cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/mc37xdzw74.5
title: Data_Mexico_COVID19

description: As spatial analysis can contribute to the understanding of COVID-19 epidemic, we compiled and georeference data for Mexico. Data were compiled from the National Population Council (CONAPO), Google, the National Institute of Statistics and Geography (INEGI), and the Secretary of Health. The data describe the cases of COVID and characteristics of the population, such as distribution, mobility, and prevalence of chronic diseases such as diabetes, hypertension, and obesity. These data were processed to be compatible and georeferenced to a common geographic framework to facilitate spatial analysis in a geographic information system (GIS). The dataset comprises GIS layers (shape and geopackage files), tables (CSV formatted), and R scripts. A complete description was published in the journal Data in Brief (https://doi.org/10.1016/j.dib.2021.106843).
From version 4, population data from the 2020 INEGI Population census are incorporated in the data. COVID data was updated to data available on July 1, 2022.
DOI: 10.17632/m7fzwvsm77.1
title: Dataset on comparison of the ocular surface disease index questionnaire, the tear film break-up time and Schirmer tests for the evaluation of tear film in computer users and contact lenses without dry eye symptoms

description: Comparison of the OSDI, the Schirmer’s and tear film breakup time test to check for dry eye in healthy adult using computers and contact lenses.
DOI: 10.17632/m5d7r2rjx6.1
title: LAI Estimations of Coffee Hedges through different methods.

description: The attached excel file has the datasets for the process described on the paper submitted by Castro-Pacheco et al, with the title "Visual Assessment of Leaf Area Index in Coffee (Coffea arabica L.) Fields."

Two datasets are shown and described. 

First, a main dataset containing the results from the the first experimentations done, in which the Leaf Area Index (LAI) was estimated with three different approaches on 80 different sampling points. These approaches were: direct defoliation, visual assesmenty from trained persons, and through the use of specialized equipment (LICOR LAI-2200C  or Accupar LP-80 Ceptometer).

The second -supplementary- dataset corresponds to a second experimentation done, which included 40 sampling points. In these points, LAI was still estimated with the  same three approaches, but two different protocols were tested with the instruments.
DOI: 10.17632/hwr4dzmz48.1
title: Anterior glenohumeral dislocation reduction techniques comparison

description: In recent years, many reduction techniques have been used in the treatment of anterior glenohumeral dislocation (GHD).  90 patinets were divided into three group with blocked randomization method.  And one of the three different reduction technique was perfomed each patient. The data include the pre-reduction visual analogue scale (VAS), the intra-reduction VAS, the post-reduction VAS and the reduction time.
DOI: 10.17632/hgcg44cz99.2
title: A Multipurpose Dataset for Automatic Bangla Offensive Speech Recognition

description: This dataset contains audio data of common abusive Bengali words. The audio data includes 114 slang words with 5277 audio clips by 60 native speakers who participated, speaking in various dialects from over 20 districts. The recorded audio  data is natively recorded  by the participants in .WAV format. 

•  This dataset can be used to develop an automatic Bengali Slang Speech Recognition System, and also as a benchmark for new ML models.
•  This dataset can potentially help minimize cyberbully victims and children exposed to abusive remarks on video/audio content containing abusive language. 
   In addition, this dataset of carefully collected offensive language in Bengali aims to work towards achieving this goal. 
•  65% of the participants were male and 35% were female. 
•  150 university students participated in the evaluation of this dataset.
•  This dataset can be further enriched, and some background noise in the dataset can be useful to simulate a more real world scenario, if desired, which 
   otherwise could be removed.

***Warning: this dataset contains audio content that may be disturbing or upsetting. ***
DOI: 10.5281/zenodo.5877711
title: Datasets used on the analysis of Mediterranean Mass mortality events during the 2015-2019 period

