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These data are simulated results used in the manuscript titled "Hourly aerosol assimilation of Himawari-8 AOT using the four-dimensional local ensemble transform Kalman filter" to Journal of Advances in Modeling Earth Systems.

DTM FROM IGN

The Data supports the findings of the article with the same name.

Disclaimer: These datasets were generated during the course of academic research conducted at the Faculty of Medicine, The Chinese University of Hong Kong, which received ethics approval by The Joint Chinese University of Hong Kong ��� New Territories East Cluster Clinical Research Ethics Committee and/or the Institutional Review Board of the University of Hong Kong/Hospital Authority Hong Kong West Cluster of the Hospital Authority. They are published for further advancement of medical research in full compliance with University Regulations and Policy on Dataset Deposit and Sharing. For additional information: https://libguides.lib.cuhk.edu.hk/RDM/dataset_deposit The use of these datasets should provide acknowledgements of such efforts by citing this DOI. Data set on heart failure due to different causes

Data set from Moons P, Luyckx K, Kovacs AH, Holbein CE, Thomet C, Budts W, Enomoto J, Sluman MA, Yang HL, Jackson JL, Khairy P, Cook SC, Chidambarathanu S, Alday L, Eriksen K, Dellborg M, Berghammer M, Johansson B, Mackie AS, Menahem S, Caruana M, Veldtman G, Soufi A, Fernandes SM, White K, Callus E, Kutty S, Apers S; APPROACH-IS Consortium and the International Society for Adult Congenital Heart Disease (ISACHD). Prevalence and Effects of Cigarette Smoking, Cannabis Consumption, and Co-use in Adults From 15 Countries With Congenital Heart Disease. Can J Cardiol. 2019 Dec;35(12):1842-1850. doi: 10.1016/j.cjca.2019.07.635. Epub 2019 Aug 14. PMID: 31813510. This is the abstract: Background: The prevalence and effects of cigarette smoking and cannabis use in persons with congenital heart disease (CHD) are poorly understood. We (1) described the prevalence of cigarette smoking, cannabis consumption, and co-use in adults with CHD; (2) investigated intercountry differences; (3) tested the relative effects on physical functioning, mental health, and quality of life (QOL); and (4) quantified the differential effect of cigarette smoking, cannabis use, or co-use on those outcomes. Methods: APPROACH-IS was a cross-sectional study, including 4028 adults with CHD from 15 countries. Patients completed questionnaires to measure physical functioning, mental health, and QOL. Smoking status and cannabis use were assessed by means of the Health Behaviour Scale-Congenital Heart Disease. Linear models with doubly robust estimations were computed after groups were balanced with the use of propensity weighting. Results: Overall, 14% of men and 11% of women smoked cigarettes only; 8% of men and 4% of women consumed cannabis only; and 4% of men and 1% of women used both substances. Large intercountry variations were observed, with Switzerland having the highest prevalence for smoking cigarettes (24% of men, 19% of women) and Canada the highest for cannabis use (19% of men, 4% of women). Cigarette smoking had a small negative effect on patient-reported outcomes, and the effect of cannabis was negligible. The effect of co-use was more prominent, with a moderate negative effect on mental health. Conclusions: We found significant intercountry variability in cigarette and cannabis use in adults with CHD. Co-use has the most detrimental effects on patient-reported outcomes.

The data here were originally posted to facilitate timely and transparent peer review. The final public data release with formal metadata is now available from at the following location: Nauman, T.W., and Duniway, M.C., 2020, Predictive soil property maps with prediction uncertainty at 30 meter resolution for the Colorado River Basin above Lake Mead: U.S. Geological Survey data release, https://doi.org/10.5066/P9SK0DO2. Associated publication: Nauman, T. W., and Duniway, M. C., 2020, A hybrid approach for predictive soil property mapping using conventional soil survey data: Soil Science Society of America Journal, v. 84, no. 4, p. 1170-1194. https://doi.org/10.1002/saj2.20080. Repository includes maps of soil gypsum content (% wt of the <20 mm fraction) as defined by United States soil survey program. These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data. This data should be used in combination with a soil depth or depth to restriction layer map (both layers that will be released soon as part of this project) to eliminate areas mapped at deeper depths than the soil actually goes. This is a limitation of this data which will hopefully be updated in future updates. The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds. Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal. File Name Details: ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for both the overall sample (NRCS field pedons plus NRCS laboratory pedons; file ending _CV_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are >3000). Elements are separated by underscore (_) in the following sequence: property_r_depth_cm_geometry_model_additional_elements.extension Example: gypsum_r_0_cm_2D_QRF_bt.tif Indicates soil gypsum content (gypsum) at 0 cm depth using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions. The _bt indicates that the map has been back transformed from ln or sqrt transformation used in modeling. The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below). _95PI_h: Indicates the layer is the upper 95% prediction interval value. _95PI_l: Indicates the layer is the lower 95% prediction interval value. _95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI. References Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma

Simulation of a black-hole binary system evolved by the SpEC code.

This upload contains all data, analysis code, and research materials.

This object contains only a fraction of the available content for the portal. For further information on the content and for other fractions see: Székelyhon.Please fill in the following form before requesting access to this dataset:ACCES FORM {"references": ["https://doi.org/10.5281/zenodo.3755323"]}

The aim of this study is to draw up a tool to identify the needs detected by the Mixed Ability Rugby environment for its promotion as a means of inclusion of people with disabilities in sport and in the community. The Delphi method is used for the development and validation of the tool. A coordinating group is formed, made up of 5 people (2 linked to the university and 3 specialists in Mixed Ability Rugby), and a group of experts in which 17 professionals in processes of inclusion, sport and disability from Spain, Chile and Ecuador participated. The coordinating group drafts the questionnaire and identifies the groups within the agents involved in the Mixed Ability Rugby environment to whom the questionnaire is addressed: players with and without disabilities, family members/personal assistants/support persons or legal representatives of players, coaching and support staff of clubs, and referees. Three consultation rounds with experts are carried out to determine the final structure and content of the questionnaire. As a result, the Q-NeMAR questionnaire is obtained, which will show the needs detected by these agents to promote Mixed Ability Rugby. This will enable the development of strategies and policies to improve its visibility in order to create opportunities for inclusion of all people in sport. CC BY-NC 4.0 This work was supported by the INDITEX-UDC 2021 Grant for predoctoral stays. The authors wish to thank all the experts who collaborated in the validation process.