Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELATIONSHIP OF SKILL USE AND MOTIVATION OF SPORT COACHES IN HAMEDAN, IRAN

Over the past decade, the rapid pace of skill into education has changed the way teaching and learning is conducted in higher education. However, this promising approach seems to be neglected about Hamedan sport coaches. This study investigated sport coaches’ motivation and practices of skill. To this end, eighty-eight sport coaches from three universities in Iran participated in this study. The data collection instrument measured coaches’ motivations, teaching methods, and skill use. The findings of the study indicated that Hamedan sport coaches held positive motivation toward the use of skill, yet a limited use of skill. The participants further reported several barriers in integrating skill in Hamedan physical education classes. It was also found that skill use positively and significantly correlated to coaches’ motivation. Based on the current study physical educators may be willing to apply skill teaching if given opportunities to prepare, practice and utilize appropriate resources. Article visualizations:
Capacity optimizing power loading scheme for spatially constrained antenna arrays: Channels with narrow angular spread

This paper proposes a capacity optimizing power loading scheme for spatially constrained antenna arrays. The proposed power loading scheme is designed mainly for MIMO systems that are operating over channels with narrow angular spread values. The design problem is approached from a physical wave field perspective, in particular using a modal expansion for free space wave propagation. When a signal is transmitted from a spatially constrained antenna array, there will be an infinite number of modes excited at the transmit antenna region and only a finite number of those excited modes will have sufficient power to carry information to the other end of the channel. We show that in a non-isotropic scattering environment, correlation between adjacent modes is significantly higher than the correlation between well separated mode orders. Based on this finding, the power loading scheme is designed to eliminate the correlation between adjacent modes by allocating zero power to every second effective mode at the transmitter region. The capacity performance of the proposed scheme is evaluated for 1-D and 2-D antenna array geometries and results are compared with the traditional equal power loading scheme. We show that the proposed scheme gives more scope for capacity improvements for 1-D arrays at low angular spread values than for 2-D arrays.
A Proposal for Analysis and Prediction for Software Projects using Collaborative Filtering, In-Process Measurements and a Benchmarks Database

This paper proposes a new method for developing predictions and estimates for ongoing projects by comparing in-proc ess measurements of the current project with benchmark data from previous p rojects. The method uses collaborative filtering to identify groups of simil ar projects in the benchmark database and then to develop predictions and estima tes based on the in-process measurements of the current project and the compari son data from the similar projects. The authors base this proposal on experim ents with multidimensional in-process project measurement in a middle-scale multi-vendor development that lacked transparency in its processes. The auth ors' measurement trial verified the usefulness of the measurement methods, especially in project management, as reported in the paper.
Graph application on face for personal authentication and recognition

This paper presents a novel face recognition technique with graph topology drawn on scale invariant feature transform (SIFT) features and is compared with all the available well known techniques on SIFT features, and elastic bunch graph matching (EBGM) technique drawn on gabor wavelet feature. IITK face database is used for evaluation purpose. Test results show that the proposed graph matching technique will be an appropriate one for face recognition. Finally, the test results have been compared with the results found on BANCA face database following MC protocol only.
An Empirical Study of the Use of Relevance Information in Inductive Logic Programming

Inductive Logic Programming (ILP) systems construct models for data using domain-specific background information. When using these systems, it is typically assumed that sufficient human expertise is at hand to rule out irrelevant background information. Such irrelevant information can, and typically does, hinder an ILP system's search for good models. Here, we provide evidence that if expertise is available that can provide a partial-ordering on sets of background predicates in terms of relevance to the analysis task, then this can be used to good effect by an ILP system. In particular, using data from biochemical domains, we investigate an incremental strategy of including sets of predicates in decreasing order of relevance. Results obtained suggest that: (a) the incremental approach identifies, in substantially less time, a model that is comparable in predictive accuracy to that obtained with all background information in place; and (b) the incremental approach using the relevance ordering performs better than one that does not (that is, one that adds sets of predicates randomly). For a practitioner concerned with use of ILP, the implication of these findings are two-fold: (1) when not all background information can be used at once (either due to limitations of the ILP system, or the nature of the domain) expert assessment of the relevance of background predicates can assist substantially in the construction of good models; and (2) good "first-cut" results can be obtained quickly by a simple exclusion of information known to be less relevant.
Serially concatenated continuous phase modulation with symbol interleavers: performance, properties and design principles

