Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Alanine Catabolism in Pseudomonas aeruginosa and Its Importance for Proliferation In Vivo

ABSTRACT The opportunistic pathogen Pseudomonas aeruginosa causes a variety of infections in immunocompromised individuals, including individuals with the heritable disease cystic fibrosis. Like the carbon sources metabolized by many disease-causing bacteria, the carbon sources metabolized by P. aeruginosa at the host infection site are unknown. We recently reported that l-alanine is a preferred carbon source for P. aeruginosa and that two genes potentially involved in alanine catabolism (dadA and dadX) are induced during in vivo growth in the rat peritoneum and during in vitro growth in sputum (mucus) collected from the lungs of individuals with cystic fibrosis. The goals of this study were to characterize factors required for alanine catabolism in P. aeruginosa and to assess the importance of these factors for in vivo growth. Our results reveal that dadA and dadX are arranged in an operon and are required for catabolism of l-alanine. The dad operon is inducible by l-alanine, d-alanine, and l-valine, and induction is dependent on the transcriptional regulator Lrp. Finally, we show that a mutant unable to catabolize dl-alanine displays decreased competitiveness in a rat lung model of infection.
TSAC: Enforcing Isolation ofVirtual Machines in Clouds

Virtualization plays a vital role in building the infrastructure of clouds, and isolation is considered as one of its important features. However, we demonstrate with practical measurements that there exist two kinds of isolation problems in current virtualized systems, due to cache interference in a multi-core processor. That is, one virtual machine could degrade the performance or obtain the load information of another virtual machine, which running on a same physical machine. Then we present a time-sensitive contention management approach (TSAC) for allocating resources dynamically in the virtual machine monitor, in which virtual machines are controlled to share some physical resources (e.g., CPU or page color) in a dynamical manner, in order to enforce isolation between the virtual machines without sacrificing performance of the virtualized system. We have implemented a working prototype based on Xen, evaluated the implemented prototype with experiments, and experimental results show that TSAC could significantly improve isolation of virtualization. Specifically, compared to the default Xen, TSAC could improve the performance of the victim virtual machine by up to about 78 percent, and perform well in blocking its cache-based load information leakage.
Normative data and psychometric properties of the Thai version of the Strengths and Difficulties Questionnaire (SDQ)

Objective: To study normative data and psychometric properties of the Thai Strengths and Difficulties Questionnaire (SDQ; parent-, teacher-, and self-rated forms), which addresses positive and negative aspects of childrenus and adolescentsu behaviour and generates clinically relevant scale scores. Materials and Methods: Using multistage random cluster sampling method, data were collected in 13 provinces from parents, teachers, and as self-reports of 9,491 children aged between 5 and 16 years. Evaluation methods included scale reliability analyses (Cronbachus alpha), correlations with age and among scales, testing for gender effects, and comparing urban and rural regions. A factor analysis examines the specific scale structure of the Thai parent-rated SDQ. Bandings are recommended to identify normal, borderline, and abnormal score ranges. Results Problem scores were higher than those observed in Western countries, stressing the necessity to establish national norms. Thai SDQ norms identify probable behaviour problems if the total difficulties score is 19-40 in the parent-rated form, 17-40 in the teacher form, and/or 19-40 in the self-report. Internal reliabilities were satisfactory for all but one subscale. Age and gender effects on SDQ scores as well as correlations between subscales were well in line with the English original and its many other translated versions. Conclusion The Thai SDQ was shown to possess sufficiently favourable psychometric properties. Thus, this instrument promises to be a useful assessment and screening tool, as in other parts of the world. Ongoing validation studies and cross-cultural comparisons will provide further culture-specific findings.
Findings of the 2017 DiscoMT Shared Task on Cross-lingual Pronoun Prediction

We describe the design, the setup, and the evaluation results of the DiscoMT 2017 shared task on cross-lingual pronoun prediction. The task asked participants to predict a target-language pronoun given a source-language pronoun in the context of a sentence. We further provided a lemmatized target-language human-authored translation of the source sentence, and automatic word alignments between the source sentence words and the target-language lemmata. The aim of the task was to predict, for each target-language pronoun placeholder, the word that should replace it from a small, closed set of classes, using any type of information that can be extracted from the entire document. We offered four subtasks, each for a different language pair and translation direction: English-to-French, English-to-German, German-to-English, and Spanish-to-English. Five teams participated in the shared task, making submissions for all language pairs. The evaluation results show that most participating teams outperformed two strong n-gram-based language model-based baseline systems by a sizable margin.
Subjective stimulant and sedative effects of alcohol during early drinking experiences predict alcohol involvement in treated adolescents.

