Miracle-dz/UniFAR-FTUs huggingface dataset:
Thread block compaction for efficient SIMT control flow

Manycore accelerators such as graphics processor units (GPUs) organize processing units into single-instruction, multiple data “cores” to improve throughput per unit hardware cost. Programming models for these accelerators encourage applications to run kernels with large groups of parallel scalar threads. The hardware groups these threads into warps/wavefronts and executes them in lockstep-dubbed single-instruction, multiple-thread (SIMT) by NVIDIA. While current GPUs employ a per-warp (or per-wavefront) stack to manage divergent control flow, it incurs decreased efficiency for applications with nested, data-dependent control flow. In this paper, we propose and evaluate the benefits of extending the sharing of resources in a block of warps, already used for scratchpad memory, to exploit control flow locality among threads (where such sharing may at first seem detrimental). In our proposal, warps within a thread block share a common block-wide stack for divergence handling. At a divergent branch, threads are compacted into new warps in hardware. Our simulation results show that this compaction mechanism provides an average speedup of 22% over a baseline per-warp, stack-based reconvergence mechanism, and 17% versus dynamic warp formation on a set of CUDA applications that suffer significantly from control flow divergence.
Local Invariant Shape Feature for Cartoon Image Retrieval

In this paper, we propose a new method for cartoon image retrieval based on the local invariant shape feature, named Scalable Shape Context. The proposed feature uses the Harris-Laplace corner to localize the key points and corresponding scale in the cartoon image. Then, we use Shape Context to describe the local shape. The feature point matching is achieved by a weighted bipartite graph matching algorithm and the similarity between the query and the indexing image is presented by the match cost. The experimental results show that our method is more efficient than Shape Context and SIFT for the cartoon image retrieval.
The potential of lipocalin-2/NGAL as biomarker for inflammatory and metabolic diseases

Abstract Lipocalin-2 (LCN2), also known as neutrophil gelatinase-associated lipocalin (NGAL), is a secreted glycoprotein that belongs to a group of transporters of small lipophilic molecules in circulation. LCN2 has been recently characterized as an adipose-derived cytokine. This adipokine is believed to bind small substances, such as steroids and lipopolysaccharides, and has been reported to have roles in the induction of apoptosis in hematopoietic cells, transport of fatty acids and iron, modulation of inflammation, and metabolic homeostasis. Recently, LCN2 has emerged as a useful biomarker and rheumatic diseases. This review provides an overview of LCN2 in inflammation, immunity, and metabolism.
Meta-Analysis of 2-Treatment Clinical Trials Including Both Continuous and Dichotomous Results

To expedite the timely creation of medical practice guidelines, a meta-analytic method was developed to combine both dichotomous survival data and continuous physiologic data from multiple studies of differing experimental design, which compare the same innovative clinical intervention to standard care. An aggregate ratio, R*, of the observed treatment effect to a clinically optimal treatment effect for studies in a series is computed and compared to the 95% confidence limit for R* under the null hypothesis. Input data for continuous variables include sample means, standard errors, and sample sizes. Input data for dichotomous variables include group proportions and sizes. The analysis can be done using a simple, 1-page spreadsheet. It allows one to judge biological significance, to test for statistical significance, to compare subgroups of studies, to test for outliers, and to compute the power of the meta-analysis. These features are demonstrated for studies of interposed abdominal compression-cardiopulmonary resuscitation.
Muscular motion estimation from 4-D ultrasound image using Kalman filter and rotation-invariant feature descriptor

Muscular motion estimation in ultrasound images is of great importance for investigating causes of musculoskeletal conditions in pathological examinations. However, the quality of ultrasound images is usually depressed due to speckle noises and temporal decorrelation of speckle patterns, making certain difficulties in motion estimation. To resolve the problem, this paper presents a new model-based tracking method for estimating the perimysium motion from 4-D ultrasound images. From the first frame of the given motion images, the proposed method builds a perimysium model, which consists of 3-D surface and rotation-invariant feature descriptor (RIFD) to characterize its structural and image appearances. Then, the model is applied to the next frame using Kalman filter for estimating the best matching position with the highest similarity of RIFD. The estimation is used to update the motion state for predicting and refining the model position in the next frame. The Kalman filtering is iteratively performed until the entire image sequence is processed. Overall, the proposed method efficiently combines the structure, image and motion priors, so it can overcome the aforementioned difficulties. Experimental results showed that the proposed method can provide reliable and accurate estimation of perimysium motion with tracking errors 6.26 voxels using three 4-D ultrasound volumes.
-1 - Gender and Speaker Identification as a Function of the Number of Channels in Spectrally Reduced Speech. Short Running Title: Gender and Speaker Identification in Spectrally Reduced Speech

