Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel Support Vector Machines in Practice

In this paper, we evaluate the performance of various parallel optimization methods for Kernel Support Vector Machines on multicore CPUs and GPUs. In particular, we provide the first comparison of algorithms with explicit and implicit parallelization. Most existing parallel implementations for multi-core or GPU architectures are based on explicit parallelization of Sequential Minimal Optimization (SMO)---the programmers identified parallelizable components and hand-parallelized them, specifically tuned for a particular architecture. We compare these approaches with each other and with implicitly parallelized algorithms---where the algorithm is expressed such that most of the work is done within few iterations with large dense linear algebra operations. These can be computed with highly-optimized libraries, that are carefully parallelized for a large variety of parallel platforms. We highlight the advantages and disadvantages of both approaches and compare them on various benchmark data sets. We find an approximate implicitly parallel algorithm which is surprisingly efficient, permits a much simpler implementation, and leads to unprecedented speedups in SVM training.
Nitrous oxide persistently alleviates pain hypersensitivity in neuropathic rats: A dose-dependent effect

Currently, for patients experiencing neuropathic pain, there are no common analgesic drugs that produce meaningful relief. Although nitrous oxide (N2O) is a weak analgesic and there are concerns regarding its deleterious effects, reviews of current controversies have concluded that it should remain an option in anesthesia. The authors of this study had two objectives: to evaluate the lowest N2O concentration and the shortest time of N2O postinjury exposure that would produce persistent relief of neuropathic pain; and to compare the effects of N2O with gabapentin.
Interactive High-Resolution Boundary Surfaces for Deformable Bodies with Changing Topology

Recent work has demonstrated that composite finite-elements provide an effective means for physically based modeling of deformable bodies. In this paper we present a number of highly effective improvements of previous work to allow for a high-performance and high-quality simulation of boundary surfaces of deformable bodies with changing topology, for instance, due to cuts and incisions. Starting at a coarse resolution simulation grid, along a cut we perform an adaptive octree refinement of this grid down to a desired resolution and iteratively pull the fine level finite-element equations to the coarse level. In this way, the fine level dynamics can be approximated with a small number of degrees of freedom at the coarse level. By embedding the hierarchical adaptive composite finite-element scheme into a geometric multigrid solver, and by exploiting the fact that during cutting only a small number of cells are modified in each time step, high update rates can be achieved for high resolution surfaces at very good approximation quality. To construct a high quality surface that is accurately aligned with a cut, we employ the dual-contouring approach on the fine resolution level, and we instantly bind the constructed triangle mesh to the coarse grid via geometric constrains.
Self-Rated Health Status and Cardiorespiratory Fitness in a Sample of Schoolchildren from Bogotá, Colombia. The FUPRECOL Study

To evaluate the relationship between Self-Rated Health (SRH) and cardiorespiratory fitness (CRF) in a sample of children and adolescents enrolled in official schools in Bogotá, Colombia. A cross-sectional study was performed with 7402 children and adolescents between 9 and 17 years of age. Participants were asked to rate their health based on eight validated questions, addressing the participants propensity for headache, stomach-ache, backache, feeling-low, irritability/bad mood, nervousness, sleeping-difficulties, and dizziness. The choices were “rarely or never”, “almost every month”, “almost every week”, and “more than once a week/about every day”. Participants performed the international course-navette shuttle run test to estimate CRF, and cut-off points for age and gender were used to categorize the healthy/unhealthy fitness zone according to the FITNESSGRAM® criteria. Overall, 16.4% of those surveyed reported a perception of irritability/bad mood “more than once a week/about every day”, followed by feeling-low and nervousness (both with 9.9%). Dizziness had the lowest prevalence with a percentage of 6.9%. Unhealthy CRF in boys increased the likelihood of headaches by 1.20 times, stomach aches by 1.31 times, feeling-low by 1.29 times, nervousness by 1.24 times, and dizziness by 1.29 times. In girls, unhealthy CRF increased the likelihood of headaches by 1.19 times, backache by 1.26 times, feeling-low by 1.28 times, irritability/bad mood by 1.17 times, sleeping-difficulties by 1.20 times, and dizziness by 1.27 times. SRH was associated with CRF in both genders. Early identification of children and adolescents with low CRF levels will permit interventions to promote healthy behaviors and prevent future diseases during adulthood.
Cancer incidence among workers exposed to softwood dust in Lithuania

