Miracle-dz/UniFAR-FTUs huggingface dataset:
The Th1:Th2 Dichotomy of Pregnancy and Preterm Labour

Pregnancy is a unique immunological state in which a balance of immune tolerance and suppression is needed to protect the fetus without compromising the mother. It has long been established that a bias from the T helper 1 cytokine profile towards the T helper 2 profile contributes towards successful pregnancy maintenance. The majority of publications that report on aberrant Th1:Th2 balance focus on early pregnancy loss and preeclampsia. Over the last few decades, there has been an increased awareness of the role of infection and inflammation in preterm labour, and the search for new biomarkers to predict preterm labour continues. In this paper, we explore the evidence for an aberrant Th1:Th2 profile associated with preterm labour. We also consider the potential for its use in screening women at high risk of preterm labour and for prophylactic therapeutic measures for the prevention of preterm labour and associated neonatal adverse outcomes.
Oxygen and Carbon Dioxide Regulation of Toxic Shock Syndrome Toxin 1 Production by Staphylococcus aureus MN8

ABSTRACT The production of toxic shock syndrome toxin 1 (TSST-1) byStaphylococcus aureus MN8 exposed to a range of oxygen concentrations (0 to 21% [vol/vol]) was examined in batch and thin-film cultures. The response of S. aureus to this range of oxygen concentrations was studied in the absence and in the presence of 7% (vol/vol) carbon dioxide. In the absence of carbon dioxide, TSST-1 production in batch cultures increased from negligible levels in the presence of oxygen concentrations of 1% or less to 500 ng/ml in the presence of 2% oxygen and then decreased to 70 ng/ml or less in the presence of oxygen concentrations of 6% and higher. In the presence of carbon dioxide, however, toxin production increased from negligible levels in the presence of 1% oxygen to 1,900 ng/ml in the presence of 21% oxygen. In thin-film cultures, TSST-1 production increased from nearly undetectable levels under anaerobic conditions to 1 and 10 μg/ml under 21% oxygen in the absence and presence of carbon dioxide, respectively. This study demonstrates the controlling effects of both oxygen and carbon dioxide on TSST-1 production.
Price Jumps in Visegrad Country Stock Markets: An Empirical Analysis

I empirically study price jumps using high frequency data comprising 5-, 10-, 15- and 30-minute market data on the main indices from the Prague, Warsaw, Budapest and Frankfurt Stock Exchanges for June 2003 to the end of 2008. I use two definitions of price jumps: the price jump index and normalized returns. First, I analyze the distribution of returns to support the presence of jumps. Second, I find that the distributions of the price jump indicators employed are significantly different for positive moves compared with negative moves in all the markets studied. In addition, the comparison of jump distributions across different frequencies and markets suggests a possible relationship with market micro-structure as well as with the composition of investors. In particular, at the Prague Stock Exchange, the lower the frequency, the lower the number of extreme jumps, but this is not so at the other markets. Last but not least, I show that the recent financial crisis caused an overall increase in volatility. However, this was not translated into an increase in the absolute number of jumps.
Phosphatidate Phosphatase Plays Role in Zinc-mediated Regulation of Phospholipid Synthesis in Yeast*