Considerable research on speech intelligibility for cochlear-implant users has been conducted using acoustic simulations with normal-hearing subjects. However, some relevant topics about perception through cochlear implants remain scantly explored. The present study examined the perception by normal-hearing subjects of gender and identity of a talker as a function of the number of channels in spectrally reduced speech. Two simulation strategies were compared. They were implemented by two different processors that presented signals as either the sum of sine waves (SW) at the center of the channels or as the sum of noise bands (NB). In Experiment 1, 15 subjects determined the gender of 40 talkers (20 males + 20 females) from a natural utterance processed subjects matched a natural sentence uttered by 10 talkers with the corresponding simulation replicas processed through 3, 4, 8, and 16 channels for each processor. In Experiment 3, 72 subjects performed the same task but different sentences were used for natural and processed stimuli. A control Experiment 4 was conducted to equate the processing steps between the two simulation strategies. Results showed that gender and talker identification was better for the sine-wave processor, and that performance through the noise-band processor was more sensitive to the number of channels. Implications and possible explanations for the superiority of sine-wave simulations are discussed.
Varying body stiffness for aquatic locomotion

Fish excel in their swimming capabilities. These result from a dynamic interplay of actuation, passive properties of fish body, and interaction with the surrounding fluid. In particular, fish are able to exploit wakes that are generated by objects in flowing water. A powerful demonstration that this is largely due to passive body properties are studies on dead trout. Inspired by that, we developed a multi joint swimming platform that explores the potential of a passive dynamic mechanism. The platform has one actuated joint only, followed by three passive joints whose stiffness can be changed online, individually, and can be set to an almost arbitrary nonlinear stiffness profile. In a set of experiments, using online optimization, we investigated how the platform can discover optimal stiffness distribution along its body in response to different frequency and amplitude of actuation. We show that a heterogeneous stiffness distribution - each joint having a different value - outperforms a homogeneous one in producing thrust. Furthermore, different gaits emerged in different settings of the actuated joint. This work illustrates the potential of online adaption of passive body properties, leading to optimized swimming, especially in an unsteady environment.
Mininet Clustering

This paper presents a distributed version of Mininet, an Openflow network emulator. Normally, Mininet emulates an entire network of hosts and switches, each running as a seperate process within a Linux container, all on the same machine. Unfortunately, emulating networks that require more resources than a single machine are currently impossible in Mininet. By extending Mininet with cross-machine virtual links, this work allows researchers to emulate larger and more complex networks. Further, we demonstrate that network topologies can be automatically partitioned across machines, alleviating the otherwise burdensome task of doing so by hand.
Concentrations of Phthalate Metabolites in Milk, Urine, Saliva, and Serum of Lactating North Carolina Women

Background Phthalates are ubiquitous in the environment, but concentrations in multiple media from breast-feeding U.S. women have not been evaluated. Objectives The objective of this study was to accurately measure and compare the concentrations of oxidative monoester phthalate metabolites in milk and surrogate fluids (serum, saliva, and urine) of 33 lactating North Carolina women. Methods We analyzed serum, saliva, urine, and milk for the oxidative phthalate metabolites mono(3-carboxypropyl) phthalate, mono(2-ethyl-5-carboxypentyl) phthalate (MECPP), mono(2-ethyl-5-hydroxyhexyl) phthalate, and mono(2-ethyl-5-oxohexyl) phthalate using isotope-dilution high-performance liquid chromatography tandem mass spectroscopy. Because only urine lacks esterases, we analyzed it for the hydrolytic phthalate monoesters. Results We detected phthalate metabolites in few milk (< 10%) and saliva samples. MECPP was detected in > 80% of serum samples, but other metabolites were less common (3–22%). Seven of the 10 urinary metabolites were detectable in ≥ 85% of samples. Monoethyl phthalate had the highest mean concentration in urine. Metabolite concentrations differed by body fluid (urine > serum > milk and saliva). Questionnaire data suggest that frequent nail polish use, immunoglobulin A, and fasting serum glucose and triglyceride levels were increased among women with higher concentrations of urinary and/or serum phthalate metabolites; motor vehicle age was inversely correlated with certain urinary phthalate concentrations. Conclusions Our data suggest that phthalate metabolites are most frequently detected in urine of lactating women and are less often detected in serum, milk, or saliva. Urinary phthalate concentrations reflect maternal exposure and do not represent the concentrations of oxidative metabolites in other body fluids, especially milk.
Extraction de motifs dans des dialogues annotés par programmation dynamique

