cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/z6s3hyyj87.1
title: Drug dependence and emotional dysregulation

description: About 332 male and female students responded to Substance Dependence Scale (SDS) and Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Descriptive and inferential statistics were used to analyze data. Reported prevalence of psychoactive substances use are 16.9% (alcohol), 7.2% (sedatives), 7.2% (hallucinogens), 3.0% (inhalants), 3.0% (amphetamines), 2.4% (cocaine), 2.0% (cannabis), 2.0% (opioid) and 1.2% (tobacco). The nature of PSD showed that 5.6% are not in control of their psychoactive substance use, 27.2% are anxious on missing doses, 9.4% are worried about their substance use. 22.8% wish they could stop the use of illicit drugs while 5.0% find it difficult to abstain from drugs. In all, 21.7% and 7.2% of participants reported mild – moderate - severe PSD, respectively. Significant gender influence was observed on PSD, with male reporting higher mean score than female students. No significant mean score difference was found in PSD of secondary and tertiary education students.
DOI: 10.17632/z6s3hyyj87.2
title: Drug dependence and emotional dysregulation

description: About 332 male and female students responded to Substance Dependence Scale (SDS) and Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Descriptive and inferential statistics were used to analyze data. Reported prevalence of psychoactive substances use are 16.9% (alcohol), 7.2% (sedatives), 7.2% (hallucinogens), 3.0% (inhalants), 3.0% (amphetamines), 2.4% (cocaine), 2.0% (cannabis), 2.0% (opioid) and 1.2% (tobacco). The nature of PSD showed that 5.6% are not in control of their psychoactive substance use, 27.2% are anxious on missing doses, 9.4% are worried about their substance use. 22.8% wish they could stop the use of illicit drugs while 5.0% find it difficult to abstain from drugs. In all, 21.7% and 7.2% of participants reported mild – moderate - severe PSD, respectively. Significant gender influence was observed on PSD, with male reporting higher mean score than female students. No significant mean score difference was found in PSD of secondary and tertiary education students.
DOI: 10.17632/vxwmtsdg8t.1
title: IELTS Score recaps_raw data

description: This file contains scores of 9816 participants
DOI: 10.17632/fw8vch8rch.1
title: Supporting Dataset Ohmic Charging

description: This dataset contains a COMSOL model file for modeling capacitive deionization (CDI) with capacitive spacers.
DOI: 10.17632/vfzjzdnh9h.1
title: Depression level estimation during covid 19

description: This Dataset presents data for the estimation of depression level estimation based in factor psychological and life experiences during and after pandemic Covid-19. The data contains 31 attributes and 2953 records, the records are labelled with the class variable Normal and Anormal that indicate the respective level of depression. 33% of the data was generated synthetically using the Weka tool and the SMOTE filter, 66% of the data was collected directly from users through a web platform. This data can be used to generate intelligent computational tools to identify the depression level of an individual and to build recommender systems that monitor depression levels.
DOI: 10.17632/vfzjzdnh9h.2
title: Depression level estimation during covid 19

description: This Dataset presents data for the estimation of depression level estimation based in factor psychological and life experiences during and after pandemic Covid-19. The data contains 31 attributes and 2953 records, the records are labelled with the class variable Normal and Anormal that indicate the respective level of depression. 33% of the data was generated synthetically using the Weka tool and the SMOTE filter, 66% of the data was collected directly from users through a web platform. This data can be used to generate intelligent computational tools to identify the depression level of an individual and to build recommender systems that monitor depression levels.
DOI: 10.17632/p2yhyx7335.1
title: Ground Based SAR Data for Classification - 9 Objects in the Near Distance

description: GBSAR parameters
The dataset consists of 267 raw Ground Based SAR (GBSAR) measurements obtained with GBSAR-Pi [1]. 
GBSAR-Pi works in stop-and-go mode. GBSAR sensor is FMCW (Frequency Modulated Continuous Wave) radar with central frequency at 24 GHz. Total GBSAR aperture is 20 cm with 0.5 cm step size (40 steps).  FMCW radar periodically transmits sawtooth signal every 155 ms. Wave polarization of FMCW radar is set to vertical.

Classes
There are 4 aluminum objects, 3 glass, and 2 plastic objects with different shapes and sizes. The objects were distanced approximately 30 cm from the radar. 

