Miracle-dz/UniFAR-FTUs huggingface dataset:
Business simulation as an active learning activity for developing soft skills

ABSTRACT Business simulations are innovative instruction models for active or cooperative learning. In this paper, we look at the social constructionist roots of these education models in light of the current efforts to enhance employability skills in undergraduate and graduate studies. More specifically, we analyse the role of business simulations in developing soft skills based on an international survey of students’ perceptions of developing soft skills during business simulations. Our objective is to test whether business simulations contribute to the development of soft skills and whether gender, ethno-cultural origin, and professional experience affect the acquisition process. We also discuss the use and benefits of these innovative instruction models. The analysis suggests the need to take into account specific factors, especially ethno-cultural origin, when instructing via business simulations. It also calls for sharing best practices in the context of a globalised education.
On the use of topological features and hierarchical characterization for disambiguating names in collaborative networks

Many features of complex systems can now be unveiled by applying statistical physics methods to treat them as social networks. The power of the analysis may be limited, however, by the presence of ambiguity in names, e.g., caused by homonymy in collaborative networks. In this paper we show that the ability to distinguish between homonymous authors is enhanced when longer-distance connections are considered, rather than looking at only the immediate neighbors of a node in the collaborative network. Optimized results were obtained upon using the 3rd hierarchy in connections. Furthermore, reasonable distinction among authors could also be achieved upon using pattern recognition strategies for the data generated from the topology of the collaborative network. These results were obtained with a network from papers in the arXiv repository, into which homonymy was deliberately introduced to test the methods with a controlled, reliable dataset. In all cases, several methods of supervised and unsupervised machine learning were used, leading to the same overall results. The suitability of using deeper hierarchies and network topology was confirmed with a real database of movie actors, with the additional finding that the distinguishing ability can be further enhanced by combining topology features and long-range connections in the collaborative network.
No Compelling Evidence that Preferences for Facial Masculinity Track Changes in Women’s Hormonal Status

Although widely cited as strong evidence that sexual selection has shaped human facial-attractiveness judgments, findings suggesting that women’s preferences for masculine characteristics in men’s faces are related to women’s hormonal status are equivocal and controversial. Consequently, we conducted the largest-ever longitudinal study of the hormonal correlates of women’s preferences for facial masculinity (N = 584). Analyses showed no compelling evidence that preferences for facial masculinity were related to changes in women’s salivary steroid hormone levels. Furthermore, both within-subjects and between-subjects comparisons showed no evidence that oral contraceptive use decreased masculinity preferences. However, women generally preferred masculinized over feminized versions of men’s faces, particularly when assessing men’s attractiveness for short-term, rather than long-term, relationships. Our results do not support the hypothesized link between women’s preferences for facial masculinity and their hormonal status.
A SURVEY ON VARIOUS APPROACHES OF TEXT EXTRACTION IN IMAGES

Text Extraction plays a major role in finding vital and valuable information. Text extraction involves detection, localization, tracking, binarization, extraction, enhancement and recognition of the text from the given image. These text characters are difficult to be detected and recognized due to their deviation of size, font, style, orientation, alignment, contrast, complex colored, textured background. Due to rapid growth of available multimedia documents and growing requirement for information, identification, indexing and retrieval, many researches have been done on text extraction in images.Several techniques have been developed for extracting the text from an image. The proposed methods were based on morphological operators, wavelet transform, artificial neural network,skeletonization operation,edge detection algorithm, histogram technique etc. All these techniques have their benefits and restrictions. This article discusses various schemes proposed earlier for extracting the text from an image. This paper also provides the performance comparison of several existing methods proposed by researchers in extracting the text from an image.
Excitation source design for high-quality speech manipulation systems based on a temporally static group delay representation of periodic signals

A new group delay representation, which yields value zero for periodic signals irrespective to the initial phase and the relative level of each harmonic component. This new group delay representation provides a unified basis for defining "aperiodicity" in speech sounds. For example, the periodic to noise ratio or harmonic to noise ratio is directly derived from the deviation of this group delay representation from value zero, after removing FM effects of harmonic frequencies and removing AM effects of harmonic component level. The derived deviation is combined with estimated excitation duration information and used to design aperiodic components of excitation source for high-quality synthetic speech. The proposed group delay representation is based on FO-adaptive weighted average of frequency shifted versions and temporally shifted versions of group delays with power spectral weighting.
Test-Driving Static Analysis Tools in Search of C Code Vulnerabilities

