Miracle-dz/UniFAR-FTUs huggingface dataset:
ace, Which Encodes an Adhesin in Enterococcus faecalis, Is Regulated by Ers and Is Involved in Virulence

ABSTRACT Enterococcus faecalis is an opportunistic pathogen that causes numerous infectious diseases in humans and is a major agent of nosocomial infections. In this work, we showed that the recently identified transcriptional regulator Ers (PrfA like), known to be involved in the cellular metabolism and the virulence of E. faecalis, acts as a repressor of ace, which encodes a collagen-binding protein. We characterized the promoter region of ace, and transcriptional analysis by reverse transcription-quantitative PCR and mobility shift protein-DNA binding assays revealed that Ers directly regulates the expression of ace. Transcription of ace appeared to be induced by the presence of bile salts, probably via the deregulation of ers. Moreover, with an ace deletion mutant and the complemented strain and by using an insect (Galleria mellonella) virulence model, as well as in vivo-in vitro murine macrophage models, we demonstrated for the first time that Ace can be considered a virulence factor for E. faecalis. Furthermore, animal experiments revealed that Ace is also involved in urinary tract infection by E. faecalis.
An Optimal Fractional Order Controller for an AVR System Using Particle Swarm Optimization Algorithm

Application of fractional order PID (FOPID) controller to an automatic voltage regulator (AVR) is presented and studied in this paper. An FOPID is a PID whose derivative and integral orders are fractional numbers rather than integers. Design stage of such a controller consists of determining five parameters. This paper employs particle swarm optimization (PSO) algorithm to carry out the aforementioned design procedure. A novel cost function is defined to facilitate the control strategy over both the time-domain and the frequency-domain specifications. Comparisons are made with a PID controller from standpoints of transient response, robustness and disturbance rejection characteristics. It is shown that the proposed FOPID controller can improve the performance of the AVR in all the three respects.
Predicting judicial decisions of the European Court of Human Rights: a Natural Language Processing perspective

Recent advances in Natural Language Processing and Machine Learning provide us with the tools to build predictive models that can be used to unveil patterns driving judicial decisions. This can be useful, for both lawyers and judges, as an assisting tool to rapidly identify cases and extract patterns which lead to certain decisions. This paper presents the first systematic study on predicting the outcome of cases tried by the European Court of Human Rights based solely on textual content. We formulate a binary classification task where the input of our classifiers is the textual content extracted from a case and the target output is the actual judgment as to whether there has been a violation of an article of the convention of human rights. Textual information is represented using contiguous word sequences, i.e., N-grams, and topics. Our models can predict the court’s decisions with a strong accuracy (79% on average). Our empirical analysis indicates that the formal facts of a case are the most important predictive factor. This is consistent with the theory of legal realism suggesting that judicial decision-making is significantly affected by the stimulus of the facts. We also observe that the topical content of a case is another important feature in this classification task and explore this relationship further by conducting a qualitative analysis.
Value of detecting immunoglobulin E antibodies for the serological diagnosis of Toxoplasma gondii infection

The presence of immunoglobulin E (IgE) antibodies was determined by using the immunosorbent-agglutination assay (ISAGA) with 611 serum samples from patients with different clinical conditions to evaluate its value for the serodiagnosis of acute Toxoplasma gondii infection. By analyzing 43 consecutively drawn serum samples from 10 pregnant women who seroconverted, we could show that specific IgE antibodies seem to appear early after infection and are usually present for less than 3 to 5 months. Therefore, we assumed that IgE antibodies seem to be detectable only during the acute or reactivated stage of infection. According to our studies, the IgE ISAGA has an overall sensitivity of only 79.5%, but a specificity of 98.0%, with positive and negative predictive values of 95.5 and 89.8%, respectively. Detection of IgE antibodies in immunosuppressed patients with reactivation of latent T. gondii infection correlates with disease activity. Despite these encouraging results, one must note that IgE antibodies were not detectable in 4 of 14 patients with very recent infection proven by seroconversion. Therefore, detection of IgE antibodies seems to correlate with early acute or reactivated toxoplasmosis, whereas negative IgE results do not exclude the possibility of the acute stage of toxoplasmosis.
ADVANCED FUSION TECHNIQUES FOR AUTOMATED DETECTION OF SETTLEMENT AREAS

