cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/7rpnpjvk7b.1
title: Daily Rainfall data from 1 July 2016 to 30 June 2018 and from 1 Jan. 2019 to 31 Dec. 2020

description: The zip file includes rainfall.xlsx and ReadMe.txt. The words in the cells of the first row in the excel sheet indicate the meaning of individual columns. The data were downloaded from CWB Observation Data Inquire System (CODiS) and then combined. Note that the rainfall station is called Chihshang station in Taitung County. Here is the CODiS link: https://e-service.cwb.gov.tw/HistoryDataQuery/

Contact:
Huang22@ncu.edu.tw
Wen-Jeng Huang
DOI: 10.17632/4dtzj4hyyj.1
title: The Relationship between Aggression and Sportsmanship in Male Basketball Players: Observational Study

description: Background: Basketball is a team sport which requires skills which includes shooting, offensive rebounding, passing and dribbling. Aggression is a vital trail of aggressive sports activities, and its appearance is inevitable in some sports. In games, aggression is a function that can have many negative as well as fantastic effects on performance. Contact game players had higher levels of aggression, whereas noncontact game players had lower levels of aggression. Sportsmanship is the aspiration or ethos that a sport or hobby could be enjoyed for its own sake. Previous studies show that the aggressive stages of athlete will decrease as their stage of sportsmanship behaviour increases.
Aim: The purpose of this study was to find the relationship between aggression and sportsmanship in male basketball players.
Materials and methods: An observational study was conducted on 74 male basketball players by using purposive sampling. 74 male basketball players, between the age group of 18-25 with experience of 2 years or more were recruited in the study. Buss Perry aggression Questionnaire and the Multidimensional Sportsmanship Orientation Scale were used to assess aggression and sportsmanship, respectively.
Results and Discussion: Spearman’s correlation coefficient test was used to check the relation of aggression and sportsmanship. The mean and standard demographic data are age group [(20.0541±1.85)(in years)], height [(172.308±8.429)(in cm)] , weight [(61.41±7.93)(in kg)], and  body mass index [(20.860±2.352)(in kg\m2 ). The result indicates inverse correlation between aggression and sportsmanship (r = -.266, p<0.02.). The result shows that the correlation is significant at the 0.05 level (2-tailed).
Conclusion: The present study concluded that aggression and sportsmanship show negative relationship with each other.
DOI: 10.17632/7z9y5rxcmz.1
title: ERT data for the survey at Tapo E.S., eastern Taiwan

description: The zip file contains two files: the .urf file for the resistance data and the .trn file for the terrain data. The file format is described in the followings:

A 2D sample Universal Resistivity data File (URF)
Top two lines are comments and the third line defines the length unit.
Unit: meters
;This file is used for illustration of URF file format only.
;Any line starting with a semicolon (;) is a comment line

;A line starting with a colon (:) defines a section header.
;A section header is required and must be spelled correctly.
;A blank line will be ignored
;Data entries are comma-separated.
;Electrode locations are defined with XYZ coordinates.
;Z = 0 on the surface and negative downwards

: Geometry
;ID, X, Y, Z
1, 0.00, 0.00, -18.90
2, 0.00, 0.00, -18.10
3, 0.00, 0.00, -17.30
4, 0.00, 0.00, -16.50
5, 0.00, 0.00, -15.70
6, 0.00, 0.00, -14.90
7, 0.00, 0.00, -14.10
8, 0.00, 0.00, -13.30
9, 0.00, 0.00, -12.50
10, 0.00, 0.00, -11.70
11, 0.00, 0.00, -10.90
12, 0.00, 0.00, -10.10
13, 0.00, 0.00, -9.30
… …

:Measurements
;A, B, M, N, V/I(ohm), I(mA), Error(%), Chargeability(mV/V)
1, 5, 8,12, -0.000025545
2, 6, 9, 13, -0.000025567
… …

; TRN File       // A semicolon (;) starts a comment line
unit=meters      // Unit of distance measure
2                // 1 = horizontal distance is given, 2 = tape measure is given
-1, 0.3            // X, elevation (positive upward)
1.0, -0.3
3.6, -1.2
6.1, -2.7
7.4, -2.3
9.0, -1.3
10.5, -1.0
13.7, -1.5
15.2, -2.5
17.0, -1.0
19.2, -0.2

The terrain file (*.trn) is a comma separated text file that may be created in any text editor such 
as the NotePad.