Naming:
Each of the test objects used in the measurements represent one class. Therefore, there are 9 classes in total. Class naming is based on the material of the object and its size in a way that A4 is bigger than A1, but both of them are made from aluminum. 

Number of data points per class:
A1 - 27
A2 - 29
A3 - 28
A4 - 30
G1 - 35
G2 - 33
G3 - 29
P1 - 28
P2 - 28


Data format
GBSAR matrices are given in .npy format. The dimensions of the matrices are 40x1024 (40 GBSAR steps x 1024 FMCW frequency points).



This work was supported in part by Croatian Science Foundation (HRZZ) under the project number IP-2019-04-1064.

[1]  Kačan M, Turčinović F, Bojanjac D, Bosiljevac M. Deep Learning Approach for Object Classification on Raw and Reconstructed GBSAR Data. Remote Sensing. 2022; 14(22):5673. https://doi.org/10.3390/rs14225673
DOI: 10.17632/gdxnvcxhw3.1
title: Restaurant-Cafe Surabaya

description: This data is related to the spatial distribution study of restaurants and cafes in Surabaya City. There are two operational data: 1) spatial data in *shp, shx, prj, cpg, qpj, dbf format, which can be opened using GIS software; and 2) statistical data in *omv format, opened using Jamovi software.
DOI: 10.17632/d5g5f78hcm.1
title: Laser-Induced Transient Conversion of Rhodochrosite/Polyimide into Multifunctional MnO2/Graphene Electrodes for Energy Storage Applications

description: The origin data for this manuscript.
DOI: 10.5281/zenodo.5669484
title: Activity of antioxidant enzymes and lipid peroxidation of soybean plants treated with five Diaporthe species

description: Absorbance data from spectrophotometric measurements of catalase, reduced glutathion, lipid peroxidation and superoxide-dismutase of soybean cv. Sava plants infected with five <em>Diaporthe</em> species (i.e. <em>D. aspalathi</em>, <em>D. caulivora</em>, <em>D. eres</em>, <em>D. gulyae</em>, <em>D. longicolla</em>). Supplementary data to the publication Petrovic et al. (2023) The biochemical response of soybean cultivars infected by <em>Diaporthe</em> species complex. Plants 12, 2896. https://doi.org/10.3390/plants12162896
DOI: 10.17632/r6ddtmwxw9.1
title: Breakup length and droplet size of distilled water and Surfactin sprayed droplets in flat fan, full cone, and low energy precision application (LEPA) bubbler nozzles

description: The objective of this work was to investigate the effects on spray dynamics of adding Surfactin to distilled water; four fan nozzles (F1-F4), one cone nozzle, and three bubbler (B1-3) nozzles were investigated at various pressure s. Twenty images were recorded for each nozzle, pressure, and spray solution (distilled water and surfactant solution) and analyzed for breakup length, droplet sizes, spray angle in the fan and cone nozzles, and ligament diameter in the bubbler nozzles. This data set provides each image's pressure, mass flow rate, and ambient relative humidity. For the fan and cone nozzle, it provides the volumetric mean diameter  (D_V50), breakup length, and spray angle for each image. For the bubbler nozzle, it provides droplet diameter, breakup length, and ligament diameter from images. Data used in Stallbaumer-Cyr, E.M. Identifying droplet boundaries: impacts of surface topography on droplet freezing and investigation of Surfactin on spraying dynamics (https://krex.k-state.edu/handle/2097/42990).
DOI: 10.5281/zenodo.5669483
title: Activity of antioxidant enzymes and lipid peroxidation of soybean plants treated with five Diaporthe species

description: Absorbance data from spectrophotometric measurements of catalase, reduced glutathion, lipid peroxidation and superoxide-dismutase of soybean cv. Sava plants infected with five <em>Diaporthe</em> species (i.e. <em>D. aspalathi</em>, <em>D. caulivora</em>, <em>D. eres</em>, <em>D. gulyae</em>, <em>D. longicolla</em>). Supplementary data to the publication Petrovic et al. (2023) The biochemical response of soybean cultivars infected by <em>Diaporthe</em> species complex. Plants 12, 2896. https://doi.org/10.3390/plants12162896
DOI: 10.17632/r6ygd7t9ry.1
title: Nutrition Knowledge and Practice of Irish Male and Female Soccer Players

description: Nutrition Knowledge and Practice of Irish Male and Female Soccer Players - Dean Morgan, Data
DOI: 10.17632/7x6dk5mt53.1
title: Relation between mixing and plume geometry in porous media under highly transient flow fields

description: Highly transient boundary conditions affect mixing processes in porous media. An example these boundaries is the case of fluctuating rivers that are in contact with the aquifer. Here we apply flow-through experiments to study the relation between mixing and plume geometry under such transient boundary coditions, using experimental data and simulation results. This dataset contains information to reproduce the following figures:

Figures 3 and 4 (data_Figs_3_4.mat): Concentration distibution of the tracer under transient flow conditions.
Figure 5 (data_Fig_5.mat):  Observed and simulated breakthrough curves for the transient flow.
Figure 6 (data_Fig_6.mat): Vertical profiles for the transient flow.
Figures 7 and 8 (data_Figs_7_8.mat): Dilution index, perimeter and area.
Figure 9 (data_Fig_9.mat): Maps of flux components. 
Figure 10 (data_Fig_10.mat): Spatially averaged flux components.
DOI: 10.17632/7x6dk5mt53.2
title: Relation between mixing and plume geometry in porous media under highly transient flow fields

description: Highly transient boundary conditions affect mixing processes in porous media. An example these boundaries is the case of fluctuating rivers that are in contact with the aquifer. Here we apply flow-through experiments to study the relation between mixing and plume geometry under such transient boundary coditions, using experimental data and simulation results.  The transport simulations are performed with a modified version of the MT3D-USGS (Bedekar et al., 2016), in which we implement a non-linear velocity-dependent dispersion parametrization.

This dataset contains the following files: 

data_Figs_3_4.mat          Data for Figures 3 and 4. Concentration distibution of the tracer under transient flow conditions.
data_Fig_5.mat                Data for Figure 5. Observed and simulated breakthrough curves for the transient flow.
data_Fig_6.mat                Data for Figure 6. Vertical profiles for the transient flow.
data_Figs_7_8.mat          Data for Figures 7 and 8. Dilution index, perimeter and area.
data_Fig_9.mat                Data for Figures 7 and 8. Maps of flux components. 
data_Fig_10.mat              Data for Figure 10. Spatially averaged flux components.
mt_dsp5_modified.for     Modified version of the dispersion code of MT3D-USGS  with non-linear velocity-dependent parametrization

The original source code of MT3D-USGS can be found in https://github.com/MODFLOW-USGS/mt3d-usgs

References:
Bedekar, V., Morway, E.D., Langevin, C.D., and Tonkin, M., 2016, MT3D-USGS version 1.0.0: Groundwater Solute Transport Simulator for MODFLOW: U.S. Geological Survey Software Release, 30 September 2016, http://dx.doi.org/10.5066/F75T3HKD
DOI: 10.17632/7x6dk5mt53.3
title: Evolution of plume geometry, dilution and reactive mixing in porous media under highly transient flow fields at the surface water-groundwater interface

description: Highly transient boundary conditions affect mixing processes in porous media. An example these boundaries is the case of fluctuating rivers that are in contact with the aquifer. Here we apply flow-through experiments to study the evolution of plume geometry, dilution and mixing under such transient boundary coditions, using experimental data and simulation results.  The transport simulations are performed with a modified version of the MT3D-USGS (Bedekar et al., 2016), in which we implement a non-linear velocity-dependent dispersion parametrization.

This dataset contains the following files: 

data_Figs_3_4.mat          Data for Figures 3 and 4. Concentration distibution of the tracer under transient flow conditions.
data_Fig_5.mat                Data for Figure 5. Observed and simulated breakthrough curves for the transient flow.
data_Fig_6.mat                Data for Figure 6. Vertical profiles for the transient flow.
data_Figs_7_8.mat          Data for Figures 7 and 8. Dilution index, perimeter and area.
data_Fig_9.mat                Data for Figure 9. Dilution index fand critical dilution index for different mixing ratios.
mt_dsp5_modified.for     Modified version of the dispersion code of MT3D-USGS  with non-linear velocity-dependent parametrization

The original source code of MT3D-USGS can be found in https://github.com/MODFLOW-USGS/mt3d-usgs