description: This upload contains three datasets in CSV files and a PDF file with the specific description of the CSV files. These data was used for the analysis of the mass mortality events reported during the period 2015-2019 across the Mediterranean. The datasets are 1) a CSV file with the data used for the description of the spatial-temporal, depth and biological patterns of mortality observed in the Mediterranean Sea in the 2015-2019 period; 2) a CSV file with the data used to conduct the analyses on the relationship between marine heatwaves (MHW) days found on the surface (averaged per monitored area and year) and the corresponding mass mortality incidence of benthic organisms; 3) a CSV file with the data used to conduct the analyses on the relationship between in-situ MHW days (averaged per monitored area, depth and year) and the corresponding mass mortality incidence. Data were obtained through benthic community field surveys conducted by 33 research teams from 11 Mediterranean countries. Surveys covered thousands of kms of coastline, spanning 13º of latitude (32 °S to 45 °N) and 40º of longitude (-5°W to 35°E) in the Mediterranean Sea. The dataset provides the most updated inventory of mass mortality events records for benthic species between 2015-2019 in the region. The surveys were conducted in 142 monitoring areas. Monitoring areas were considered as geographic areas (10-25 km coastline, e.g., a marine protected area and the nearby coast) sharing common environmental features. In situ temperature conditions datasets base consists of high frequency (hourly) time series obtained using HOBO data loggers (accuracy ± 0.21°C) set-up at standard depths along rocky walls by divers, generally every 5 m from the surface to 40 m depth.This dataset as in the case of the mortality was assembled under the T-MEDNet initiative (www.t-mednet.org). Satellite derived sea surface temperature (SST) across the Mediterranean Sea was obtained from CMEMS (https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=SST_MED_SST_L4_REP_OBSERVATIONS_010_021). The data consists of daily (night-time), gap free, optimally interpolated foundation SST at ~4 km resolution from AVHRR with improved accuracy and stability over the 1982-2019 period
DOI: 10.17632/2bdjn23g69.1
title: Optimization method of temperature measuring point layout for steel-concrete composite bridge based on TLS-IPDP

description: An optimization method of temperature measurement point layout for steel-concrete composite bridges based on the total least squares improved piecewise Douglas-Peucker (TLS-IPDP) algorithm was proposed to solve the problem that the traditional temperature measurement data cannot reflect the actual temperature gradient (TG) due to the distance of measurement points on different paths is not reasonable. The results show that compared with the classical Douglas-Peucker (DP) algorithm, the TLS-IPDP algorithm has a better approximation effect on the original data, and has the function of artificially specifying the location and number of feature points to be retained. Compared with the traditional temperature measuring point arrangement method, the TLS-IPDP algorithm optimized arrangement in this paper realized the measuring point arrangement with different variable spacing under different paths, and the temperature gradient curve obtained was more close to the real temperature distribution, and had higher accuracy in the region with large gradient.
DOI: 10.5281/zenodo.6602408
title: Melt pond from aerial photographs of the Healy–Oden Trans Arctic Expedition (HOTRAX)

description: The dataset contains mapped melt pond zones from aerial photographs which were obtained during helicopter photography flights as part of the Healy–Oden Trans Arctic Expedition (HOTRAX) between 5 August and 30 September 2005. The detection has been done using an original detection algorithm based on machine learning (U-Net). The areas in the images were divided into four classes: sea ice/snow, melt ponds, sub-merged ice and open water. The filenames contain IDs from the original dataset [Perovich et al 2008].
description: This work was supported by the Division of Physics at the U.S. National Science Foundation (NSF) through Grant PHY-2102906
DOI: 10.5281/zenodo.6644499
title: River flows and nutrient discharges to the Atlantic ocean basin

description: This dataset includes i) River flows and ii) nutrient discharges to the Atlantic ocean basin: <strong>River flow</strong> data are a subset of the WaterGAP 2.2d model (Monthly data on a 0.5° x 0.5° grid between 90°N and 60°S. 1901–2016) (Müller Schmied et al. 2020) The original watergap2.2d data is provided in netcdf format. Our postprocessing includes the selection of the coastal cells and the extraction of the monthly values in these cells. The resulting dataset is provided as a shapefile (Global_YearMonthly_River_flow_watermap22_coast.shp), including Date, latitude and longitude of the coastal cell’s centroids and the discharge values (m3s-1). Watergap2.2d outputs offers a very good spatio-temporal extent and resolution, and according to the Müller Schmied et al. 2020, the validation results for streamflow (or discharges values) are reasonably satisfactory, although there is some spatial variability in the performance results. Moreover, the recently published “Global Freshwater Fluxes into the World's Oceans (GRDC, 2021)” product and paper, uses the yearly outcomes of this model, which has also supported our selection. <strong>River nutrient discharges</strong> are a subset of observations from the “Global River Water Quality Archive”. (Virro et al, 2021), that among the publicly available and downloadable datasets, gathers the highest number of observations as includes data from different international and national databases. The GRQA data is provided as csv files (one file for each nutrient). These files have been processed to subset only observations at stations near the coastline. To do this a intersection between station locations and a buffer of 0.2 degrees around the coastline has been made. For each nutrient, a shapefile with the subsetted observations is provided. All shapefiles provided are accompanied by a “.qmd” file that includes metadata information in QGIS 3 format.
description: This dataset has been generated as part of deliverable D3.2 of MISSION ATLANTIC project (https://missionatlantic.eu/ ). Grant Agreement number: 862428 — MISSION ATLANTIC — H2020-BG-2018-2020 / H2020-BG-2019-2.
DOI: 10.5281/zenodo.6644498
title: River flows and nutrient discharges to the Atlantic ocean basin