OBJECTIVE Research on low subjective response to alcohol has focused primarily on alcohol's sedative effects during early drinking experiences. This study examined subjective response to both stimulant and sedative effects of alcohol during initial drinking experiences as predictors of treated adolescents' severity of alcohol involvement before treatment and over 1-year follow-up. METHOD Adolescents (N = 169) recruited from addictions treatment reported on the number of drinks needed to obtain stimulant and sedative effects of alcohol for early and heavy drinking periods. The number of drinks needed to obtain stimulant and sedative effects, as well as the degree of stimulant and sedative effect obtained, were examined as predictors of adolescents' alcohol involvement at baseline (before treatment) and 1-year follow-up. RESULTS During early drinking experiences, females reported a greater degree of sedative effect compared with males; there was no gender difference in degree of stimulant effect reported during early drinking experiences. Both early subjective stimulant and sedative effects of alcohol predicted the usual number of drinks needed to become intoxicated and the maximum drinking quantity per day before treatment. However, at 1-year follow-up, only early sedative effects predicted 1-year outcomes. CONCLUSIONS Study findings suggest potentially important roles for both early subjective stimulant and sedative effects of alcohol in relation to adolescent alcohol involvement.
Functional Connectivity in the First Year of Life in Infants at Risk for Autism Spectrum Disorder: An EEG Study

In the field of autism research, recent work has been devoted to studying both behavioral and neural markers that may aide in early identification of autism spectrum disorder (ASD). These studies have often tested infants who have a significant family history of autism spectrum disorder, given the increased prevalence observed among such infants. In the present study we tested infants at high- and low-risk for ASD (based on having an older sibling diagnosed with the disorder or not) at 6- and 12-months-of-age. We computed intrahemispheric linear coherence between anterior and posterior sites as a measure of neural functional connectivity derived from electroencephalography while the infants were listening to speech sounds. We found that by 12-months-of-age infants at risk for ASD showed reduced functional connectivity compared to low risk infants. Moreover, by 12-months-of-age infants later diagnosed with ASD showed reduced functional connectivity, compared to both infants at low risk for the disorder and infants at high risk who were not later diagnosed with ASD. Significant differences in functional connectivity were also found between low-risk infants and high-risk infants who did not go onto develop ASD. These results demonstrate that reduced functional connectivity appears to be related to genetic vulnerability for ASD. Moreover, they provide further evidence that ASD is broadly characterized by differences in neural integration that emerge during the first year of life.
Metric-Field Conditioning for Mesh Adaptation Problems

Metric tensor fields computed from solution data for adaptation problems are not always well-behaved. They may contain noise, high gradients in desired directionality and anisotropy, global undulations in directionality, and other defects that pose challenges for meshing algorithms. We focus on the application of filters to address some of these defects through noise removal and a form of fairing. At the same time, it is desirable to retain characteristics of the original metric data. These methods are demonstrated on metric data from a high-speed, 2D flow problem.
Some Implications of System Dynamics Analysis of Discrete-Time Recurrent Neural Networks for Learning Algorithms Design

It is not clear so far what the implications of bifurcations in Discrete-Time Recurrent Neural Networks dynamics are with respect to learning algorithms. Previous studies discussed different phenomena in a general purpose framework, and here we are going to discuss in more detail. We perform an analysis of the dynamics of a neuron with feedback in order to find the different behaviors that it shows depending on the magnitude of the offset weight, the input weight and the feedback weight. We calculate the bifurcation manifolds that show the regions where the neuron behavior changes. We discuss the implications that these findings can have for the design of DTRNN learning algorithms.
Biologically Inspired Intercellular Slot Synchronization

The present article develops a decentralized interbase station slot synchronization algorithm suitable for cellular mobile communication systems. The proposed cellular firefly synchronization (CelFSync) algorithm is derived from the theory of pulse-coupled oscillators, common to describe synchronization phenomena in biological systems, such as the spontaneous synchronization of fireflies. In order to maintain synchronization among base stations (BSs), even when there is no direct link between adjacent BSs, some selected user terminals (UTs) participate in the network synchronization process. Synchronization emerges by exchanging two distinct synchronization words, one transmitted by BSs and the other by active UTs, without any a priori assumption on the initial timing misalignments of BSs and UTs. In large-scale networks with inter-BS site distances up to a few kilometers, propagation delays severely affect the attainable timing accuracy of CelFSync. We show that by an appropriate combination of CelFSync with the timing advance procedure, which aligns uplink transmission of UTs to arrive simultaneously at the BS, a timing accuracy within a fraction of the inter-BS propagation delay is retained.
Critical IT systems in the value chain for successfully moving from mass production to mass customization