Contact:
Huang22@ncu.edu.tw
Wen-Jeng Huang


 
 


 

Contact:
Huang22@ncu.edu.tw
Wen-Jeng Huang
DOI: 10.17632/68b58cpdcy.1
title: Predictions of transcription factor binding sites of JA-, ABA-, SA- and Ethylene pathway genes in Arabidopsis thaliana 

description: Plant physiological processes are under the strong regulation of the phytohormone signaling network. Phytohormones are derivatives of primary and secondary metabolism, like salicylic acid, ethylene, jasmonic acid, and abscisic acid. The regulation of plant stress responses, adaptation to the environment, growth, or differentiation depend on the synthesis, transport, expression, and transcription control of genes and their regulatory proteins involved in these pathways. Therefore, we collected and grouped the all-possible transcription factors (TFs) and their predicted promoter binding sites of 35 genes that regulate these four pathways. This data presents the lists of TFs of the investigated key genes and their promoter specificity data queried from the EPDnew database using two probability P values in A. thaliana model plant.
DOI: 10.17632/87znj6hptk.1
title: DATASET: Melanin-based plumage coloration is associated with exposure in tawny owls under novel conditions

description: Dataset associated with paper Melanin-based plumage coloration is associated with exposure in tawny owls under novel conditions
DOI: 10.17632/9zpr58m5vh.1
title: Effect of physical therapy on sleep pattern with chronic low back pain

description: Chronic low back pain (CLBP) is a common condition that often leads to disrupted sleep patterns and reduced quality of life. Physical therapy has been proposed as a potential intervention to alleviate CLBP and improve sleep quality. To determine the long-term advantages of physical therapy interventions on sleep patterns in this population, more research with bigger sample numbers and longer follow-up periods is required.
DOI: 10.17632/b5gkch4msv.1
title: Dynamic Cupping vs MFR on MTPs in calf pain

description: This study is performed to compare the effectiveness of Dynamic cupping and MFR on MTPs in chronic calf pain
DOI: 10.17632/g54hj4cf3j.1
title: The Effects of a Laparoscopy by Single-Port Endoscopic Access in Benign Adnexal Surgery: A Randomized Controlled Trial

description: Prospective data about patients included and outcomes, collected during the clinical study.
DOI: 10.17632/rpx2d6nbvk.1
title: Turkish Women's NGOs and State Relations

description: This is a dataset of survey research conducted with women's NGOs from Ankara and İstanbul, Turkey. The questions focus on demographic questions as well as questions on cooperation perception of members of women's NGOs.
DOI: 10.17632/5btczp897z.1
title: Fluorescence microscopy-based assay assessing regulatory mechanisms of global genome nucleotide excision repair in cultured cells. Kusakabe et al.

description: The datasets of fluorescence images used for image analyses were deposited.
DOI: 10.5281/zenodo.7933200
title: Nitrogen trade between plants that differ in their temporal demand of nutrients

description: Primary data and to reproduce the analyses reported in the publication: Data S1 to S12 [Land_sp_feno2_18, Land_sp_feno2_19, Mypatches, Res2, PhenoWC2, INtran, INenrich, Npheno, Temp_var_pheno_N, land, phenoind, avgWC]. A description of each item is provided in the file Metadata_Readme.doc included in the zip.file deposited <br>
DOI: 10.5281/zenodo.7933199
title: Nitrogen trade between plants that differ in their temporal demand of nutrients

description: Primary data and to reproduce the analyses reported in the publication: Data S1 to S12 [Land_sp_feno2_18, Land_sp_feno2_19, Mypatches, Res2, PhenoWC2, INtran, INenrich, Npheno, Temp_var_pheno_N, land, phenoind, avgWC]. A description of each item is provided in the file Metadata_Readme.doc included in the zip.file deposited <br>
DOI: 10.34740/kaggle/dsv/5772558
title: 2021 World Population (updated daily)
DOI: 10.34740/kaggle/dsv/5772560
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.23182622
title: Code and questionnaire used in the analysis for Exploring the Effectiveness of Stack Overflow for PyTorch: An Empirical Analysis of Question-Answer Dynamics.