Objectives The aim of this study was to assess cancer incidence in a cohort of woodworkers exposed to softwood dust in a Lithuanian wooden joinery products factory. Methods The study population consisted of 1518 workers (1080 men and 438 women) employed in the factory for at least 1 year between 1947 and 1996 and living in Lithuania on 1 January 1978, when the follow-up for cancer incidence began. The follow-up period for cancer was 1978–2007. Cancer risk was assessed by standardised incidence ratios (SIR) with reference to the national population. Results Overall cancer incidence was not increased among woodworkers. However, the number of mouth and pharynx cancer cases among male woodworkers was significantly increased compared with expected numbers (SIR 2.19, 95% CI 1.17 to 3.74). A higher risk was found for cancer of the buccal cavity than for pharyngeal cancer (SIRs 2.83 and 1.45, respectively). The SIR for larynx cancer was also elevated (SIR 1.39, 95% CI 0.64 to 2.64) among men, while the number of lung cancer cases was higher than expected only among women (SIR 2.07, 95% CI 00.57 to 5.31). Conclusions This results of this study support the hypothesis that exposure to softwood dust may increase the risk of oral and pharyngeal cancer. No support was found for an increased risk of other respiratory cancers among workers exposed to softwood dust.
Major pulmonary embolism: review of a pathophysiologic approach to the golden hour of hemodynamically significant pulmonary embolism.

Major pulmonary embolism (PE) results whenever the combination of embolism size and underlying cardiopulmonary status interact to produce hemodynamic instability. Physical findings and standard data crudely estimate the severity of the embolic event in patients without prior cardiopulmonary disease (CPD) but are unreliable indicators in patients with prior CPD. In either case, the presence of shock defines a threefold to sevenfold increase in mortality, with a majority of deaths occurring within 1 h of presentation. A rapid integration of historical information and physical findings with readily available laboratory data and a structured physiologic approach to diagnosis and resuscitation are necessary for optimal therapeutics in this "golden hour. " Echocardiography is ideal because it is transportable, and is capable of differentiating shock states and recognizing the characteristic features of PE. Spiral CT scanning is evolving to replace angiography as a confirmatory study in this population. Thrombolytic therapy is acknowledged as the treatment of choice, with embolectomy reserved for those in whom thrombolysis is contraindicated.
Creating programming languages for ( and from ) the internet

Programming language design is essentially a quest for appropriate abstractions. Each new application domain brings new issues that may suggest new abstractions. The challenge for the language designer is to match abstraction to issueions. The challenge for the language designer is to match abstraction to issue in a way that is minimally disruptive. We explore the ways in which one might build a language framework that is truly internet-centric, in the twin senses of leveraging the internet to construct languages dynamically, and of improving the programmability of internet applications using such dynamically-constructed languages. We suggest that internet programming may not simply be facilitated by such technology but may actually depend upon it for building the next generation of pervasively-connected devices
Optimization of JADE using a novel optimally weighted joint diagonalization approach

The JADE algorithm (Cardoso and Souloumiac, 1993) is a popular batch-type algorithm for Blind Source Separation (BSS), which employs approximate joint diagonalization (AJD) of fourth-order cumulant matrices, following a whitening stage. In this paper we propose a computationally attractive optimization of JADE for noiseless mixtures, in the form of a post-processing tool. First, we cast the AJD of 4th- and 2nd- order estimated matrices as a weighted least-squares (WLS) problem. We then show (under some commonly met conditions), that in the vicinity of a non-mixing condition (such as at the output of traditional JADE), the asymptotically optimal WLS criterion can be easily formulated and conveniently optimized via a novel algorithm, which uses non-unitary AJD of transformed subsets of the estimated matrices. Optimality with respect to general mixing is maintained, as we show, thanks to the equivariance of the optimal WLS solution. The performance of the new algorithm is analyzed and compared to JADE, identifying the conditions for most pronounced improvement, as demonstrated by simulation.
Differentially Private Variational Inference for Non-conjugate Models

Many machine learning applications are based on data collected from people, such as their tastes and behaviour as well as biological traits and genetic data. Regardless of how important the application might be, one has to make sure individuals' identities or the privacy of the data are not compromised in the analysis. Differential privacy constitutes a powerful framework that prevents breaching of data subject privacy from the output of a computation. Differentially private versions of many important Bayesian inference methods have been proposed, but there is a lack of an efficient unified approach applicable to arbitrary models. In this contribution, we propose a differentially private variational inference method with a very wide applicability. It is built on top of doubly stochastic variational inference, a recent advance which provides a variational solution to a large class of models. We add differential privacy into doubly stochastic variational inference by clipping and perturbing the gradients. The algorithm is made more efficient through privacy amplification from subsampling. We demonstrate the method can reach an accuracy close to non-private level under reasonably strong privacy guarantees, clearly improving over previous sampling-based alternatives especially in the strong privacy regime.
Automatic assessment and analysis of public speaking anxiety: A virtual audience case study