Background: In yeast, phospholipid synthesis is regulated by zinc deficiency. Results: PAH1-encoded phosphatidate phosphatase activity was induced in zinc-deficient cells by a transcriptional mechanism. Conclusion: The zinc-mediated regulation of phosphatidate phosphatase affects phospholipid synthesis by controlling phosphatidate and diacylglycerol. Significance: The transcriptional regulation of phosphatidate phosphatase plays an important role in controlling phospholipid synthesis by zinc. In the yeast Saccharomyces cerevisiae, the synthesis of phospholipids is coordinately regulated by mechanisms that control the homeostasis of the essential mineral zinc (Carman, G.M., and Han, G. S. (2007) Regulation of phospholipid synthesis in Saccharomyces cerevisiae by zinc depletion. Biochim. Biophys. Acta 1771, 322–330; Eide, D. J. (2009) Homeostatic and adaptive responses to zinc deficiency in Saccharomyces cerevisiae. J. Biol. Chem. 284, 18565–18569). The synthesis of phosphatidylcholine is balanced by the repression of CDP-diacylglycerol pathway enzymes and the induction of Kennedy pathway enzymes. PAH1-encoded phosphatidate phosphatase catalyzes the penultimate step in triacylglycerol synthesis, and the diacylglycerol generated in the reaction may also be used for phosphatidylcholine synthesis via the Kennedy pathway. In this work, we showed that the expression of PAH1-encoded phosphatidate phosphatase was induced by zinc deficiency through a mechanism that involved interaction of the Zap1p zinc-responsive transcription factor with putative upstream activating sequence zinc-responsive elements in the PAH1 promoter. The pah1Δ mutation resulted in the derepression of the CHO1-encoded phosphatidylserine synthase (CDP-diacylglycerol pathway enzyme) and loss of the zinc-mediated regulation of the enzyme. Loss of phosphatidate phosphatase also resulted in the derepression of the CKI1-encoded choline kinase (Kennedy pathway enzyme) but decreased the synthesis of phosphatidylcholine when cells were deficient of zinc. This result confirmed the role phosphatidate phosphatase plays in phosphatidylcholine synthesis via the Kennedy pathway.
Long-acting injectable risperidone: efficacy and safety of the first long-acting atypical antipsychotic.

OBJECTIVE The authors assessed the efficacy and safety of the first long-acting atypical antipsychotic (long-acting injectable risperidone) in patients with schizophrenia. METHOD In a 12-week, multicenter, double-blind, randomized study, patients received intramuscular injections every 2 weeks of placebo or long-acting risperidone (25 mg, 50 mg, or 75 mg). The primary measure of efficacy was the change in total score on the Positive and Negative Syndrome Scale. RESULTS Of the 554 patients who were enrolled, 400 entered the double-blind study, and 370 received at least one postbaseline assessment. Mean changes in score of -6.2, -8.5, and -7.4 on the Positive and Negative Syndrome Scale were seen at endpoint for the 25-, 50-, and 75-mg risperidone groups, respectively; all three change scores were significantly different from that seen with placebo (+2.6). Improvements in positive and negative symptoms were also significantly greater in patients receiving risperidone. Long-acting risperidone was well tolerated. Adverse events related to extrapyramidal symptoms were spontaneously reported by 13% of patients receiving placebo and 10% of patients in the 25-mg risperidone group, with higher rates in the 50-mg and 75-mg groups. Severity of extrapyramidal symptoms was mild at baseline and throughout the trial in each treatment group. Mean weight changes were small in the 25-, 50-, and 75-mg risperidone groups (0.5 kg, 1.2 kg, and 1.9 kg, respectively). Injection site pain was rated as low by the patients, consistent with the investigators' pain ratings. CONCLUSIONS Long-acting injectable risperidone was efficacious and well tolerated and provides both clinicians and patients with a new mode of treatment that can improve the outcome of long-term therapy.
Estimation of the Spanish secondary reserves requirements

The increasing penetration of Intermittent Generation (IG) is being accompanied by the revision of the needs of traditional regulation reserves, as well as the discussion of new flexibility products for system balancing. In the context of electricity generation models, it is of high relevance to adequately represent, not only the energy, but also the reserve dispatch constraints, by providing the models with the expected secondary reserve requirements (SRR), so as to output more realistic energy and reserve schedules and prices. This paper analyses the SRR published by the Spanish System Operator and uses several forecasting tools for determining its main explanatory variables. Results confirm that the SRR have remained almost constant during the years of significant IG growth (and even slightly decreasing in the most recent years), and that the best SRR estimation models found use the demand and its inter-hour variations as the main explanatory variables, but not wind productions as could be expected.
Distributed Neural Processing Predictors of Multi-dimensional Properties of Affect