description: This archive contains the jupyternotebook files used for the data analysis of PyTorch questions on Stack Overflow. Additionally, it contains a questionnaire which was written but not used.
DOI: 10.6084/m9.figshare.23182622.v1
title: Code and questionnaire used in the analysis for Exploring the Effectiveness of Stack Overflow for PyTorch: An Empirical Analysis of Question-Answer Dynamics.

description: This archive contains the jupyternotebook files used for the data analysis of PyTorch questions on Stack Overflow. Additionally, it contains a questionnaire which was written but not used.
DOI: 10.57745/s8sbtl
title: ControlledVocabularyRest.zip

description: :unav
DOI: 10.57745/hdwt8f
title: SicpaOpenData-for-dotNet.zip

description: :unav
DOI: 10.57745/njxzct
title: SicpaOpenData-for-java.zip

description: :unav
DOI: 10.57745/wdpgw9
title: SicpaOpenData-for-php.zip

description: :unav
DOI: 10.57745/afzoi2
title: SicpaOpenData-for-python.zip

description: :unav
DOI: 10.21942/uva.23180807.v1
title: Corpus study on polar questions in Sign Language of the Netherlands - Annotation files

description: These are ELAN annotation files of polar questions in the Corpus NGT, created by Marleen Gaasbeek as part of her MSc thesis project. Her thesis described the method used, and provides an analysis of polar questions in NGT based on these annotations.
DOI: 10.17894/ucph.b594b3f5-6660-4517-8d0c-bc2ed7ad00f5
title: FWB Lobelia dortmanna 2023
DOI: 10.5281/zenodo.7970596
title: image classification dataset on tailored textiles quality control

description: This dataset was geared towards representing practical quality control scenarios, specifically involving the quality inspection of glass fiber fabric. Continuous rolls of glass fiber fabric were cut into samples of 300x200 mm. Half of these samples were reinforced with a single carbon fiber. These samples were then classified into six different categories based on the presence of common defects or if they were error-free textiles. Each category consists of 300 images, with a resolution of 4288x2848 pixels.
DOI: 10.5281/zenodo.7970595
title: image classification dataset on tailored textiles quality control

description: This dataset was geared towards representing practical quality control scenarios, specifically involving the quality inspection of glass fiber fabric. Continuous rolls of glass fiber fabric were cut into samples of 300x200 mm. Half of these samples were reinforced with a single carbon fiber. These samples were then classified into six different categories based on the presence of common defects or if they were error-free textiles. Each category consists of 300 images, with a resolution of 4288x2848 pixels.
DOI: 10.5281/zenodo.7970490
title: image classification dataset on carbon fiber reinforcement quality control

description: Image classification dataset on carbon fiber quality control. To represent a practical quality control problem, a dataset was generated using carbon plain weave with a grammage of 200g/m². Pieces of the weave, measuring 300x300 mm², were cut using a CNC cutter table. Two such pieces were stacked, with a binder applied between them for shape stability after the forming process. The formed stacks were then scanned using a high-resolution camera mounted on a robotic arm, resulting in 500 images of the textiles' surfaces in three-dimensional shape. The images were then cropped to 341x384 pixels patches and transformed to grayscale. Each patch was classified into one of three classes: normal textile, gap, or fold. Images that were blurred, out of focus, or had bad contrast were sorted out. The dataset has not yet been released, and will be available upon the acceptance of the document.
DOI: 10.5281/zenodo.7970489
title: image classification dataset on carbon fiber reinforcement quality control