Recently, a number of tools for automated code scanning came in the limelight. Due to the significant costs associated with incorporating such a tool in the software lifecycle, it is important to know what defects are detected and how accurate and efficient the analysis is. We focus specifically on popular static analysis tools for C code defects. Existing benchmarks include the actual defects in open source programs, but they lack systematic coverage of possible code defects and the coding complexities in which they arise. We introduce a test suite implementing the discussed requirements for frequent defects selected from public catalogues. Four open source and two commercial tools are compared in terms of their effectiveness and efficiency of their detection capability. A wide range of C constructs is taken into account and appropriate metrics are computed, which show how the tools balance inherent analysis tradeoffs and efficiency. The results are useful for identifying the appropriate tool, in terms of cost-effectiveness, while the proposed methodology and test suite may be reused.
Dinucleotide Analogues as Novel Inhibitors of RNA-Dependent RNA Polymerase of Hepatitis C Virus

ABSTRACT Replication of hepatitis C virus (HCV) RNA is catalyzed by the virally encoded RNA-dependent RNA polymerase NS5B. It is believed that the viral polymerase utilizes a de novo or primer-independent mechanism for initiation of RNA synthesis. Our previous work has shown that dinucleotides were efficient initiation molecules for NS5B in vitro (W. Zhong, E. Ferrari, C. A. Lesburg, D. Maag, S. K. Ghosh, C. E. Cameron, J. Y. Lau, and Z. Hong, J. Virol. 74:9134-9143, 2000). In this study, we further demonstrated that dinucleotide analogues could serve as inhibitors of de novo initiation of RNA synthesis directed by HCV NS5B. Both mononucleotide- and dinucleotide-initiated RNA syntheses were affected by dinucleotide analogues. The presence of the 5′-phosphate group in the dinucleotide compounds was required for efficient inhibition of de novo initiation. Optimal inhibitory activity also appeared to be dependent on the base-pairing potential between the compounds and the template terminal bases. Because the initiation process is a rate-limiting step in viral RNA replication, inhibitors that interfere with the initiation process will have advantages in suppressing virus replication. The use of dinucleotide analogues as inhibitor molecules to target viral replication initiation represents a novel approach to antiviral interference.
University Student Desertion Analysis using Agent-Based Modeling Approach

Student dropout at universities is a worldwide phenomenon that exceeds a 40% rate of the students admitted to first semester. In Colombia, it exceeds 45%, an alerting rate that makes studies on the subject very important for Governments and universities considering that it has a huge social impact and affects the resources of the education area. Traditionally, studies are performed by statistical and mathematical methods and the Ministry of National Education acknowledges that they have been insufficient since they fail to explain the dropout behavior. Agent-based modeling and simulation (ABMS) has been considered a new way of doing science when managing social problems that are complex systems forcing an evolution simulation as a useful approach to develop this phenomenon.
Positive selection in AvrP4 avirulence gene homologues across the genus Melampsora

Pathogen genes involved in interactions with their plant hosts are expected to evolve under positive Darwinian selection or balancing selection. In this study a single copy avirulence gene, AvrP4, in the plant pathogen Melampsora lini, was used to investigate the evolution of such a gene across species. Partial translation elongation factor 1-alpha sequences were obtained to establish phylogenetic relationships among the Melampsora species. We amplified AvrP4 homologues from species pathogenic on hosts from different plant families and orders, across the inferred phylogeny. Translations of the AvrP4 sequences revealed a predicted signal peptide and towards the C-terminus of the protein, six identically spaced cysteines were identified in all sequences. Maximum likelihood analysis of synonymous versus non-synonymous substitution rates indicated that positive selection played a role in the evolution of the gene during the diversification of the genus. Fourteen codons under significant positive selection reside in the C-terminal 28 amino acid region, suggesting that this region interacts with host molecules in most sequenced accessions. Selection pressures on the gene may be either due to the pathogenicity or avirulence function of the gene or both.
THE CONCEPTS OF MEMBRANE FLOW AND MEMBRANE VESICULATION AS MECHANISMS FOR ACTIVE TRANSPORT AND ION PUMPING