: Data fusion exists in different forms in different scientific communities. The term is used by the image community to address the problem of sensor fusion, where images from different sensors are combined. The term is also used by the database community for parts of the interoperability problem. The logic community uses the term for knowledge fusion. Usually, they can be classified into three levels: pixel level (ikonic), feature level (symbolic) and knowledge or decision level (Pohl and van Genderen, 1998). In this paper, we focus on the development of a decision based fusion. For automated detection of settlement areas, we developed a hierarchical decision tree which is based on homogeneous image segments rather than on image pixels. Within an integrated GIS/remote sensing environment registered multisensor image and GIS data-sets were used to facilitate an automated settlement detection. The datasets included remote sensing images from SPOT 5 (5 m GSD), LANDSAT 7 ETM (30 m GSD), KOMPSAT 1 (6,6 m GSD), and ASTER (15 m GSD) satellite programs as well as GIS data from the ATKIS landscape and digital elevation models. Our method for multisensor decision-based data fusion was initially developed and tested in selected urban and suburban areas first with the fusion of SPOT and LANDSAT data and later on extended to KOMPSAT and ASTER images. The methodology is based mainly on an adapted texture and segment oriented hierarchical classification approach: based on panch-romatic high resolution image data as primary input. Segments at three different scales (levels) are the basis for a hierarchical decisi-on-based classification procedure. Beginning with large segments, texture and shape parameters were calculated for each single segment. In addition, we used the normalized vegetation index (NDVI) calculated from the multispectral lower resolution satellite image data to distinguish between vegetation and non-vegetation areas. Using adapted threshold parameters, candidate regions for settlement areas were identified. In the second level with medium-sized segments, texture and shape parameters were calculated again using different restriction thresholds. This procedure was only performed within the selected settlement candidates of the previous step. This procedure was repeated for fine segments and high threshold values to isolate the actual settlement areas. Finally, the settlement segments were merged and cleaned by automated filter procedures to eliminate small remaining agriculture segments and to include urban parks and lakes in the settlement areas. By checking the results with actual GIS base data and photo interpretation results, the automated procedure achieved a total accuracy of more than 90% for the settlement class. Furthermore, we applied the same technique to fuse KOMPSAT and ASTER image data. Because of the lower spatial resolution of KOMPSAT compared to SPOT 5, only the threshold values for the texture parameters had to be readjusted. Again, the achieved accuracy exceeded 90%.
The Initial State for Californian English Learners of Spanish and Portuguese Vowels

Second language (L2) learners often struggle with achieving native-like production and perception of L2 sounds. While there is ample research on the non-native perception of English vowels by native speakers of languages with smaller vowel inventories, scant research exists up-to-date on the opposite scenario. The aim of the present study is to investigate the initial state for Californian English (CE) listeners' perception of two different smaller vowel inventories, namely Spanish and Portuguese vowels, before any perceptual learning has taken place. The objective is to determine how CE listeners' native vowel inventory of (at least) ten phonemes affects their non-native perception of the five Spanish and seven Portuguese vowel phonemes.Monolingual speakers of English from Southern California (N = 18) completed a perceptual assimilation task, in which they labeled naturally produced tokens of Spanish and Portuguese vowels in terms of ten native English categories, as well as a categorial discrimination task with four Spanish and six Portuguese vowel contrasts. In the perceptual assimilation task, CE listeners mapped almost every Spanish and Portuguese vowel contrast to more than two native categories, resulting in many instances of Multiple Category Assimilation (MCA, Escudero and Boersma, 2002). Furthermore, some phonologically common vowels between Spanish and Portuguese, namely /e/, /o/, and /a/, were mapped differently to English categories, suggesting that cross-linguistic differences in the acoustic distributions of these sounds result in differences in their categorization by non-native listeners.In the discrimination task, CE listeners were highly accurate at distinguishing all Spanish vowel contrasts but were less accurate on three Portuguese vowel contrasts, /i-e/, /o-u/, and /a-O/. Crucially, MCA was found to be responsible for listeners' lower discrimination accuracy only when it contributed to two vowels being perceptually assimilated to an overlapping set of native categories, i.e., when two different vowels had a high perceptual assimilation overlap score. The results are examined vis-a-vis two main models of second language speech perception, the Perceptual Assimilation Model (PAM, Best, 1995) and the Second Language Linguistic Perception Model (L2LP, Escudero, 2005). Implications for L2 acquisition of Spanish and Portuguese vowels by English-speaking learners are discussed.
Estimating Collision Set Size in Framed Slotted Aloha Wireless Networks and RFID Systems