description: Image classification dataset on carbon fiber quality control. To represent a practical quality control problem, a dataset was generated using carbon plain weave with a grammage of 200g/m². Pieces of the weave, measuring 300x300 mm², were cut using a CNC cutter table. Two such pieces were stacked, with a binder applied between them for shape stability after the forming process. The formed stacks were then scanned using a high-resolution camera mounted on a robotic arm, resulting in 500 images of the textiles' surfaces in three-dimensional shape. The images were then cropped to 341x384 pixels patches and transformed to grayscale. Each patch was classified into one of three classes: normal textile, gap, or fold. Images that were blurred, out of focus, or had bad contrast were sorted out. The dataset has not yet been released, and will be available upon the acceptance of the document.
DOI: 10.5281/zenodo.7970466
title: Spatio-temporal Dynamics of Coworking Spaces Development: The Case of Selected Central European Capitals

description: The dataset provides geolocation coordinates and years of activity of coworking spaces in the selected Central European capitals - Bratislava, Budapest, Prague, and Warsaw.
description: Acknowledgements This work was supported by: the Ministry of Education, Youth and Sports, Czech Republic, programme INTER- EXCELLENCE, subprogramme INTER-COST, under Grant No. LTC20047 'Regional development and public policy under creative economy: Mapping, knowledge sharing and management of New Working Spaces in the Czech Republic'; the Polish National Science Centre under the PRELUDIUM BIS 1 scheme, under Grant No. 2019/35/O/HS4/00861; the Ministry of Education, Science, Research and Sport of the Slovak Republic, VEGA Foundation under Grant No. 1/0249/22; COST Action under the Grant No. CA18214 'The geography of New Working Spaces and the impact on the periphery', which is funded by the Horizon 2020 Framework programme of the European Union (project website: http://www.new-working-spaces.eu/; European Union Website: https://www.cost.eu/actions/CA18214).
DOI: 10.5281/zenodo.7970465
title: Spatio-temporal Dynamics of Coworking Spaces Development: The Case of Selected Central European Capitals

description: The dataset provides geolocation coordinates and years of activity of coworking spaces in the selected Central European capitals - Bratislava, Budapest, Prague, and Warsaw.
description: Acknowledgements This work was supported by: the Ministry of Education, Youth and Sports, Czech Republic, programme INTER- EXCELLENCE, subprogramme INTER-COST, under Grant No. LTC20047 'Regional development and public policy under creative economy: Mapping, knowledge sharing and management of New Working Spaces in the Czech Republic'; the Polish National Science Centre under the PRELUDIUM BIS 1 scheme, under Grant No. 2019/35/O/HS4/00861; the Ministry of Education, Science, Research and Sport of the Slovak Republic, VEGA Foundation under Grant No. 1/0249/22; COST Action under the Grant No. CA18214 'The geography of New Working Spaces and the impact on the periphery', which is funded by the Horizon 2020 Framework programme of the European Union (project website: http://www.new-working-spaces.eu/; European Union Website: https://www.cost.eu/actions/CA18214).
DOI: 10.5281/zenodo.7970574
title: DataSet for "Hybrid Based on Phenazine Conjugated Microporous Polymer as a High-Performance Organic Electrode in Aqueous Electrolytes"

description: All raw data were obtained directly by the instruments and were then elaborated by us using Origin and/or Excel. All the facilities used, except for the NMR measurements, are present in IMDEA Energy Institute <br> <br>
description: Information about funding sources or sponsorship that supported the collection of the data: European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement (Grant No 860403), Spanish Government; MCIN/AEI/10.13039/501100011033/FEDER "A way of making Europe" (PID2021-124974OB−C21 and PID2019-106315RB−I00) for the funding. N. P. appreciates fellowship IJC2020-043076-I−I funded by MCIN/AEI/0.13039/501100011033 and by the European Union NextGenerationEU/PRTR A. M. thanks the TALENTO grant (2021-5 A/AMB-20946) from Comunidad de Madrid
DOI: 10.5281/zenodo.7970573
title: DataSet for "Hybrid Based on Phenazine Conjugated Microporous Polymer as a High-Performance Organic Electrode in Aqueous Electrolytes"