description: This dataset includes i) River flows and ii) nutrient discharges to the Atlantic ocean basin: <strong>River flow</strong> data are a subset of the WaterGAP 2.2d model (Monthly data on a 0.5° x 0.5° grid between 90°N and 60°S. 1901–2016) (Müller Schmied et al. 2020) The original watergap2.2d data is provided in netcdf format. Our postprocessing includes the selection of the coastal cells and the extraction of the monthly values in these cells. The resulting dataset is provided as a shapefile (Global_YearMonthly_River_flow_watermap22_coast.shp), including Date, latitude and longitude of the coastal cell’s centroids and the discharge values (m3s-1). Watergap2.2d outputs offers a very good spatio-temporal extent and resolution, and according to the Müller Schmied et al. 2020, the validation results for streamflow (or discharges values) are reasonably satisfactory, although there is some spatial variability in the performance results. Moreover, the recently published “Global Freshwater Fluxes into the World's Oceans (GRDC, 2021)” product and paper, uses the yearly outcomes of this model, which has also supported our selection. <strong>River nutrient discharges</strong> are a subset of observations from the “Global River Water Quality Archive”. (Virro et al, 2021), that among the publicly available and downloadable datasets, gathers the highest number of observations as includes data from different international and national databases. The GRQA data is provided as csv files (one file for each nutrient). These files have been processed to subset only observations at stations near the coastline. To do this a intersection between station locations and a buffer of 0.2 degrees around the coastline has been made. For each nutrient, a shapefile with the subsetted observations is provided. All shapefiles provided are accompanied by a “.qmd” file that includes metadata information in QGIS 3 format.
description: This dataset has been generated as part of deliverable D3.2 of MISSION ATLANTIC project (https://missionatlantic.eu/ ). Grant Agreement number: 862428 — MISSION ATLANTIC — H2020-BG-2018-2020 / H2020-BG-2019-2.
DOI: 10.5281/zenodo.6646659
title: Temperature measurements from the SMS Gazelle, Valdivia, and SMS Planet in the Indian Ocean

description: This dataset contains digitized temperature records from the SMS Gazelle (1874–1876), Valdivia (1898–1899), and SMS Planet (1906–1907) observations in the Indian Ocean. The data is described in: Wenegrat, J.O., E. Bonanno, U. Rack, and G. Gebbie, 2022: A century of observed temperature change in the Indian Ocean. <em>Geophys. Res. Letters.</em> doi:10.1029/2022GL098217. Data was digitized from the original cruise reports using independent double-entry, and checked for consistency. A number of observations were discarded due to data problems, as described in Wenegrat et al. 2022 (see also associated code repository doi:10.5281/zenodo.6646645).
description: {"references": ["Wenegrat et al. 2022: A century of observed temperature change in the Indian Ocean. Geophysical Research Letters. doi:10.1029/2022GL098217"]}
DOI: 10.5281/zenodo.6646658
title: Temperature measurements from the SMS Gazelle, Valdivia, and SMS Planet in the Indian Ocean

description: This dataset contains digitized temperature records from the SMS Gazelle (1874–1876), Valdivia (1898–1899), and SMS Planet (1906–1907) observations in the Indian Ocean. The data is described in: Wenegrat, J.O., E. Bonanno, U. Rack, and G. Gebbie, 2022: A century of observed temperature change in the Indian Ocean. <em>Geophys. Res. Letters.</em> doi:10.1029/2022GL098217. Data was digitized from the original cruise reports using independent double-entry, and checked for consistency. A number of observations were discarded due to data problems, as described in Wenegrat et al. 2022 (see also associated code repository doi:10.5281/zenodo.6646645).
description: {"references": ["Wenegrat et al. 2022: A century of observed temperature change in the Indian Ocean. Geophysical Research Letters. doi:10.1029/2022GL098217"]}
DOI: 10.17632/9yyfy6z6fc.1
title: Data for energy security elements and clean energy stock returns: a volatility analysis

