cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3631137
title: DataSetSubstitutionStudyBelgiumDeconincketal

description: Dataset containing samples (pseudonymized) gathered to assess substitution fraud in the Belgian fishing supply chain from the paper: <strong>A high-quality genetic reference database for European commercial fishes reveals substitution fraud of processed Atlantic cod (<em>Gadus morhua</em>) and common sole (<em>Solea solea</em>) at different steps in the Belgian supply chain</strong>
DOI: 10.3886/e143001
title: Study of Importance of Male Body Features to Americans and South Koreans

description: This study sought to examine cultural similarities and differences in the ways in which American and South Korean university students in the US engage with male body ideals. Using cultural domain analysis, cultural consensus analysis, and residual agreement analysis, these data suggest that Americans and South Koreans evaluate male bodies in distinct ways owing to particular histories and philosophies of male bodies.
DOI: 10.3886/e143001v1
title: Study of Importance of Male Body Features to Americans and South Koreans

description: This study sought to examine cultural similarities and differences in the ways in which American and South Korean university students in the US engage with male body ideals. Using cultural domain analysis, cultural consensus analysis, and residual agreement analysis, these data suggest that Americans and South Koreans evaluate male bodies in distinct ways owing to particular histories and philosophies of male bodies.
DOI: 10.6084/m9.figshare.14785275.v1
title: Table 2 Full Characteristics of Included Reviews

description: Full Characteristics of Included Reviews in Teacher Digital Competence Overview.
DOI: 10.5517/ccdc.csd.cc266c0t
title: CCDC 2031895: Experimental Crystal Structure Determination

description: Related Article: Zhao Chen, Peng Tao, Yujia Cai, Yuanjie Ma, Lei Huang, Jun Luo, Lei Wang, Yongli Zhao|2021|J.Mol.Struct.|1243|130783|doi:10.1016/j.molstruc.2021.130783
DOI: 10.6084/m9.figshare.14785275
title: Table 2 Full Characteristics of Included Reviews

description: Full Characteristics of Included Reviews in Teacher Digital Competence Overview.
DOI: 10.5517/ccdc.csd.cc26l4cb
title: CCDC 2043221: Experimental Crystal Structure Determination

description: Related Article: Nadezhda A. Shcherbina, Igor V. Kazakov, Anna V. Pomogaeva, Anna S. Lisovenko, Maria A. Kryukova, Dmitry A. Doinikov, Nikita Yu. Gugin, Yuri V. Kondrat'ev, Alexey Y. Timoshkin|2021|J.Organomet.Chem.|948|121909|doi:10.1016/j.jorganchem.2021.121909
DOI: 10.5517/ccdc.csd.cc26l4fd
title: CCDC 2043223: Experimental Crystal Structure Determination

description: Related Article: Nadezhda A. Shcherbina, Igor V. Kazakov, Anna V. Pomogaeva, Anna S. Lisovenko, Maria A. Kryukova, Dmitry A. Doinikov, Nikita Yu. Gugin, Yuri V. Kondrat'ev, Alexey Y. Timoshkin|2021|J.Organomet.Chem.|948|121909|doi:10.1016/j.jorganchem.2021.121909
DOI: 10.5517/ccdc.csd.cc26l4lk
title: CCDC 2043228: Experimental Crystal Structure Determination

description: Related Article: Nadezhda A. Shcherbina, Igor V. Kazakov, Anna V. Pomogaeva, Anna S. Lisovenko, Maria A. Kryukova, Dmitry A. Doinikov, Nikita Yu. Gugin, Yuri V. Kondrat'ev, Alexey Y. Timoshkin|2021|J.Organomet.Chem.|948|121909|doi:10.1016/j.jorganchem.2021.121909
DOI: 10.5517/ccdc.csd.cc26l4ml
title: CCDC 2043229: Experimental Crystal Structure Determination

description: Related Article: Nadezhda A. Shcherbina, Igor V. Kazakov, Anna V. Pomogaeva, Anna S. Lisovenko, Maria A. Kryukova, Dmitry A. Doinikov, Nikita Yu. Gugin, Yuri V. Kondrat'ev, Alexey Y. Timoshkin|2021|J.Organomet.Chem.|948|121909|doi:10.1016/j.jorganchem.2021.121909
DOI: 10.5517/ccdc.csd.cc26q89j
title: CCDC 2047187: Experimental Crystal Structure Determination

