cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6069/jzag-h814
title: United States Health Care Spending by Payer and Health Condition 1996-2016

description: The Disease Expenditure Project (DEX) at IHME produced estimates for US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016. Types of care include ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, prescribed pharmaceutical care, and government administration and net cost of insurance programs. Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were used to produce the results. Spending estimates were produced for 154 conditions, which were aggregated into 14 health categories. This dataset contains estimates for the aggregate health categories.
DOI: 10.5281/zenodo.2622986
title: Binary black-hole simulation SXS:BBH:0976

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638961
title: Binary black-hole simulation SXS:BBH:1056

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2623710
title: Binary black-hole simulation SXS:BBH:1056

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622201
title: Binary black-hole simulation SXS:BBH:0859

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638969
title: Binary black-hole simulation SXS:BBH:1083

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2623985
title: Binary black-hole simulation SXS:BBH:1083

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638968
title: Binary black-hole simulation SXS:BBH:0802

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638973
title: Binary black-hole simulation SXS:BBH:0838

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622173
title: Binary black-hole simulation SXS:BBH:0838

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638972
title: Binary black-hole simulation SXS:BBH:0745

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622060
title: Binary black-hole simulation SXS:BBH:0745

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.6069/9dtk-y505
title: Global Educational Attainment Distributions 1970-2030

description: IHME researchers produced this dataset as part of an analysis measuring and forecasting progress by countries towards education-related Sustainable Development Goal (SDG) targets. Annual estimates were created for the average years of schooling and single-year distribution of educational attainment by sex for adults ages 25-29 for 1970 to 2018. Projections were also generated for these indicators to 2030. Estimates were created for the 195 countries and territories examined in the Global Burden of Disease 2017 study. The estimates were produced using a compiled database of 3,180 nationally representative surveys and censuses describing the distribution of years of schooling by age and sex.
DOI: 10.5281/zenodo.2638975
title: Binary black-hole simulation SXS:BBH:0742

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622057
title: Binary black-hole simulation SXS:BBH:0742

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638974
title: Binary black-hole simulation SXS:BBH:0996

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2623182
title: Binary black-hole simulation SXS:BBH:0996

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622044
title: Binary black-hole simulation SXS:BBH:0729

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638963
title: Binary black-hole simulation SXS:BBH:1038

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2623562
title: Binary black-hole simulation SXS:BBH:1038

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638971
title: Binary black-hole simulation SXS:BBH:0924

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2622549
title: Binary black-hole simulation SXS:BBH:0924

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2638970
title: Binary black-hole simulation SXS:BBH:0859

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625841
title: Binary black-hole simulation SXS:BBH:0377

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642225
title: Binary black-hole simulation SXS:BBH:0513

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625992
title: Binary black-hole simulation SXS:BBH:0513

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642224
title: Binary black-hole simulation SXS:BBH:0544

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2626028
title: Binary black-hole simulation SXS:BBH:0544

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642221
title: Binary black-hole simulation SXS:BBH:0505

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625918
title: Binary black-hole simulation SXS:BBH:0445

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642204
title: Binary black-hole simulation SXS:BBH:0353

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625803
title: Binary black-hole simulation SXS:BBH:0353

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642201
title: Binary black-hole simulation SXS:BBH:0484

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625962
title: Binary black-hole simulation SXS:BBH:0484

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642200
title: Binary black-hole simulation SXS:BBH:0417

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.6069/aqsn-er59
title: Low- and Middle-Income Country Childhood Overweight and Wasting Geospatial Estimates 2000-2017

description: "Annual estimates were produced for overweight and wasting prevalence for children under 5 years of age at the 5x5 km-level for 105 low- and middle-income countries (LMICs) between 2000-2017. These estimates were produced using a geo-positioned dataset created from 420 household surveys. Survey sources used include the Demographic and Health Survey (DHS) and UNICEF Multiple Indicator Cluster Survey (MICS) series, and other country‐specific surveys.