Résumé : Dans le cadre de la modélisation du dialogue, nous nous intéressons à la recherche de régularités dans les échanges entre interlocuteurs, et plus particulièrement dans l’expression d’un processus mentaliste. Nous utilisons pour cela une grille mentaliste afin de coder l’expression des états mentaux et des émotions dans les énoncés. Nous présentons une nouvelle heuristique pour calculer des alignements globaux et locaux de motifs en deux dimensions par programmation dynamique. Cette méthode consiste en une généralisation des formules de récurrence utilisées pour les alignements de séquences. A notre connaissance, cette étude est la première qui considère le calcul d’alignements locaux de motifs 2D, qui plus est avec des scores quelconques. Nous avons évalué cette méthode sur la recherche de motifs répétés sur des annotations de dialogues entre parents et enfants de quatre ans lors de la narration de deux histoires enfantines.
Health and Safety Issues associated with Virtual Reality-A Review of Current Literature

VR techniques provide the user with a new and more powerful method of interacting with computers than the traditional techniques of keyboard and mouse. As such, there are many potential VR applications in areas such as entertainment, medicine and engineering and many research groups in the UK and abroad are now investigating this technology with the view to developing commercially viable products. There are various implementations of VR and these can be placed broadly into three categories; desktop, semi-immersive and fully immersive depending on the sophistication of the technologies being used. However, the exploitation of this technology has not been without it’s drawbacks. A number of recent reports have suggested that the use of VR equipment may have unwanted physical, physiological and psychological side-effects. This report provides an overview of current research in this area, the principal findings and the relationship between potential side-effects and the VR implementation being used. It is hoped that this report will provide a thorough overview of the area of VR health and safety for members of the AGOCG user commumity who are considering buying, or already own, a VR system.
Block-LDPC Codes vs Duo-Binary Turbo-Codes for European Next Generation Wireless Systems

In this paper, we investigate the performance-complexity trade-off for two leading-edge channel coding techniques, namely duo-binary turbo-codes (DBTC) and block LDPC codes (BLDPCC). We assess their respective decoding complexity in terms power consumption and cycle delays, as a function of both the code rate and packet length, to derive a domain of suitability for both techniques. We also compare their capabilities to serve as mother codes for rate-compatible punctured codes (RCPC) and finally analyze their achievable throughput, as a function of the degree of parallelism.
A Comprehensive Disfluency Model for Multi-Party Interaction

We present a disuenc y model derived from analysing transcriptions of the AMI meeting corpus. Our model goes beyond previous work in that it discriminates several classes that are elsewhere regarded the same. Furthermore, we provide a formal account for naturally occurring phenomena that are rarely modeled in other schemes. Our annotations show signicant occurrences of these classes. An evaluation of the annotations from four different annotators reveals a high agreement,
The Structural Relationship of personality virtues, authentic personality and Personal Growth Initiative with wisdom in students

The aim of this study was to evaluate the structural relationships of personality virtues, authentic personality and Personal Growth Initiative with wisdom acquisition in students. For this purpose, in a hypothetical structural model plan, which represented a network of direct and indirect relationships between personality virtues, authentic personality, Personal Growth Initiative and wisdom acquisition, 200 students (101 boys and 99 girls) of the University of Isfahan were selected by accessible sampling method. They were evaluated with Values in action inventory of strengths (VIA-72), Authenticity Scale (Wood et al., 2008) Personal Growth Initiative Scale (Robitschek, 1998), and Three-Dimensional Wisdom Scale (Ardelt, 2003). Structural equation modeling indicated that there was a positive and significant relationship between the components of personality virtue and Character Strengths; Authentic Personality; Personal Growth Initiative; and the amount of wisdom in students. Furthermore, the findings indicated that there was a positive relationship among the components of personality virtues, authentic personality and personal growth initiative. The findings supported the appropriateness of the hypothetical structure of the variables. In addition to practical implications, the findings provided a useful framework for identifying the components affecting the process of wisdom growth and acquisition in students.
GA-based support vector machines for adaptive power system damping controller of SMES

