Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Selection using Distributed Ensemble Classifiers for Very Large Datasets

Datasets are becoming larger and there is an acute need to use data mining techniques to exploit the available data. The increasing size of the datasets poses a challenge to the data miners, which can be solved using two approaches – high speed computing systems, and pre-processing techniques. In this paper, we propose a solution combining the above two techniques using a distributed feature selection method to address the challenge of mining very large datasets. The dependencies of the features of a dataset are computed by an ensemble of classifiers in a distributed computing environment called Hadoop, leading to faster processing and increased reliability. A subset of features is selected based on the averaged estimated dependency vector. The proposed model is verified with different data sets and the validated results are presented. Keywords-data mining; feature selection; large datasets; data preprocessing; mapreduce
Probabilistic Linear Discriminant Analysis for Acoustic Modeling

In this letter, we propose a new acoustic modeling approach for automatic speech recognition based on probabilistic linear discriminant analysis (PLDA), which is used to model the state density function for the standard hidden Markov models (HMMs). Unlike the conventional Gaussian mixture models (GMMs) where the correlations are weakly modelled by using the diagonal covariance matrices, PLDA captures the correlations of feature vector in subspaces without vastly expanding the model. It also allows the usage of high dimensional feature input, and therefore is more flexible to make use of different type of acoustic features. We performed the preliminary experiments on the Switchboard corpus, and demonstrated the feasibility of this acoustic model.
Rethinking schizophrenia in the context of normal neurodevelopment

The schizophrenia brain is differentiated from the normal brain by subtle changes, with significant overlap in measures between normal and disease states. For the past 25 years, schizophrenia has increasingly been considered a neurodevelopmental disorder. This frame of reference challenges biological researchers to consider how pathological changes identified in adult brain tissue can be accounted for by aberrant developmental processes occurring during fetal, childhood, or adolescent periods. To place schizophrenia neuropathology in a neurodevelopmental context requires solid, scrutinized evidence of changes occurring during normal development of the human brain, particularly in the cortex; however, too often data on normative developmental change are selectively referenced. This paper focuses on the development of the prefrontal cortex and charts major molecular, cellular, and behavioral events on a similar time line. We first consider the time at which human cognitive abilities such as selective attention, working memory, and inhibitory control mature, emphasizing that attainment of full adult potential is a process requiring decades. We review the timing of neurogenesis, neuronal migration, white matter changes (myelination), and synapse development. We consider how molecular changes in neurotransmitter signaling pathways are altered throughout life and how they may be concomitant with cellular and cognitive changes. We end with a consideration of how the response to drugs of abuse changes with age. We conclude that the concepts around the timing of cortical neuronal migration, interneuron maturation, and synaptic regression in humans may need revision and include greater emphasis on the protracted and dynamic changes occurring in adolescence. Updating our current understanding of post-natal neurodevelopment should aid researchers in interpreting gray matter changes and derailed neurodevelopmental processes that could underlie emergence of psychosis.
De la conduite du changement instrumentalisée au changement agile

En 40 ans, la conduite du changement est devenue une pratique gestionnaire courante dans la plupart des organisations du fait du role croissant des changements et des attentes du corps social en termes d’accompagnement. Un travail d’analyse historique sur les pratiques de conduite du changement montre cinq paradigmes installes. Le dernier paradigme intitule « Paradigme Experientiel » montre les limites du modele classique de la conduite du changement instrumentalise developpe a partir des travaux de Kanter (1992). Juge trop bureaucratique et pas assez collaboratif, ce modele evolue vers le changement agile. En privilegiant les boucles d’experiences a partir d’ateliers participatifs et un pilotage de la transformation dans une logique de developpement de la capacite a changer, le changement agile apparait comme une solution aux questions actuelles de la conduite du changement.
Modulation of Neuritogenesis by a Protein Implicated in X-Linked Mental Retardation