Today, organizations operate in an environment characterized by a number of changed business conditions. One of the main aspects in the market they comprise is the rise of individualized products, which for manufacturing organizations means a move towards mass customization. The key to successfully pursuing mass customization from mass production is situated in information technologies (IT). However, existing manufacturing and information systems provide little support for moving from mass production to mass customization, because they are based on standardization approaches. Mass customization on the other side requires IT systems in the value chain that are more based on the aspects of obtaining customer specifications, planning and scheduling, process flexibility and knowledge sharing. IT systems supporting these four aspects are critical IT success systems in the current business environment of mass customization, and critical in the process when moving from mass production to mass customization. This means that existing mass production techniques and information systems can only be applied to a limited extent in the new situation.
Socio-Economic / Family Background on Students Academic Performance in Tertiary Institutions using Decision Tree Algorithm

*Correspondence author <afolashadeng@gmail.com> Abstract The causes of the difference in the academic performance of students in tertiary institutions has for a long time been the focus of study among higher education managers, parents, government and researchers. The cause of this differential can be due to intellective, non-intellective factors or both. From studies investigating student performance and related problems it has been determined that academic success is dependent on many factors such as; grades and achievements, personality and expectations, and academic environments. This work uses data mining techniques to investigate the effect of socio-economic or family background on the performance of students using the data from one of the Nigerian tertiary institutions as case study. The analysis was carried out using Decision Tree algorithms. The data comprised of two hundred forty (240) records of students. The academic performance of students was measured by the students’ first year cumulative grade point average (CGPA). Various Decision Tree algorithms were investigated and the algorithm which best models the data was used to generate rule sets which can be used to analyze the effect of the socio-economic background of students on their academic performance. The rules generated can serve as a guide to educational administrators in their planning activities.
Fitting of 3D reaction surface of three-atomic system in the natural collision coordinates

The objective of present investigation to prove the possibility of representation the 3D interaction between particles in various reacting three-body systems by analytical function with a set of adjusting parameters in natural collision coordinates. Realization of this idea imply the procedure of fitting of 3D numerical data by 3D analytical function or more precisely, calculation of adjusting parameters in mentioned analytical function. In the work is used Levenberg-Marquardt algorithm on the basis of which the numerical method is developed. The possibility of implementation of 3D fitting with the big accuracy, on the example of reaction H + H2 is shown.
Stroke-Based Suibokuga -Like Rendering for Three-Dimensional Geometric Models - Ten and Shun Touches -

Non-photorealistic rendering has become an important research topics in computer graphics in recent years. We have previously proposed a non-photorealistic rendering method to generate Suibokuga-like images of trees. This method was suitable only for representing trees in Mokkotsuho paintings because the images were generated from three-dimensional skeleton data. In this paper, we propose a method to generate Suibokuga-like images of arbitrary objects from three-dimensional geometric models, such as polygonal models. The proposed method realizes Kou , Ten, and Shun brush stroke techniques for creating Sensenbyoho paintings, which are a typical Suibokuga style for representing landscapes. Moreover, the images can be generated from arbitrary viewpoints and light source information. The ability of this method is demonstrated by showing various example.
Tumor Necrosis Factor-α Stimulates Focal Adhesion Kinase Activity Required for Mitogen-activated Kinase-associated Interleukin 6 Expression*

Focal adhesion kinase (FAK) is a cytoplasmic protein-tyrosine kinase that promotes cell migration, survival, and gene expression. Here we show that FAK signaling is important for tumor necrosis factor-α (TNFα)-induced interleukin 6 (IL-6) mRNA and protein expression in breast (4T1), lung (A549), prostate (PC-3), and neural (NB-8) tumor cells by FAK short hairpin RNA knockdown and by comparisons of FAK-null (FAK–/–) and FAK+/+ mouse embryo fibroblasts. FAK promoted TNFα-stimulated MAPK activation needed for maximal IL-6 production. FAK was not required for TNFα-mediated nuclear factor-κB or c-Jun N-terminal kinase activation. TNFα-stimulated FAK catalytic activation and IL-6 production were inhibited by FAK N-terminal but not FAK C-terminal domain overexpression. Analysis of FAK–/– fibroblasts stably reconstituted with wild type or various FAK point mutants showed that FAK catalytic activity, Tyr-397 phosphorylation, and the Pro-712/713 proline-rich region of FAK were required for TNFα-stimulated MAPK activation and IL-6 production. Constitutively activated MAPK kinase-1 (MEK1) expression in FAK–/– and A549 FAK short hairpin RNA-expressing cells rescued TNFα-stimulated IL-6 production. Inhibition of Src protein-tyrosine kinase activity or mutation of Src phosphorylation sites on FAK (Tyr-861 or Tyr-925) did not affect TNFα-stimulated IL-6 expression. Moreover, analyses of Src–/–, Yes–/–, and Fyn–/– fibroblasts showed that Src expression was inhibitory to TNFα-stimulated IL-6 production. These studies provide evidence for a novel Src-independent FAK to MAPK signaling pathway regulating IL-6 expression with potential importance to inflammation and tumor progression.
A study for access control flow analysis with a proposed job analyzer component based on stack inspection methodology

