Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Parallel Algorithm for Nonlinear Dimensionality Reduction on GPU

Advances in nonlinear dimensionality reduction provide a way to understand and visualize the underlying structure of complex data sets. The performance of large-scale nonlinear dimensionality reduction is of key importance in data mining, machine learning, and data analysis. In this paper, we concentrate on improving the performance of nonlinear dimensionality reduction using large-scale data sets on the GPU. In particular, we focus on solving problems including k nearest neighbor (KNN) search and sparse spectral decomposition for large-scale data, and propose an efficient framework for Local Linear Embedding (LLE). We implement a k-d tree based KNN algorithm and Krylov subspace method on the GPU to accelerate the nonlinear dimensionality reduction for large-scale data. Our results enable GPU-based k-d tree LLE processes of up to about 30-60 X faster compared to the brute force KNN [10] LLE model on the CPU. Overall, our methods save O (n2-6n-2k-3) memory space.
PTEN/Akt Signaling Controls Mitochondrial Respiratory Capacity through 4E-BP1

Akt, a serine/threonine kinase has been shown to stimulate glycolysis in cancer cells but its role in mitochondrial respiration is unknown. Using PTEN-knockout mouse embryonic fibroblasts (MEFPTEN−/−) with hyper-activated Akt as a cell model, we observed a higher respiratory capacity in MEFPTEN−/− compared to the wildtype (MEFWT). The respiratory phenotype observed in MEFPTEN−/− was reproduced in MEFWT by gene silencing of PTEN which substantiated its role in regulating mitochondrial function. The increased activities of the respiratory complexes (RCs) I, III and IV were retained in the same relative proportions as those present in MEFWT, alluding to a possible co-ordinated regulation by PTEN/Akt. Using LY294002 (a PI3K inhibitor) and Akt inhibitor IV, we showed that the regulation of enzyme activities and protein expressions of the RCs was dependent on PI3K/Akt. There was insignificant difference in the protein expressions of mitochondrial transcription factor: peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) and its downstream targets, the nuclear respiratory factor 1 (NRF-1) and mitochondrial transcription factor A (mtTFA) between MEFPTEN−/− and MEFWT. Similarly, mRNA levels of the same subunits of the RCs detected in Western blots were not significantly different between MEFPTEN−/− and MEFWT suggesting that the regulation by Akt on mitochondrial function was probably not via gene transcription. On the other hand, a decrease of total 4E-BP1 with a higher expression of its phosphorylated form relative to total 4E-BP1 was found in MEFPTEN−/−, which inferred that the regulation of mitochondrial respiratory activities by Akt was in part through this protein translation pathway. Notably, gene silencing of 4E-BP1 up-regulated the protein expressions of all RCs and the action of 4E-BP1 appeared to be specific to these mitochondrial proteins. In conclusion, PTEN inactivation bestowed a bioenergetic advantage to the cells by up-regulating mitochondrial respiratory capacity through the 4E-BP1-mediated protein translation pathway.
The Influence of Peer Victimization on Educational Outcomes for LGBTQ and Non-LGBTQ High School Students

A total of 11,447 high school students were surveyed to test the relation between victimization and the educational outcomes of truancy, post–high school intentions, and grades for lesbian, gay, bisexual, transgender, and questioning (LGBTQ) and non-LGBTQ students. LGBTQ students reported statistically higher truancy, lower grades, greater expectations not to finish high school, and lower expectations to attend a four-year college. Victimization partially mediated these differences between LGBTQ and non-LGBTQ youth. These results highlight the role of victimization in partially accounting for academic disparities between LGBTQ and non-LGBTQ youth.
Higher-order expansions for compound distributions and ruin probabilities with subexponential claims

Let X i (i=1,2, …) be a sequence of subexponential positive independent and identically distributed random variables. In this paper, we offer two alternative approaches to obtain higher-order expansions of the tail of and subsequently for ruin probabilities in renewal risk models with claim sizes X i . In particular, these emphasize the importance of the term for the accuracy of the resulting asymptotic expansion of . Furthermore, we present a more rigorous approach to the often suggested technique of using approximations with shifted arguments. The cases of a Pareto type, Weibull and Lognormal distribution for X i are discussed in more detail and numerical investigations of the increase in accuracy by including higher-order terms in the approximation of ruin probabilities for finite realistic ranges of s are given.
Sustained attention in young Down syndrome children

Claire B. Kopp, PhD Codirector, Project REACH Associate Professor in Residence Graduate School of Education University of California, Los Angeles Los Angeles, California MANY OF THE Project REACH (Research on the Early Abilities of Children with Handicaps) infancy and toddler studies have centered on describing cognitive and social characteristics of normally developing and handicapped children during the second and third years of life. This emphasis was dictated by the fact that this age period is a time of major intellectual and social growth, yet one that is vastly underresearched. As a result, major challenges confront those attempting to understand and interpret the functioning of handicapped and at-risk children or to address issues related to the origins of problematic performance.
Dealing with Disorder ∗

