Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing pain in critically ill brain-injured patients: a psychometric comparison of three pain scales and videopupillometry.

Three clinical scales (the Nociception-Coma-Scale adapted for Intubated-patients (NCS-I), its Revised version (NCS-R-I), and the Behavioral-Pain-Scale (BPS)) and videopupillometry were compared for measuring pain in intubated, non-communicating, critically ill, brain-injured (CIBI) patients. Pain assessment was performed before, during, just after and 5-min after three procedures: the reference non-nociceptive procedure (assessment of the Richmond-Agitation-Sedation-Scale), and two nociceptive procedures (turning and tracheal-suctioning). The primary-endpoint was construct validity (discriminant and criterion validation), determined by comparing pain measurements between different times/procedures. Secondary-endpoints were internal consistency, interrater reliability and feasibility. Fifty patients (54% women, median age 63-yr [56-68]) were included 13 [7-24] days after brain-injury (76% hemorrhagic or ischemic strokes). All tools increased significantly more (p<0.001) during the nociceptive procedures versus the non-nociceptive procedure. The BPS was the only pain tool that did not increase significantly during the non-nociceptive procedure (p=0.41), suggesting that it was the most discriminant tool. BPS, NCS-I and NCS-R-I were good predictors of nociception with areas-under-thecurves (AUC) ≥0.96, contrary to videopupillometry (AUC=0.67). The BPS, NCS-I and NCS-I-R had high interrater reliabilities (weighted-kappa=0.86, 0.82 and 0.84, respectively). Internal consistency was moderate (>0.60) for all pain-scales. Factor-analysis represented a majority of information on a first dimension, with motor domains represented on a second dimension. Scale feasibility was better for NCS-I and NCS-R-I than for BPS. In conclusion, BPS, NCS-I and NCS-R-I are valid, reliable and acceptable pain-scales for use in intubated CIBI patients, unlike videopupillometry. Future research requires tool design centered on domains of observation adapted to this very specific population.
Education trajectories and malpractice complaints—A study among Danish general practitioners

Abstract Malpractice litigation is an increasing concern in general practice and other healthcare services but possibly is susceptible to changes in education schemes. In this study using Danish register data, we aimed to investigate the association between general practitioners’ risk of becoming involved in a malpractice complaint in a 1-year time frame and their educational trajectory. Greater age at graduation was associated with increased odds of later complaints, but decreased odds of complaints leading to critique by a disciplinary board. In addition, the time following specialisation, in particular, was associated with increased odds of complaints. Complaint occurrence appeared unrelated to place of education. These findings suggest that, from the point of view of complaints, attention may reasonably be drawn to the significance of medical education and continuing professional development.
Timing of Antiretroviral Therapy and Systemic Inflammation in Sub-Saharan Africa: Results From the META Longitudinal Cohort Study

Chronic inflammation predicts complications in persons with human immunodeficiency virus infection. We compared D-dimer, soluble CD14, and interleukin 6 levels before and 12 months after antiretroviral therapy (ART) initiation, among individuals starting ART during earlier-stage (CD4 T-cell count >350/µL) or late-stage disease (CD4 T-cell count <200/µL). Female sex, older age, viral load, and late-stage disease were associated with pre-ART biomarkers (n = 661; P < .05). However, there were no differences in biomarkers by disease stage after 12 months of ART (n = 438; P > .05), owing to loss from observation and greater declines in biomarkers in late-stage initiators (P < .001). Earlier initiation of ART is associated with decreased inflammation, but levels seem to converge between earlier and later initiators surviving to 12 months.
Dynamic models in space and time

This paper presents a first-order autoregressive distributed lag model in both space and time. It is shown that this model encompasses a wide series of simpler models frequently used in the analysis of space-time data as well as models that better fit the data and have never been used before. A framework is developed to determine which model is the most likely candidate to study space-time data. As an application, the relationship between the labor force participation rate and the unemployment rate is estimated using regional data of Germany, France and the UK derived from Eurostat, 1983-1993.
An Eight-Dimensional Systematic Evaluation of Optimized Search Algorithms on Modern Processors

Searching in sorted arrays of keys is a common task with a broad range of applications. Often searching is part of the performance critical sections of a database query or index access, raising the question what kind of search algorithm to choose and how to optimize it to obtain the best possible performance on real-world hardware. This paper strives to answer this question by evaluating a large set of optimized sequential, binary and k-ary search algorithms on a modern processor. In this context, we consider hardware-sensitive optimization strategies as well as algorithmic variations resulting in an eight-dimensional evaluation space. As a result, we give insights on expected interactions between search algorithms and optimizations on modern hardware. In fact, there is no single best optimized algorithm, leading to a set of advices on which variants should be considered first given a particular array size.
Multi-Module Recurrent Neural Networks with Transfer Learning