Public speaking has become an integral part of many professions and is central to career building opportunities. Yet, public speaking anxiety is often referred to as the most common fear in everyday life and can hinder one's ability to speak in public severely. While virtual and real audiences have been successfully utilized to treat public speaking anxiety in the past, little work has been done on identifying behavioral characteristics of speakers suffering from anxiety. In this work, we focus on the characterization of behavioral indicators and the automatic assessment of public speaking anxiety. We identify several indicators for public speaking anxiety, among them are less eye contact with the audience, reduced variability in the voice, and more pauses. We automatically assess the public speaking anxiety as reported by the speakers through a self-assessment questionnaire using a speaker independent paradigm. Our approach using ensemble trees achieves a high correlation between ground truth and our estimation (r=0.825). Complementary to automatic measures of anxiety, we are also interested in speakers' perceptual differences when interacting with a virtual audience based on their level of anxiety in order to improve and further the development of virtual audiences for the training of public speaking and the reduction of anxiety.
Epidemiology and Results of Treatment of Colorectal Cancer in Poland.

Cancer is a serious social and economic problem of the modern world. It is one of the most dangerous threats to human health and life. The formation of malignant tumours is a combined result of genetic predispositions and the level of exposure to exogenous and endogenous carcinogens. The starting point for all epidemiological examinations concerning cancer are the three following elements: first of all those who have been touched by the illness, place and time of appearance. Comparison is, however, the main reason for conducting epidemiological research. Results from various time periods, the incidence of the illness or deaths in a given city, region with its appearance in other territories, based on sex, age and all sort of occupational groups are compared. To draw such comparisons, it is necessary to use all available measuring methods, such as narrative descriptions that determine the frequency of incidence (spread) of the disease entity in a given population in respective years taking into account sex, age, occupation, marital status, etc. It allows to determine essential factors that illustrate the epidemiological state of a given population. These factors are: incidence, prevalence, mortality and fatality. According to the estimated data of GLOBOCAN (WHO-World Health Organization), in 2012, there were 14,1 million people worldwide diagnosed with cancer. That same year, 8,2 million deaths provoked by cancer were registered and there were 32,6 people living with cancer within 5 years from the diagnosis. That year in Europe 3,737 million new cases were registered, 1,932 million people died and 9,750 million people had been alive 5 years after the diagnosis. In the European Union, 2,657 cases, 1,276 million deaths and 7,246 million people that survived 5 years since the diagnosis were registered (1). However in Poland, in 2011, 144,336 thousand new cases of cancer were registered (71,786 men 72,550 women) and 92,198 thousand deaths (51,554 men and 40,644 women) (2).
Human Neuroscience Original Research Article an Abundance of Riches: Cross-task Comparisons of Semantic Richness Effects in Visual Word Recognition

There is considerable evidence (e.g., Pexman et al., 2008) that semantically rich words, which are associated with relatively more semantic information, are recognized faster across different lexical processing tasks.The present study extends this earlier work by providing the most comprehensive evaluation to date of semantic richness effects on visual word recognition performance. Specifically, using mixed effects analyses to control for the influence of correlated lexical variables, we considered the impact of number of features , number of senses, semantic neighborhood density, imageability, and body–object interaction across five visual word recognition tasks: standard lexical decision, go/no-go lexical decision, speeded pronunciation, progressive demasking, and semantic classification. Semantic richness effects could be reliably detected in all tasks of lexical processing, indicating that semantic representations, particularly their imaginal and featural aspects, play a fundamental role in visual word recognition. However, there was also evidence that the strength of certain richness effects could be flexibly and adaptively modulated by task demands, consistent with an intriguing interplay between task-specific mechanisms and differentiated semantic processing. Although the ultimate goal of reading is to extract meaning from visually printed words, the effect of meaning-level influences on lexical processing is surprisingly poorly understood (see Pexman, in press, for a recent review; see also Balota et al., 1991). For the most part, the empirical literature has focused on how sublexi-cal (see Carreiras and Grainger, 2004) and lexical (see Balota et al., 2006) representations influence visual word recognition. Likewise, despite their complexity and theoretical sophistication, influential computational models of visual word recognition (e.g., Perry et al., 2007) are silent on the role of semantic information (but see Harm and Seidenberg, 2004). Indeed, semantic effects are difficult to reconcile with classic logogen-based models of word recognition , which implicitly assume that lexical processing latencies tap a magic moment (Balota, 1990), i.e., a discrete moment in time when the lexical entry for a word has been identified but meaning-level information has not yet been accessed. suggests that a word associated with relatively more semantic information can be considered to be semantically richer, and word recognition is generally facilitated for such words. A number of dimensions have been identified that appear to tap a word's semantic richness, including: (1) the number of features (NF) associated with its referent, (2) its semantic neighborhood density (SND) in high-dimensional semantic space, (3) the number of distinct first associates (NoA) elicited by the word in a free-association task …
Role of the Gut Microbiota in Osteoarthritis, Rheumatoid Arthritis, and Spondylarthritis: An Update on the Gut–Joint Axis

