Futsal and the Social Culture: Integration of Practice of Futsal in the Programming of Physical Education and Sports in Tunisia

Abstract Physical education and sport are an integral part of education. Its major components in the education system are clearly defined. Objectives express an identity of integral education of the child. However, certain principles in the development of physical and sports education objectives allow the definition of the capabilities in the school environment and the effectiveness of teaching. In our research we have noticed that the number of participants in the course of physical education and sports decreases in remarkable ways. Indeed both researches have explained this phenomenon to psychological such as adolescence and physiological as obesity factors. While this phenomenon can be explained following the analysis of the direct interaction teaching and content of education. The objective of this study is to know the impact of the integration of new sport which is our investigation such as Futsal on the motivation of participants and the resolution of this problem

FEA-Assisted steady-state modelling of a spoke type IPM machine with enhanced flux weakening capability

Interior permanent magnet (IPM) machines with spoke-type design are possible candidates for various applications, including vehicle traction. One of their drawback is the high demagnetizing current required in the flux weakening region to let the motor achieve high speeds. This problem can be mitigated by equipping the motor with a mechanical devices consisting of mobile rotor yokes. These move radially by centrifugal force so as to reduce the air-gap flux at high speed with no need for demagnetizing current injection. This paper addresses the problem of modeling such IPM motor to study its steady-state behavior under different operating conditions, both in the full-flux and in the flux-weakening region of the speed range. The approach uses a limited set of non-linear finite element analysis to characterize the dependency of motor flux linkages on the stator currents and rotor position. Interpolating functions are then obtained to mathematically capture this dependency and plug it into the steady-state electromechanical equations of the motor. The effectiveness and accuracy of the method are assessed through on-load measurements taken on the modelled motor both in low and high speed operation

A comparison of machine learning algorithms for chemical toxicity classification using a simulated multi-scale data model

<p>Abstract</p> <p>Background</p> <p>Bioactivity profiling using high-throughput <it>in vitro </it>assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also reduce the need for animal testing. Several public efforts are aimed at discovering patterns or classifiers in high-dimensional bioactivity space that predict tissue, organ or whole animal toxicological endpoints. Supervised machine learning is a powerful approach to discover combinatorial relationships in complex <it>in vitro/in vivo </it>datasets. We present a novel model to simulate complex chemical-toxicology data sets and use this model to evaluate the relative performance of different machine learning (ML) methods.</p> <p>Results</p> <p>The classification performance of Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), Recursive Partitioning and Regression Trees (RPART), and Support Vector Machines (SVM) in the presence and absence of filter-based feature selection was analyzed using K-way cross-validation testing and independent validation on simulated <it>in vitro </it>assay data sets with varying levels of model complexity, number of irrelevant features and measurement noise. While the prediction accuracy of all ML methods decreased as non-causal (irrelevant) features were added, some ML methods performed better than others. In the limit of using a large number of features, ANN and SVM were always in the top performing set of methods while RPART and KNN (k = 5) were always in the poorest performing set. The addition of measurement noise and irrelevant features decreased the classification accuracy of all ML methods, with LDA suffering the greatest performance degradation. LDA performance is especially sensitive to the use of feature selection. Filter-based feature selection generally improved performance, most strikingly for LDA.</p> <p>Conclusion</p> <p>We have developed a novel simulation model to evaluate machine learning methods for the analysis of data sets in which in vitro bioassay data is being used to predict in vivo chemical toxicology. From our analysis, we can recommend that several ML methods, most notably SVM and ANN, are good candidates for use in real world applications in this area.</p

Hybrid Meta-heuristics with VNS and Exact Methods: Application to Large Unconditional and Conditional Vertex p-Centre Problems

Large-scale unconditional and conditional vertex p-centre problems are solved using two meta-heuristics. One is based on a three-stage approach whereas the other relies on a guided multi-start principle. Both methods incorporate Variable Neighbourhood Search, exact method, and aggregation techniques. The methods are assessed on the TSP dataset which consist of up to 71,009 demand points with p varying from 5 to 100. To the best of our knowledge, these are the largest instances solved for unconditional and conditional vertex p-centre problems. The two proposed meta-heuristics yield competitive results for both classes of problems

A Cell Permeable Peptide Inhibitor of NFAT Inhibits Macrophage Cytokine Expression and Ameliorates Experimental Colitis

Nuclear factor of activated T cells (NFAT) plays a critical role in the development and function of immune and non-immune cells. Although NFAT is a central transcriptional regulator of T cell cytokines, its role in macrophage specific gene expression is less defined. Previous work from our group demonstrated that NFAT regulates Il12b gene expression in macrophages. Here, we further investigate NFAT function in murine macrophages and determined the effects of a cell permeable NFAT inhibitor peptide 11R-VIVIT on experimental colitis in mice. Treatment of bone marrow derived macrophages (BMDMs) with tacrolimus or 11R-VIVIT significantly inhibited LPS and LPS plus IFN-γ induced IL-12 p40 mRNA and protein expression. IL-12 p70 and IL-23 secretion were also decreased. NFAT nuclear translocation and binding to the IL-12 p40 promoter was reduced by NFAT inhibition. Experiments in BMDMs from IL-10 deficient (Il10−/−) mice demonstrate that inhibition of IL-12 expression by 11R-VIVIT was independent of IL-10 expression. To test its therapeutic potential, 11R-VIVIT was administered systemically to Il10−/− mice with piroxicam-induced colitis. 11R-VIVIT treated mice demonstrated significant improvement in colitis compared to mice treated with an inactive peptide. Moreover, decreased spontaneous secretion of IL-12 p40 and TNF in supernatants from colon explant cultures was demonstrated. In summary, NFAT, widely recognized for its role in T cell biology, also regulates important innate inflammatory pathways in macrophages. Selective blocking of NFAT via a cell permeable inhibitory peptide is a promising therapeutic strategy for the treatment of inflammatory bowel diseases