This paper describes multiple solutions designed and tested for the problem of word-level metaphor detection. The proposed systems are all based on variants of recurrent neural network architectures. Specifically, we explore multiple sources of information: pre-trained word embeddings (Glove), a dictionary of language concreteness and a transfer learning scenario based on the states of an encoder network from neural network machine translation system. One of the architectures is based on combining all three systems: (1) Neural CRF (Conditional Random Fields), trained directly on the metaphor data set; (2) Neural Machine Translation encoder of a transfer learning scenario; (3) a neural network used to predict final labels, trained directly on the metaphor data set. Our results vary between test sets: Neural CRF standalone is the best one on submission data, while combined system scores the highest on a test subset randomly selected from training data.
An Automatic Method for Creating a Sense-Annotated Corpus Harvested from the Web

This paper reports on an automatic and language-independent method for compiling a sense-annotated corpus of web data. To validate its language-independence, the method has been applied to English and German. The sense inventories are taken from the Princeton WordNet for English and from the German wordnet GermaNet. The web-harvesting utilizes existing mappings of WordNet and GermaNet to the English and German versions of the web-based dictionary Wiktionary, respectively. The data obtained by this method have resulted in the English WebCAP (short for: Web-Harvested Corpus Annotated with Princeton WordNet Senses) and the German WebCAGe (short for: Web-Harvested Corpus Annotated with GermaNet Senses) resources.
An Investigation of Teachers' Attitudes towards Children with Asperger's Syndrome.

The purpose of this research is to measure the teachers’ awareness of, and attitudes towards children with Asperger’s Syndrome (AS, hereafter). The main intention was to sample primary school teachers; however time constraints dictated that the 30 teachers (male and female), who participated in this study, were postgraduate students and teaching staff. The instrument used in this study was a questionnaire that consisted of 34 items; 15 on attitude and 15 on knowledge. The independent variables were gender, age and experience of teaching children with Special Educational Needs; the dependent variables were knowledge of and attitude towards children with AS. The responses were subjected to a range of tests which, in the first place, showed there were some problems with the design of the questionnaire, also that responses were not a normal distribution, so the chosen tests were non-parametric, mainly Mann-Whitney U test. Very few differences in knowledge or attitude were found among the different groups of teachers. No significant differences in either knowledge or attitude were found in age or gender. The one interesting finding was that whilst teachers with experience of teaching children with Special Educational Needs (SEN, hereafter) had more knowledge, they were no more likely to have positive attitudes than others.
Inside the Query Space of DL Knowledge Bases

We structure the query space of DL knowledge bases (KBs) by finding equivalent and partial ordering relations between answer sets of conjunctive queries, and defining a formal graph structure that allows qualitative and quantitative exploration of the query space. We also discuss how to compute such a graph for restricted DL-LiteR KBs.
A Partially Rule-Based Approach to AMR Generation

This paper presents a new approach to generating English text from Abstract Meaning Representation (AMR). In contrast to the neural and statistical MT approaches used in other AMR generation systems, this one is largely rule-based, supplemented only by a language model and simple statistical linearization models, allowing for more control over the output. We also address the difficulties of automatically evaluating AMR generation systems and the problems with BLEU for this task. We compare automatic metrics to human evaluations and show that while METEOR and TER arguably reflect human judgments better than BLEU, further research into suitable evaluation metrics is needed.
Neurobehavioral Mechanisms of Resilience Against Emotional Distress: An Integrative Brain-Personality-Symptom Approach Using Structural Equation Modeling

Abstract Clarifying individual differences that predict resilience or vulnerability to emotional distress is crucial for identifying etiological factors contributing to affective disturbances, and to promoting emotional well-being. Despite recent progress identifying specific brain regions and personality traits, it remains unclear whether there are common factors underlying the structural aspects of the brain and the personality traits that, in turn, protect against symptoms of emotional distress. In the present study, an integrative structural equation model was developed to examine the associations among (1) a latent construct of Control, representing the volumes of a system of prefrontal cortical (PFC) regions including middle, inferior, and orbital frontal cortices; (2) a latent construct of Resilience personality traits including cognitive reappraisal, positive affectivity, and optimism; and (3) Anxiety and Depression symptoms, in a sample of 85 healthy young adults. Results showed that the latent construct of PFC volumes positively predicted the latent construct of Resilience, which in turn negatively predicted Anxiety. Mediation analysis confirmed that greater latent PFC volume is indirectly associated with lower Anxiety symptoms through greater latent trait Resilience. The model did not show a significant mediation for Depression. These results support the idea that there are common volumetric and personality factors that help protect against symptoms of emotional distress. These findings provide strong evidence that such brain-personality-symptom approaches can provide novel insights with valuable implications for understanding the interaction of these factors in healthy and clinically diagnosed individuals.
Adding an integration and global asymptotic stabilization of feedforward systems

