Miracle-dz/UniFAR-FTUs huggingface dataset:
Trehalose-P synthase of mycobacteria: its substrate specificity is affected by polyanions.

The trehalose-P synthase was purified to near homogeneity from the cytoplasmic fraction of Mycobacterium smegmatis. At the final stage of purification, the enzyme preparation showed one major band of 59 kDa on SDS gels. The 59 kDa band became labeled with N3-UDP[32P]-glucose, and this labeling was inhibited in a concentration-dependent manner by either unlabeled UDP-glucose or GDP-glucose. The native enzyme also had a molecular weight of about 60 kDa by gel filtration, indicating that the active enzyme is a monomer. The 59 kDa protein was subjected to endoproteinase Lys-C digestion, and three peptides isolated by HPLC were sequenced. The sequences of 56 amino acids in these three peptides showed 60% identity to the trehalose-P synthases of Saccharomyces cerevesiae and Schizosaccharomyces pombe. The purified mycobacterial enzyme catalyzed the synthesis of trehalose-P from glucose-6-P and a variety of nucleoside diphosphate glucose derivatives, depending on whether a polyanion was absent or present. Thus, UDP-glucose and GDP-glucose were the best glucosyl donors, but maximum activity with UDP-glucose required the presence of a polyanion such as heparin, whereas activity with GDP-glucose was relatively independent of polyanion. The presence of heparin in the incubation mixture increased the affinity of the enzyme for UDP-glucose by a factor of 100, or more. However, the affinity for GDP-glucose was only twofold better in the presence of heparin. The purified synthase also utilized ADP-glucose and CDP-glucose, but the K(m) for these glucosyl donors was quite high even in the presence of polyanion. The effect of heparin on UDP-glucose activity was dose-dependent and maximum at about 1-2 micrograms of heparin/incubation. However, the size of the heparin molecule (i.e., the number of monosaccharide residues) was critical for activation, and only those heparins with 18 or more monosaccharide units were effective in stimulating activity.
Modélisation du carnet d’ordres, Applications Market Making

Cette these aborde differents aspects de la modelisation de la microstructure du marche et des problemes de Market Making, avec un accent particulier du point de vue du praticien. Le carnet d’ordres, au cœur du marche financier, est un systeme de files d’attente complexe a haute dimension. Nous souhaitons ameliorer la connaissance du LOB pour la communaute de la recherche, proposer de nouvelles idees de modelisation et developper des applications pour les Market Makers. Nous remercions en particuler l’equipe Automated Market Making d’avoir fourni la base de donnees haute-frequence de tres bonne qualite et une grille de calculs puissante, sans laquelle ces recherches n’auraient pas ete possible. Le Chapitre 1 presente la motivation de cette recherche et reprend les principaux resultats des differents travaux. Le Chapitre 2 se concentre entierement sur le LOB et vise a proposer un nouveau modele qui reproduit mieux certains faits stylises. A travers cette recherche, non seulement nous confirmons l’influence des flux d’ordres historiques sur l’arrivee de nouveaux, mais un nouveau modele est egalement fourni qui replique beaucoup mieux la dynamique du LOB, notamment la volatilite realisee en haute et basse frequence. Dans le Chapitre 3, l’objectif est d’etudier les strategies de Market Making dans un contexte plus realiste. Cette recherche contribuea deux aspects : d’une part le nouveau modele propose est plus realiste mais reste simple a appliquer pour la conception de strategies, d’autre part la strategie pratique de Market Making est beaucoup amelioree par rapport a une strategie naive et est prometteuse pour l’application pratique. La prediction a haute frequence avec la methode d’apprentissage profond est etudiee dans le Chapitre 4. De nombreux resultats de la prediction en 1- etape et en plusieurs etapes ont retrouve la non-linearite, stationarite et universalite de la relation entre les indicateurs microstructure et le changement du prix, ainsi que la limitation de cette approche en pratique.
When and How-Long: A Unified Approach for Time Perception