description: This data is made up of daily stock prices and commodities' futures of a range of variables including NASDAQ clean focused price index, ARCA technology price index, Brent oil futures, Henry hub natural gas futures, Newcastle coal futures, carbon emission futures and green information technology stock price. The dataset supports empirical analysis which examines the volatility of clean energy stock returns (CERs) given the aggregate influence of energy security elements (ESEs) internal to CERs and the individuals influences of a range of exogenous variables including oil futures, natural gas futures, coal futures, carbon emission futures and green information technology stock price.
DOI: 10.17632/h6k6k37m9r.1
title: Effect Of Chemicals On The Biochar Derived From Textile Waste 

description: In this study, we wanted to draw the attention of scientists to the importance of specific biomass treatments for functional activated carbon preparation. For this, cost-free waste textile materials that could not be reused in the textile industry were pretreated in a controlled manner. The effect of chemical treatment was investigated in terms of SEM, BET, XRD, and FT-IR characterization techniques with the dye removal performances of samples for methyl orange (MO) and industrial wastewater (IW) solution. 
-  Waste textile remnants were converted into functional carbon-rich adsorbents
-  Chemical type, amounts, and carbonization conditions were seen as dominant in material properties
- Recycling waste materials had double outcomes: environmental preservation, and production of fine chemicals by controlled chemical activation of waste textile materials. 25-85 mg/g methyl orange (MO) and industrial textile water (ITW) removal capacity were recorded for all samples.
-  As a result of chemical treatment, an energy-saving method is presented by decreasing the optimum carbonization temperature by 50 °C.
DOI: 10.17632/vszwvv2ytd.1
title: Technical and economic viability of greenfield large scale photovoltaic plants in Romania - Assumptions and supporting data

description: This dataset provides the detailed assumptions and supporting data for the research paper: ”Technical and economic viability of greenfield large scale photovoltaic plants in Romania” 
"Location data.xlsx" - detailed information regarding the analyzed locations - GPS coordinates and global horizontal irradiation
"Module specifications" - Electrical specifications at STC for the modules
"Array configurations.pdf" - Array configuration and row spacing of the fixed tilt and 1-axis tracking system
"Capital and operational costs.xlxs" - Capital costs for solar PV & Operational yearly costs for solar PV
"Revenues modelling.xlxs" - Revenue scenarios modelling
"Results - PR.xlxs" - The solar PV systems PR in the 14 locations across Romania
"Final results" - Study results and data for the graphics
DOI: 10.17632/dy97xr6t8h.1
title: Dataset for Designing extrusion dies on the basis of eXplainable Artificial Intelligence

description: This dataset contains the porthole die data used to develop a design support tool for aluminium extrusion porthole dies based on eXplainable IA. 
The tool is useful for dies with 4 cavities and 4 ports per cavity. 
Dataset includes the geometrical data related to 596 different ports from 88 first-trial 4 cavities and 4 ports per cavity dies. 
In terms of the R² metric and the results obtained with the application examples, the results obtained with this ML-based model are significantly better than those of a previous model based on linear regression. 
It also includes the results and geometries of the FEM simulations performed to validate the model.
DOI: 10.17632/t33njykbvd.1
title: Housing cooperatives' energy actions in the Finnish media 2005-2021

description: A dataset of 312 media articles published in Finnish mainstream media between 1.1.2005 and 31.12.2021. The dataset includes 191 articles on the National Broadcasting Service Yle, 90 articles in the nationally largest coverage newspaper Helsingin Sanomat and 31 articles in the regionally significant newspaper Keskisuomalainen. The data was deemed covering the whole public media discussion on the housing cooperatives' energy action at the time of the searches.