Posttranscriptional regulation is an important control mechanism governing gene expression in neurons. We recently demonstrated that VCX-A, a protein implicated in X-linked mental retardation, is an RNA-binding protein that specifically binds the 5′ end of capped mRNAs to prevent their decapping and decay. Previously, expression of VCX-A was reported to be testes restricted. Consistent with a role in cognitive function, we demonstrate that VCX-A is ubiquitously expressed in human tissues including the brain. Moreover, retinoic acid-induced differentiation of human SH-SY5Y neuroblastoma cells promoted the accumulation of VCX-A in distinct cytoplasmic foci within neurites that colocalize with staufen1-containing RNA granules, suggesting a role in translational suppression and/or mRNA transport. Exogenous expression of VCX-A in rat primary hippocampal neurons, which normally do not express the primate-restricted VCX proteins, promoted neurite arborization, and shRNA-directed knockdown of the VCX genes in SH-SY5Y cells resulted in a reduction of both primary and secondary neurite projections upon differentiation. We propose that the cap-binding property of VCX-A reflects a role of this protein in mRNA translational regulation. In support of this hypothesized role, we demonstrate that VCX-A can specifically bind a subset of mRNAs involved in neuritogenesis and is also capable of promoting translational silencing. Thus, VCX-A contains the capacity to modulate the stability and translation of a subset of target mRNAs involved in neuronal differentiation and arborization. It is plausible that defects of these functions in the absence of the VCX genes could contribute to a mental retardation phenotype.
Sparsification of Two-Variable Valued Constraint Satisfaction Problems

A valued constraint satisfaction problem (VCSP) instance $(V,\Pi,w)$ is a set of variables $V$ with a set of constraints $\Pi$ weighted by $w$. Given a VCSP instance, we are interested in a reweighted subinstance $(V,\Pi'\subset \Pi,w')$ that preserves the value of the given instance (under every assignment to the variables) within factor $1\pm\epsilon$. A well-studied special case is cut sparsification in graphs, which has found various applications. We show that a VCSP instance consisting of a single boolean predicate $P(x,y)$ (e.g., for cut, $P=\mathsf{XOR}$) can be sparsified into $O(|V|/\epsilon^2)$ constraints iff the number of inputs that satisfy $P$ is anything but one (i.e., $|P^{-1}(1)| \neq 1$). Furthermore, this sparsity bound is tight unless $P$ is a relatively trivial predicate. We conclude that also systems of 2SAT (or 2LIN) constraints can be sparsified.
Study of TOA Positioning Using UWB Reflected Waves

With the global spread of mobile terminals, positioning technologies have become an important research issue. The recent main challenges in positioning technologies are the non-line-of sight (NLOS) and reflected wave problems. This paper presents a positioning method that utilizes reflected waves in a positive manner. This method realizes accurate positioning with few base stations (BSs) (one BS at minimum). NLOS positioning is possible if more than three reflected waves can be received at the BS. The proposed method was verified by fundamental experiments, and the estimation errors were evaluated theoretically and by computer simulation.
The “Dynamic Unconscious” May Be Experienced: Can We Discuss Unconscious Emotions When There Are no Adequate Measures of Affective Change?

The brain has many deeply unconscious neural processes, but the realm of phenomenal consciousness (qualia) rather than “awareness” is the critical issue whether there is nothing relevant in mind while so-called “dynamically unconscious” processes are operating in the brain. Concepts such as “conscious awareness” are one step above phenomenal experiences and can easily lead to confusions about what is or is not experienced during dynamically “unconscious” emotional information processing. If one does not explicitly evaluate for the presence of affective phenomenal experiential shifts, with the most sensitive and relevant measures, one can fall into the trap of calling something unconscious when it is simply not being processed in higher order “awareness. ” I provide examples of where the failure to monitor affective experiential shifts has too easily led investigators to place experienced aspects of mind into the unconscious, based more on their limited methodologies rather than on the absence of experiential affective shifts that pass through the mind experimentally unnoticed. Such lapses in experimental control may have had invidious, but currently unevaluated, effects on the very substantial review of available research and thinking on the “dynamic unconscious” that Heather Berlin superbly summarizes.
Repetitions and Contrasts

