral Gaussian process and use this information to propagate super pixels in an online fashion. We consider four novel metrics to quantify performance of a temporal super pixel representation and demonstrate superior performance when compared to supermodel methods. |
Microservices Validation: Methodology and Implementation | Due to the wide spread of cloud computing, arises actual question about architecture, design and implementation of cloud applications. The microservice model describes the design and development of loosely coupled cloud applications when computing resources are provided on the basis of automated IaaS and PaaS cloud platforms. Such applications consist of hundreds and thousands of service instances, so automated validation and testing of cloud applications developed on the basis of microservice model is a pressing issue. There are constantly developing new methods of testing both individual microservices and cloud applications at a whole. This article presents our vision of a framework for the validation of the microservice cloud applications, providing an integrated approach for the implementation of various testing methods of such applications, from basic unit tests to continuous stability testing. |
Generating Images from Captions with Attention | Motivated by the recent progress in generative models, we introduce a model that generates images from natural language descriptions. The proposed model iteratively draws patches on a canvas, while attending to the relevant words in the description. After training on MS COCO, we compare our models with several baseline generative models on image generation and retrieval tasks. We demonstrate our model produces higher quality samples than other approaches and generates images with novel scene compositions corresponding to previously unseen captions in the dataset. For more details, visit http://arxiv.org/abs/ 1511.02793. |
Duality of Hardy and BMO spaces associated with operators with heat kernel bounds | The introduction and development of Hardy and BMO spaces on Euclidean spaces R in the 1960s and 1970s played an important role in modern harmonic analysis and applications in partial differential equations. These spaces were studied extensively in [32], [22], [18], [19], [31] and many others. An L function f on R is in the Hardy space H(R) if the area integral function of the Poisson integral e−t √ f satisfies |
Non-pharmacological interventions for breathlessness in advanced stages of malignant and non-malignant diseases. | BACKGROUND
Breathlessness is a common and distressing symptom in the advanced stages of malignant and non-malignant diseases. Appropriate management requires both pharmacological and non-pharmacological interventions.
OBJECTIVES
The primary objective was to determine the effectiveness of non-pharmacological and non-invasive interventions to relieve breathlessness in participants suffering from the five most common conditions causing breathlessness in advanced disease.
SEARCH STRATEGY
We searched the following databases: The Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CINAHL, British Nursing Index, PsycINFO, Science Citation Index Expanded, AMED, The Cochrane Pain, Palliative and Supportive Care Trials Register, The Cochrane Database of Systematic Reviews, and Database of Abstracts of Reviews of Effectiveness in June 2007. We also searched various websites and reference lists of relevant articles and textbooks.
SELECTION CRITERIA
We included randomised controlled and controlled clinical trials assessing the effects of non-pharmacological and non-invasive interventions to relieve breathlessness in participants described as suffering from breathlessness due to advanced stages of cancer, chronic obstructive pulmonary disease (COPD), interstitial lung disease, chronic heart failure or motor neurone disease.
DATA COLLECTION AND ANALYSIS
Two review authors independently assessed relevant studies for inclusion. Data extraction and quality assessment was performed by three review authors and checked by two other review authors. Meta-analysis was not attempted due to heterogeneity of studies.
MAIN RESULTS
Forty-seven studies were included (2532 participants) and categorised as follows: single component interventions with subcategories of walking aids (n = 7), distractive auditory stimuli (music) (n = 6), chest wall vibration (CWV, n = 5), acupuncture/acupressure (n = 5), relaxation (n = 4), neuro-electrical muscle stimulation (NMES, n = 3) and fan (n = 2). Multi-component interventions were categorised in to counselling and support (n = 5), breathing training (n = 3), counselling and support with breathing-relaxation training (n = 2), case management (n = 2) and psychotherapy (n = 2). There was a high strength of evidence that NMES and CWV could relieve breathlessness and moderate strength for the use of walking aids and breathing training. There is a low strength of evidence that acupuncture/acupressure is helpful. There is not enough data to judge the evidence for distractive auditory stimuli (music), relaxation, fan, counselling and support, counselling and support with breathing-relaxation training, case management and psychotherapy. Most studies have been conducted in COPD patients, only a few studies included participants with other conditions.
AUTHORS' CONCLUSIONS
Breathing training, walking aids, NMES and CWV appear to be effective non-pharmacological interventions for relieving breathlessness in advanced stages of disease. |
An Efficient Oblivious Database for the Public Cloud | Hardware enclaves such as Intel SGX are a promising technology to increase the security of databases outsourced to the cloud. These enclaves provide an execution environment isolated from the hypervisor/OS, and encryption of data in memory. However, for applications that use large amounts of memory—including most realistic databases—enclaves do not protect against access pattern leaks, where an attacker observes which locations in memory are accessed. The näıve way to address this issue, using Oblivious RAM (ORAM) primitives, adds prohibitive overhead. In this paper, we propose ObliDB, a database that co-designs both its data structures (e.g., oblivious B+ trees) and physical operators to accelerate oblivious relational queries, giving up to 329× speedup over näıve ORAM. On analytics workloads, ObliDB ranges from competitive to 19× faster than previous oblivious systems designed only for analytics, such as Opaque, and comes within 2.6× of Spark SQL. Moreover, ObliDB also supports point queries, insertions, and deletions with latencies of 3–10ms, which is 7–22× faster than previously published oblivious data structures, and makes ObliDB suitable for transactional workloads too. To our knowledge, ObliDB is the first general-purpose oblivious database to approach practical performance. PVLDB Reference Format: Saba Eskandarian and Matei Zaharia. An Efficient Oblivious Database for the Public Cloud. PVLDB, 11 (4): xxxx-yyyy, 2017. DOI: https://doi.org/TBD |
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