We are concerned with systems which generalize the form x/spl dot/=h(y,u), y/spl dot/=f(y,u), where the state components x integrates functions of the others components y and the inputs u. We give sufficient conditions under which global asymptotic stabilizability of the y-subsystem (represented by saturated control) implies global asymptotic stabilizability of the overall system. This is established by an explicit Lyapunov design of the control law. We show how it serves as a basic tool to be used, may be recurrently, to deal with more complex systems. In particular the stabilization problem of the so called feedforward systems is solved this way. <<ETX>>
HMD-TMO: A Tone Mapping Operator for 360° HDR Images Visualization for Head Mounted Displays

We propose a Tone Mapping Operator, denoted HMD-TMO, dedicated to the visualization of 360 ◦ High Dynamic Range images on Head Mounted Displays. The few existing studies about this topic have shown that the existing Tone Mapping Operators for classic 2D images are not adapted to 360 ◦ High Dynamic Range images. Consequently, several dedicated operators have been proposed. Instead of operating on the entire 360 ◦ image, they only consider the part of the image currently viewed by the user. Tone mapping a part of the 360 ◦ image is less challenging as it does not preserve the global luminance dynamic of the scene. To cope with this problem, we propose a novel tone mapping operator which takes advantage of both a view-dependant tone mapping that enhances the contrast, and a Tone Mapping Operator applied to the entire 360 ◦ image that preserves global coherency. Furthermore, we present a subjective study to model lightness perception in a Head Mounted Display.
Statin Therapy on Insulin Resistance and Plasma Level of Adiponectin in Non-Diabetic, Hypercholesterolemic Patients

Background: Adiponectin is an adipocyte-derived plasma protein with various anti-atherogenic properties. However, the effect of statins on insulin sensitivity and plasma level of adiponectin remains controversial. Methods: Forty-eight non-diabetic, hypercholesterolemic patients were enrolled and assigned to statin treatment (atorvastatin 10 or 40 mg) group (n = 27) or no statin treatment group (n = 21). In addition, another 20 age- and sex-matched non-diabetic, normocholesterolemic patients were enrolled as control group. Insulin sensitivity (indicated by HOMAindex) and plasma level of adiponectin were determined before and 6 weeks after treatment in all patients. Results: The HOMAindex (1.76 0.81 vs. 1.42 0.57, p = 0.09) and adiponectin level (8.22 2.83g/dl vs. 9.23 4.36g/dl, p = 0.26) were similar between hypercholesterolemic and normocholesterolemic patients. The treatment with statin did not affect the fasting plasma level of glucose, insulin or HOMAindex, suggesting the neutral effects of statins on insulin sensitivity. However, the treatment with statin significantly reduced the plasma level of adiponectin (from 8.6 3.1g/ml to 7.8 3.2g/ml, P= 0.01). All of these variables did not change in the no statin treatment group. Conclusion: The result of this study showed that the insulin sensitivity and the plasma level of adiponectin were similar between hypercholesterolemic and normocholesterolemic non-diabetic patients. Although treatment with statins for 6 weeks did not deteriorate insulin sensitivities, the plasma level of adiponectin significantly decreased.
Genetic admixture analysis in Prestice Black-Pied pigs

Abstract. The Prestice Black-Pied pig (PC) is a genetic resource of the Czech Republic. Information about boar variability has been provided in preceding papers. The objective of this work was to compare genetic variability of boars and sows. A total of 21 microsatellite markers were used to study genetic diversity and population structure of 149 PC breeding animals. In this paper, current parameters of assessments of diversity in PC are listed. All loci were polymorphic, and a total of 167 alleles were observed across the studied loci. The range of alleles was found to be 4 to 15 with a mean of 7.95. Overall allele frequency ranged from 0.07 to 0.25. The calculated observed and expected heterozygosity values were 0.70 and 0.73, respectively. The polymorphism information content (PIC) was 0.69 and the overall within-population inbreeding estimate (FIS) was 0.04. Genetic differentiation and population subdivision were tested. The level of admixture of breeds used for improvement of the PC breed was evaluated (Landrace, Large White and Pietrain). Five percent of analysed PC breeding boars had more than 20% admixture of other monitored breeds. The obtained results are important for the future sustainability of this local breed.
Effects of Symbol Sets and Needs Gratifications on Audience Engagement: Contextualizing Police Social Media Communication