Recent evidence suggests that emotions have a distributed neural representation, which has significant implications for our understanding of the mechanisms underlying emotion regulation and dysregulation as well as the potential targets available for neuromodulation-based emotion therapeutics. This work adds to this evidence by testing the distribution of neural representations underlying the affective dimensions of valence and arousal using representational models that vary in both the degree and the nature of their distribution. We used multi-voxel pattern classification (MVPC) to identify whole-brain patterns of functional magnetic resonance imaging (fMRI)-derived neural activations that reliably predicted dimensional properties of affect (valence and arousal) for visual stimuli viewed by a normative sample (n = 32) of demographically diverse, healthy adults. Inter-subject leave-one-out cross-validation showed whole-brain MVPC significantly predicted (p < 0.001) binarized normative ratings of valence (positive vs. negative, 59% accuracy) and arousal (high vs. low, 56% accuracy). We also conducted group-level univariate general linear modeling (GLM) analyses to identify brain regions whose response significantly differed for the contrasts of positive versus negative valence or high versus low arousal. Multivoxel pattern classifiers using voxels drawn from all identified regions of interest (all-ROIs) exhibited mixed performance; arousal was predicted significantly better than chance but worse than the whole-brain classifier, whereas valence was not predicted significantly better than chance. Multivoxel classifiers derived using individual ROIs generally performed no better than chance. Although performance of the all-ROI classifier improved with larger ROIs (generated by relaxing the clustering threshold), performance was still poorer than the whole-brain classifier. These findings support a highly distributed model of neural processing for the affective dimensions of valence and arousal. Finally, joint error analyses of the MVPC hyperplanes encoding valence and arousal identified regions within the dimensional affect space where multivoxel classifiers exhibited the greatest difficulty encoding brain states – specifically, stimuli of moderate arousal and high or low valence. In conclusion, we highlight new directions for characterizing affective processing for mechanistic and therapeutic applications in affective neuroscience.
A Methodology for Terminology-based Knowledge Acquisition and Integration

In this paper we propose an integrated knowledge management system in which terminology-based knowledge acquisition, knowledge integration, and XML-based knowledge retrieval are combined using tag information and ontology management tools. The main objective of the system is to facilitate knowledge acquisition through query answering against XML-based documents in the domain of molecular biology. Our system integrates automatic term recognition, term variation management, context-based automatic term clustering, ontology-based inference, and intelligent tag information retrieval. Tag-based retrieval is implemented through interval operations, which prove to be a powerful means for textual mining and knowledge acquisition. The aim is to provide efficient access to heterogeneous biological textual data and databases, enabling users to integrate a wide range of textual and non-textual resources effortlessly.
Introduction to Policing

This groundbreaking new text by Michael Rowe is the first genuinely introductory, comprehensive textbook on policing. Introduction to Policing has been carefully developed to incorporate all the key areas of a policing course, from the history of the police and the legal framework, to current debates around issues such as diversity, surveillance, and the impact of the media. The book highlights the way in which theory applies to practice at every step.
A Bayesian approach for epileptic seizures detection with 3D accelerometers sensors

In this paper, an algorithm able to detect epilepsy seizure based on 3D accelerometers and with patient adaptation is presented. This algorithm is based on a Bayesian approach using hidden Markov models for statistical modelling of moves signals. A particular focus is set on the learning procedure and in particular on its initialisation to ensure a good learning and to avoid numerical instability. Numerical simulations show that, without inhibition of the detection algorithm when the person is standing up, the algorithm is able to detect close to 90% of seizures when false alarms are 25% of alarms.
Recruitment of a protein complex containing Tat and cyclin T1 to TAR governs the species specificity of HIV‐1 Tat