Serially concatenated continuous phase modulation (SCCPM) systems with symbol interleavers are investigated. The transmitted signals are disturbed by additive white Gaussian noise (AWGN). Iterative detection with extrinsic information is used at the receiver side. Compared to bit interleaved SCCPM systems, this scheme shows a substantial improvement in convergence threshold at the price of a higher error floor. In addition to showing this property, we also investigate the underlying reason by error event analysis. In order to estimate bit error rate performance, we generalize traditional union bounds for a bit interleaver to the non-binary interleaver. For the latter, both the order and the position of permuted non-zero symbols have to he considered. From the analysis, some principal properties are presented. Finally some design principles are proposed. The paper concentrates on SCCPM, but the proposed analysis methods and conclusions can he widely used in many other systems such as serially concatenated trellis coded modulation, et cetera.
Multi-tenant Database Access Control

Storing data in the cloud is a new multi-tenant database solution that has recently emerged to deliver database for multiple users, who can store and access their data over the internet. This multi-tenant database designed to be used by multiple tenants and each tenant may have multiple users. Therefore, this database type demands a special multi-tenant access control model, which provides an access control not only for multiple tenants, but also for multiple users per tenant. In this paper, we are proposing a multi-tenant access control model based on a multi-tenant database schema called Elastic Extension Tables (EET). In this model, we define access control data architecture, and the EET access grants which can be granted to tenants' users. Moreover, we propose an access control algorithm, which allows users to access the data granted to them based on a number of groups or roles assigned to these users.
Why do male students underachieve in tertiary education? A St. Lucian case study

III ACKNOWLEDGEMENTS . IV CHAPTER ONE: INTRODUCTION . 4 1.1. The Context of Education in St. Lucia . 7 1.2. Statement of the problem . 13 1.3. Purpose of the Research . 14 1.4. Research Questions . 15 1.5. Overview of Research Design and Methodology . 15 1.6. Significance of the research . 17 1.7. Motivation and interest in the research . 18 1.8. Definition of Key Terms . 20 1.9. Overview of the Research . 22 CHAPTER TWO LITERATURE REVIEW . 24 2.
Model-based Situational Security Analysis

Security analysis is growing in complexity with the increase in functionality, connectivity, and dynamics of current electronic business processes. To tackle this complexity, the application of models in pre-operational phases is becoming standard practice. Runtime models are also increasingly applied to analyze and validate the actual security status of business process instances. In this paper we present an approach to support not only model-based evaluation of the current security status of business process instances, but also to allow for decision support by analyzing close-future process states. Our approach is based on operational formal models derived from development-time process and security models. This paper exempliﬁes our approach utilizing real world processes from the logistics domain and demonstrates the systematic development and application of runtime models for situational security analysis.
The Association Between Personality Traits and Sport-Related Concussion History in Collegiate Student-Athletes

Cross-sectional survey data were used to test whether personality traits were associated with a self-reported history of diagnosed sport-related concussions (SRC) and undiagnosed SRCs. A total of 1,398 of 2,055 (68%) collegiate student-athletes from four National Collegiate Athletic Association (NCAA) institutions voluntarily completed a one-time survey during their preparticipation physical examinations or a team meeting. Previously diagnosed SRCs and undiagnosed SRCs were measured with self-reports. The personality traits of neuroticism, extraversion, openness, agreeableness, and conscientiousness were captured via the 44-item Big Five Inventory. After exclusions, responses from 1,246 collegiate student-athletes (n = 702 males; n = 544 females; n = 727 SRC high-risk sport participants; and n = 518 SRC low-risk sport participants) were included for the final analyses. SRC history responses were grouped into 0, 1, and 2+ for diagnosed and undiagnosed. Nominal logistic regression models that included personality traits, demographics, and sport information were used for the primary analyses. No personality traits were found to be significantly related to 0, 1, or 2+ diagnosed SRCs. Agreeableness (p ⩽ .01) was the only personality trait that was significantly associated with self-reporting 2+ undiagnosed SRCs compared with 0. One possible explanation is that broad personality traits may not be important risk factors for SRCs. Future studies should investigate specific individual differences that could be related to SRCs, such as risk-taking propensities and thrill-seeking tendencies. Likewise, future studies should use prospective designs to provide some constraints on inferences about the direction of the associations.
The Monte Carlo Method

The “Monte Carlo Method,” also known as the “Method of Statistical Trials,” is a statistical method for solving deterministic or probabilistic problems across the scientific and engineering disciplines. It is generally applied in two steps. First, the solution of a problem is represented as a parameter of a hypothetical population. Second, a random sequence of numbers is used to construct a sample of the population, from which statistical estimates of the needed parameters can be obtained. It can be considered as a method of solving various problems in computational mathematics by constructing for each problem a random process with parameters equal to the required quantities of the initial problem. The unknowns are determined by carrying out observations on the constructed random process, and by computing its statistical characteristics, which would be equal to the required parameters of the initial process. More simply stated, it is a numerical method for solving mathematical problems by means of random sampling. In even simpler terms, it is a physics experiment carried out numerically on a computing platform, rather than in the laboratory or the real world. Several excellent publications have been published about the method. These include a monograph by Hammersley and Handscomb, a report by Kahn, a review by Halton, and the books by Shreider, Sobol, Spanier and Gelbard, and by Carter and Cashwell.
The glial glutamate transporter, GLT‐1, is oxidatively modified by 4‐hydroxy‐2‐nonenal in the Alzheimer's disease brain: the role of Aβ1–42