Often, queries over data streams require input that is ordered in some predetermined way. This order may simply be arrival order or given explicitly on specific attributes, such as timestamp or sequence numbers. For various reasons, data in a stream may not arrive in the expected order. We first introduce a new operator, called the punctuate operator, which is one way to embed punctuations into a data stream. We then discuss two ways for handling disorder in data streams, and compare them to how disorder can be addressed using punctuations embedded with the punctuate operator.
The development of student teachers’ professional identity

This study focuses on student teachers’ perceptions of their professional identity. The respondents are students enrolled in a three‐year course in secondary education teaching at bachelor level. Questionnaires were filled out by first‐year, second‐year and third‐year students from two colleges. The questionnaire included four scales: commitment to teaching, professional orientation, task orientation and self‐efficacy. In the first five months of the first‐year course, a shift in students’ task orientation was observed: students developed a more pupil‐centred view on teaching. Practical experience with classroom teaching again caused a shift: students focused less on the subject matter, on maintaining order in the classroom, on the long‐term educational qualification targets and self‐efficacy decreased. Students with work placement experience developed a more ‘realistic’ view of learning and teaching compared to students without this experience. A final important difference in professional identity is based on students’ gender: while male students tend to attach more importance to discipline in the classroom, their female counterparts focus more on student involvement.
Evaluation of E-Learners Behaviour using Different Fuzzy Clustering Models: A Comparative Study

This paper introduces an evaluation methodologies for the e-learners' behaviour that will be a feedback to the decision makers in e-learning system. Learner's profile plays a crucial role in the evaluation process to improve the e-learning process performance. The work focuses on the clustering of the e-learners based on their behaviour into specific categories that represent the learner's profiles. The learners' classes named as regular, workers, casual, bad, and absent. The work may answer the question of how to return bad students to be regular ones. The work presented the use of different fuzzy clustering techniques as fuzzy c-means and kernelized fuzzy c-means to find the learners' categories and predict their profiles. The paper presents the main phases as data description, preparation, features selection, and the experiments design using different fuzzy clustering models. Analysis of the obtained results and comparison with the real world behavior of those learners proved that there is a match with percentage of 78%. Fuzzy clustering reflects the learners' behavior more than crisp clustering. Comparison between FCM and KFCM proved that the KFCM is much better than FCM in predicting the learners' behaviour.
Concordance between clinical assessments and patients' self-report in depression.

In a survey of 200 depressed patients, clinical symptoms of depression were assessed by both semistructured clinical interview and self-report. Both instruments were given during the acute episode and at follow-up, ten months later, when a majority of patients had recovered. Results indicate concordance between clinical assessment and self-report is low during the acute episode but generally improved at follow-up. Ratings of individual symptoms show a fair degree of specificity. The overall assessment of severity during the acute episode is particularly discordant. These findings demonstrate that self-reports are useful in measuring the presence or absence of symptoms and therefore valuable in assessing recovery. However, self-report ratings from acutely depressed patients are not a reliable estimate of the severity of their symptoms.
Channel network extraction from high resolution topography using wavelets

The availability of high resolution topography from LIDAR offers new opportunities for objectively extracting the channels directly from a DEM using local topographic information, instead of inferring them indirectly based on global criteria, such as area or area‐slope threshold relationships. Here we introduce the use of wavelet filtering to delineate threshold curvatures for defining valleys and threshold slope‐direction‐change for defining probable channeled portions of the valleys. This approach exploits the topographic signatures uniquely found in high resolution topography, and reveals the fuzzy topographic transition in which local weakly convergent areas lie at the transition between hillslopes and valleys.
Yersinia pestis: New Evidence for an Old Infection

The successful reconstruction of an ancient bacterial genome from archaeological material presents an important methodological advancement for infectious disease research. The reliability of evolutionary histories inferred by the incorporation of ancient data, however, are highly contingent upon the level of genetic diversity represented in modern genomic sequences that are publicly accessible, and the paucity of available complete genomes restricts the level of phylogenetic resolution that can be obtained. Here we add to our original analysis of the Yersinia pestis strain implicated in the Black Death by consolidating our dataset for 18 modern genomes with single nucleotide polymorphism (SNP) data for an additional 289 strains at over 600 positions. The inclusion of this additional data reveals a cluster of Y. pestis strains that diverge at a time significantly in advance of the Black Death, with divergence dates roughly coincident with the Plague of Justinian (6th to 8th century AD). In addition, the analysis reveals further clues regarding potential radiation events that occurred immediately preceding the Black Death, and the legacy it may have left in modern Y. pestis populations. This work reiterates the need for more publicly available complete genomes, both modern and ancient, to achieve an accurate understanding of the history of this bacterium.
Service discovery 101