This paper proposes the application of support vector machines (SVMs) to design of an adaptive power system damping controller for superconducting magnetic energy storage (SMES). A genetic algorithm is used to optimize the SVM parameters based on k-fold cross-validation. The SVMs for SMES controllers are trained by the data obtained from a multi-machine power system, and the optimal SVM parameters. The SVMs can be adapted by various operating conditions when the power system operates either inside or outside of the training set. Simulation results in a two-area four-machine power system demonstrate that the proposed SVMs for adaptive SMES is much superior to the conventional SMES controller with fixed parameters under various operating conditions and severe disturbances.
Making Dissemination a Two-Way Process

Despite repeated expressions of concern, both academic researchers and programme delivery practitioners have neglected the dissemination of new knowledge about health promotion programmes. This has meant that effective programmes are often not implemented as widely as they could be and that health promotion programmes are not achieving their full potential. This paper analyses what has been written in the published literature about dissemination and discusses the problems from the point of view of practitioners who are involved in programme delivery. Factors influencing dissemination have been well described; yet the dominant notion in the literature is of dissemination as a one-way process, a downstream transfer from a group who produce knowledge to a group who implement programmes. At the same time, there is considerable theoretical and practical evidence that linkage systems between researcher and implementer groups can foster more effective transfer of programmes. From the perspective of those involved in programme delivery, it appears that dissemination is most likely to be influential if it is based on a two-way process of exchanging knowledge between researcher and implementer groups. While linkage systems offer the kind of structure or process to support two-way exchange, they need to overcome significant barriers if they are to become a feature of the health promotion system we work in. Linkage systems must span different organisations, and these organisations do not necessarily have compatible purposes. A two-way construction of dissemination also has implications for how research on dissemination is tackled, and makes apparent how such research could benefit from collaboration with programme delivery practitioners. The irony of dissemination researchÐ that the existing publications and ideas do not have wide currencyÐitself indicates that a new approach that genuinely tackles dissemination as a two-way exchange is essential, if we are to achieve the full benefits of our knowledge in health promotion.
Lens proteomics: the accumulation of crystallin modifications in the mouse lens with age.

PURPOSE To identify modified crystallins associated with aging of lens and produce two-dimensional electrophoresis (2-DE) proteome maps of crystallins in mouse lens. METHODS Lens proteins from mice of increasing age or different strains were separated by either chromatography or 2-DE. Masses of whole proteins or tryptic peptides were analyzed by mass spectrometry. Changes in the abundance of individual crystallins were determined by image analysis of 2-DE gels. RESULTS The measured masses of all known mouse crystallins, with the exception of gammaD and gammaF, matched the masses calculated from their reported sequences. Analysis by 2-DE indicated that most posttranslational modifications took place in mice after 6 weeks of age. Partially degraded crystallins, including betaB1, betaB2, betaB3, betaA3, alphaA, and alphaB, were found in greater proportion in the insoluble fractions. gamma-Crystallins A through F also became insoluble during aging. However, insolubilization of gamma-crystallins was associated with a decrease in isoelectric point (pI). Aging was also associated with increased phosphorylation of soluble alphaA- and alphaB-crystallins, confirmed by mass measurements of these proteins eluted from 2-DE gels. Comparison of protein profiles between several strains of mice used to produce transgenic or knockout models of cataract indicated few differences, except for an additional acidic form of a gamma-crystallin, possibly due to a polymorphism. CONCLUSIONS These results suggest that partial degradation of alpha- and beta-crystallins and increased acidity of gamma-crystallins may cause insolubilization during aging. The 2-DE proteome maps of mouse lens proteins created in this study, using immobilized pH gradients, will be useful for comparison with maps of lens proteins of mice with cataracts so that cataract-specific modifications may be identified.
On-line evolving clustering for financial statements' anomalies detection

This document proposes an approach for financial statements' anomalies detection by using on-line evolving clustering [1]. Official records of the financial activities of a business are called financial statements and they are recorded in journals and general ledger in a supervised process. Anomalies in financial statements are caused by human mistakes during forming of financial statements, or as a result of changes in the software that produced un-expected errors, or as possible financial fraud.
Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.