Miracle-dz/UniFAR-FTUs huggingface dataset:
Processing of Acoustic Cues in Lexical-Tone Identification by Pediatric Cochlear-Implant Recipients.

Purpose The objective was to investigate acoustic cue processing in lexical-tone recognition by pediatric cochlear-implant (CI) recipients who are native Mandarin speakers. Method Lexical-tone recognition was assessed in pediatric CI recipients and listeners with normal hearing (NH) in 2 tasks. In Task 1, participants identified naturally uttered words that were contrastive in lexical tones. For Task 2, a disyllabic word (yanjing) was manipulated orthogonally, varying in fundamental-frequency (F0) contours and duration patterns. Participants identified each token with the second syllable jing pronounced with Tone 1 (a high level tone) as eyes or with Tone 4 (a high falling tone) as eyeglasses. Results CI participants' recognition accuracy was significantly lower than NH listeners' in Task 1. In Task 2, CI participants' reliance on F0 contours was significantly less than that of NH listeners; their reliance on duration patterns, however, was significantly higher than that of NH listeners. Both CI and NH listeners' performance in Task 1 was significantly correlated with their reliance on F0 contours in Task 2. Conclusion For pediatric CI recipients, lexical-tone recognition using naturally uttered words is primarily related to their reliance on F0 contours, although duration patterns may be used as an additional cue.
Concentrating pre-mRNA processing factors in the histone locus body facilitates efficient histone mRNA biogenesis

Concentrating factors in nuclear bodies is thought to promote efficient gene expression. Tatomer et al. show that the histone locus body (HLB) concentrates pre-mRNA processing factors at replication-dependent histone genes, resulting in optimal 3′ end formation of histone mRNAs coupled with transcription termination.
The slag/metal interface and associated phenomena

Interfacial energies in actual industrial systems vary greatly depending upon the exact slag chemistry found in the mold of the continuous caster. They also vary as a function oftime. Studies showed that interfacial tension in practical fluxes tends to increase with a reduction influxes of calcium fluoride and sodium oxide and an increase in alumina.
Moving Threat: Attention and Distance Change Interact in Threat Responding

Defensive reactions need to be quick and appropriate to ensure survival. Thus, it is crucial that threats trigger immediate action upon detection, even in the absence of awareness. In addition, the form of such action should be appropriate to the imminence of the threat. Thus, attention should be guided by signals of increasing threat imminence. We examined whether subliminally presented threat stimuli provoke automatic avoidance tendencies, and whether threat cues’ distance change and threat potential determine attention allocation. Following fear conditioning, participants performed an approach-avoidance task with subliminally presented conditioned threat and safety stimuli, and an attentional bias task with approaching versus distancing signals of threat and safety. Preattentive processing of threat cues resulted in approach rather than avoidance tendencies; attention was captured preferentially by signals of increasing threat imminence. The results support the importance of threat imminence and extend findings of previous research on preattentive influences on defensive responding.
Endothelial to Mesenchymal Transition (EndoMT) in the Pathogenesis of Human Fibrotic Diseases

Fibrotic diseases encompass a wide spectrum of clinical entities including systemic fibrotic diseases such as systemic sclerosis, sclerodermatous graft versus host disease, nephrogenic systemic fibrosis, and IgG4-associated sclerosing disease, as well as numerous organ-specific disorders including radiation-induced fibrosis, and cardiac, pulmonary, liver, and kidney fibrosis. Although their causative mechanisms are quite diverse, these diseases share the common feature of an uncontrolled and progressive accumulation of fibrous tissue macromolecules in affected organs leading to their dysfunction and ultimate failure. The pathogenesis of fibrotic diseases is complex and despite extensive investigation has remained elusive. Numerous studies have identified myofibroblasts as the cells responsible for the establishment and progression of the fibrotic process. Tissue myofibroblasts in fibrotic diseases originate from several sources including quiescent tissue fibroblasts, circulating CD34+ fibrocytes, and the phenotypic conversion of various cell types including epithelial and endothelial cells into activated myofibroblasts. However, the role of the phenotypic transition of endothelial cells into mesenchymal cells (Endothelial to Mesenchymal Transition or EndoMT) in the pathogenesis of fibrotic disorders has not been fully elucidated. Here, we review the evidence supporting EndoMT’s contribution to human fibrotic disease pathogenesis.
Bayesian analysis of split sex ratios: methods and application to the ant Aphaenogaster rudis