In wireless networks and RFID systems, a collision set is a group of nodes such that the simultaneous transmission of two or more nodes generates destructive interference at the receiver and, consequently, the loss of all transmitted packets. Knowing the number of nodes in the collision set, i.e., the collision set size, it is possible to design effective channel access strategies that minimize the time required to read all the tags or, more generally, collect the packets generated by each node in the set. However, the collision set size is often unknown and, then, needs to be estimated. In this paper we propose a novel estimation method for Framed Slotted Aloha systems that applies a maximum likelihood argument on a Poisson approximation of the packet arrivals process to the transmission channel, yielding an estimate with minimal mean error and mean square error, with respect to the best-performing estimate algorithms in the literature having similar complexity.
Students’ Motivation for Participating in Discussion Board

Online discussion boards are considered beneficial to learning activities. The effectiveness of discussion boards is greatly dependent on students’ levels of participation. In this study we examine the motivational factors for student participation in online discussion boards in blended learning contexts, that is, hybrids of in-class and online learning. We propose that desire for esteem and affiliation, conformity to group norms, and reciprocity have a direct impact on the level of participation in the activity. A quantitative survey will be conducted to test our theoretical model in the next step of the research.
Software Tools for Developing Parallel Applications, Part 1: Code Development and Debugging

Developing an application for parallel computers can be a lengthy and frustrating process making it a perfect candidate for software tool support. Yet application programmers are often the last to hear about new tools emerging from R and D efforts. This paper provides an overview of two focuses of tool support: code development and debugging. Each is discussed in terms of the programmer needs addressed, the extent to which representative current tools meet those needs, and what new levels of tool support are important if parallel computing is to become more widespread.
Logspace Hierarchies, Polynomial Time and the Complexity of Fairness Problems Concerning Omega-Machines

In this paper, we define a restricted logspace oracle hierarchy which turns out to be equivalent to the logspace alternation hierarchy (of Chandra, Kozen and Stockmeyer) and thus is contained within the second level of the logspace oracle heirarchy (of Ruzzo, Simon and Tompa). We then examine problems concerning various types of “fair” computations with respect to $\omega $-Finite State Machines ($\omega $-FSM’s) and $\omega $-One Counter Machines ($\omega $-1CM’s). For example, we consider the nonemptiness problem for $\omega $-FSM’s and $\omega $-1CM’s where acceptance is defined in the usual fashion, but with a fairness constraint imposed on accepting computations. Our results yield problems that are complete not only for LOGSPACE and PTIME but the second and third levels of the restricted logspace oracle hierarchy as well. As far as we know, these are the first natural problems shown to be complete for various levels of the logspace alternation hierarchy. The problems are also of independent interest.
USP2 as a potential link between miR-125b and psoriasis