Development of a Halotolerant Community in the St. Lucia Estuary (South Africa) during a Hypersaline Phase

Background: The St. Lucia Estuary, Africa’s largest estuarine lake, is currently experiencing unprecedented freshwater deprivation which has resulted in a northward gradient of drought effects, with hypersaline conditions in its northern lakes. Methodology/Principal Findings: This study documents the changes that occurred in the biotic communities at False Bay from May 2010 to June 2011, in order to better understand ecosystem functioning in hypersaline habitats. Few zooplankton taxa were able to withstand the harsh environmental conditions during 2010. These were the flatworm Macrostomum sp., the harpacticoid copepod Cletocamptus confluens, the cyclopoid copepod Apocyclops cf. dengizicus and the ciliate Fabrea cf. salina. In addition to their exceptional salinity tolerance, they were involved in a remarkably simple food web. In June 2009, a bloom of an orange-pigmented cyanobacterium (Cyanothece sp.) was recorded in False Bay and persisted uninterruptedly for 18 months. Stable isotope analysis suggests that this cyanobacterium was the main prey item of F. cf. salina. This ciliate was then consumed by A. cf. dengizicus, which in turn was presumably consumed by flamingos as they flocked in the area when the copepods attained swarming densities. On the shore, cyanobacteria mats contributed to a population explosion of the staphylinid beetle Bledius pilicollis. Although zooplankton disappeared once salinities exceeded 130, many taxa are capable of producing spores or resting cysts to bridge harsh periods. The hypersaline community was disrupted by heavy summer rains in 2011, which alleviated drought conditions and resulted in a sharp increase in zooplankton stock an

From community approaches to single-cell genomics: the discovery of ubiquitous hyperhalophilic Bacteroidetes generalists

The microbiota of multi-pond solar salterns around the world has been analyzed using a variety of culture-dependent and molecular techniques. However, studies addressing the dynamic nature of these systems are very scarce. Here we have characterized the temporal variation during 1 year of the microbiota of five ponds with increasing salinity (from 18% to >40%), by means of CARD-FISH and DGGE. Microbial community structure was statistically correlated with several environmental parameters, including ionic composition and meteorological factors, indicating that the microbial community was dynamic as specific phylotypes appeared only at certain times of the year. In addition to total salinity, microbial composition was strongly influenced by temperature and specific ionic composition. Remarkably, DGGE analyses unveiled the presence of most phylotypes previously detected in hypersaline systems using metagenomics and other molecular techniques, such as the very abundant Haloquadratum and Salinibacter representatives or the recently described low GC Actinobacteria and Nanohaloarchaeota. In addition, an uncultured group of Bacteroidetes was present along the whole range of salinity. Database searches indicated a previously unrecognized widespread distribution of this phylotype. Single-cell genome analysis of five members of this group suggested a set of metabolic characteristics that could provide competitive advantages in hypersaline environments, such as polymer degradation capabilities, the presence of retinal-binding light-activated proton pumps and arsenate reduction potential. In addition, the fairly high metagenomic fragment recruitment obtained for these single cells in both the intermediate and hypersaline ponds further confirm the DGGE data and point to the generalist lifestyle of this new Bacteroidetes group.This work was supported by the projects CGL2012-39627-C03-01 and 02 of the Spanish Ministry of Economy and Competitiveness, which were also co-financed with FEDER support from the European Union. TG group research is funded in part by a grant from the Spanish Ministry of Economy and Competitiveness (BIO2012-37161), a grant from the Qatar National Research Fund grant (NPRP 5-298-3-086) and a grant from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC (grant agreement no. ERC-2012-StG-310325)

Biallelic variants in KARS1 are associated with neurodevelopmental disorders and hearing loss recapitulated by the knockout zebrafish

Purpose: Pathogenic variants in Lysyl-tRNA synthetase 1 (KARS1) have increasingly been recognized as a cause of early-onset complex neurological phenotypes. To advance the timely diagnosis of KARS1-related disorders, we sought to delineate its phenotype and generate a disease model to understand its function in vivo. Methods: Through international collaboration, we identified 22 affected individuals from 16 unrelated families harboring biallelic likely pathogenic or pathogenic in KARS1 variants. Sequencing approaches ranged from disease-specific panels to genome sequencing. We generated loss-of-function alleles in zebrafish. Results: We identify ten new and four known biallelic missense variants in KARS1 presenting with a moderate-to-severe developmental delay, progressive neurological and neurosensory abnormalities, and variable white matter involvement. We describe novel KARS1-associated signs such as autism, hyperactive behavior, pontine hypoplasia, and cerebellar atrophy with prevalent vermian involvement. Loss of kars1 leads to upregulation of p53, tissue-specific apoptosis, and downregulation of neurodevelopmental related genes, recapitulating key tissue-specific disease phenotypes of patients. Inhibition of p53 rescued several defects of kars1−/− knockouts. Conclusion: Our work delineates the clinical spectrum associated with KARS1 defects and provides a novel animal model for KARS1-related human diseases revealing p53 signaling components as potential therapeutic targets