Objective: We develop the use of Bayesian logistic regression models for the analysis of sex ratio data for organisms with variable brood sizes. Background: Ant populations often exhibit ‘split sex ratios’, whereby most colonies produce strongly male-biased or female-biased broods. Furthermore, colony-level sex ratios may depend on brood size or other non-normally distributed covariates. The lack of fit of such data to the assumptions of traditional statistical models can produce inaccurate estimates of population sex ratios. Methods: Using the freeware program OpenBUGS, we demonstrate the Bayesian approach by analysing the effects of food supplements on sex ratio expression in the ant Aphaenogaster rudis. Posterior sampling facilitates model checking and improves the estimation of populationlevel sex ratios for non-standard models. Results: Bayesian logistic regression modelling with a random effects term is effective for analysing ant sex ratio data. The distribution of sex ratios among colonies of A. rudis was bimodal with larger broods tending to be more male-biased. Posterior sampling confirmed that a random-effects model is consistent with the observed split sex ratios. The population-level sex ratio was estimated taking into account that brood size was greater for colonies with male-biased sex ratios. The investment sex ratio was 0.80 (proportion female investment: 95% credibility interval = 0.69 to 0.88), consistent with worker control of the sex ratio. We found no evidence to suggest that experimental food supplements affected brood size or sex ratio expression.
The FloWr Online Plat-form: Automated Programming and Computational Creativity as a Service

We present recent developments in the Flowchart Writer (FloWr) project, where we have built a framework for imple- menting creative systems as flowcharts of processing nodes. We describe how the system has been migrated from a desk- top application to a web portal and document the various fea- tures that the portal provides to support Computational Cre- ativity research and development. This includes a node devel- opment package and automated chart development assistants. We detail how we have supplemented the online graphical platform with a web service API to enable developers to re- motely access the features of FloWr through a programming language of their choice. This encompasses developing sys- tems as flowcharts, together with running flowcharts remotely and also allows developers to publish flowcharts as web ser- vices. Importantly, the API allows Computational Creativity researchers to experiment with the automated development of creative software systems. To encourage this, we have also in- troduced simple models for automated software development into the FloWr API itself, providing a novel system for un- sophisticated users to experiment with. We demonstrate the potential benefits of using FloWr, with case studies showing how the web portal has been used for both node and chart development by novice and expert users.
Empirical research on corporate credit-ratings: A literature review

We report on the current state and important older findings of empirical studies on corporate credit ratings and their relationship to ratings of other entities. Specifically, we consider the results of three lines of research: The correlation of credit ratings and corporate default, the influence of ratings on capital markets, and the determinants of credit ratings and rating changes. Results from each individual line are important and relevant for the construction and interpretation of studies in the other two fields, e.g. the choice of statistical methods. Moreover, design and construct of credit ratings and the credit rating scale are essential to understand empirical findings.
Rapid and Sensitive Liquid Chromatographic Method for Determination of Paclitaxel from Parenteral Formulation and Nanoparticles

A simple and fast reversed phase liquid chromatographic method was developed for estimation of paclitaxel in commercially available parenteral formulation and nanoparticles. Separations were carried out using mobile phase consisting of acetonitrile and 20 mM potassium dihydrogen phosphate (45:55, v/v) on Lichrocart® C18 analytical column at a flow rate of 1 ml/min and detection wavelength of 230 nm. The developed method exhibited linearity over an analytical range of 50-2000 ng/ml with regression equation, mean peak area= 137.58 concentration (ng/ml)+1765.94, (R2 =0.9999). The method demonstrated selectivity with no interfering peaks eluting near the vicinity of drug peak. The method was found to be sensitive with detection and quantification limits of 7.57 ng/ml and 22.94 ng/ml. The method has shown consistent and good recoveries from parenteral formulation (100.06±0.86%) and nanoparticles (100.43±0.91%). The method was successfully employed for the analysis of in vitro release study samples of nanoparticle formulation. The method was also applied for determination of paclitaxel content in various pharmaceutical formulations.
nsemble perception of emotions in autistic and typical children and dolescents

Ensemble perception, the ability to assess automatically the summary of large amounts of information presented in visual scenes, is available early in typical development. This ability might be compromised in autistic children, who are thought to present limitations in maintaining summary statistics representations for the recent history of sensory input. Here we examined ensemble perception of facial emotional expressions in 35 autistic children, 30 ageand ability-matched typical children and 25 typical adults. Participants received three tasks: a) an ‘ensemble’ emotion discrimination task; b) a baseline (single-face) emotion discrimination task; and c) a facial expression identification task. Children performed worse than adults on all three tasks. Unexpectedly, autistic and typical children were, on average, indistinguishable in their precision and accuracy on all three tasks. Computational modelling suggested that, on average,
Statistical methods for detecting differentially methylated regions based on MethylCap-seq data

