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  • This data set can be used to plot bar charts of COVID 19 incidence and estimate time dependent reproduction number in Nigeria and the six geo - political zones in the country. The data was collated from the daily COVID – 19 infections situation report in Nigeria numbers 01 – 89 from the 28th of February to 27th of May 2020 downloaded from the country’s Nigeria Centre for Disease Control (NCDC) website (https://ncdc.gov.ng/diseases/sitreps/?cat=14&name=An%20update%20of%20COVID-19%20outbreak%20in%20Nigeria ). The data files in .csv are presented with r codes that can be used to recreate the analysis. We used the R software version 3.6.1 to draw a combine bar plot of COVID 19 incidence in Nigeria and across the six geo - political zones. We estimated the TD - R0 for the country and the six geo - political zones in the country using the EpiEstim package and tested the fitness in the pattern of distribution of the estimated TD - R0 across the six geo - political zones in the country using the Kolmogorov - Smirnov test adjusting for Type 1 error.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • File Set
  • The data from the two experiments in the study of categorical perception of control.
    Data Types:
    • Tabular Data
    • Dataset
  • Bathing facilities and health phronesis: a preliminary English investigation. Mixed methods sequential research in five phases. Research questions and hypotheses • RQ1: Does the geospatial distribution of swimming facilities impact health? (Nomothetic). (H10: Pools is insignificant vs. H1A: Pools is significant) • RQ2: Is the construction of swimming pools adequate for national health need? (Nomothetic). (H20: Forecast pool construction stable vs. H2A: Forecast increase in pool construction) • RQ3: What policy learning emerges from idiosyncratic cases? (Idiographic & qualitative) Approach After problematisation (1) and structured literature review (2), the study conducted cross-sectional analysis of excess mortality and swimming pools (3a & 3b) and longitudinal analysis of pool construction (3c-e). Cross-sectional investigation involved factor analysis (3a) to explore and regression to analysis (3b) to investigate English mortality and its covariates (3b). The For the time series analysis, the study analysed 120 years of English pool construction data using autoregressive distributed lag models - ARIMA (3c), ADL (3d) and ECM (3e). Data Cross sectional analysis Deaths (DV, Yd): ONS standardised mortality ratio (2013-2017). Observed total deaths from all causes (by five year age and gender band) as a percentage of expected deaths. Access Leisure (IV, X1): reflects accessibility to 727 leisure centres, swimming baths or 2,738 health clubs in kilometres. Liverpool University’s Consumer Data Research Centre, Access to Healthy Assets and Hazards (AHAH) index. Obesity (IV, X2): percentage of adult population with a body mass index (BMI) of 30 kg/m2 or higher, age-standardized, WHO 2389 NCD_BMI_30 (2020). Deprivation (IV, X3): deprivation score for English small areas, sourced from Index of Multiple Deprivation (2019). Environment (IV, X4) measures accessible blue and green space, sourced via SE (2020), data constitutes an element of AHAH (2017). Pools (IV, X5): reflects pools per 10,000 in 2018. Data extracted from SE Active Places Power (APP) Time series analysis Pools constructed (PC & ∆PC): English swimming pools constructed each year during a 120 year period since 1900, SE Active Places Power (2020) database. English output (GDP & ∆GDP): Bank of England millennium of macroeconomic data UK (2017) provides historical macroeconomic and financial statistics. English population (Pop & ∆Pop): English population and population growth 1900-2020, Office for National Statistics (ONS): Total population (2018). Notable findings The evidence from cross sectional regression analysis (3b) supports the alternative hypothesis, H1A, that pool density significantly influences excess mortality in England. All three times series models project an increase in pool construction which lends support to H2A of an increased pool construction need. For RQ2 then, current levels of swimming pool construction appears inadequate.