description: Related Article: Ayelén F. Crespi, Verónica M. Sánchez, Daniel Vega, Ana L. Pérez, Carlos D. Brondino, Yamila Garro Linck, Paul Hodgkinson, Enrique Rodríguez-Castellón, Juan M. Lázaro-Martínez|2021|RSC Advances|11|20216|doi:10.1039/D1RA02512K
DOI: 10.5517/ccdc.csd.cc26q8bk
title: CCDC 2047188: Experimental Crystal Structure Determination

description: Related Article: Ayelén F. Crespi, Verónica M. Sánchez, Daniel Vega, Ana L. Pérez, Carlos D. Brondino, Yamila Garro Linck, Paul Hodgkinson, Enrique Rodríguez-Castellón, Juan M. Lázaro-Martínez|2021|RSC Advances|11|20216|doi:10.1039/D1RA02512K
DOI: 10.5517/ccdc.csd.cc26ry0y
title: CCDC 2048790: Experimental Crystal Structure Determination

description: Related Article: Yang Zou|2020|CSD Communication|||
description: Related Article: Jing-Wei Yu, Hai-Jiao Yu, Qiu Ren, Jin Zhang, Yang Zou, Hong-Bin Luo, Lifeng Wang, Xiao-Ming Ren|2021|Dalton Trans.|50|8070|doi:10.1039/D1DT00296A
DOI: 10.5517/ccdc.csd.cc26ry1z
title: CCDC 2048791: Experimental Crystal Structure Determination

description: Related Article: Yang Zou|2020|CSD Communication|||
description: Related Article: Jing-Wei Yu, Hai-Jiao Yu, Qiu Ren, Jin Zhang, Yang Zou, Hong-Bin Luo, Lifeng Wang, Xiao-Ming Ren|2021|Dalton Trans.|50|8070|doi:10.1039/D1DT00296A
DOI: 10.5517/ccdc.csd.cc26tcs6
title: CCDC 2050178: Experimental Crystal Structure Determination

description: Related Article: Anna A. Mukhacheva, Vladislav Yu. Komarov, Vasily V. Kokovkin, Alexander S. Novikov, Pavel A. Abramov, Maxim N. Sokolov|2021|CrystEngComm|23|4125|doi:10.1039/D1CE00319D
DOI: 10.5281/zenodo.4817253
title: Data for: "Possible link between decadal variability in precipitation in the South China Sea and the North Atlantic Oscillation during the 20th century: A perspective from coral geochemical records"

description: This dataset includes all the data for the paper "Possible link between decadal variability in precipitation in the South China Sea and the North Atlantic Oscillation during the 20th century: A perspective from coral geochemical records" by Cui et al.
DOI: 10.5281/zenodo.4957405
title: ddPCR Quantasoft Files for quantification of Atlantic salmon

description: Quantasoft data used for the results section in the paper: "Identification and semi-quantification of Atlantic salmon in processed and mixed seafood products using Droplet Digital PCR (ddPCR)"
description: Identification and semi-quantification of Atlantic salmon in processed and mixed seafood products using Droplet Digital PCR (ddPCR)
DOI: 10.5281/zenodo.4957404
title: ddPCR Quantasoft Files for quantification of Atlantic salmon

description: Quantasoft data used for the results section in the paper: "Identification and semi-quantification of Atlantic salmon in processed and mixed seafood products using Droplet Digital PCR (ddPCR)"
description: Identification and semi-quantification of Atlantic salmon in processed and mixed seafood products using Droplet Digital PCR (ddPCR)
DOI: 10.17043/stordalen-mire-ch4-surface-concentration-1
title: Methane concentrations from surface water on the Stordalen Mire, Abisko, Northern Sweden
DOI: 10.17632/94s687fvdp.1
title: Dataset: How Different Genders Use Profanity on Twitter?

