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  • Feeding a Saccharomyces cerevisiae fermentation product during an intestinal barrier challenge in lactating Holstein cows impacts the ruminal microbiota and metabolome
    Through its influence on the gut microbiota, feeding of Saccharomyces cerevisiae fermentation products (SCFP) has been a successful strategy to enhance the health of dairy cows during periods of physiological stresses. Although production and metabolic outcomes from feeding SCFP are relatively well-known, combined impacts on the ruminal microbiota and metabolome during intestinal barrier challenges remain unclear. To address this gap in knowledge, multiparous Holstein cows (97.1 ± 7.6 DIM; n = 8/group) fed a control diet (CON) or CON plus 19 g/d SCFP for 9 wk were subjected to a feed restriction (FR) challenge for 5 d, during which they were fed 40% of their ad-libitum intake from the 7 d prior to FR. DNA extracted from ruminal fluid was subjected to PacBio Full-Length 16S rRNA gene sequencing, RT-PCR of 12 major ruminal bacteria, and metabolomics analysis of up to 189 metabolites via GC-MS. High-quality amplicon sequence analyses were performed with Targeted Amplicon Diversity Analysis (TADA), MicrobiomeAnalyst, PICRUSt, and STAMP software, while metabolomics data were analyze via MetaboAnalyst 5.0. Ruminal fluid metabolites from the SCFP group exhibited a greater alpha diversity Chao 1 (P = 0.03) and Shannon indices (P = 0.05), and the PLS-DA analysis clearly discriminated metabolite profiles between dietary groups. The abundance of CPla_4_termite_group, Candidatus_Saccharimonas, Oribacterium, and Pirellula genus in cows fed SCFP was greater. In the SCFP group, concentrations of ethanolamine, 2-amino-4,6-dihydroxypyrimidine, glyoxylic acid, serine, threonine, cytosine, stearic acid, and pyrrole-2-carboxylic acid were greater in ruminal fluid. Both Fretibacterium and Succinivibrio abundance were positively correlated with metabolites across various biological processes: gamma-aminobutyric acid, galactose, butane-2,3-diol, fructose, 5-amino pentanoic acid, beta-aminoisobutyric acid, ornithine, malonic acid, 3-hydroxy-3-methylbutyric acid, hexanoic acid, heptanoic acid, cadaverine, glycolic acid, beta-alanine, 2-hydroxybutyric acid, methyl alanine, and alanine. In the SCFP group, compared with CON, the mean proportion of 14 predicted pathways based on metabolomics data was greater, while 10 predicted pathways were lower. Integrating metabolites and upregulated predicted enzymes (NADP+-dependent glucose-6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, serine: glyoxylate aminotransferase, and D-glycerate 3-kinase) indicated that the pentose phosphate pathway and photorespiration pathway were most upregulated by SCFP. Overall, SCFP during FR led to alterations in ruminal microbiota composition and key metabolic pathways. Among those, there was a shift from the tricarboxylic acid (TCA) cycle to the glyoxylate cycle and nitrogenous base production was enhanced. The utilization of metatranscriptomics and bacterial culture techniques could aid in evaluating the functional significance of these changes.
    • Dataset
  • Flood Amateur Video for Semantic Segmentation Dataset
    This dataset is flood data in the city of Parepare, South Sulawesi Province, which contains video data collected from social media Instagram. This dataset was created to develop deep learning methods for recognizing floods and surrounding objects, specializing in semantic segmentation methods. This dataset consists of three folders, namely raw video data collected from Instagram, image data resulting from splitting the video into several images, and annotation data containing images that have been color-labeled according to their objects. There are 6 object classifications based on color labels, namely: floods (blue light), buildings (red), plants (green), people (sage), vehicles (orange), and sky (dark blue). This dataset has data in image (JPEG/PNG) and video (MP4) formats. This dataset is suitable for object recognition tasks with the semantic segmentation method. In addition, because this dataset contains original data in the form of videos and images, it can be developed for other purposes in the future. As a note, if you intend to use this dataset, please ensure that you comply with applicable copyright, privacy, and regulatory requirements. If you intend to read the paper about this dataset, please visit this link: https://doi.org/10.1016/j.dib.2023.109768
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  • Data set: Social assessment model for renewable energy megaprojects in Colombia
    This data contains the excel workbooks used for the development of the tesis Social assessment model for renewable energy megaprojects in Colombia
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  • Analysis of Library User Behavior and Research on Personalized Service Based on Data Mining and Machine Learning
    Data of manuscript "Analysis of Library User Behavior and Research on Personalized Service Based on Data Mining and Machine Learning"
    • Dataset
  • Biologic Treatment Options for Pityriasis Rubra Pilaris: An Evidence-Based Systematic Review
    Pityriasis rubra pilaris (PRP) is a rare inflammatory condition characterized by follicular hyperkeratosis and palmoplantar keratoderma. There are currently no FDA-approved therapies for PRP, however, use of biologics has been reported in literature. This systematic review summarizes evidence surrounding biologic treatment for PRP.
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  • Weight cycling has distinct effects on the liver, adipose tissues, and muscle performance in a male zebrafish model
    physiological data, histology analysis, and gene expression of zebrafish with weight fluctuation
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  • NORMATIVE REFERENCE VALUES OF Y-BALANCE TEST IN RELATION TO BMI IN HEALTHY YOUNG MALES AND FEMALES
    The Y-Balance-Test (YBT) is a valuable field-based assessment tool for evaluating dynamic balance performance in both lower and upper extremities. By measuring the ability to maintain a stable base of support during prescribed movements, the YBT offers insights into dynamic postural control essential for executing movement skills, particularly in athletic populations. Understanding BMI's influence on balance is vital for effective weight management and injury prevention strategies. Therefore, understanding the relationship between BMI and balance levels is crucial for developing effective intervention strategies aimed at promoting weight management and enhancing postural stability, thereby reducing the risk of injuries and improving overall quality of life.
    • Dataset
  • Load dataset
    The present dataset is the combined details of hourly load variation along with the hourly varying weather parameters. The load dataset has been obtained from one of the substations (location Ahmedabad) and weather parameters dataset has been extracted from the NASA open-source website.
    • Dataset
  • Empirical modelling of supercritical Nusselt number correlations with possible combinations of indicative dimensionless variables (Parametric, Grid Sensitivity)
    There are currently over 100 correlations for estimating the Nusselt number in supercritical heat transfer, with over 30 dimensionless variables utilized to model the correlation. However, a systematic approach to identify the optimal correlation form that best represents the underlying dataset has yet to be established. Therefore, in this study, a comprehensive model for supercritical Nusselt number correlations was developed through a preliminary Spearman's rank correlation analysis and empirical modelling for conceivable combinations of dimensionless variables. The dataset validated with Bae's experimental dataset for upward supercritical carbon dioxide flow at 8.12 MPa inside 6.32 mm diameter channel was post-processed to 33 commonly used dimensionless variables and 1,149,016 dimensionless groups. Through Spearman's rank correlation analysis, 7408 dimensionless groups with a strong positive monotonic relationship with Nusselt number were identified. Subsequently, the 1,149,016 dimensionless groups were empirically correlated and compared to the Spearman's rank correlation coefficients. The present study reveals one correlation that has a minimum RMSPE of 0.595% with no outliers exceeding 5%. Overall, this study provides valuable insights into the empirical modelling of supercritical Nusselt number correlations for millions of dimensionless groups, and can be applied to the modelling of Nusselt number correlations under various heat transfer conditions.
    • Dataset
  • Targeted National Suicide Prevention Strategies
    Targeted National Suicide Prevention Strategies
    • Dataset
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