Human cyclin T1 (hCycT1), a major subunit of the essential elongation factor P‐TEFb, has been proposed to act as a cofactor for human immunodeficiency virus type 1 (HIV‐1) Tat. Here, we show that murine cyclin T1 (mCycT1) binds the activation domain of HIV‐1 Tat but, unlike hCycT1, cannot mediate Tat function because it cannot be recruited efficiently to TAR. In fact, overexpression of mCycT1, but not hCycT1, specifically inhibits Tat–TAR function in human cells. This discordant phenotype results from a single amino acid difference between hCycT1 and mCycT1, a tyrosine in place of a cysteine at residue 261. These data indicate that the ability of Tat to recruit CycT1/P‐TEFb to TAR determines the species restriction of HIV‐1 Tat function in murine cells and therefore demonstrate that this recruitment is a critical function of the Tat protein.
100 years of sperm chemotaxis

Exactly 100 years ago, F.R. Lillie reported chemotaxis in animal sperm for the first time ([Lillie, 1912][1]). Chemotaxis refers to the directed movement of a cell or organism to the source of a chemical gradient; the chemical agent that elicits this movement is called a chemoattractant. Chemotaxis
Influence of Exercise on the Metabolic Profile Caused by 28 days of Bed Rest with Energy Deficit and Amino Acid Supplementation in Healthy Men

Objective Muscle loss and metabolic changes occur with disuse [i.e. bed rest (BR)]. We hypothesized that BR would lead to a metabolically unhealthy profile defined by: increased circulating tumor necrosis factor (TNF)-α, decreased circulating insulin-like-growth-factor (IGF)-1, decreased HDL-cholesterol, and decreased muscle density (MD; measured by mid-thigh computerized tomography). Methods We investigated the metabolic profile after 28 days of BR with 8±6% energy deficit in male individuals (30-55 years) randomized to resistance exercise with amino acid supplementation (RT, n=24) or amino acid supplementation alone (EAA, n=7). Upper and lower body exercises were performed in the horizontal position. Blood samples were taken at baseline, after 28 days of BR and 14 days of recovery. Results We found a shift toward a metabolically unfavourable profile after BR [compared to baseline (BLN)] in both groups as shown by decreased HDL-cholesterol levels (EAA: BLN: 39±4 vs. BR: 32±2 mg/dL, RT: BLN: 39±1 vs. BR: 32±1 mg/dL; p<0.001) and Low MD (EAA: BLN: 27±4 vs. BR: 22±3 cm2, RT: BLN: 28±2 vs. BR: 23±2 cm2; p<0.001). A healthier metabolic profile was maintained with exercise, including NormalMD (EAA: BLN: 124±6 vs. BR: 110±5 cm2, RT: BLN: 132±3 vs. BR: 131±4 cm2; p<0.001, time-by-group); although, exercise did not completely alleviate the unfavourable metabolic changes seen with BR. Interestingly, both groups had increased plasma IGF-1 levels (EAA: BLN:168±22 vs. BR 213±20 ng/mL, RT: BLN:180±10 vs. BR: 219±13 ng/mL; p<0.001) and neither group showed TNFα changes (p>0.05). Conclusions We conclude that RT can be incorporated to potentially offset the metabolic complications of BR.
A novel pruning model of deep learning for large-scale distributed data processing

In this paper, we propose a novel pruning model of deep learning for large-scale distributed data processing to simulate a potential application in the geographical neighbor of Internet of Things. We formulate a general model of pruning learning, and we investigate the procedure of pruning learning to satisfy hard constraint and soft constraint. The hard constraint is a class of non-flexible setting without parameter learning to match the structure of distributed data. The soft constraint is a process of adaptive parameter learning to satisfy an inequality without any degradation of accuracy if the size of training data is large enough. Based on the simulation using distributed MNIST image database with large-scale samples, the performance of the proposed pruning model is better than that of a state-of-the-art model of deep learning in case of big data processing.
Internet Banking Adaptation Behavior