In this article, an approach to unit plans using essential questions is described within the context of general music education and illustrated in the unit Repetition and Contrasts: Understanding Music Through Form. This unit is founded on the essential question: As musicians, how do we use form to organize and understand music? Learning guideposts provide direction and impetus for the essential questions on which the unit is founded. Learning guideposts detailed for this unit include content and materials, processes, culminating project/performance, and propensities. Summaries of lessons illustrate how the ideas presented in this framework transfer to daily instruction. Student assessment is embedded within lessons from multiple perspectives denoted as assessment for learning, assessment as learning, and assessment of learning.
ULTRA SONOGRAPHIC EVALUATION OF FIRST TRIMESTER VAGINAL BLEEDING

Objective: To evaluate role of ultrasound in patients with first trimester vaginal bleeding. Design: Hospital based study. Subject: A total of 250 cases presented with complaint of bleeding per vaginum during first trimester, were enrolled for study. Methods: Ultrasonographic examinations were done per abdominally by using ultrasound equipment with picture monitor, Transducer of 3.5 MHz and high transmission jelly. Results: Missed abortion is commonest diagnosis seen in 32.4% cases followed by threatened abortion seen in 28.8% of cases by ultrasonography. Blighted ovum was seen in 17.6% of cases which can not be diagnosed by clinical methods. We found very high discrepancy between clinical diagnosis and sonographic diagnosis. Conclusion: Correct management of cases depends on correct diagnosis and correct diagnosis is very difficult without ultrasound in cases of first trimester vaginal bleeding.
Quality Assessment of the Affymetrix U133A&B Probesets by Target Sequence Mapping and Expression Data Analysis

Careful analysis of microarray probe design should be an obligatory component of MicroArray Quality Control (MACQ) project [Patterson et al., 2006; Shi et al., 2006] initiated by the FDA (USA) in order to provide quality control tools to researchers of gene expression profiles and to translate the microarray technology from bench to bedside. The identification and filtering of unreliable probesets are important preprocessing steps before analysis of microarray data. These steps may result in an essential improvement in the selection of differentially expressed genes, gene clustering and construction of co-regulatory expression networks. We revised genome localization of the Affymetrix U133A&B GeneChip initial (target) probe sequences, and evaluated the impact of erroneous and poorly annotated target sequences on the quality of gene expression data. We found about 25% of Affymetrix target sequences overlapping with interspersed repeats that could cause cross-hybridization effects. In total, discrepancies in target sequence annotation account for up to approximately 30% of 44692 Affymetrix probesets. We introduce a novel quality control algorithm based on target sequence mapping onto genome and GeneChip expression data analysis. To validate the quality of probesets we used expression data from large, clinically and genetically distinct groups of breast cancers (249 samples). For the first time, we quantitatively evaluated the effect of repeats and other sources of inadequate probe design on the specificity, reliability and discrimination ability of Affymetrix probesets. We propose that only functionally reliable Affymetrix probesets that passed our quality control algorithm (approximately 86%) for gene expression analysis should be utilized. The target sequence annotation and filtering is available upon request.
Chronic Oxidative Stress, Mitochondrial Dysfunction, Nrf2 Activation and Inflammation in the Hippocampus Accompany Heightened Systemic Inflammation and Oxidative Stress in an Animal Model of Gulf War Illness

