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  • In this research, we developed a high throughput method to systematically map functional connections from the dorsal cortex to the thalamus in awake mice by combing optogenetic inactivation with multichannel recording. Here, we provide: 1. Raw data of multi-units and single-units obtained in this study. 2. MATLAB codes for data analysis.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Document
    • File Set
  • Background: Vitamin D metabolism and obesity have been linked by several studies, however the reason for this association is unclear. Our objective was to investigate potential correlations between genetic variants in key enzymes of vitamin D metabolism and body mass index on a representative sample of the Hungarian adult population. Methods: Altogether 462 severely vitamin D deficient individuals were studied at the end of winter to minimize environmental and maximize any relevant genetic effect. Furthermore, participants with lifestyle factors known to affect vitamin D metabolism were also excluded. We selected 23 target SNPs in five genes that encode key proteins of vitamin D metabolism (NADSYN1, GC, CYP24A1, CYP2R1, VDR). Results: Variants in 2 genetic polymorphisms; rs2853564 (VDR) and rs11023374 (CYP2R1) showed a significant association with participants‘ BMI levels . These associations survived further adjustment for total-, free-, or bioactive-25(OH) vitamin D levels, although the variance explained by these 2 SNPS in BMI heterogeneity was only 3.2%. Conclusion: Our results show two novel examples of the relationship between genetics of vitamin D and BMI, highlighting the potential role of vitamin D metabolism in the physiology of obesity.
    Data Types:
    • Software/Code
    • Dataset
  • Cavitation inside fuel injection nozzles affects the atomization process of injected liquids. It is necessary to understand and model the process for realizing an appropriate injection strategy for an efficient combustion. As the nature of the fuel injector, it has contraction, divergent and bending parts from small to large scale. These geometrical characteristics of the nozzle have an effect on the cavitation phenomena even if it is kind of a small manufacturing variation. However, a simultaneous contained database for the transient cavitation structure especially inside the real-scale nozzle and the nozzle geometry has not been established well. Therefore, parametric investigations have been done on our manufactured transparent nozzles. And the results will be shared step by step for the cavitation model evaluations and developments. In this database, the results in below on each nozzle are uploaded. 1. High speed imaging of the transient cavitation structure. 2. Nozzle geometry which modified as close as the measured shape. 3. Samples of mesh files and simulation results (PDF). The purpose of this database is to provide the data to someone who intends to understand and model the cavitation phenomena. This research work is financially supported by German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the project DI 591/29-1. First of all, please read "About_this_database.pdf".
    Data Types:
    • Other
    • Geospatial Data
    • Image
    • Dataset
    • Document
  • Locations, trips, travel times, and travel distances for the simulation of an integrated item-sharing and crowdshipping platform in Atlanta, Georgia, US. Further information is provided in Description_of_files.html.
    Data Types:
    • Software/Code
    • Dataset
    • Text
  • Materials used to produce figures in the manuscript entitled "Photonuclear Reactions in Lightning II: Comparison between Observation and Simulation Model" (Y. Wada et al., submitted to Journal of Geophysical Research - Atmospheres) are included.
    Data Types:
    • Other
    • Tabular Data
    • Dataset
    • Text
  • Filename: TestData.xlsx The data is test stress-strain data for cadaveric human supraspinatus tendon obtained in a uni-axial tensile test on MTS EM Tension testing equipment at University of South Africa's Biomechanics Research Laboratory. The equipment was operated in displacement mode on all the three tests at 0.1 s-1 of strain rate. The samples were not preconditioned. All columns are appropriately labelled to enable researchers to understand what each column represents. The test equipment did not have an environmental chamber at the time of the test so the samples were inevitably exposed to varying conditions before and during the test procedure. Filename: Hyperelastic_vs_Viscoelastic_Nonlin_Modelling.m This is a main processing MATLAB program file. It calculates the stress using nonlinear least squares curve fitting routine. Filename: funTestData_ShoulderTendon.m The function is called by the above file to fetch test data from the Excel file 'TestData.xlsx' and extracts only the section within the elastic region. There are three tests in the file and each test data is different in terms of the upper limit of the elastic region. The function calls each test data as specified in its argument. Filename: funyehmod.m This MATLAB function implements the Yeoh material model. Filename: funstdnonlinsolid.m This MATLAB function implements the standard nonlinear solid model using the sigmoidal kernel function.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
  • This a data about the corona virus COVID-19. It contains the actual reported data. Also, it includes the predicted COVID-19 data in the future based on a model developed to predict in the future. The model used will be published in one of the journals later and will be found on my profile with title "Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis". The daily folder contains the daily data. The predicted folder contains the predicted data for each country. The total cases folder contains the total cases for each country. he section folder contains a latex code for plotting the figures for each country. Also the source file from European Centre for Disease Prevention and Control is included. More updated files available in the website of European Centre for Disease Prevention and Control.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Document
    • Text
  • The digital entrepreneurship research & publication dataset, which was indexed by Scopus from 1993 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
    Data Types:
    • Tabular Data
    • Dataset
  • CMIP6 and observational data for trend comparisons in the lower- and mid-troposphere
    Data Types:
    • Tabular Data
    • Dataset
  • Supplemental material: 1. Additional File 1 (pdf) Figure S1. Overview of study design. Figure S2. Complete workflow followed in the present study. Figure S3. Differential association between arachidonic acid and BMI across CS and control group. Figure S4. PCA and PLS-DA models of metabolomic signature. 2. Additional File 2 (xslx) Table S1. Chromatographic separation and mass spectrometric detection conditions. Table S2. Raw concentration and biochemical data of the identified metabolites. Table S3. Descriptive statistics of metabolite concentrations. Table S4. Descriptive statistics of total concentrations from metabolic classes. Table S5. Concentration changes of serum metabolic classes in Cushing syndrome compared with control group. Table S6. Spearman correlations between the concentrations of metabolites from the same metabolic class grouped by CS. Table S7. Classification performance and selection of the PLS components. Table S8. Metabolomic signature performance based on sPLSDA model. Table S9. Pairwise correlations between the 374 metabolites assessed. Table S10. Differential correlations across groups between metabolites of the same metabolic class. Table S11. Cushing syndrome differential network correlations. Table S12. Centrality measures of differential network analysis. Table S13. Altered biochemical canonical pathways during CS.
    Data Types:
    • Tabular Data
    • Dataset
    • Document
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