This dataset includes the following:

- GeoTIFF raster files for pixel-level estimates of under-5 overweight and wasting prevalence
- CSV files of aggregated overweight and wasting prevalence for each country at zero, first, and second administrative divisions
- Code files used to generate the estimates
"
DOI: 10.5281/zenodo.2625795
title: Binary black-hole simulation SXS:BBH:0346

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642231
title: Binary black-hole simulation SXS:BBH:0433

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625906
title: Binary black-hole simulation SXS:BBH:0433

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642229
title: Binary black-hole simulation SXS:BBH:0590

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2626077
title: Binary black-hole simulation SXS:BBH:0590

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642227
title: Binary black-hole simulation SXS:BBH:0377

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625984
title: Binary black-hole simulation SXS:BBH:0505

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642216
title: Binary black-hole simulation SXS:BBH:0577

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2626064
title: Binary black-hole simulation SXS:BBH:0577

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642211
title: Binary black-hole simulation SXS:BBH:0585

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2626072
title: Binary black-hole simulation SXS:BBH:0585

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642208
title: Binary black-hole simulation SXS:BBH:0571

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625879
title: Binary black-hole simulation SXS:BBH:0409

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642234
title: Binary black-hole simulation SXS:BBH:0453

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625928
title: Binary black-hole simulation SXS:BBH:0453

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642233
title: Binary black-hole simulation SXS:BBH:0427

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625899
title: Binary black-hole simulation SXS:BBH:0427

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642232
title: Binary black-hole simulation SXS:BBH:0346

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/dyv8824kns.1
title: Mindset Behaviour Intellect

description: Heterogeneous sample including items to assess the growth mindset about personality, intellect according to the TIF, SJT items to measure behaviour tendencies, as well as demographic data.
DOI: 10.5281/zenodo.2626056
title: Binary black-hole simulation SXS:BBH:0571

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642207
title: Binary black-hole simulation SXS:BBH:0606

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/48257xrmx3.1
title: WACCM-X simulations 2019 SSW

description: The following data set contains the temperature from WACCM-X simulation for the 2018/2019 SSW event for all levels, latitudes and longitudes. In total, there are 145 levels and the latitude x longitude grid size is 96 x 144. The data begins on 01.12.2018 and ends on 31.01.2019. The simulation has been performed by including the lunar tide at the lower boundary in WACCM-X according to the methods described in Pedatella et al., 2012 (refer to the manuscript for more details). This data set has been used to compare the WACCM-X temperature with AURA-MLS temperature observations and to calculate the SW2 and M2 tides in the MLT region.
DOI: 10.5281/zenodo.2626093
title: Binary black-hole simulation SXS:BBH:0606

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/cc6m499bmm.1
title: Dataset of seed production in temperate broadleaved tree species using different sampling methods

description: The repository stores 223 records about seed production (number of seeds) of three broadleaved (beech, chestnut and Turkey oak) tree species obtained from different ground sampling methods. The seeds were collected in Italy during fall 2019 using Litter Traps (LT), ground quadrats (GQ) and Image quadrats (IQ). A quadrat of 0.25 m² (the same size and shape of litter trap) was placed on the ground and the seeds were either manually counted in the field (GQ) or in images acquired in the same quadrats (IQ) and then compared against LT measurements. For some records LT data were not available. This is the dataset used in the paper "A comparison of ground-based count methods for quantifying seed production in temperate broadleaved tree species" submitted to Annals of Forest Science, currently under review. Field description : Field Description Data type Format Missing values N Unique record number Integer Date Date of sampling Date dd/mm/yyyy ID_site Site name Character ID_point Sampling point Integer IQ Seed counted with image quadrats Integer NA GQ Seed counted with ground quadrats Integer NA LT Seed counted with litter traps Integer NA Species Species Character
DOI: 10.5281/zenodo.2649860
title: Binary black-hole simulation SXS:BBH:0325

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/c3m4tdyvfm.1
title: Wearable Light Data Logger

description: This project offers the necessary hardware and software files for creating a wearable light data logger. This equipment is capable of logging measurements of light intensity, color temperature, UV index, as well as red, green, blue, and clear components of light. Measurements are sampled approximately once per minute and stored onto a microSD card. Battery life with a 350 mAh LiPoly battery is approximately 29 hours.
DOI: 10.5281/zenodo.2625769
title: Binary black-hole simulation SXS:BBH:0325