We propose a research model based on media synchronicity theory (MST) and examine how the use of different symbol sets (e.g., images and text) is related to audience engagement on social media. We include uses and gratifications theory (UGT) in the model to identify task characteristics that are relevant to message recipients in the specific context of community policing. Based on our analyses of Facebook posts by five police departments, we find first that, consistent with MST, posts conveying information garner more responses when accompanied by more natural symbol sets, and more textual content is preferred to less, but responses differ depending on the type of engagement: intimacy (likes), interaction (comments), or influence (shares). Second, posts intended for meaning convergence gratify the audience’s socialization and assistance needs and are positively related to intimacy and interaction. Finally, the fit between symbol sets and task characteristics impacts different dimensions of audience engagement. These findings provide empirical support for relying on MST when studying social media and for integrating with UGT to capture contextual task characteristics. We conclude the paper with a discussion of the implications of its findings for theory and offer recommendations for practice.
Interactive comment on “Evaluation of uncertainties in mean and extreme precipitation under climate changes for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles” by Antoine

The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed over high resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, the Lez and the Aude located in France, and the Muga, located in northeastern Spain and eight pairs of global and regional climate 15 models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over past period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over past period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher order quantile. The ensemble mean and the spread for future period remain 20 unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the last part of the 21th century.
Verbal Working Memory Skills of Children Who Stutter: A Preliminary Investigation

CONTEMPORARY ISSUES IN COMMUNICATION SCIENCE AND DISORDERS • Volume 32 • 38–42 • Spring 2005 © NSSLHA 1092-5171/05/3201-0038 ABSTRACT: In the field of speech-language pathology, recent attention has focused on the role of verbal working memory in language processing. The current study examined the verbal working memory skills of children who stutter (CWS) via a digit and letter span experiment. The CWS showed significantly reduced recall when compared to an age-matched group of children who do not stutter (CWDS). This effect was apparent across both written and oral response modalities. Implications for the relationship between verbal working memory, phonological development, and stuttering are discussed. Furthermore, we call for more extensive investigation of these associated phenomena among CWS.
An Expressive Sub-language of OWL 2 Full for Domain Meta-modeling

With the motivation of reasoning with real-world, complex domain ontologies in the category of OWL 2 Full, in this paper, we study meta-modeling extension in SROIQ, and propose an expressive sub-language of OWL 2 Full, called Hi(SROIQ), where the same names can be used as classes, roles and individuals simultaneously. For accessing meta-knowledge, meta-queries are introduced by allowing variables to occur in the class and role positions in conjunctive queries. In order to take advantage of the highly optimized reasoners for description logics, we provide a sound and complete way of reducing satisfiability checking and meta-query answering in Hi(SROIQ) to the corresponding reasoning tasks in SROIQ. Based on this, we conclude that meta-modeling extension in SROIQ does not increase the complexity of reasoning.
Permittivity Structure Derived from Group Velocities of Guided GPR Pulses

On a 2D profile of subsurface permittivity structure derived from guided GPR pulses recorded in the Kuparuk River watershed, Alaska, the transition from a stream channel to a peat layer is interpreted. Although multichannel data are used, guided waves are analyzed using single-channel analysis, which sidesteps assumptions regarding lateral homogeneity within receiver arrays. As a result, 2D structure is obtained along a profile using an inversion procedure. These data were processed in three steps: (1) picking group traveltimes, (2) performing tomography in the lateral direction, and (3) inverting local group-velocity dispersion curves. When the permittivity profile obtained from the guided waves is compared to a GPR reflection profile, it is clear that the guided waves capture shallow structure near a stream channel that is not imaged accurately on the reflection profile. This demonstrates the utility of using guided waves to provide information on shallow structure that cannot be obtained from reflections.
Analytic-geometric methods for finite Markov chains
with applications to quasi-stationarity

For a relatively large class of well-behaved absorbing (or killed) finite Markov chains, we give detailed quantitative estimates regarding the behavior of the chain before it is absorbed (or killed). Typical examples are random walks on box-like finite subsets of the square lattice $\mathbb Z^d$ absorbed (or killed) at the boundary. The analysis is based on Poincar\'e, Nash, and Harnack inequalities, moderate growth, and on the notions of John and inner-uniform domains.
Toward Interpretable Music Tagging with Self-Attention

Self-attention is an attention mechanism that learns a representation by relating different positions in the sequence. The transformer, which is a sequence model solely based on self-attention, and its variants achieved state-of-the-art results in many natural language processing tasks. Since music composes its semantics based on the relations between components in sparse positions, adopting the self-attention mechanism to solve music information retrieval (MIR) problems can be beneficial. Hence, we propose a self-attention based deep sequence model for music tagging. The proposed architecture consists of shallow convolutional layers followed by stacked Transformer encoders. Compared to conventional approaches using fully convolutional or recurrent neural networks, our model is more interpretable while reporting competitive results. We validate the performance of our model with the MagnaTagATune and the Million Song Dataset. In addition, we demonstrate the interpretability of the proposed architecture with a heat map visualization.