Dr. Palade has shown that in many cells the cell membrane is infolded extensively and that such folds may carry the cell membrane to positions deep in the cell. Moreover, he has shown that such deep folds often appear to lie close to isolated vesicles in the cytoplasm. Dr. Palade has pointed out that such vesicles are often arranged so as to suggest that they might have formed from the pinching off of a recessed tip of such a fold, or that they might represent vesicles destined to coalesce with such a recessed fold. Dr. Palade referred to the classical paper on pinocytosis by Lewis (8). Lewis showed cells in which the cell surface and adjacent cytoplasm were in a state of vigorous activity, with an orderly flow of granules and vesicles from one portion of a cell to another. Similar activity and orderly movements within cells have been demonstrated by Gey, Shapras, and Borysko (6), by Frederic and Ch~vremont (5), and by Blandau, De Marsh, and Ralph (1). Dr. Palade's pictures suggest that in such cells as macrophages, in which pinocytosis and orderly flow of cytoplasmic particles are evident, the cytoplasmic membranes of the endoplasmic reticulum, particularly those components representing membranes folded inwards from the outer cell border, might participate in or even mediate these activities. I would like to introduce the hypothesis that membrane flow may be an important part of a type of active transport mechanism carrying particles, including ions, along, within, into, and out of cells. If membrane is being formed or synthesized in one region, and is being broken down or enzymatically destroyed at another, it would be expected to flow from the membrane source to the membrane sink or site of breakdown. If the source is at the exposed cell surface, as at A and A' in Fig. 1, and the sink is deep in the cell as at B (Fig. 1), the membrane would flow from the surface to a position deep in the recess as indicated by the arrows. A membrane flow in the reverse direction would result from a source at the tip of the recess at B and a sink on the surface at A or A'. Membranes entirely within the cell or entirely on the exposed cell surface or extending through the cell as tunnels or slits could be envisioned as similarly motivated to flow from sources to appropriately placed sinks. The energy required for such kinesis would be provided by oxidative mechanisms in the cell. 99
An Efficient face detection based on improved Viola &

Human face detection plays an important role in many applications such as computer-human interaction, face recognition and video surveillance and so on. In human face detection application a false detection rate and slow detection speed remain major problems. In this paper, we present a method to avoid these problems, by combining a Fast Saliency-based visual attention (FSBVA), skin color filtering (SCF), and Viola and Jones Face detector (VJFD) : After determining all possible face candidate regions using FSBVA with SC, the VJFD is applied to detect Human face and then a discrimination based SCF is used to reject false positive. Our method takes advantage from the visual attention mechanism to rapidly find the attractive face regions and to overcome the problems of false negatives when both VJFD and SC are applied directly in video frames with complex backgrounds. Experimental results show the effectiveness of the proposed
Using endophenotypes for pathway clusters to map complex disease genes

Nature determines the complexity of disease etiology and the likelihood of revealing disease genes. While culprit genes for many monogenic diseases have been successfully unraveled, efforts to map major complex disease genes have not been as productive as hoped. The conceptual framework currently adopted to deal with the heterogeneous nature of complex diseases focuses on using homogeneous internal features of the disease phenotype for mapping. However, phenotypic homogeneity does not equal genotypic homogeneity. In this report, we advocate working with well‐measured phenotypes portrayed by amounts of transcripts and activities of gene products or their metabolites, which are pertinent to relatively small pathway clusters. Reliable and controlled measures for oligogenic traits resulting from proper dissection efforts may enhance statistical power. The large amounts of information obtained on gene and protein expression from technological advances can add to the power of gene finding, particularly for diseases with unclear etiology. Data‐mining tools for dimension reduction can assist biologists to reveal novel molecular endophenotypes. However, there are still hurdles to overcome, including high cost, relatively poor reproducibility and comparability among platforms, the cross‐sectional nature of the information, and the accessibility of human tissues. Concerted efforts are required to carry out large‐scale prospective studies that are integrated at the levels of phenotype characterization, high throughput experimental techniques, data analyses, and beyond. Genet. Epidemiol. 30:143–154, 2006. © 2006 Wiley‐Liss, Inc.
Stopover behaviour in migratory songbirds: timing, orientation and departures

Songbird migrants use stopovers between flight bouts to rest and refuel for the upcoming flights. Behaviours affecting where, when and how long to stay at stopover sites will affect how successful the overall migration will be, which has significant consequences for the overall fitness and mortality of the birds. The main purpose of this work was to investigate stopover behaviours in free-flying migrants to understand the effects of intrinsic (age and body condition) and environmental (weather) factors on the behaviours that guide birds as they depart from migratory stopovers. I studied some of our most common migratory songbirds using an automated radiotelemetry system at the Falsterbo peninsula, Sweden. Our results show that stopover duration is affected by fuel load and weather conditions, and that they differ between the migratory seasons. Furthermore, timing of departures on nocturnal flights appears primarily determined by ecological factors, and are to a large degree affected by the lengths of the nights. Birds with larger fuel stores departed before lean individuals, indicating that they prepared for a longer flight. We found that reverse movements during migration are slower, take place at lower latitudes and later in the night than movements in the expected migratory direction, and are most common in juvenile or lean individuals. Route choice across the Baltic Sea after departure from Falsterbo is largely affected by wind directions. In cue conflict experiments between magnetic compass and celestial cues at sunset we found no recalibration of the magnetic compass. We suggest that access to stars during calibration is necessary for all compasses to be calibrated when the birds depart for a night’s flight. Comparisons between departure directions and directions of birds in climbing and level flight revealed that birds adjust their directions after take-off, once at cruising altitudes. Winds were the primary factor affecting flight duration for the first 50 km of flight after departure. Interestingly, cloud coverage affected flight duration negatively, while fuel load affected it positively. Collectively, this work shows how intrinsic and environmental factors modulate stopover behaviours in migratory songbirds, with essential implications on the birds’ migratory schedules.
Integrative random forest for gene regulatory network inference