description: File 01 - a summary table of keywords used to crawled those tweets in File 02 In this file, we summaries the keywords that used to obtain the 102464 tweets that we refer to the first study from this article- https://dl.acm.org/doi/abs/10.1145/3193077.3193078 File 02 - All the Original tweets that were collected using the keywords from File 01 File 03 - All the processed tweets categories by location File 04 - All the Public and Targeted Male and Female set of Tweets For File 01, the method to obtain the set of keywords is descript in this article https://dl.acm.org/doi/abs/10.1145/3193077.3193078 Phoey Lee Teh, Chi-Bin Cheng, and Weng Mun Chee. 2018. Identifying and Categorising Profane Words in Hate Speech. In Proceedings of the 2nd International Conference on Compute and Data Analysis (ICCDA 2018). Association for Computing Machinery, New York, NY, USA, 65–69. DOI:https://doi.org/10.1145/3193077.3193078 For File 04, the result is published in this article, kindly refer https://dl.acm.org/doi/abs/10.1145/3388142.3388145 Phoey Lee Teh, Chi-Bin Cheng, and Weng Mun Chee. 2018. Identifying and Categorising Profane Words in Hate Speech. In Proceedings of the 2nd International Conference on Compute and Data Analysis (ICCDA 2018). Association for Computing Machinery, New York, NY, USA, 65–69. DOI:https://doi.org/10.1145/3193077.3193078
DOI: 10.17632/z2gfw64fv2.1
title: Vaccine Data Files

description: Design of epitope-based vaccines from tRNA peptides. The Vaccine Data Used And Download Paths to Intermediate Results are available. We initially obtained all available sequences of tRNA nucleotides from GtRNAdb from various species. It was then translated from the EMBOSSTranseq tool into equivalent peptide sequences tREP’s. These tREPs were subsequently screened for complete structural peptide selection via VaxiJen v2.0 to predict antigenic peptides. Depending on T-cell epitope prediction, these antigenic peptides are further screened based on major histocompatibility complex (MHC) class I binding, proteasomal C terminal cleavage, and TAP transport efficiency using NetCTL1.2 Server. The promising epitopes were then selected, based on cell penetration (CellPPD), toxicity (ToxinPred), antigenicity (VaxiJen v2.0), allergenicity (AllerTop v.2.0), conservancy (ECA IEDB Suite), and higher immunogenicity (C1I IEDB Suite) filtration. These epitopes should then be identified by (MHC) I alleles which are present in the endoplasmic reticulum, so that it can bind to them, and can be brought to the surface of the cell, where a T-cell or a B-cell can identify to produce an antibody. In order to bind these epitopes with alleles, the 3D structures of epitopes were generated and the corresponding allele was retrieved from RCSB to perform docking. The stability and conformational changes of these two bindings along with their dynamic interactions are then analyzed, through molecular dynamics.
DOI: 10.5281/zenodo.4957665
title: dAndrea_etal_mateials

description: synthetic networks realizations and codes for epidemic dynamics simulations
DOI: 10.5281/zenodo.4957664
title: dAndrea_etal_mateials

description: synthetic networks realizations and codes for epidemic dynamics simulations
DOI: 10.25345/c5mf90
title: MassIVE MSV000087625 - ginger OR test for metabolomic approach on cytoscape
title: UHPLC analysis of ginger oleoresin for the detection of new compounds. CO2 extracted from Indian origin. GNPS test for fast screening and cytoscape evaluation
DOI: 10.34740/kaggle/dsv/2327405
title: RNA seq CRC
DOI: 10.5281/zenodo.4957778
title: Thymine, C5H6N2O2

description: Thymine, C5H6N2O2
DOI: 10.5281/zenodo.4957777
title: Thymine, C5H6N2O2

description: Thymine, C5H6N2O2
DOI: 10.5281/zenodo.4957780
title: Adenine, C5H5N5

description: Adenine, C5H5N5
DOI: 10.5281/zenodo.4957779
title: Adenine, C5H5N5

description: Adenine, C5H5N5
DOI: 10.5066/p9q4zwbq
title: National Assessment of Oil and Gas Project - Southwestern Wyoming Province (037 Quarter-Mile Cells

description: Cell maps for each oil and gas assessment unit were created by the USGS as a method for illustrating the degree of exploration, type of production, and distribution of production in an assessment unit or province. Each cell represents a quarter-mile square of the land surface, and the cells are coded to represent whether the wells included within the cell are predominantly oil-producing, gas-producing, both oil and gas-producing, dry, or the type of production of the wells located within the cell is unknown. The well information was initially retrieved from the IHS Energy Group, PI/Dwights PLUS Well Data on CD-ROM, which is a proprietary, commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary PI/Dwights PLUS Well Data. No proprietary data are displayed or included in the cell maps. The data from PI/Dwights PLUS Well Data were current as of October 2001 when the cell maps were created in 2002.
DOI: 10.6073/pasta/d3f293fbf5e2094489475c099694d9a6
title: Biomass Inventories at Harvard Forest EMS Tower since 1993