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/whbk485wbw.1
title: Adult Lung Health Study

description: The Adult Lung Health Study was a propective cohort study conducted in Chikhwawa, rural Malawi, between August 2014 and November 2017. The published manuscript can be found at http://dx.doi.org/10.1136/thoraxjnl-2019-213941 Data were collected at baseline and 2 follow-up visits from a population-representative sample of adults (aged 18 or over). At each time-point participants completed a respiratory symptom questionnaire, performed pre- and post-bronchodilator spirometry and underwent a 48-hour period of personal air pollution monitoring. 1481 adults were recruited between August 2014 and July 2015. Spirometry data (meeting BOLD [Burden of Obstructive Lung Disease] Study QC standards) were collected for 886 participants at baseline, 594 participants at first follow-up and 537 participants at second follow-up. Spirometry was performed before and after administration of 200 microgram salbutamol, via Volumatic spacer. Spirometry measurements were considered repeatable if there were 2 acceptable traces within 200ml of each other. Personal air pollution exposure data were collected using Aprovecho monitors (measuring carbon monoxide and fine particulate matter), worn by each participant for a period of 48-hours. In order to minimise missing data and ensure measurements represented a full 24-hour cycle, readings were truncated at 24-hours. Aprovecho data were available for 1029 participants at baseline, 830 at first follow-up and 811 at second follow-up.
DOI: 10.17632/jryhnrhbg6.1
title: Supplementary materials

description: Efficacy and prognostic factors of postoperative radiotherapy for high-risk cutaneous squamous cell carcinoma: a systematic review and meta-analysis eFigure1. Adjusted analysis of overall survival and disease-free survival: Overall survival analysis exclude study by Kyrgidis 2010 using the random effects model eFigure2. Forest plots for prognostic factors relevant to disease-free survival: Concerning the deleterious impact of PNI demonstrated by our analysis, the AJCC staging system for cSCC also regards PNI as a high risk factor. Besides, our analysis of PNI also was determined robustly since the presence of PNI increases T stage of cSCC in the NCCN guidelines. Surprisingly, immunosuppression in this study showed a high heterogeneity indicating the uncertainty of its influence, whereas the recent AJCC Cancer Staging Manual recommanded this risk factor as additional aspect for clinical care in patients with cSCC of the head and neck region. We included IS as a general category without specific stratification and most selected articles also had not defined the IS. Although Estall et al1 presented IS associated with an increased risk of metastases on the basis of well-defined patients with coexisting hematological malignancy, immunosuppressant use, and end stage renal failure requiring dialysis, it is difficult for a meta-analysis to anlyze all cohorts with vague definition of IS. In this situation, the data suggested that clarification of the types of IS is essential for the comprehension of the factors influencing DFS. A high heterogeneity was observed among included studies concerning the treatment of adjuvant radiotherapy. Some reporters implied that adjuvant radiotherapy showed significant benefit in DFS, while Harris et al and Trosman et al found little association between adjuvant radiotherapy and DFS. It is consistent with the 2018 NCCN guidelines, in which the diversity of study populations was addressed to complicate the comparison of treatment outcomes. Nonetheless, the more accurate N-stage information is crucial for further analysis to identify whether patients with regional metastases would benefit from adjuvant radiotherapy with increased DFS. eFigure3. Funnel plot of recurrence analyses eTable1. Prognostic hazard ratio summarize eTable2. New-castle Ottawa Scale scoring of included studies
DOI: 10.5281/zenodo.2642205
title: Binary black-hole simulation SXS:BBH:0445