The representation of the environment assumes the encoding of four basic dimensions in the brain, that is the 3D space and time. The vital role of time for cognition is a topic that recently attracted increasing research interest. Surprisingly, the scientific community investigating mind-time interactions has mainly focused on interval timing, paying less attention on the encoding and processing of distant moments. The present work highlights two basic capacities that are necessary for developing temporal cognition in artificial systems. In particular, the seamless integration of agents in the environment assumes they are able to consider when events have occurred and how-long they have lasted. This information, although rather standard in humans, is largely missing from artificial cognitive systems. In this work we consider how a time perception model that is based on neural networks and the Striatal Beat Frequency (SBF) theory is extended in a way that besides the duration of events, facilitates the encoding of the time of occurrence in memory. The extended model is capable to support skills assumed in temporal cognition and answer time-related questions about the unfolded events.
Adiposity, Aerobic Fitness and Depressive Symptomology in Children at Risk for Obesity

Elevated levels of adiposity in children have been tied to various pathologies including increased depressive symptomology. Aerobic fitness has been associated with reductions in adiposity and depressive symptomology and may moderate the association between these variables. This study examined this association. Five hundred and two children completed questionnaires on depressive symptoms, were tested for VO2 Peak , and underwent a DEXA scan to measure adiposity. Adiposity and aerobic fitness were tested as predictors of depressive symptomology while controlling for age, pubertal status and socioeconomic status. For boys, aerobic fitness but not adiposity was a significant correlate of depressive symptomology. The interaction between adiposity and aerobic fitness was significant. In girls, adiposity but not aerobic fitness was a significant correlate of depressive symptomology. The interaction between adiposity and aerobic fitness was not significant. These findings highlight sex-specific factors, which may inform targeted approaches to prevent and treat depressive symptoms in children.
Adopting a Stigmatized Label: Social Determinants of Identifying as an Atheist beyond Disbelief

Abstract:An individual's identity may not appear to correspond to his or her beliefs and behaviors. Such incongruence may be particularly likely when an identity is stigmatized. We examine this dynamic in the context of atheists. Being an atheist has often been equated with stating a disbelief in God, but this ignores the distinct phenomenon of identifying as an atheist. This study asks what influences the likelihood that an individual will identify as an atheist beyond saying that he or she does not believe in God. Drawing upon research examining the social dynamics of stigma and identity, we hypothesize that having close friends who are atheists will support an individual's own adoption of the atheist label. On the other hand, we hypothesize that the presence of other stigmatized or at least competing identities, beliefs, and behaviors will serve as a barrier to an individual's adoption of the atheist label. These expectations are largely supported in an analysis of unique survey data offering separate measures of atheist self-identification and belief in God. This study provides a framework for future research to examine these dynamics in the context of other identities, particularly those that are stigmatized.
Intensive Glucose-Lowering Therapy Reduces Cardiovascular Disease Events in Veterans Affairs Diabetes Trial Participants With Lower Calcified Coronary Atherosclerosis

OBJECTIVE This study investigated the hypothesis that baseline calcified coronary atherosclerosis may determine cardiovascular disease events in response to intensive glycemic control within the Veterans Affairs Diabetes Trial (VADT). RESEARCH DESIGN AND METHODS At baseline, 301 type 2 diabetic participants in the VADT, a randomized trial comparing the effects of intensive versus standard glucose lowering on cardiovascular events, had baseline coronary atherosclerosis assessed by coronary artery calcium (CAC) measured by computed tomography. Participants were followed over the 7.5-year study for development of cardiovascular end points. RESULTS During a median follow-up duration of 5.2 years, 89 cardiovascular events occurred. Although intensive glucose-lowering therapy did not significantly reduce cardiovascular events in the substudy cohort as a whole, there was evidence that the response was modified by baseline CAC, as indicated by significant P values for treatment by log(CAC + 1) interaction terms in unadjusted and multivariable-adjusted models (0.01 and 0.03, respectively). Multivariable-adjusted hazard ratios (HRs) for the effect of treatment indicated a progressive diminution of benefit with increasing CAC. Subgroup analyses were also conducted for clinically relevant CAC categories: those above and below an Agatston score of 100. Among those randomized to intensive treatment, for the subgroup with CAC >100, 11 of 62 individuals had events, while only 1 of 52 individuals with CAC ≤100 had an event. The multivariable HR for intensive treatment for those with CAC >100 was 0.74 (95% CI 0.46–1.20; P = 0.21), while for the subgroup with CAC ≤100, the corresponding HR was 0.08 (0.008–0.77; P = 0.03), with event rates of 39 and 4 per 1,000 person-years, respectively. CONCLUSIONS These data indicate that intensive glucose lowering reduces cardiovascular events in those with less extensive calcified coronary atherosclerosis.
A three-dimensional continuum theory of dislocation systems: kinematics and mean-field formulation

