758 research outputs found

    KINETIC DIFFERENCES IN LOWER EXTREMITY BETWEEN BASEBALL PITCHING FROM PITCHER’S MOUND AND FLAT-GROUND

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    The purpose of this study was to investigate the kinetic differences in lower extremity between pitching from a mound and flat-ground. A motion capture system and two force plates were used simultaneously to collect the dynamic data of 8 baseball male pitchers. The results revealed that pitching from the mound generated higher propulsive force at the trailing leg as well as greater braking force and vertical ground reaction force at the lead leg (p< .05). The trailing leg in the mound condition generated greater knee posterior joint force while the lead leg had greater axial joint force at ankle and knee, as well as greater extension moment at ankle, knee and hip (p< .05). It was concluded that pitching from the mound generated higher ground reaction force, which resulted in higher joint forces and moments and thus might increase stresses at lower extremity

    MetaSquare: An integrated metadatabase of 16S rRNA gene amplicon for microbiome taxonomic classification

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    MOTIVATION: Taxonomic classification of 16S ribosomal RNA gene amplicon is an efficient and economic approach in microbiome analysis. 16S rRNA sequence databases like SILVA, RDP, EzBioCloud and HOMD used in downstream bioinformatic pipelines have limitations on either the sequence redundancy or the delay on new sequence recruitment. To improve the 16S rRNA gene-based taxonomic classification, we merged these widely used databases and a collection of novel sequences systemically into an integrated resource. RESULTS: MetaSquare version 1.0 is an integrated 16S rRNA sequence database. It is composed of more than 6 million sequences and improves taxonomic classification resolution on both long-read and short-read methods. AVAILABILITY AND IMPLEMENTATION: Accessible at https://hub.docker.com/r/lsbnb/metasquare_db and https://github.com/lsbnb/MetaSquare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online
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