Memory and mood dysfunction are the key symptoms of Gulf war illness (GWI), a lingering multi-symptom ailment afflicting >200,000 veterans who served in the Persian Gulf War-1. Research probing the source of the disease has demonstrated that concomitant exposures to anti-nerve gas agent pyridostigmine bromide (PB), pesticides, and war-related stress are among the chief causes of GWI. Indeed, exposures to GWI-related chemicals (GWIR-Cs) and mild stress in animal models cause memory and mood impairments alongside reduced neurogenesis and chronic low-level inflammation in the hippocampus. In the current study, we examined whether exposure to GWIR-Cs and stress causes chronic changes in the expression of genes related to increased oxidative stress, mitochondrial dysfunction, and inflammation in the hippocampus. We also investigated whether GWI is linked with chronically increased activation of Nrf2 (a master regulator of antioxidant response) in the hippocampus, and inflammation and enhanced oxidative stress at the systemic level. Adult male rats were exposed daily to low-doses of PB and pesticides (DEET and permethrin), in combination with 5 min of restraint stress for 4 weeks. Analysis of the hippocampus performed 6 months after the exposure revealed increased expression of many genes related to oxidative stress response and/or antioxidant activity (Hmox1, Sepp1, and Srxn1), reactive oxygen species metabolism (Fmo2, Sod2, and Ucp2) and oxygen transport (Ift172 and Slc38a1). Furthermore, multiple genes relevant to mitochondrial respiration (Atp6a1, Cox6a1, Cox7a2L, Ndufs7, Ndufv1, Lhpp, Slc25a10, and Ucp1) and neuroinflammation (Nfkb1, Bcl6, Csf2, IL6, Mapk1, Mapk3, Ngf, N-pac, and Prkaca) were up-regulated, alongside 73–88% reduction in the expression of anti-inflammatory genes IL4 and IL10, and nuclear translocation and increased expression of Nrf2 protein. These hippocampal changes were associated with elevated levels of pro-inflammatory cytokines and chemokines (Tnfa, IL1b, IL1a, Tgfb, and Fgf2) and lipid peroxidation byproduct malondialdehyde in the serum, suggesting the presence of an incessant systemic inflammation and elevated oxidative stress. These results imply that chronic oxidative stress, inflammation, and mitochondrial dysfunction in the hippocampus, and heightened systemic inflammation and oxidative stress likely underlie the persistent memory and mood dysfunction observed in GWI.
Evolutionary Divergence in the Catalytic Activity of the CAM-1, ROR1 and ROR2 Kinase Domains

Receptor tyrosine kinase-like orphan receptors (ROR) 1 and 2 are atypical members of the receptor tyrosine kinase (RTK) family and have been associated with several human diseases. The vertebrate RORs contain an ATP binding domain that deviates from the consensus amino acid sequence, although the impact of this deviation on catalytic activity is not known and the kinase function of these receptors remains controversial. Recently, ROR2 was shown to signal through a Wnt responsive, β-catenin independent pathway and suppress a canonical Wnt/β-catenin signal. In this work we demonstrate that both ROR1 and ROR2 kinase domains are catalytically deficient while CAM-1, the C. elegans homolog of ROR, has an active tyrosine kinase domain, suggesting a divergence in the signaling processes of the ROR family during evolution. In addition, we show that substitution of the non-consensus residues from ROR1 or ROR2 into CAM-1 and MuSK markedly reduce kinase activity, while restoration of the consensus residues in ROR does not restore robust kinase function. We further demonstrate that the membrane-bound extracellular domain alone of either ROR1 or ROR2 is sufficient for suppression of canonical Wnt3a signaling, and that this domain can also enhance Wnt5a suppression of Wnt3a signaling. Based on these data, we conclude that human ROR1 and ROR2 are RTK-like pseudokinases.
Socially Responsible Teaching and English Language Coursebooks: Focus on Ethnicity, Sex, and Disability

The purpose of this study is to analyze the reading passages and related pictures published in English language coursebooks in terms of ethnicity, sex and disability by relating them to socially responsible teaching. A checklist formerly used by Cunningsworth (1995) was adapted and used for the purposes of this study. This checklist included the headings of nationalities, whether any kind of disability is included or not, types of disability, number of males and females and gender specific roles attached to males and females. A total of 240 reading passages were analyzed throughout the study and frequencies and percentages for each coursebook were calculated. Results indicate that the coursebooks analyzed generally lack sensitivity to differences based on nationalities, sexes and disability. Results also demonstrate that disability gets little or no place in the coursebooks studied. Also, it was found that females are not represented equally with males. With regards to ethnicity, native speakers of English appear in the coursebooks more than non-native speakers do
Evaluation of Gridded Precipitation Data for Driving SWAT Model in Area Upstream of Three Gorges Reservoir