description: In 1993, we installed 40 circular, 10 m radius biometric plots in the footprint of the EMS tower on Prospect Hill. We randomly placed the plots within 100 m increments along ten 500 m transects that extend from the tower in the northwest and southwest directions. In 2001, we removed three plots (G3, H3, H4) from the datasets and ceased measurements there due to their inundation by a beaver pond. In 1999, we installed 6 additional circular, 10 m radius biometric plots on the Simes Lot, adjacent to Prospect Hill to study the effects of a selective harvest that occurred there in the winter of 2000-01. In the summer of 2001, we expanded the harvested plots in size to 15 m radius and ceased measurements at one plot (X4) because it was unaffected by the harvest. The harvest also affected three of the original tower plots (A4, A5, B5), which were expanded in size as a part of the harvest plot group. Consequently, there are 34 tower plots and 8 harvest plots. We have taken the following ecological measurements at each site: tree growth, woody debris, litter, leaf area increment (LAI), leaf chemistry, and soil respiration and moisture.
DOI: 10.6084/m9.figshare.13415807
title: Betascan2 scores for each population

description: Raw Betascan2 scores for each population, Brazil-Mediterranean (BM), East Africa 1-2 (EA1-2) and the Indian Subcontinent 1-2 (ISC1-2). <br><br>Betascan2 test was performed with BM as the outgroup population in 10kb genomic windows. All other parameters were kept at default.<br>
DOI: 10.6084/m9.figshare.13415813
title: NCD2 scores for each population

description: Raw data from NCD2 test performed on each population. <br>
DOI: 10.6084/m9.figshare.13415807.v1
title: Betascan2 scores for each population

description: Raw Betascan2 scores for each population, Brazil-Mediterranean (BM), East Africa 1-2 (EA1-2) and the Indian Subcontinent 1-2 (ISC1-2). <br><br>Betascan2 test was performed with BM as the outgroup population in 10kb genomic windows. All other parameters were kept at default.<br>
DOI: 10.6084/m9.figshare.13415813.v1
title: NCD2 scores for each population

description: Raw data from NCD2 test performed on each population. <br>
DOI: 10.5281/zenodo.4817605
title: UniToBrain Dataset

description: The University of Turin (UniTO) released the open-access dataset UniTOBrain collected for the homonymous Use Case 3 in the DeepHealth project (https://deephealth-project.eu/). UniToBrain is a dataset of Computed Tomography (CT) perfusion images (CTP). The dataset includes 100 training subjects and 15 testing subjects used in a submitted publication for the training and the testing of a Convolutional Neural Network (CNN, see for details: https://arxiv.org/abs/2101.05992, https://paperswithcode.com/paper/neural-network-derived-perfusion-maps-a-model, https://www.medrxiv.org/content/10.1101/2021.01.13.21249757v1). At this stage, the UniTO team released this dataset privately, but soon it will be public. This is a subsample of a greater dataset of 258 subjects that will be soon available for download at https://ieee-dataport.org/.<br> CTP data from 258 consecutive patients were retrospectively obtained from the hospital PACS of Città della Salute e della Scienza di Torino (Molinette). CTP acquisition parameters were as follows: Scanner GE, 64 slices, 80 kV, 150 mAs, 44.5 sec duration, 89 volumes (40 mm axial coverage), injection of 40 ml of Iodine contrast agent (300 mg/ml) at 4 ml/s speed.
description: {"references": ["Bennink E, Oosterbroek J, Kudo K, Viergever MA, Velthuis BK, de Jong HWAM. Fast nonlinear regression method for CT brain perfusion analysis. Journal of Medical Imaging 2016. https://doi.org/10.1117/1.jmi.3.2.026003.", "Klein S, Staring M, Murphy K, Viergever MA, Pluim JPW. Elastix: A toolbox for intensity-based medical image registration. IEEE Transactions on Medical Imaging 2010. https://doi.org/10.1109/TMI.2009.2035616.", "Tomasi C, Manduchi R. Bilateral filtering for gray and color images. Proceedings of the IEEE International Conference on Computer Vision, 1998. https://doi.org/10.1109/iccv.1998.710815."]}
DOI: 10.6073/pasta/efb11a0f58c2ffd21ac741b6e683039a
title: Prospect Hill Hydrological Stations at Harvard Forest since 2005