DNA methylation is a well-established epigenetic mark, whose pattern throughout the genome, especially in the promoter or CpG islands, may be modified in a cell at a disease stage. Recently developed probabilistic approaches allow distributing methylation signals at nucleotide resolution from MethylCap-seq data. Standard statistical methods for detecting differential methylation suffer from 'curse of dimensionality' and sparsity in signals, resulting in high false-positive rates. Strong correlation of signals between CG sites also yields spurious results. In this article, we review applicability of high-dimensional mean vector tests for detection of differentially methylated regions (DMRs) and compare and contrast such tests with other methods for detecting DMRs. Comprehensive simulation studies are conducted to highlight the performance of these tests under different settings. Based on our observation, we make recommendations on the optimal test to use. We illustrate the superiority of mean vector tests in detecting cancer-related canonical gene pathways, which are significantly enriched for acute myeloid leukemia and ovarian cancer.
Systemic antibodies towards mucosal bacteria in ulcerative colitis and Crohn’s disease differentially activate the innate immune response

Background and aims: The mucosa in ulcerative colitis (UC) is replete with antibody producing plasma B cells and polymorphonuclear leucocytes (PMN). This combination of effector cells requires a crosslinking antigen to evoke an antibody driven PMN inflammatory response via their Fc receptors. The stimulus for activation is thought to be commensal bacteria colonising the gut mucosa. The aim of this investigation was to compare the principal culturable bacterial populations on the rectal mucosa of UC patients, and to determine whether specific antibodies towards these bacteria can activate infiltrating PMN through opsonisation. This would provide an explanation for this chronic inflammatory condition. Methods: Bacteria colonising rectal tissue were characterised using chemotaxonomic techniques. Systemic antibody responses were measured against total antigens and surface antigens of these organisms in UC and Crohn’s disease (CD) patients, together with healthy controls. Antibody enhancement of the respiratory burst in PMN was also investigated, against a range of mucosal isolates. Results: Distinct differences were observed in some bacterial populations in UC biopsies, which were generally reflected in antibody responses towards these organisms. UC patients had higher IgG responses to surface antigens, primarily IgG1, whereas the response in CD was mainly IgG2. Antibodies from UC patients greatly enhanced the respiratory burst in PMN, in response to individual bacterial species. Conclusions: Changes in mucosal bacteria, and a switch from internal to surface antigen/antibody reactivity of a predominantly IgG1 type, leads to greater opsonisation of the respiratory burst in PMN, providing a mechanism for maintaining the inflammatory state in UC.
2 Model Setup and Several Methods in Variable Selection 2 . 1 Model Setup and Notations

Regularization is a popular variable selection technique for high dimensional regression models. However, under the ultra-high dimensional setting, a direct application of the regularization methods tends to fail in terms of model selection consistency due to the possible spurious correlations among predictors. Motivated by the ideas of screening (Fan and Lv, J R Stat Soc Ser B Stat Methodol 70:849–911, 2008) and retention (Weng et al, Manuscript, 2013), we propose a new two-step framework for variable selection, where in the first step, marginal learning techniques are utilized to partition variables into different categories, and the regularization methods can be applied afterwards. The technical conditions of model selection consistency for this broad framework relax those for the one-step regularization methods. Extensive simulations show the competitive performance of the new method.
Two-Time-Scale Approximation for Wonham Filters

This paper is concerned with approximation of Wonham filters. A focal point is that the underlying hidden Markov chain has a large state space. To reduce computational complexity, a two-time-scale approach is developed. Under time scale separation, the state space of the underlying Markov chain is divided into a number of groups such that the chain jumps rapidly within each group and switches occasionally from one group to another. Such structure gives rise to a limit Wonham filter that preserves the main features of the filtering process, but has a much smaller dimension and therefore is easier to compute. Using the limit filter enables us to develop efficient approximations and useful filters for hidden Markov chains. The main advantage of our approach is the reduction of dimensionality
Application of Neural Networks to an Emerging Financial Market: Forecasting and Trading the Taiwan Stock Index