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/xtv5y29xvz.2
title: GGG - Rough or Noisy? Metrics for Noise Detection in SfM Reconstructions

description: The proposed dataset is part of the paper with the same name "Rough or Noisy? Metrics for Noise Detection in SfM Reconstructions", which proposes 9 geometrical and SfM capturing setup metrics for training a classification method for detecting noise on a SfM reconstructed surfaces. The dataset contains images for Structure from Motion reconstruction of 15 objects. The images were taken using a Canon 5Ds DSLR camera with a resolution of 8688x5792. The images contain EXIF data that can be used to assist the 3D reconstruction. For all objects, except the wind turbine blade the images are 36 in a circle around the object. For the wind turbine blade the images are positioned in 2 vertical bands of 17 images each in a semi-circle. Together with the images there are reconstruction point clouds. These are created using Agisoft Metashape (Photoscan). For easier processing they are separated into: - one file containing vertex positions in X,Y,Z column stacked format, together with color for each vertex position in RGB - one file containing the normals in Nx, Ny, Nz column stacked format - one file containing triangulated faces for the used vertices Finally there are manually annotated ground truth segmentations of the point clouds into noise and not noise for each of the 15 objects.
DOI: 10.5281/zenodo.2642248
title: Binary black-hole simulation SXS:BBH:0519

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/bz3dvhf95s.1
title: Rio Grande isolated pools temperature

description: Dought and irrigation diversions result in streamflow intermittency and stranding of an endangered fish in the Rio Grande of New Mexico, USA. We collected temperatures of isolated pools (by date and time) that formed during streamflow intermittency in the Middle Rio Grande of New Mexico, USA, 2011-2016 (time.temp2.cs) during fish rescue. We compared these temperatures to stream temperature at an upstream perennial site in Albuquerque, New Mexico, USA, by date and time (alameda_combined_final.csv). We also collected Rio Grande silvery minnow during streamflow intermittency in 2018 and 2020 to evaluate post-rescue survival in captivity in 2018 and 2020 (rescue_surv_all.csv).
DOI: 10.5281/zenodo.2626000
title: Binary black-hole simulation SXS:BBH:0519

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642247
title: Binary black-hole simulation SXS:BBH:0440

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/9cfdbp6xnf.1
title: PEMAT tool

description: PEMAT Tool for the video education
DOI: 10.5281/zenodo.2625913
title: Binary black-hole simulation SXS:BBH:0440

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/yf3bwvhcmt.1
title: EMU and business cycle synchronization

description: These three datasets include data for the variables of business cycle synchronization (eight year period with one year window, eight year period with four year window and eight year period non overlapping), institutional distance, cultural distance, geographical distance and time dummies. They also indicate categorical (0 or 1) variables that indicate which where the treated EMU countries and which were the non-treated countries. They also indicate the timing of EMU intervention. I use these data to test with a difference in differences specification if the degree of business cycle synchronization was higher (or lower) compared to what would have been in case that the euro had not been adopted.
DOI: 10.5281/zenodo.2642244
title: Binary black-hole simulation SXS:BBH:0328

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/ygnzzzppxd.1
title: Developing a Lean Six Sigma Implementation Framework in a Civil Engineering Laboratory

description: An excel spreadsheet for the raw data used for a master of industrial engineering thesis titled Developing a Lean Six Sigma Implementation Framework in a Civil Engineering Laboratory. The thesis was written by Shimwe Shapwa Ya France 2020.
DOI: 10.5281/zenodo.2625774
title: Binary black-hole simulation SXS:BBH:0328

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/gfdy6fm8f9.2
title: USCO2Emission

description: Consumption and CO2 Emissions of Nuclear Energy and Fossil Fuels
DOI: 10.5281/zenodo.2625887
title: Binary black-hole simulation SXS:BBH:0417

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.17632/yf6h9v4vdb.1
title: Datasets-Techniques for analysing and monitoring during continuous bio-hydrogenation of kerosene from palm oils

description: This datasets are included in method article "Techniques for analysing and monitoring during continuous bio-hydrogenation of kerosene from palm oils"
DOI: 10.5281/zenodo.2642199
title: Binary black-hole simulation SXS:BBH:0443

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625916
title: Binary black-hole simulation SXS:BBH:0443

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642194
title: Binary black-hole simulation SXS:BBH:0357

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2625814
title: Binary black-hole simulation SXS:BBH:0357

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2642243
title: Binary black-hole simulation SXS:BBH:0599

description: Simulation of a black-hole binary system evolved by the SpEC code.
DOI: 10.5281/zenodo.2626086
title: Binary black-hole simulation SXS:BBH:0599

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