treatment-Abstract Background: The extensive involvement of miRNA in the pathophysiology of psoriasis is well-documented. However, in order for this information to be useful towards therapeutic manipulation of miRNA-levels, it is essential that detailed functional mechanisms are elucidated. MiR-125b has previously been shown to be strongly associated with psoriasis, and presents as an obvious candidate for further investigation. Objectives Elucidate the specific pathway and mechanism of interest in this association. Methods A three-step bioinformatical hypothesis-generation pipeline was performed to identify genes of interest. This pipeline was based on miR-125b-binding, expression in psoriatic lesions and genome-wide association study-based evidence of involvement. The identified candidate gene was then carefully evaluated using luciferase binding assays, in-vitro overexpression, siRNA knock-down and downstream gene read-outs. Results Based on our bioinformatical pipeline, the Ubiquitin Specific Peptidase 2 (USP2) was selected as a likely candidate for a mechanistic explanation for psoriasis association. After establishing a definite connection to miR-125b, we proceeded to show that modulation of NFkB-mediated inflammation is the likely mechanism through which this miRNA-gene pair functioned. Conclusions Shedding further light on the multi-factorial causes of psoriasis is essential, if the goal is to progress towards finer control of therapeutic tools in disease management. Findings, such as the ones presented herein, are therefore necessary in order to achieve the future of personalized medicine.
Point/Counterpoint Point: Myeloperoxidase 463 G3 A Polymorphism and Lung Cancer Risk 1

Myeloperoxidase (MPO) is released from neutrophils in lung tissue in response to exposure to various pulmonary insults, including tobacco smoking. This enzyme is involved in the activation of an intermediate metabolite of benzo(a)pyrene to the highly reactive benzo(a)pyrene diol epoxide. A 463 G3 A polymorphism in the promoter region of the MPO gene has been identified. The A allele is associated with a decreased transcriptional activity attributable to the disruption of a SP1-binding site. We therefore examined whether carriers of the A allele may be at reduced risk of lung cancer in a case-control study of 150 cases and 172 control individuals, all Caucasian smokers. Relative to subjects with the MPO G/G genotype, a significant decreased risk of lung cancer was found for carriers of the G/A genotype [odds ratio (OR) 0.5, 95% confidence interval (CI): 0.29 – 0.88]. A reduction in risk, although not statistically significant, was also observed for subjects with the A/A genotype (OR 0.84, 95% CI: 0.31–2.32). The lung cancer risk for carriers of one or two copies of the A allele was 0.55 (95% CI: 0.33– 0.93). Because of the low prevalence of the A/A genotype, we also performed a meta-analysis of 2686 lung cancer cases and 3325 controls. The summary OR suggested a slight protective effect of the A/A genotype (OR 0.86, 95% CI: 0.67–1.1), but this finding was strongly influenced by the results of a single large study. The meta-analysis restricted to studies comprising a homogeneous set yielded an OR of 0.68 (95% CI: 0.5– 0.93). However, because of the heterogeneity in individual study results, additional large case-control studies are warranted to provide a more definitive conclusion.
Upstream Single-Use Bioprocessing Systems Future Market Trends and Growth Assessment