Glutamate transporters are involved in the maintenance of synaptic glutamate concentrations. Because of its potential neurotoxicity, clearance of glutamate from the synaptic cleft may be critical for neuronal survival. Inhibition of glutamate uptake from the synapse has been implicated in several neurodegenerative disorders. In particular, glutamate uptake is inhibited in Alzheimer's disease (AD); however, the mechanism of decreased transporter activity is unknown. Oxidative damage in brain is implicated in models of neurodegeneration, as well as in AD. Glutamate transporters are inhibited by oxidative damage from reactive oxygen species and lipid peroxidation products such as 4‐hydroxy‐2‐nonenal (HNE). Therefore, we have investigated a possible connection between the oxidative damage and the decreased glutamate uptake known to occur in AD brain. Western blots of immunoprecipitated HNE‐immunoreactive proteins from the inferior parietal lobule of AD and control brains suggest that HNE is conjugated to GLT‐1 to a greater extent in the AD brain. A similar analysis of beta amyloid (Aβ)‐treated synaptosomes shows for the first time that Aβ1–42 also increases HNE conjugation to the glutamate transporter. Together, our data provide a possible link between the oxidative damage and neurodegeneration in AD, and supports the role of excitotoxicity in the pathogenesis of this disorder. Furthermore, our data suggests that Aβ may be a possible causative agent in this cascade.
Implementing rapid testing for tuberculosis in Mozambique

Abstract Problem In Mozambique, pulmonary tuberculosis is primarily diagnosed with sputum smear microscopy. However this method has low sensitivity, especially in people infected with human immunodeficiency virus (HIV). Patients are seldom tested for drug-resistant tuberculosis. Approach The national tuberculosis programme and Health Alliance International introduced rapid testing of smear-negative sputum samples. Samples were tested using a polymerase-chain-reaction-based assay that detects Mycobacterium tuberculosis deoxyribonucleic acid and a mutation indicating rifampicin resistance; Xpert® MTB/RIF (Xpert®). Four machines were deployed in four public hospitals along with a sputum transportation system to transfer samples from selected health centres. Laboratory technicians were trained to operate the machines and clinicians taught to interpret the results. Local setting In 2012, Mozambique had an estimated 140 000 new tuberculosis cases, only 34% of which were diagnosed and treated. Of tuberculosis patients, 58% are HIV-infected. Relevant changes From 2012–2013, 1558 people were newly diagnosed with tuberculosis using sputum smears at intervention sites. Xpert® detected M. tuberculosis in an additional 1081 sputum smear-negative individuals, an increase of 69%. Rifampicin resistance was detected in 58/1081 (5%) of the samples. However, treatment was started in only 82% of patients diagnosed by microscopy and 67% of patients diagnosed with the rapid test. Twelve of 16 Xpert® modules failed calibration within 15 months of implementation. Lessons learnt Using rapid tests to diagnose tuberculosis is promising but logistically challenging. More affordable and durable platforms are needed. All patients diagnosed with tuberculosis need to start and complete treatment, including those who have drug resistant strains.
Exploiting visual appearance to cluster and detect rogue software

Rogue software, such as Fake A/V and ransomware, trick users into paying without giving return. We show that using a perceptual hash function and hierarchical clustering, more than 213,671 screenshots of executed malware samples can be grouped into subsets of structurally similar images, reflecting image clusters of one malware family or campaign. Based on the clustering results, we show that ransomware campaigns favor prepay payment methods such as ukash, paysafecard and moneypak, while Fake A/V campaigns use credit cards for payment. Furthermore, especially given the low A/V detection rates of current rogue software -- sometimes even as low as 11% -- our screenshot analysis approach could serve as a complementary last line of defense.
Displacements of Prohead Protease Genes in the Late Operons of Double-Stranded-DNA Bacteriophages

ABSTRACT Most of the known prohead maturation proteases in double-stranded-DNA bacteriophages are shown, by computational methods, to fall into two evolutionarily independent clans of serine proteases, herpesvirus assemblin-like and ClpP-like. Phylogenetic analysis suggests that these two types of phage prohead protease genes displaced each other multiple times while preserving their exact location within the late operons of the phage genomes.
Evacuating Robots from a Disk Using Face-to-Face Communication (Extended Abstract)