    Data Types:
    • Tabular Data
    • Dataset
  • SS, SAOS, LAOS, Triangle Ramp, UDLAOS
    Data Types:
    • Tabular Data
    • Dataset
  • Dataset to evaluate serious games The process has the following phases: Selecting the sample Defining users Define the scenario List the barriers Evaluate manually Record the data Analyze the data
    Data Types:
    • Tabular Data
    • Dataset
  • This is the raw data captured for a systematic review and individual participant data (IPD) meta-analysis evaluating the trends in body mass indices of obese patients with end-stage heart failure (ESHF) with ventricular assist devices (VADs) after undergoing bariatric surgery (BS). A systematic search was performed in ClinicalTrials.gov, Cochrane, Embase and PubMed on November 23rd, 2019. Additional searches were conducted in Google Scholar, websites of the most important journals for ESHF and BS, which also contained the proceedings of the most relevant scientific meetings in such specialties: -The Journal of Heart and Lung Transplantation -Journal of Cardiac Failure, Obesity Surgery -Surgery for Obesity and Related Diseases -Journals of following groups (journal families): --Journal of the American College of Cardiology --Circulation --European Heart Journal These searches were performed at different before April 20th, 2020. Multiple official indexing terms and additional relevant terms for VADs and BS were used. Studies were selected if they reported IPD for the postoperative BMI of VAD patients after undergoing BS. Only patients with VAD support at the time of BS were included in the study. References selection, and data extraction were performed independently and in parallel by two investigators. In cases of disagreements, consensus was attempted through discussion, but if that was not achieved, a third investigator helped to solve the tie by simple majority. This database contains the most relevant variables from an ESHF and BS stand point. More details about data description and analyses can be found in the meta-analysis and data publication related to this project.
    Data Types:
    • Image
    • Tabular Data
    • Dataset
    • Document
  • data for orbital cellulitis with 79 patients
    Data Types:
    • Tabular Data
    • Dataset
  • Viewing time for famous and unknown faces
    Data Types:
    • Tabular Data
    • Dataset
  • This dataset provides additional data for the study The impact of digital transformation and industry 4.0 on the aspects of value: Evidence from a meta-synthesis. It's composed of three files: Reviewed_studies.xlsx, which contain the details of the 76 studies (duplicated papers were already removed) collected from at the databases Web of Science (WOS), Scopus and EBSCO. This dataset contains the studies categorized considering their DATABASE, SEARCH STRING USED, TITLE, AUTHORSHIP, JOURNAL, YEAR OF PUBLICATION, SELECTED TO BE FULLY READ - meaning that upon reading the abstract the paper was selected to be entirely read, and REASON FOR EXCLUSION / SELECTED - pointing the criteria that resulted in the exclusion of the paper or if it was selected for the final sample. Coding_form.xlsx, which contains the coding form for the five studies of the final sample, thus providing the details of the study codification. Causal_networks.xlsx, which contains the causal network for each of the five analyzed studies of the final sample.
    Data Types:
    • Tabular Data
    • Dataset
  • In this work we assessed if using augmented reality (AR) instructions to guide a manual task, could potentially impact the visual system of operators. A before/after design study was carried out asking participants (N=23) to perform LEGO assemblies for 30 minutes with paper or AR instructions. The effects of using AR (optical see-through) compared to paper instructions were evaluated, on binocular vision with classical optometric measurements, and on visual fatigue with the Virtual Reality Symptoms Questionnaire. This dataset contains two files : 1. Optometric measurements : Raw data for monocular visual acuity, stereoacuity, vertical fixation disparity, vertical phoria, amplitude of fusion, monocular accommodation amplitude. Data are available for the four different blocks, i.e., with AR instructions, paper instructions, before and after. 2. Virtual reality symptoms questionnaire Raw data for the 13 symptoms items Data are available for the four different blocks, i.e., with AR instructions, paper instructions, before and after. For each file, a dataset description is included to explain content and column headings. For most optometric measurements, no clinically significant changes were found for AR and paper instructions, and only negligible fatigue symptoms were found specifically for AR. Results from both objective and subjective measurements suggest that there is no impact of AR on the oculomotor system and that in this specific use case, AR can be safely used for production operators.
    Data Types:
    • Tabular Data
    • Dataset
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