S ingle-use bioprocessing equipment has become wellaccepted technology in a relatively short time. Disposable devices and components have created market niches and new segments that continue to evolve. In this dynamic environment, it is diff icult to measure acceptance or assess market growth. Here we project the world market for cell culture single-use systems (SUS) as well as problems affecting that market, including adoption for commercial manufacture. This is based on our 10-year analysis of the industry, with data from our eighth annual survey report on biomanufacturing (1). Complex SUS devices with unique attributes continue to emerge. The first single-use bioreactors — Wave rocker platforms (now from GE Healthcare) — entered the market just about 10 years ago. The disposable-bioreactor market remains dynamic, with new entrants and variants continually being tested as alternatives to stainless steel for commercial applications. Single-use technologies (SUTs) now make up a large percentage of smalland midscale biopharmaceutical manufacturing, particularly in clinical testing and research and development (R&D). Upstream SUT includes disposable bioreactors, mixers, containers, tubing, connectors, sampling systems, purification devices and columns, and probes/sensors. Almost all such equipment, particularly the critical parts that contact process streams, is composed primarily of various types of polymers (“plastics”). Market value estimations and the number of devices sold are both moving targets. By now, the industry is well aware that SUTs provide many economic and other advantages over f ixed stainless-steel systems, with companies on average spending about US$1 million/year on disposable equipment (1). Even assuming comparable overall costs, SUTs offer compelling advantages over stainless steel. Greater f lexibility allows companies to buy and assemble systems as needed and store them on site for future use. Those advantages have resulted in SUT capturing a majority of the market for new bioreactors in smallscale research and clinical supplies manufacturing. However, new disposable equipment needs to be purchased for each product run/lot manufactured. No matter the scale, even at ≥2,000 L, SUTs involve cycles of equipment one-time use, disposal and replacement. So although up-front, operating, and total costs are generally lower for SUTs than stainless steel, recurring expenses will be higher because of regular repeated purchases (whereas stainless steel equipment is purchased and installed once). Although SUT dominates much of biopharmaceutical R&D already and is emerging in clinical-scale segments, biopharmaceutical manufacturing is currently dominated by mammalian cell culture capacity, use, and expenditures, especially for monoclonal antibodies (MAbs) that require repeated large doses. Currently, disposable devices have not entered mainstream commercial manufacturing, partly for regulatory reasons. When regulatory agencies approve broad use of plastic singleuse devices, the total market for such devices will increase significantly.
Curvature-driven smoothing: a learning algorithm for feedforward networks

The performance of feedforward neural networks in real applications can often be improved significantly if use is made of a priori information. For interpolation problems this prior knowledge frequently includes smoothness requirements on the network mapping, and can be imposed by the addition to the error function of suitable regularization terms. The new error function, however, now depends on the derivatives of the network mapping, and so the standard backpropagation algorithm cannot be applied. In this letter, we derive a computationally efficient learning algorithm, for a feedforward network of arbitrary topology, which can be used to minimize such error functions. Networks having a single hidden layer, for which the learning algorithm simplifies, are treated as a special case.
Schistosome Long Terminal Repeat Retrotransposons

The human schistosomes, blood flukes of the Genus Schistosoma, have a large genome estimated to be at least 270 megabase pairs (haploid) in size, arrayed on eight pairs (2n = 16) of chromosomes including the Z (male) and W (female) sex chromosomes. The genome appears to include about 14,000 protein encoding genes and a large amount of repetitive sequences. Much of this repetitive component of the schistosome genome is comprised of mobile genetic elements. Of these elements, an expanding number of discrete long terminal repeat (LTR) retrotransposons have been identified in the past five years. The identity, structure, phylogenetic relationships, and size contributions of these schistosome LTR retrotransposons are reviewed here. These elements include the gypsy-like or Pao/BEL -like retrotransposons Boudicca, Sinbad, fugitive, Saci-1, Saci-2, and Saci-3 from Schistosoma mansoni and Gulliver from Schistosoma japonicum.
A test–retest reliability study of child-reported psychiatric symptoms and diagnoses using the Child and Adolescent Psychiatric Assessment (CAPA-C)

SYNOPSIS Seventy-seven 10–18-year-old psychiatric in-patients and out-patients took part in a test-retest study of the Child and Adolescent Psychiatric Assessment (CAPA). They were interviewed on two occasions several days apart. Overall reliability of diagnosis ranged from K = 0·55 (conduct disorder) to 1·0 (substance abuse or dependence). In general, reliability for scale scores of psychopathology was somewhat lower in out-patients than in-patients, though the opposite was the case for anxiety disorders and psychosocial incapacity and the reliability of the diagnosis of conduct disorder – the only individual diagnosis sufficiently common to permit this comparison. Unreliability of reports of behavioural problems was found to be related to admitting to being a liar in the first interview. The implications of these results for the use of the CAPA are discussed.