A key aspect of the service-oriented architecture approach for middleware is that services advertise themselves using directory or lookup services so that prospective clients can find them. The service location and discovery abstractions required to support this are not much different from those we use to conduct business with other people. As a result, we can gain insights into how distributed service discovery systems work by comparing them to everyday human-oriented service discovery approaches. Given that service discovery depends on discovery services, how does an application actually find a discovery service?
Regulation of Two Renal Chloride Transporters, AE1 and Pendrin, by Electrolytes and Aldosterone

The renal handling of salt and protons and bicarbonate are intricately linked through shared transport mechanisms for sodium, chloride, protons, and bicarbonate. In the collecting duct, the regulated fine-tuning of salt and acid-base homeostasis is achieved by a series of transport proteins located in different cell types, intercalated and principal cells. Intercalated cells are considered to be of less importance for salt handling but recent evidence has suggested that the anion exchanger pendrin may participate in salt reabsorption and blood pressure regulation. Here, we examined the regulated expression of two functionally related but differentially expressed anion exchangers, AE1 and pendrin, by dietary electrolyte intake and aldosterone. Cortical expression of pendrin was regulated on mRNA and protein level. The combination of NaHCO3 and DOCA enhanced pendrin mRNA and protein levels, whereas DOCA or NaHCO3 alone had no effect. NaCl or KHCO3 increased pendrin mRNA, KCl decreased its mRNA abundance. On protein level, NH4Cl, NaCl, and KCl reduced pendrin expression, the other treatments were without effect. In contrast, AE1 mRNA or protein expression in kidney cortex was regulated by none of these treatments. In kidney medulla, NaHCO3/DOCA or NaHCO3 alone enhanced AE1 mRNA levels. AE1 protein abundance was increased by NH4Cl, NaHCO3/DOCA, and NaCl. Immunolocalization showed that during NH4Cl treatment the relative number of AE1 positive cells was increased and pendrin expressing cells reduced. Thus, pendrin and AE1 are differentially regulated with distinct mechanisms that separately affect mRNA and protein levels. Pendrin is regulated by acidosis and chloride intake, whereas AE1 is enhanced by acidosis, NaCl, and the combination of DOCA and NaHCO3.
Multi-lingual deep neural networks for language recognition

Multi-lingual feature extraction using bottleneck layers in deep neural networks (BN-DNNs) has been proven to be an effective technique for low resource speech recognition and more recently for language recognition. In this work we investigate the impact on language recognition performance of the multi-lingual BN-DNN architecture and training configurations for the NIST 2011 and 2015 language recognition evaluations (LRE11 and LRE15). The best performing multi-lingual BN-DNN configuration yields relative performance gains of 50% on LRE11 and 40% on LRE15 compared to a standard MFCC/SDC baseline system and 17% on LRE11 and 7% on LRE15 relative to a single language BN-DNN system. Detailed performance analysis using data from all 24 Babel languages, Fisher Spanish and Switchboard English shows the impact of language selection and the amount of training data on overall BN-DNN performance.
Creativity and Values

ABSTRACT Barron (1997) and Helson (1990) independently have suggested that a central element in all forms of creativity is the desire or goal to be creative, implying creativity as a core value. Based on these assertions and Schwartz's (1992) theory, we tested the prediction that creative individuals will hold a different values system than their less creative counterparts. University students (N = 278) completed the Schwartz Values Survey (Schwartz, 1992), as well as a behaviorally-based self-report measure of creative accomplishments. At separate occasions, 134 of these participants also devised three creative products rated by the consensual assessment method. In keeping with prediction, creative accomplishments and products correlated significantly not only with the self-direction value composite (both including and excluding the individual item creativity), but also universalism and stimulation. Accomplishments and products correlated negatively with the value composites of tradition, security, and power. These results support the view that creativity is grounded in values, and support Schwartz's model of the dynamic structure of values as a predictor of behavior.
Comparison of WTC Dust Size on Macrophage Inflammatory Cytokine Release In vivo and In vitro