How and why individuals use Internet banking (IB) has attracted a great deal of academic attention. This chapter reviews the literature on IB behavior through the lenses of nine adoption theories. This review suggests that IB adoption is a complex and multifaceted process; joint consideration of customers’ personal, social, psychological, utilitarian, and behavioral aspects is essential; managers and system developers should undertake a customer-centric approach focusing on managing belief formation rather than directly influencing behavior. However, IB research is in an inconclusive state, and is far from unanimity regarding the approaches and conceptualizations used to understand the beliefs that truly influence IB behavior. There is limited research dealing with the role of interventions that can assist managers in making effective decisions to speed the adoption process. An understanding of customer’s cognitive, emotional, and contextual processes is more important than adoption itself and will ultimately result in the intended behavior.
The Sexual Politics of Meat: A Feminist-Vegetarian Critical Theory

What does the eating of meat have to do with the women's movement? Is there a cultural correlation between our image of and attitude toward women and the slaughter of animals? This study answers these questions by establishing the connections between the women's movement, ecological concerns and our increasing awareness of the environment in the 1990s. In this approach to violence against women and animals, the book uses feminist literary theory to enlighten social practices and develops the thesis that women and animals are linked as "absent referents" in the context of patriarchal society. It provides the beginnings of a feminist history of vegetarianism from 1790 to the present day, and examines works by women writers that depict a connection between meat eating, male dominance and war. In identifying the cross-mapping of feminism and vegetarianism, the book argues that vegetarianism can act as a sign of autonomous female being, and signals a rejection of male control.
Analysis of a New Human Parechovirus Allows the Definition of Parechovirus Types and the Identification of RNA Structural Domains

ABSTRACT Human parechoviruses (HPeV), members of the Parechovirus genus of Picornaviridae, are frequent pathogens but have been comparatively poorly studied, and little is known of their diversity, evolution, and molecular biology. To increase the amount of information available, we have analyzed 7 HPeV strains isolated in California between 1973 and 1992. We found that, on the basis of VP1 sequences, these fall into two genetic groups, one of which has not been previously observed, bringing the number of known groups to five. While these correlate partly with the three known serotypes, two members of the HPeV2 serotype belong to different genetic groups. In view of the growing importance of molecular techniques in diagnosis, we suggest that genotype is an important criterion for identifying viruses, and we propose that the genetic groups we have defined should be termed human parechovirus types 1 to 5. Complete nucleotide sequence analysis of two of the Californian isolates, representing two types, confirmed the identification of a new genetic group and suggested a role for recombination in parechovirus evolution. It also allowed the identification of a putative HPeV1 cis-acting replication element, which is located in the VP0 coding region, as well as the refinement of previously predicted 5′ and 3′ untranslated region structures. Thus, the results have significantly improved our understanding of these common pathogens.
Shaping the Supreme Court's Federal Certiorari Docket

The size of the Supreme Court's discretionary docket has varied considerably over the last fifty years, and that variation has received more attention in both scholarly and journalistic circles in light of declines over the past fifteen years. To understand the sources of such variation, one must account for external and internal influences on the docket. This study shows that the Supreme Court's docket is not influenced by the ideological distance between the Supreme Court and the lower courts, nor is it driven by the internal division within the lower courts. The chief justice, as first among equals, also appears unable to affect the size of the docket. The justices' preferences appear to play the pivotal role in determining the size of the Court's docket. These findings add to the perception that justices are free of institutional constraints when making their decisions.
An online outlier detection technique for wireless sensor networks using unsupervised quarter-sphere support vector machine

The main challenge faced by outlier detection techniques designed for wireless sensor networks is achieving high detection rate and low false alarm rate while maintaining the resource consumption in the network to a minimum. In this paper, we propose an online outlier detection technique with low computational complexity and memory usage based on an unsupervised centered quarter-sphere support vector machine for real-time environmental monitoring applications of wireless sensor networks. The proposed approach is completely local and thus saves communication overhead and scales well with increase of nodes deployed. We take advantage of spatial correlations that exist in sensor data of adjacent nodes to reduce the false alarm rate in real-time. Experiments with both synthetic and real data collected from the Intel Berkeley Research Laboratory show that our technique achieves better mining performance in terms of parameter selection using different kernel functions compared to an earlier offline outlier detection technique designed for wireless sensor networks.