Motivation: Gene regulatory network (GRN) inference based on genomic data is one of the most actively pursued computational biological problems. Because different types of biological data usually provide complementary information regarding the underlying GRN, a model that integrates big data of diverse types is expected to increase both the power and accuracy of GRN inference. Towards this goal, we propose a novel algorithm named iRafNet: integrative random forest for gene regulatory network inference. Results: iRafNet is a flexible, unified integrative framework that allows information from heterogeneous data, such as protein–protein interactions, transcription factor (TF)-DNA-binding, gene knock-down, to be jointly considered for GRN inference. Using test data from the DREAM4 and DREAM5 challenges, we demonstrate that iRafNet outperforms the original random forest based network inference algorithm (GENIE3), and is highly comparable to the community learning approach. We apply iRafNet to construct GRN in Saccharomyces cerevisiae and demonstrate that it improves the performance in predicting TF-target gene regulations and provides additional functional insights to the predicted gene regulations. Availability and implementation: The R code of iRafNet implementation and a tutorial are available at: http://research.mssm.edu/tulab/software/irafnet.html Contact: zhidong.tu@mssm.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Development of Career Plateau Questionnaire and Research on Its Validity and Reliability

Objective: To develop a questionnaire that can measure the concept of career plateau.Methods: 219 valid data from 4 enterprises were collected in order to develop career plateau questionnaire by exploratory factor analysis.288 samples from other 4 enterprises were collected in order to test the validity and reliability of the career plateau questionnaire.Results: ①Career plateau questionnaire was composed of hierarchal plateau、content plateau and inclusive plateau;②There was significant difference between logistics、 professionals and managers;③The Cronbach α of subtest of hierarchal plateau、 content plateau and inclusive plateau were 0.84、0.87、0.88,respectively.Conclusion: Career plateau questionnaire has good construct validity、empirical validity and internal consistency reliability.
Evaluating load balancing in peer-to-peer resource sharing algorithms for wireless mesh networks

Wireless mesh networks are a promising area for the deployment of new wireless communication and networking technologies. In this paper, we address the problem of enabling effective peer-to-peer resource sharing in this type of networks. In particular, we consider the well-known Chord protocol for resource sharing in wired networks and the recently proposed MeshChord specialization for wireless mesh networks, and compare their performance under various network settings for what concerns total generated traffic and load balancing. Both iterative and recursive key lookup implementation in Chord/MeshChord are considered in our extensive performance evaluation. The results confirm superiority of MeshChord with respect to Chord, and show that recursive key lookup is to be preferred when considering communication overhead, while similar degree of load unbalancing is observed. However, recursive lookup implementation reduces the efficacy of MeshChord cross-layer design with respect to the original Chord algorithm. MeshChord has also the advantage of reducing load unbalancing with respect to Chord, although a moderate degree of load unbalancing is still observed, leaving room for further improvement of the MeshChord design.
MINKOWSKI’S SUCCESSIVE MINIMA

In this note we give a brief survey on some classical and old problems involving Minkowski’s successive minima of a 0-symmetric convex body as well as on some recent developments concerning these functionals. Among others we show that the successive minima are closely related to intrinsic volumes, the lattice point enumerator, the zeros of the Ehrhart polynomial and to simultaneous Diophantine approximation problems.
Automated interictal spike detection and source localization in MEG using ICA and spatial-temporal clustering

MEG dipole localization of epileptic spikes is useful in epilepsy surgery for mapping the extent of abnormal cortex and to focus intracranial electrodes. Visually analyzing large amounts of data produces fatigue and error. Most existing methods are based on matching of interictal spike templates or predictive filtering of the data and do not explicitly include source localization as part of the analysis. We describe a fully automated method that combines time-series analysis with source localization to detect clusters of focal generators within the brain that produce interictal spike activity. We first use an ICA (Independent Component Analysis) method to decompose the multichannel MEG data and identify those components that exhibit spikelike characteristics. From these detected spikes we then find those whose spatial topographies across the array are consistent with focal neural sources and determine the foci of equivalent current dipoles and their associated time courses. Finally we perform a clustering of the sources based on distance metrics that takes into consideration both their locations and time courses. Tight clusters of equivalent current dipoles with a fit of greater than 95% are considered to be the reliably determined sources and are the final output of our detection scheme.