We propose a dislocation density measure which is able to account for the evolution of systems of three-dimensional curved dislocations. The definition and evolution equation of this measure arise as direct generalizations of the definition and kinematic evolution equation of the classical dislocation density tensor. The evolution of this measure allows us to determine the plastic distortion rate in a natural fashion and therefore yields a kinematically closed dislocation-based theory of plasticity. A self-consistent theory is built upon the measure which accounts for both the long-range interactions of dislocations and their short-range self-interaction which is incorporated via a line-tension approximation. A two-dimensional kinematic example illustrates the definitions and their relations to the classical theory.
The effect of genre-based instruction on foreign language writing anxiety

The present study aimed to find out if Genre-Based Writing Instruction had an effect on learners’ Foreign Language Writing Anxiety levels. The research setting was a compulsory English Literature course in an English Language Teaching (ELT) department, in which a writing module adopting a Genre-Based Approach was integrated with the aim of teaching the literary analysis essay as a genre. The participants of the study were 78 2 nd year undergraduate students of ELT who were taking the course. The study employed an Embedded Mixed Methods Design and Writing Anxiety was measured by means of the Second Language Writing Anxiety Inventory. The scale was adapted to the research context using the data obtained from 153 participants from the same context, who would not participate in the intervention study. 3 measurements before (Week 1), during (Week 7) and after (Week 12) the intervention were taken from the participants for comparisons. The perceptions of the participants were also sought for by means of interview sessions. Since the quantitative data was found to have been both normally distributed and spherical, a One-Way Repeated Measures of ANOVA was administered to reveal if there was any change in the Writing Anxiety levels of the participants. Pairwise comparisons were made by means of the Bonferroni Post Hoc criterion. The findings showed that the Genre-Based writing module may have had an effect on the Writing Anxiety levels of the participants as the analyses revealed a declining trend with significant differences among all measurements, indicating small to medium effects.
The Deep Journey from Content to Collaborative Filtering

In Recommender Systems research, algorithms are often characterized as either Collaborative Filtering (CF) or Content Based (CB). CF algorithms are trained using a dataset of user explicit or implicit preferences while CB algorithms are typically based on item profiles. These approaches harness very different data sources hence the resulting recommended items are generally also very different. This paper presents a novel model that serves as a bridge from items content into their CF representations. We introduce a multiple input deep regression model to predict the CF latent embedding vectors of items based on their textual description and metadata. We showcase the effectiveness of the proposed model by predicting the CF vectors of movies and apps based on their textual descriptions. Finally, we show that the model can be further improved by incorporating metadata such as the movie release year and tags which contribute to a higher accuracy.
Contribution of Organic Anion Transporter 3 (Slc22a8) to the Elimination of p-Aminohippuric Acid and Benzylpenicillin across the Blood-Brain Barrier