Assume that two robots are located at the centre of a unit disk. Their goal is to evacuate from the disk through an exit at an unknown location on the boundary of the disk. At any time the robots can move anywhere they choose on the disk, independently of each other, with maximum speed $$1$$. The robots can cooperate by exchanging information whenever they meet. We study algorithms for the two robots to minimize the evacuation time: the time when both robots reach the exit. In [9] the authors gave an algorithm defining trajectories for the two robots yielding evacuation time at most $$5.740$$ and also proved that any algorithm has evacuation time at least $$3+ \frac{\pi }{4} + \sqrt{2} \approx 5.199$$. We improve both the upper and lower bounds on the evacuation time of a unit disk. Namely, we present a new non-trivial algorithm whose evacuation time is at most $$5.628$$ and show that any algorithm has evacuation time at least $$3+ \frac{\pi }{6} + \sqrt{3} \approx 5.255$$. To achieve the upper bound, we designed an algorithm which non-intuitively proposes a forced meeting between the two robots, even if the exit has not been found by either of them.
Mechanisms of Candida albicans Trafficking to the Brain

During hematogenously disseminated disease, Candida albicans infects most organs, including the brain. We discovered that a C. albicans vps51Δ/Δ mutant had significantly increased tropism for the brain in the mouse model of disseminated disease. To investigate the mechanisms of this enhanced trafficking to the brain, we studied the interactions of wild-type C. albicans and the vps51Δ/Δ mutant with brain microvascular endothelial cells in vitro. These studies revealed that C. albicans invasion of brain endothelial cells is mediated by the fungal invasins, Als3 and Ssa1. Als3 binds to the gp96 heat shock protein, which is expressed on the surface of brain endothelial cells, but not human umbilical vein endothelial cells, whereas Ssa1 binds to a brain endothelial cell receptor other than gp96. The vps51Δ/Δ mutant has increased surface expression of Als3, which is a major cause of the increased capacity of this mutant to both invade brain endothelial cells in vitro and traffic to the brain in mice. Therefore, during disseminated disease, C. albicans traffics to and infects the brain by binding to gp96, a unique receptor that is expressed specifically on the surface of brain endothelial cells.
Ranking annotators for crowdsourced labeling tasks

With the advent of crowdsourcing services it has become quite cheap and reasonably effective to get a dataset labeled by multiple annotators in a short amount of time. Various methods have been proposed to estimate the consensus labels by correcting for the bias of annotators with different kinds of expertise. Often we have low quality annotators or spammers–annotators who assign labels randomly (e.g., without actually looking at the instance). Spammers can make the cost of acquiring labels very expensive and can potentially degrade the quality of the consensus labels. In this paper we formalize the notion of a spammer and define a score which can be used to rank the annotators—with the spammers having a score close to zero and the good annotators having a high score close to one.
The development of narrative ability in English-Chinese bilingual primary school students in Singapore

This study reports the comparative narrative ability of bilingual English- and Chinese-speaking primary school students in Singapore from a developmental perspective, an area attracting little research in the past. A total of 36 primary one, three and five students from mainstream schools narrated in Mandarin and in English whilst being shown accompanying pictures. The students’ narrative ability was then measured in terms of their grasp of narrative structure, temporality and the evaluative expressions. Analyses showed that the students’ English stories were more advanced than were their Chinese stories. Although similar developmental patterns were found in the children’s English and Chinese, there were many more connectives and evaluative expressions in their English than in their Chinese stories. The evidence suggests that the English and Chinese competence of the bilingual learners in Singapore schools do not develop in close parallel. The implications for bilingual teaching in Singapore schools are discussed, especially the finding that the children’s English ability was better than their Chinese language ability.
The Use of Illegal Drugs and Infectious Contagious Diseases: Knowledge and Intervention among Dockworkers

This study’s objective was to analyze the use of illegal drugs by dockworkers and provide risk communication regarding the use of illegal drugs and test for infectious contagious diseases among dockworkers. This cross-sectional study including an intervention addressed to 232 dockworkers, who were individually interviewed, as well as communication of risk with testing for infectious contagious diseases for 93 dockworkers from a city in the interior of Rio Grande do Sul, Brazil. Poisson regression analysis was used. Twenty-nine workers reported the use of illegal drugs. Poisson regression indicated that being a wharfage worker, smoker, having a high income, and heavier workload increases the prevalence of the use of illegal drugs. During risk communication, two workers were diagnosed with hepatitis B (2.2%), three (3.2%) with hepatitis C, two (2.2%) with syphilis. None of the workers, though, had HIV. This study provides evidence that can motivate further research on the topic and also lead to treatment of individuals to improve work safety, productivity, and the health of workers.