File includes used search parameters for the future use and review of the searches.
DOI: 10.17632/682mmrvgv2.2
title: A study of Therapeutic and Prognostic Potential of GPCRs in Prostate Cancer From Multi-Omics Landscape, Shiqi Li et al.

description: Original data for Figures in "Therapeutic and Prognostic Potential of GPCRs in Prostate Cancer From Multi-Omics Landscape"
DOI: 10.17632/scdw9zjdrm.2
title: Perception of Value from Food Delivery Apps: A Data Report

description: The dataset records consumer perception of value in the context of using FDAs.
DOI: 10.17632/mz9grkwzwn.1
title: Community intervention by Primary Health Care to control an outbreak of COVID19.

description: The community intervention strategy implemented by Primary Health Care to control an outbreak of COVID19 is shown. This was at the Dr Gustavo Aldereguía Lima Teaching Polyclinic in Las Tunas from 07/11/2021 to 10/24/2021.
DOI: 10.17632/dk9s9zrsfc.1
title: Keikhosravi

description: These data belong to Dr. Kikhsravi's thesis entitled Relationship Between Lipoproteins and Bone Metabolic Markers Following High Intensity Interval Training and Genistein Consumption in Elderly Female Rats
DOI: 10.17632/vc8rxy598m.1
title: LFA for CAPA

description: LFA in the diagnosis of CAPA
DOI: 10.17632/9sjd7nmdr8.1
title: HARMONIZING WORK SAFETY AND HEALTH PRACTICES TOWARDS TECHNICIANS PRODUCTIVITY IN THE WORKPLACE: A MODIFIED THEORY OF PLANNED BEHAVIOUR

description: The dataset combines the theory of planned behaviour and safety management as it enhance safety performance
DOI: 10.17632/472ppv29jr.1
title: Draco_2021_2022_fall

description: nAff= (nAff Item 1 + Item 2 + Item 3) / 3
nAch= (nAch Item 1 + Item 2 + Item 3) / 3
nPow= (nPow Item 1 + Item 2 + Item 3) / 3
fAff= (fAff Item 1 + Item 2) / 2
fAch= (fAch Item 1 + Item 2) / 2
fPow= (fPow Item 1 + Item 2) / 2
Mastery= (nAff Item 1 + Item 2 + Item 3) / 3
Performance-apporach= (Performance-approach Item 1 + Item 2 + Item 3) / 3
Performance-avoidance= (Performance-avoidance Item 1 + Item 2 + Item 3) / 3
Interest= (Perceived Interest Item 1 + Item 2 + Item 3) / 3
Competence= (Perceived Competence Item 1 + Item 2 + Item 3) / 3
points= Collected Draco points for each student
user Activity= Total accomplished activities by each student
Course Grade= Final course grade of each student
Loggin= The number of times user log into the Draco System
DOI: 10.17632/p2g5sk8brb.1
title: Synth-Colon

description: Download dataset (41.2 GB): https://enric1994.github.io/synth-colon/

Synth-Colon is a synthetic dataset for polyp segmentation. It is the first dataset generated using zero annotations from medical
professionals. The dataset is composed of 20 000 images with a resolution of 500×500. Synth-Colon additionally includes realistic colon images
generated with our CycleGAN and the Kvasir training set images. Additionally, Synth-Colon can also be used for the colon depth estimation task because it includes depth and 3D information for each image. Synth-Colon includes:

• Synthetic images of the colon and one polyp.
• Masks indicating the location of the polyp.
• Realistic images of the colon and polyps generated using our CycleGAN baseline and the Kvasir dataset.
• Depth images of the colon and polyp.
• 3D meshes of the colon and polyp in OBJ format.

The 3D colon and polyps are procedurally generated using Blender, a 3D engine that can be automated via scripting. Our 3D colon structure is
a cone composed by 2454 faces. Vertices are randomly displaced following a uniform distribution in order to simulate the tissues in the colon.
Additionally, the colon structure is modified by displacing 7 segments. For the textures we used a base color [0.80, 0.13, 0.18] (RGB).
For each sample we shift the color to other tones by adding a 20% of uniform noise to each channel. One single polyp is used on every image,
which is placed inside the colon. It can be either in the colon’s walls or in the middle. Polyps are distorted spheres with 16384 faces. Samples with
polyps occupying less than 2.6% of the image are removed. This results in a dataset average polyp size of 5.87%, which is within the values of the
real datasets: the dataset with the smallest average polyp size is CVC-300 with 3.36% and the largest is Kvasir with 16.46%.
Lighting is composed by a white ambient light, two white dynamic lights that project glare into the walls, and three negative lights that project
black light at the end of the colon. We found that having a dark area at the end helps the generative models to understand the structure of the colon. The 3D scene must be similar to real colon images or the models will not properly translate the images to the real-world domain.

Dataset website: https://enric1994.github.io/synth-colon/
Source code: https://github.com/enric1994/synth-colon