The role of rat organic anion transporter 3 (rOat3; Slc22a8) in the efflux transport at the blood-brain barrier (BBB) was characterized. The expression of rOat1, rOat2, and rOat3 in the brain capillary endothelial cells (BCEC) was examined using reverse transcription-polymerase chain reaction analysis, which showed that there was no expression of rOat1 or rOat2, but moderate expression of rOat3. The expression of rOat3 in the BCEC was further confirmed by Western blotting. Immunohistochemical staining showed that rOat3 is located on the abluminal and, possibly, luminal membrane of the BCEC. The contribution of rOat3 to the efflux of para-aminohippuric acid (PAH) and benzylpenicillin (PCG), substrates of rOat3, from the cerebrum into the blood circulation across the BBB was evaluated using the Brain Efflux Index method. PAH and PCG were eliminated from the cerebrum with rate constants of 0.039 and 0.043 min–1, respectively, and the elimination was saturated at high substrate concentrations. Taking account of the dilution in the brain, the Km values for the elimination of PAH and PCG were estimated to be 168 and 29 μM, respectively. The efflux of PAH and PCG across the BBB was inhibited in a dose-dependent manner by unlabeled PCG and PAH, respectively. The Ki value of PAH for the efflux of PCG was 106 μM and that of PCG for the efflux of PAH was 58 μM. These values were comparable with their Km values, suggesting that they share the same efflux mechanism at the BBB. Furthermore, cimetidine and pravastatin, which are also substrates and inhibitors of rOat3, significantly inhibited the efflux of PAH and PCG from the cerebrum. These results suggest that rOat3 is responsible for the elimination of PAH and PCG from the brain across the BBB.
Identification of Animal Fiber Based on Scale Shape

Scale structure pattern of animal fiber is different and that is a major reference distinguishing them from each other. There are four main scale parameters, including fiber diameters, scale interval, scale perimeter and scale area, can be used to describe their basic shape. In this paper, cashmere and fine wool fiber sample are check up under light microscope with a magnification of 40× for objective and their images are captured by CCD camera. After a series of operations are performed, a simple skeletonized binary representation only having one pixel wide and showing only fiber and scale edge details can be obtained. Four basic shape parameters described above are measured from these images and a database composed of numerical data of four relative indexes is established. A LVQ neural network classification model, including four input nodes, sixteen hidden nodes and two output nodes, are developed on them. The simulation results show that whether on training set or testing set, the model can always distinguish cashmere from fine wool (70s) effectively and the average classification accuracy are higher than 91 percent.
Caregiver Depression: a Growing Mental Health Concern Information Specialist National Center on Caregiving Family Caregiver Alliance Caregiver Depression: a Growing Mental Health Concern

The opinions expressed in this policy brief are those of the author and do not necessarily reflect the views of the Archstone Foundation. ABOUT FCA Founded in 1977, Family Caregiver Alliance serves as a public voice for caregivers, illuminating the daily challenges they face, offering them the assistance they so desperately need and deserve, and championing their cause through education, services, research and advocacy. Long recognized as a pioneer among caregiver organizations, FCA operates programs at local, state and national levels. FCA is the lead agency and model for California's statewide system of Caregiver Resource Centers. In 2001, FCA established the National Center on Caregiving to advance the development of high-quality, cost-effective policies and programs for caregivers in every state in the country. Leslie Gray, MPH " Too often, attention to mental health services for older people and their caregivers is negligible or absent, despite the fact that mental health problems and caregiver distress are among the leading reasons for institutionalization " (U.S. Department of Health and Human Services, 1999).
Face-ism and Objectification in Mainstream and LGBT Magazines

In visual media, men are often shown with more facial prominence than women, a manifestation of sexism that has been labeled face-ism. The present research extended the study of facial prominence and gender representation in media to include magazines aimed at lesbian, gay, bisexual, and transgender (LGBT) audiences for the first time, and also examined whether overall gender differences in facial prominence can still be found in mainstream magazines. Face-ism emerged in Newsweek, but not in Time, The Advocate, or Out. Although there were no overall differences in facial prominence between mainstream and LGBT magazines, there were differences in the facial prominence of men and women among the four magazines included in the present study. These results suggest that face-ism is still a problem, but that it may be restricted to certain magazines. Furthermore, future research may benefit from considering individual magazine titles rather than broader categories of magazines, given that the present study found few similarities between different magazines in the same media category—indeed, Out and Time were more similar to each other than they were to the other magazine in their respective categories.
Improving Identifiability in Model Calibration Using Multiple Responses