Dysregulation of the gut microbiota and their metabolites is involved in the pathogenic process of intestinal diseases, and several pieces of evidence within the current literature have also highlighted a possible connection between the gut microbiota and the unfolding of inflammatory pathologies of the joints. This dysregulation is defined as the “gut-joint axis” and is based on the joint–gut interaction. It is widely recognized that the microbiota of the gut produce a variety of compounds, including enzymes, short-chain fatty acids, and metabolites. As a consequence, these proinflammatory compounds that bacteria produce, such as that of lipopolysaccharide, move from the “leaky gut” to the bloodstream, thereby leading to systemic inflammation which then reaches the joints, with consequences such as osteoarthritis, rheumatoid arthritis, and spondylarthritis. In this state-of-the-art research, the authors describe the connections between gut dysbiosis and osteoarthritis, rheumatoid arthritis, and spondylarthritis. Moreover, the diagnostic tools, outcome measures, and treatment options are elucidated. There is accumulating proof suggesting that the microbiota of the gut play an important part not only in immune-mediated, metabolic, and neurological illnesses but also in inflammatory joints. According to the authors, future studies should concentrate on developing innovative microbiota-targeted treatments and their effects on joint pathology as well as on organizing screening protocols to predict the onset of inflammatory joint disease based on gut dysbiosis.
Directory of clinical databases: improving and promoting their use

Background: The controversy surrounding the actual and potential use of clinical databases partly reflects the huge variation in their content and quality. In addition, use of existing clinical databases is severely limited by a lack of knowledge of their availability. Objectives: To develop and test a standardised method for assessing the quality (completeness and accuracy) of clinical databases and to establish a web based directory of databases in the UK. Methods: An expert group was set up (1) to establish the criteria for inclusion of databases; (2) to develop a quality assessment instrument with high content validity, based on epidemiological theory; (3) to test empirically, modify, and retest the acceptability to database custodians, face validity and floor/ceiling effects; and (4) to design a website. Results: Criteria for inclusion of databases were the provision of individual level data; inclusion in the database defined by a common circumstance (e.g. condition, treatment), an administrative arrangement, or an adverse outcome; and inclusion of data from more than one provider. A quality assessment instrument consisting of 10 items (four on coverage, six on reliability and validity) was developed and shown to have good face and content validity, no floor/ceiling effects, and to be acceptable to database custodians. A website (www.docdat.org) was developed. Indications over the first 18 months (number of visitors to the site) are that it is increasingly popular. By November 2002 there were around 3500 hits a month. Conclusions: A website now exists where visitors can identify clinical databases in the UK that may be suitable to meet their aims. It is planned both to develop a local version for use within a hospital and to encourage similar national systems in other countries.
Low state complexity block codes via convolutional codes

A new class of block codes with low state complexity of their conventional trellis representations called double zero-tail terminated convolutional codes (DZT codes) is introduced. It is shown that there exist DZT-codes meeting the Varshamov-Gilbert bound on the minimum distance and having asymptotically optimal state complexity. Two ways of constructing DZT-codes are considered. Examples of DZT-codes meeting a lower bound on the state complexity are given.
Implementation requirements for automated fault data analytics in power systems

Summary This paper addresses implementation requirements for a fully automated substation data integration and fault analysis for power system transmission lines. The approach is based on measurements from substation intelligent electronic device recordings. The proposed architecture provides a transparent approach to substation data management, analytics functions, as well as the visualization of the integrated data and analytics results. When combined with an efficient communication and data collection scheme, the solution bridges the gap between traditionally separated non-operational and operational data. The fault analytics results, traditionally obtained through off-line manual process, can now be used in an automated way to support on-line decisions when operating or restoring the power system. The solution is open for further expansions and interfacing to third-party systems. The paper illustrates implementation examples and provides initial in-house and field test results. Copyright © 2014 John Wiley & Sons, Ltd.