Gridded precipitation data are becoming an important source for driving hydrologic models to achieve stable and valid simulation results in different regions. Thus, evaluating different sources of precipitation data is important for improving the applicability of gridded data. In this study, we used three gridded rainfall datasets: 1) National Centers for Environmental Prediction - Climate Forecast System Reanalysis (NCEP-CFSR); 2) Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE); and 3) China trend - surface reanalysis (trend surface) data. These are compared with monitoring precipitation data for driving the Soil and Water Assessment Tool in two basins upstream of Three Gorges Reservoir (TGR) in China. The results of one test basin with significant topographic influence indicates that all the gridded data have poor abilities in reproducing hydrologic processes with the topographic influence on precipitation quantity and distribution. However, in a relatively flat test basin, the APHRODITE and trend surface data can give stable and desirable results. The results of this study suggest that precipitation data for future applications should be considered comprehensively in the TGR area, including the influence of data density and topography.
Pitch estimation in noisy speech based on temporal accumulation of spectrum peaks

In this paper, we present a study on robust pitch estimation by integrating spectral and temporal information in speech. Spectrum harmonics are important representations of the speech fundamental frequency. Harmonic-related spectral peaks of speech evolve much more slowly than the spectral peaks of noise. This motivates the proposition of temporally accumulated peak spectrum (TAPS), which is computed by cumulating spectrum peaks over consecutive analysis frames. In the TAPS, harmonic-related peaks are concentrated around the fundamental frequency and its multiples, while the peaks caused by noise are irregularly distributed with relatively small amplitude. A pitch estimation method is derived based on TAPS. The peak locations on the autocorrelation of TAPS indicate the frequency separations between the harmonic peaks, which are used to estimate the fundamental frequency. The proposed method is evaluated on speech signals corrupted by white noise, speech noise and babble noise. The results of pitch estimation show that our method performs more robustly and reliably than conventional time-domain and cepstrum-domain methods.
Smart sensor integration: A framework for multimodal emotion recognition in real-time

Affect sensing by machines has been argued as an essential part of next-generation human-computer interaction (HCI). To this end, in the recent years a large number of studies have been conducted, which report automatic recognition of emotion as a difficult, but feasible task. However most effort has been put towards offline analysis, whereas to date only few applications exist, which are able to react to a user's emotion in real-time. In response to this deficit we introduce a framework we call Smart Sensor Integration (SSI), which considerably jump-starts the development of multimodal online emotion recognition (OER) systems. In particular SSI supports the pattern recognition pipeline by offering tailored tools for data segmentation, feature extraction, and pattern recognition, as well as, tools to apply them offline (training phase) and online (real-time recognition). Furthermore, it has been designed to handle input from various input modalities and to suit the fusion of multimodal information.
Design of a simplified adaptive fuzzy backstepping control for uncertain discrete-time nonlinear systems

This paper presents a simplified adaptive fuzzy backstepping control for uncertain discrete-time nonlinear systems. It is assumed that the systems are described by a discrete-time equation with nonlinear uncertainties to be viewed as the modelling errors and the unknown external disturbances, and the states are observed with measurement noises. To design the simplified adaptive fuzzy backstepping control, the modelling errors are approximated by using the fuzzy inference approach based on the extended single-input rule modules, and the estimates for the unmeasurable states and the adjustable parameters are derived by using the weighted and its simplified weighted least squares estimators. It is proved that the states are ultimately bounded, and the estimation errors remain in the vicinity of zero. The effectiveness of the proposed approach is indicated through the simulation experiment of a simple numerical system.