In physics-based engineering modeling, the two primary sources of model uncertainty, which account for the differences between computer models and physical experiments, are parameter uncertainty and model discrepancy. Distinguishing the effects of the two sources of uncertainty can be challenging. For situations in which identifiability cannot be achieved using only a single response, we propose to improve identifiability by using multiple responses that share a mutual dependence on a common set of calibration parameters. To that end, we extend the single response modular Bayesian approach for calculating posterior distributions of the calibration parameters and the discrepancy function to multiple responses. Using an engineering example, we demonstrate that including multiple responses can improve identifiability (as measured by posterior standard deviations) by an amount that ranges from minimal to substantial, depending on the characteristics of the specific responses that are combined.
Deficits in Early Stages of Face Processing in Schizophrenia: A Systematic Review of the P100 Component.

INTRODUCTION Schizophrenia is associated with deficits in face and affect recognition, which contribute to broader social functioning deficits. The present aim was to conduct a meta-analysis of early face processing in schizophrenia, as indexed by the P100 event-related potential component. METHODS Twelve studies (n = 328 patients with schizophrenia, n = 330 healthy controls) of the P100 component during face processing were evaluated by calculating Cohen's d for each study and overall weighted mean effect size (ES). In additional exploratory analyses, moderating influences of method and design were investigated, and the P100 component during face processing was evaluated based on valence: 5 studies (n = 225 patients, n = 225 controls) included neutral stimuli, 5 studies (n = 225 patients, n = 225 controls) included happy stimuli, and 4 studies (n = 209 patients, n = 209 controls) included fearful stimuli. RESULTS The amplitude of the P100 to face stimuli was smaller in patients relative to controls (ES = .41, P < .01). Methodological or design differences did not account for heterogeneity in ES. When split by valence, results indicate smaller P100 in patients relative to control subjects in response to neutral (ES = .32, P < .001) and happy (ES = .21, P < .05) stimuli, whereas there was no difference in response to fearful faces (ES = .09, P > .05). DISCUSSION The results indicate that P100 amplitude in response to faces is smaller in patients with schizophrenia, showing that socially relevant visual processing deficits begin earlier in processing than previously suggested. Additionally, the exploratory analyses suggest emotional specificity in these deficits. Ramifications for our understanding of face processing deficits and treatment development are discussed.
Impact of Radar Data Assimilation on the Analysis and Prediction of the 8-9 May 2007 Oklahoma Tornadic Mesoscale Convective System, Part Ii: Sub-storm-scale Mesovortices on a 400 M Grid

In this two-part paper, the impact of assimilating data from the WSR-88D and the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere's (CASA) IP-1 radar network on the prediction of a tornadic mesoscale convective system is examined. The Advanced Regional Prediction System (ARPS) prediction model is employed to perform high-resolution numerical simulations of a mesoscale convective system (MCS) and the associated cyclonic line-end vortex (LEV) that spawned several tornadoes in central Oklahoma on 8-9 May 2007. In part I of this study, the assimilation procedure, and the results of analysis and prediction of the MCS and LEV scales on a 2-km-resolution grid were discussed. In this part II, nested grid simulations (400-m resolution grid within the 2-km grid) are used to examine the impact of radar data on the prediction of meso-γ-scale vortices (mesovortices). An 80-min assimilation window is used in experiments that examine the impact of radar data on this high-resolution grid. A second set of experiments examines the impact of decreasing assimilation window length on the prediction of these mesovortices. Results show that highly accurate forecasts of mesovortices up to 80 min in advance of their genesis are possible when the low-level wind and temperatures fields are effectively analyzed. Accurate analysis of low-level wind and temperature fields relies on assimilating high-resolution low-level wind information. The most accurate analysis (and resulting prediction) is obtained in experiments that assimilate low-level radial velocity data from the CASA radars. Experiments that do not assimilate low-level wind data are unable to resolve the gust front structure, precluding accurate prediction of mesovortex development. It is found that a fairly accurate prediction is still possible with an assimilation window of as short as 20 min.