Background The WTC collapse exposed over 300,000 people to high concentrations of WTC-PM; particulates up to ∼50 mm were recovered from rescue workers’ lungs. Elevated MDC and GM-CSF independently predicted subsequent lung injury in WTC-PM-exposed workers. Our hypotheses are that components of WTC dust strongly induce GM-CSF and MDC in AM; and that these two risk factors are in separate inflammatory pathways. Methodology/Principal Findings Normal adherent AM from 15 subjects without WTC-exposure were incubated in media alone, LPS 40 ng/mL, or suspensions of WTC-PM10–53 or WTC-PM2.5 at concentrations of 10, 50 or 100 µg/mL for 24 hours; supernatants assayed for 39 chemokines/cytokines. In addition, sera from WTC-exposed subjects who developed lung injury were assayed for the same cytokines. In the in vitro studies, cytokines formed two clusters with GM-CSF and MDC as a result of PM10–53 and PM2.5. GM-CSF clustered with IL-6 and IL-12(p70) at baseline, after exposure to WTC-PM10–53 and in sera of WTC dust-exposed subjects (n = 70) with WTC lung injury. Similarly, MDC clustered with GRO and MCP-1. WTC-PM10–53 consistently induced more cytokine release than WTC-PM2.5 at 100 µg/mL. Individual baseline expression correlated with WTC-PM-induced GM-CSF and MDC. Conclusions WTC-PM10–53 induced a stronger inflammatory response by human AM than WTC-PM2.5. This large particle exposure may have contributed to the high incidence of lung injury in those exposed to particles at the WTC site. GM-CSF and MDC consistently cluster separately, suggesting a role for differential cytokine release in WTC-PM injury. Subject-specific response to WTC-PM may underlie individual susceptibility to lung injury after irritant dust exposure.
Competing philosophies in the classroom: a challenge to Hong Kong teachers

The present paper examines the experiences of teachers in teaching children with special needs in mainstream schools and how they see and evaluate the feasibility of the new integration initiatives in Hong Kong. The data are based on individual and focus group interviews with general class teachers, resource class teachers and principals of mainstream schools admitting students with special needs. Teachers reported difficulties and problems in maintaining classroom discipline and ambivalence in meeting the competing demands between students with and without special needs. The structural constraints of implementing a rigidly defined curriculum and being accountable for good academic results regardless of student competence pose formidable obstacles in achieving the goals of integrated education. There is a conflict at the systemic level between the philosophy of academic excellence defined by grades on the one hand and the philosophy of equality and inclusion on the other. Improving parent participation, having an ample supply of funds, the provision of necessary equipment and facilities, the availability of pre‐ and in‐service training to teachers, and additional manpower in counselling are the most urgently needed resources in facilitating teachers to engage in teaching students with special needs alongside others.
High-level speech event analysis for cognitive load classification

The Cognitive Load (CL) refers to the load imposed on an individual’s cognitive system when performing a given task, and is usually associated with the limitations of the human working memory. Stress, fatigue, lower ability to make decisions and perceptual narrowing are induced by cognitive overload which occurs when too much information has to be processed. As many physiological measures and for a nonintrusive measurement, speech features have been investigated in order to find reliable indicators of CL levels. In this paper, we have investigated high-level speech events automatically detected using the CMU-Sphinx toolkit for speech recognition. Temporal events (speech onset latency, event starting timecodes, pause and phone segments) were extracted from the speech transcriptions (phoneme, word, silent pause, filled pause, breathing). Seven audio feature sets related to the speech events were designed and assessed. Three-class SVM classifiers (Low, Medium and High level) were developed and assessed on the CSLE (Cognitive-Load with Speech and EGG) databases provided for the Interspeech'2014 Cognitive Load Sub-Challenge. These experiments have shown an improvement of 1.5 % on the Test set compared to the official baseline Unweighted Average Recall (UAR).
Efficient Text Summarization Costs and Benefits

AbstractTwenty-four undergraduate students were asked to read a 167-word expository text about Dutch elm disease and to write a summary of the text. Five days later, they were asked to complete a sentence-recognition task and to verbalize components of a successful text summary. Efficiency of summarization (a proportion of number of judged-important ideas to total number of words) was assessed, and high-efficient and low-efficient summarizers were compared on recognition and verbalization performance. An important finding of the study was that high-efficient students "recognized" true-to-text synthesis statements, which did not appear in the original text, far more frequently than low-efficient students, but also failed to strongly reject statements inconsistent with low-importance, in-text information. It appeared, within the study, that these students not only summarized efficiently, but also stored information in memory efficiently (i.e., in a highly streamlined, condensed manner).
Robust optimization of an airplane component taking into account the uncertainty of the design parameters

A slat track, structural component of an aircraft wing that transfers the aerodynamical loads, excited by operational forces can result in excessive displacement levels if not properly designed. The design parameter values are not always precisely known but can contain a level of uncertainty to some extent due to, for example dimensional variation. During the different optimization approaches, the slat track geometry is optimized in order to limit the maximum vertical displacement, taking into account the variability of the design parameters. Application and comparison of different optimal, robust and generalized optimization approaches is presented and applied on the slat track finite element model, making use of mean and variance response functions to model the uncertainty on the finite element displacement values. Next to validating different objective function statements, a comparison is also made on the level of accuracy and practicability concerning the different response function models, based on regression techniques and Monte Carlo simulations, optimization and transmissibilities and regressive techniques and vibration reduction over a frequency range. Copyright © 2008 John Wiley & Sons, Ltd.