References:
Bedekar, V., Morway, E.D., Langevin, C.D., and Tonkin, M., 2016, MT3D-USGS version 1.0.0: Groundwater Solute Transport Simulator for MODFLOW: U.S. Geological Survey Software Release, 30 September 2016, http://dx.doi.org/10.5066/F75T3HKD
DOI: 10.17632/fk9nv9k3t8.1
title: Automatic Detection and Recognition Method of Chinese Clay Tiles Based on YOLOv4: A Case Study in Macau(Training set for machine learning)

description: This dataset is related to the paper "Automatic Detection and Recognition Method of Chinese Clay Tiles Based on YOLOv4: A Case Study in Macau". For detailed usage, please refer to our research paper.
DOI: 10.17632/94kr6ctvcy.1
title: Scale Development of Willingness to Utilize Primary Care Services

description: Pilot Study and Formal Study data
Personal information has been deleted
DOI: 10.17617/4.di
title: A single methyl group drastically changes urea’s hydration dynamics

description: Marekha, B. A., & Hunger, J. (2022). A single methyl group drastically changes urea’s hydration dynamics. The Journal of Chemical Physics, 156(16): 164504. doi:10.1063/5.0085461.
DOI: 10.17632/n6dby9gynn.1
title: RTEII: A new high-resolution (0.1° × 0.1°) road transport emission inventory for India

description: This dataset presents gridded road transport emissions based on the new road transport emission inventory for India (RTEII) in g /year on a 0.1° × 0.1° map of India for all the species that are part of the T1-MOZART chemical mechanism and used in chemical transport models. The species included for the first time are 76 speciated VOCs, CH4, CO2, and CO compiled using in-situ measured emission factors for varied fuels and vehicle technologies. It also includes PM2.5 and PM10 and NH3 and CO and NOx , BC emissions using updated activity data for the year 2015. The dataset is provided in tab-delimited and netcdf formats: Two files for all species that are part of the T1-MOZART chemical mechanism in both tab delimited and netcdf format and two files for all NMVOCs that are not in the T1-MOZART but reported by Hakkim et al., 2021, including nitromethane.
DOI: 10.17632/n6dby9gynn.2
title: RTEII: A new high-resolution (0.1° × 0.1°) road transport emission inventory for India

description: This dataset presents gridded road transport emissions based on the new road transport emission inventory for India (RTEII) in g /year on a 0.1° × 0.1° map of India for all the species that are part of the T1-MOZART chemical mechanism and used in chemical transport models. The species included for the first time are 76 speciated VOCs, CH4, CO2, and CO compiled using in-situ measured emission factors for varied fuels and vehicle technologies. It also includes PM2.5 and PM10 and NH3 and CO and NOx , BC emissions using updated activity data for the year 2015. The dataset is provided in tab-delimited and netcdf formats: Two files for all species that are part of the T1-MOZART chemical mechanism in both tab delimited and netcdf format and two files for all NMVOCs that are not in the T1-MOZART but reported by Hakkim et al., 2021, including nitromethane.
DOI: 10.17632/gfjwf6yjhs.1
title: Simulation of the Moving Boundary during Freezing of a Finite One-Dimensional Food Slab.

description: This project presents moving boundary data obtained through numerical simulation of the freezing process of a finite moist-food slab. The synthetic position-time data accounts for the impact of the temperature-dependent effective heat capacity and thermal conductivity, constant density, the cooling medium temperature and the Biot number on the moving boundary.
DOI: 10.17632/8jrbh6rgmx.1
title: Newborn and child-like molecular signatures in elderly stem from TCR shifts across the human lifespan. van de Sandt et. al.

description: The files in this data repository contain the T cell receptor sequences described in the following study:

Newborn and child-like molecular signatures in elderly stem from TCR shifts across the human lifespan. Nature Immunology, 2023.
Carolien E van de Sandt, Thi H O Nguyen, Nicholas A Gherardin, Jeremy Chase Crawford, Jerome Samir, Anastasia A Minervina, Mikhail V Pogorelyy, Simone Rizzetto, Christopher Szeto, Jasveen Kaur, Nicole Ranson, Sabrina Sonda, Alice Harper, Samuel J Redmond, Hayley A McQuilten, Tejas Menon, Sneha Sant, Xiaoxiao Jia, Kate Pedrina, Theo Karapanagiotidis, Natalie Cain, Suellen Nicholson, Zhenjun Chen, Ratana Lim, E Bridie Clemens, Auda Eltahla, Nicole L La Gruta, Jane Crowe, Martha Lappas, Jamie Rossjohn, Dale I Godfrey, Paul G Thomas, Stephanie Gras, Katie L Flanagan, Fabio Luciani and Katherine Kedzierska.
DOI: 10.17632/x85xwjky6n.1
title: Estrés y carga laboral del personal de enfermería en Ecuador durante el Covid-19

description: La población investigada fue de 240 profesionales de enfermería que brindaron cuidados y atención, a pacientes contagiados por coronavirus, en las unidades de Cuidados Intensivos (UCI), Medicina Interna y Emergencia, quienes aceptaron voluntariamente participar, de acuerdo con los criterios de inclusión y exclusión determinados en la investigación, mediante el respectivo consentimiento informado. 
Para el procesamiento de datos se utilizaron herramientas de recolección en línea (QuestionPro y Jotform), que permiten definir las características sociodemográficos;  los niveles de carga laboral y estrés se determinaron aplicando la escala  de carga de trabajo en enfermería (NAS del inglés: Nursing Activity Score) y la escala de estresores en enfermería  (NSS del inglés: Nursing Stress Scale), consideradas, actualmente como las  más importantes para evaluar el nivel de carga de trabajo en el profesional de enfermería que labora en la asistencia y las actividades realizadas en el cuidado del paciente
DOI: 10.17632/fs4t47smm2.1
title: Anchoring as a mechanism for modifying risk-taking behavior in BART-type tasks

description: This study was designed to examine the possibility of using anchor bias in changing risk-taking behavior in BART-type tasks. The study involved 90 participants organized in three experimental groups in which the subjects go through BART-type tasks in which the combination of balloons changes in such a way as to induce the anchoring effect.
For this research, we formulated the following hypotheses :
	H 1: Anchoring mechanisms operate in both uncertainty and risk conditions, and this mechanism can influence the level of risk-taking;
	H 2: Impulsivity acts on the risk-taking behavior in all stages of the experiment;
	H 3.1: Between the results of the BART sample and variables demographic: age, type of function, the risk associated to function, and number of missions doing into a TO, are significant association;
	H 3.2: There are significant associations between the results of the BART test and the variables of personality and impulsivity;
	H 4: Risk-taking behavior remains constant high or low during the three stages.
DOI: 10.17632/fs4t47smm2.2
title: Anchoring as a mechanism for modifying risk-taking behavior in military aviation

description: This study was designed to examine the possibility of using anchor bias in changing risk-taking behavior in BART-type tasks. The study involved 90 participants organized in three experimental groups in which the subjects go through BART-type tasks in which the combination of balloons changes in such a way as to induce the anchoring effect.
For this research, we formulated the following hypotheses :
	H 1: Anchoring mechanisms operate in both uncertainty and risk conditions, and this mechanism can influence the level of risk-taking;
	H 2: Impulsivity acts on the risk-taking behavior in all stages of the experiment;
	H 3.1: Between the results of the BART sample and variables demographic: age, type of function, the risk associated to function, and number of missions doing into a TO, are significant association;
	H 3.2: There are significant associations between the results of the BART test and the variables of personality and impulsivity;
	H 4: Risk-taking behavior remains constant high or low during the three stages.
DOI: 10.17632/z8btpvd7rk.1
title: Data for: Proteomic landscape of epithelial ovarian cancers 

description: We profiled the proteome of ovarian tissue and plasma samples from 813 patients with five histotypes and therapeutic regimens, covering the expression of 10,715 proteins.
DOI: 10.17632/x44tw4k3yb.1
title: Western blot-Fang Xu

description: WB-1:The expression of PD-1, PD-L1, aCD19 scFv, CD63 and CD9 in EVs and EVs-PD1-aCD19 was determined by Western blot. 
WB-2:The expression of MHCII, CD80, CD63 and CD9 in EVs and EVs-PD1-aCD19 was determined by Western blot after loading with CT26 tumor-associated antigens.
WB-3:CT26 cells and CT26-huCD19 cells were treated with 20 ng/mL IFN γ for 24 h, and the expression of PD-L1 on derived EVs was detected by Western blot .