description: All raw data were obtained directly by the instruments and were then elaborated by us using Origin and/or Excel. All the facilities used, except for the NMR measurements, are present in IMDEA Energy Institute <br> <br>
description: Information about funding sources or sponsorship that supported the collection of the data: European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant agreement (Grant No 860403), Spanish Government; MCIN/AEI/10.13039/501100011033/FEDER "A way of making Europe" (PID2021-124974OB−C21 and PID2019-106315RB−I00) for the funding. N. P. appreciates fellowship IJC2020-043076-I−I funded by MCIN/AEI/0.13039/501100011033 and by the European Union NextGenerationEU/PRTR A. M. thanks the TALENTO grant (2021-5 A/AMB-20946) from Comunidad de Madrid
DOI: 10.25625/onubev/1uu2fb
title: DTM_area2_UTM48S_ellipsoidal.tif

description: :unav
DOI: 10.25625/onubev/jxak5q
title: DTM_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/dnhavs
title: DTM_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/himgnk
title: DTM_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/klqh4q
title: DTM_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/goqzrr
title: DTM_area3_UTM48S_ellipsoidal.tif

description: :unav
DOI: 10.25625/onubev/0voxia
title: DTM_area1_UTM48S_ellipsoidal.tif

description: :unav
DOI: 10.25625/onubev/3cknsb
title: DTM_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/r9ccsh
title: DTM_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/wnr15o
title: Slope_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/cpwlva
title: curvature_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/5snmix
title: curvature_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/k8xfpt
title: profile_curvature_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/rtz0zd
title: TPI_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/rgskpl
title: Aspect_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/gpbzxs
title: flowacc_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/tuxbco
title: plan_curvature_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/dvmj2c
title: Slope_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/kfsrev
title: flowacc_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/5hiszy
title: Aspect_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/pohqps
title: TPI_area1_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/1heakt
title: plan_curvature_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/p5kk7x
title: profile_curvature_area1_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/p8cdqg
title: TPI_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/3nylfh
title: plan_curvature_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/ryxyx6
title: Aspect_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/7uvums
title: profile_curvature_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/sriy4a
title: curvature_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/gkq8iv
title: Aspect_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/44achf
title: TPI_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/iuwf0q
title: Slope_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/160gqx
title: curvature_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/fmhafw
title: flowacc_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/xnpxls
title: plan_curvature_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/kvownu
title: profile_curvature_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/ghj01r
title: flowacc_area2_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/4csk8l
title: Slope_area2_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/avce78
title: Slope_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/pujnpt
title: Aspect_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/2ymaro
title: profile_curvature_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/bb3vwe
title: curvature_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/fqklvu
title: TPI_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/qwdzpz
title: TPI_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/xg6dgv
title: flowacc_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/qjg3fh
title: plan_curvature_area3_UTM48S_ellipsoidal_10m.tif

description: :unav
DOI: 10.25625/onubev/fkea81
title: curvature_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/jzqrjm
title: Slope_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/xipkgo
title: Aspect_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/ngxiy1
title: plan_curvature_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev/pd3swt
title: profile_curvature_area3_UTM48S_ellipsoidal_50m.tif

description: :unav
DOI: 10.25625/onubev
title: Digital Terrain Models elevation metrics from acquisition in 2022

description: Digital Terrain Models (DTMs), Slope, Aspect, Topographic Position Index (TPI), curvature in profile and plan direction and their average, and flow accumulation derived from airborne LiDAR data acquired over the Bukit Duabelas, Batanghari regency and Harapan rainforest protected area, in Jambi, Sumatra, Indonesia. Slope, aspect, curvatures, flow accumulation and TPI were calculated following a two-step approach where first the DTM was resampled to 10 m pixel size and then the metrics were calculated and further aggregated to 50 m (see also Jucker et al. 2018 https://doi.org/10.1111/gcb.14415). Original pixel size of DTM: 1m. Geographic Coordinate System: EPSG 32748.
DOI: 10.25625/onubev/bs4sqd
title: flowacc_area3_UTM48S_ellipsoidal_50m.tif

description: :unav