In this study, we attempt to model and predict the direction of return on market index of the Taiwan Stock Exchange, one of the fastest growing financial exchanges in developing Asian countries. Our motivation is based on the notion that trading strategies guided by forecasts of the direction of price movement may be more effective and lead to higher profits. The probabilistic neural network (PNN) is used to forecast the direction of index return after it is trained by historical data. Statistical performance of the PNN forecasts are measured and compared with that of the generalized methods of moments (GMM) with Kalman filter. Moreover, the forecasts are applied to various index trading strategies, of which the performances are compared with those generated by the buy-and-hold strategy as well as the investment strategies guided by forecasts estimated by the random walk model and the parametric GMM models. Empirical results show that the PNN-based investment strategies obtain higher returns than other investment strategies examined in this study. Influences of length of investment horizon and commission rate are also considered.
Psychological stress and its relationship to self-effectiveness by special education teachers

This study aimed to discover the psychological stress and its relationship to self-effectiveness for the special education teachers. To achieve this goal, the researcher used the descriptive approach. The study sample consisted of (90) of the special education teachers from Jeddah divided as follow: (30) are teachers of the hearing impaired children; of whom (16) male teachers, (14) female teacher, and other (30) are teachers of the visually impaired children; of whom (14) are male teachers, and (16) are female teachers. More other (30) are teachers of the mentally handicapped children; of whom (12) are male teachers, and (18) are female teachers. The psychological stress measure of the teachers of special education as prepared by Al-Akshar (2003) has been used, in addition to the perceived general self-effectiveness measure and the teacher self-effectiveness measure as prepared by the two researchers after verifying signs of validity and reliability. The results of the study have shown that a negative and statistically referring correlation exists at the level of 0.01 between psychological stress and the general selfeffectiveness for the male and female teachers of the hearing impaired children. There is also a negative and statistically referring correlation at the level of 0.01 between psychological stress and unique self-effectiveness (teaching, classroom management, parents, creating a positive atmosphere at school) on the one hand and the overall score of the measure for whole sample of the male and female teachers of the hearing-impaired children. In addition, there is a negative and statistically referring correlation at the level of 0.05 between psychological stress and the domain of administrative self-effectiveness (as it is one of the branches of self-efficacy) for the male and female teachers of the hearing-impaired children. Research Results have also shown that there is a negative and statistically referring correlation exists at the level of 0.01 between psychological stress and both the general self-effectiveness of teachers and the unique self-effectiveness with its five dimensions and the overall score of the measure of the unique self-effectiveness for the female and male teachers of the visually-impaired children. The study has also shown that there is a negative and statistically referring correlation at the level of 0.01 between psychological stress and both the general self-effectiveness of teachers and the unique self-effectiveness with its five dimensions (administration, teaching. management, classroom management, parents, creating a positive atmosphere at school) and the overall score of the unique self-effectiveness for the female and male teacher at the special education schools of the mentally-handicapped children. [Khaled Soliman, Najati Yunis, Moayyad Humaidi, Ahmad Issa, Hamza Bani Khaled, Abdulhade Haymour and Saleh M Saleh. Psychological stress and its relationship to self-effectiveness by special education teachers. Life Sci J 2014;11(10):1230-1244]. (ISSN:1097-8135). http://www.lifesciencesite. com. 184
A Modular Deep-learning Environment for Rogue

Rogue is a famous dungeon-crawling video-game of the 80ies, the ancestor of its gender. Due to their nature, and in particular to the necessity to explore partially observable and always different labyrinths (no level replay), roguelike games are a very natural and challenging task for reinforcement learning and Q-learning, requiring the acquisition of complex, non-reactive behaviours involving memory and planning. In this article we present Rogueinabox: an environment allowing a simple interaction with the Rogue game, especially designed for the definition of automatic agents and their training via deep-learning techniques. We also show a few initial examples of agents, discuss their architecture and illustrate their behaviour.
An interactive exploded view generation using block-based re-rendering

Exploded view generation for volumetric object is a useful method in surgical simulation, but it is very hard to perform real-time operation. We present an interactive method to determine interesting regions and to render a scene with varying volume datasets in real-time. In general, since conventional methods are designed to solve the problem of occlusion of sub-volumes, they did not consider performance. Especially, exploded view generation methods are difficult to render a scene in real-time even in the case of exploiting highly optimized method. Because they perform volume rendering after defining rules to split an original volume and constraints to order sub-volumes. We present an interactive cutting operation using GPU-based parallel processing and real-time rendering using block-based re-rendering method.
Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine

In an effort to better understand the complex courtship be- haviour of pigeons, we have built a model learned from motion capture data. We employ a Conditional Restricted Boltzmann Machine (CRBM) with binary latent features and real-valued visible units. The units are conditioned on information from previous time steps to capture dynam- ics. We validate a trained model by quantifying the characteristic "head- bobbing" present in pigeons. We also show how to predict missing data by marginalizing out the hidden variables and minimizing free energy.