Security problems arise in software systems are very challenging. Using program analysis techniques and some language based security rules can help in enforcing application-level security through control access to program resources and verification of control flow of the information inside the program based on some security properties. This paper presents a new job analyzer component for an intrusion detection system which works inside our developed computational grid system called “HIMAN” to analyze access required by a certain submitted task to the grid resources. This paper consists of three parts. First part is a survey for the previous work for access control, information flow security analyses, and the stack inspection methodology. Second part is a representation for a static analysis study for enhancing the stack inspection methodology in order to optimize the program complexity. Finally, the third part explains how to use the access control flow analysis based on the enhanced stack inspection methodology described in this paper to develop the new job analyzer component.
Automatically tagging email by leveraging other users' folders

Most email applications devote a significant part of their real estate to organization mechanisms such as folders. Yet, we verified on the Yahoo! Mail service that 70% of email users have never defined a single folder. This implies that one of the most well known email features is underexploited. We propose here to revive the feature by providing a method for generating a lighter form of folders, or tags, benefiting even the most passive users. The method automatically associates, whenever possible, an appropriate semantic tag with a given email. This gives rise to an alternate mechanism for organizing and searching email. We advocate a novel modeling approach that exploits the overall population of users, thereby learning from the wisdom-of-crowds how to categorize messages. Given our massive user base, it is enough to learn from a minority of the users who label certain messages in order to label that kind of messages for the general population. We design a novel cascade classification approach, which copes with the severe scalability and accuracy constraints we are facing. Significant efficiency gains are achieved by working within a low dimensional latent space, and by using a novel hierarchical classifier. Precision level is controlled by separating the task into a two-phase classification process. We performed an extensive empirical study covering three different time periods, over 100 million messages, and thousands of candidate tags per message. The results are encouraging and compare favorably with alternative approaches. Our method successfully tags 72% of incoming email traffic. Performance-wise, the computational overhead, even on surge large traffic, is sufficiently low for our approach to be applicable in production on any large Web mail service.
Automated 3D modeling of urban environments

The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography, This paper summarizes the contributions of our group in that area. We present a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D (.)
Perfectionism and self-vulnerabilities in obsessive-compulsive and eating difficulties

Perfectionism has had a long-standing role in theorizing about psychopathology. Empirical studies have identified this construct as a key phenomenological link for OCD and EDs, in particular. Despite its apparent longevity, and recent growing interest, it is still not well understood. This is true in spite of research that has found perfectionism to be a significant hindrance to the successful treatment of disorders. Attempts at differentiating unique aspects of perfectionism for disorders have generally been unsuccessful. Moreover, developmental and motivational bases have not been adequately addressed. This thesis aims to address some of these issues. The overall aim of the thesis was to develop models of perfectionism that delineate specific facets related, in particular, to OC and ED phenomena. The thesis had three broad aims. The first aim was to construct measures of perfectionism that were uniquely related to OC and ED disorder symptoms, based on cognitive theories and empirical evidence. The second aim was to explore the relative influence of general perfectionism facets and the specific perfectionism scales developed in this thesis, on OC and ED symptoms. In addition, the research investigated the relationship between general and specific self-vulnerabilities that are hypothesized mechanisms thought to underlie perfectionism, and perfectionism facets. The third aim was to develop and compare models of perfectionism for OC and ED phenomena, incorporating selfvulnerabilities. Five hundred and two non-clinical female participants were recruited. Participants comprised undergraduate students (N = 261; mean age = 20.68; SD = 4.79) and individuals from the community (N = 241; mean age = 33.42; SD = 11.34). To measure various perfectionism facets, self-vulnerabilities, and other common factors related to OC and ED symptoms, participants completed a range of online questionnaires.
Probabilistic Parsing for German Using Sister-Head Dependencies

We present a probabilistic parsing model for German trained on the Negra treebank. We observe that existing lexicalized parsing models using head-head dependencies, while successful for English, fail to outperform an unlexicalized baseline model for German. Learning curves show that this effect is not due to lack of training data. We propose an alternative model that uses sister-head dependencies instead of head-head dependencies. This model out-performs the baseline, achieving a labeled precision and recall of up to 74%. This indicates that sister-head dependencies are more appropriate for treebanks with very flat structures such as Negra.