description: To better understand the critical role of headwater streams and wetlands in our forest ecosystem, long-term measurements were initiated in 2005 on two small watersheds in the Prospect Hill Tract of the Harvard Forest. On Nelson Brook, weirs were installed on outlet streams of an 11-ha spruce-hemlock wetland (watershed area = 44 ha). On Bigelow Brook, pipes were installed to measure flow above (watershed = 24 ha) and below (watershed = 65 ha) a 3-ha shrub-dominated beaver swamp. The gaged watersheds, though adjacent and comparable in size, differ significantly in topography, soils, wetlands, stream chemistry, stream biota, land-use history, and forest vegetation, and provide an extraordinary opportunity to study the impacts of these factors on small watershed hydrology and ecology. Weekly manual measurements were initiated in April 2005. Continuous automated measurements were initiated in December 2007. Data for the current month are available online, updated every 15 minutes, with out-of-range values replaced by NA but values not otherwise checked. Earlier data are checked and archived with missing, questionable, and estimated values flagged, following methods of the LTER ClimbDB project. A log of events affecting station measurements is also posted. For current data, please see: https://harvardforest.fas.harvard.edu/meteorological-hydrological-stations. For a complete set of archived data, please see: https://harvardforest.fas.harvard.edu/exist/apps/datasets/showData.html?id=HF070.
DOI: 10.6084/m9.figshare.14785113
title: _v2.0.pep

description: xxxxx
DOI: 10.6084/m9.figshare.14785113.v2
title: _v2.0.pep

description: xxxxx
DOI: 10.6084/m9.figshare.14785113.v1
title: Phrvla_v2.0.pep

description: Protein file of the <i>Phrynocephalus vlangalii </i>genome<i>.</i>
DOI: 10.5281/zenodo.4949935
title: Development of a Low Power, Low Cost Rural Railway Intersection Smart Detection and Warning System

description: This project explores a different approach to provide preemptive warning for train detection at grade-crossings to increase safety and reduce motor vehicle congestion. The development of a novel, low cost, low power, and off rail right-of-way (ROW) detection and warning system will be presented. A background of track circuits, which is the rail industries standard for train detection, will also be provided to highlight the benefits and challenges of the rail industry installing a system at every grade-crossings that lack any type of active warning. The benefits of using thermal imaging instead of traditional video for computer vision will also be discussed. Then, the development of a detection algorithm using convolutional neural networks and deep learning methods on a custom dataset of images created by two different thermal sensors will be overviewed. The two sensors tested are the MLX90640 and FLIR Lepton 3.0. Both react to heat radiation emitted from objects but in very different ways from a technology perspective. This difference in technology creates a large gap in cost and power between the two and was therefore worth testing to analyze the trade off in accuracy achieved in creating an outdoor detection model. Finally, the wireless communication between the detection and warning devices is discussed as well as the network communication for detected data to be logged to an online server and updated on a mobile application. Testing was done at a location approximately one mile east of the Kirby Union Pacific Railyard in San Antonio, TX from a distance that was off the property of ROW.
description: Tran-SET Project: 19SAUTSA03
DOI: 10.5281/zenodo.4949934
title: Development of a Low Power, Low Cost Rural Railway Intersection Smart Detection and Warning System

description: This project explores a different approach to provide preemptive warning for train detection at grade-crossings to increase safety and reduce motor vehicle congestion. The development of a novel, low cost, low power, and off rail right-of-way (ROW) detection and warning system will be presented. A background of track circuits, which is the rail industries standard for train detection, will also be provided to highlight the benefits and challenges of the rail industry installing a system at every grade-crossings that lack any type of active warning. The benefits of using thermal imaging instead of traditional video for computer vision will also be discussed. Then, the development of a detection algorithm using convolutional neural networks and deep learning methods on a custom dataset of images created by two different thermal sensors will be overviewed. The two sensors tested are the MLX90640 and FLIR Lepton 3.0. Both react to heat radiation emitted from objects but in very different ways from a technology perspective. This difference in technology creates a large gap in cost and power between the two and was therefore worth testing to analyze the trade off in accuracy achieved in creating an outdoor detection model. Finally, the wireless communication between the detection and warning devices is discussed as well as the network communication for detected data to be logged to an online server and updated on a mobile application. Testing was done at a location approximately one mile east of the Kirby Union Pacific Railyard in San Antonio, TX from a distance that was off the property of ROW.
description: Tran-SET Project: 19SAUTSA03
DOI: 10.6084/m9.figshare.14785107
title: _v2.0.cds

description: xxxxxxx
DOI: 10.6084/m9.figshare.14785107.v2
title: _v2.0.cds

description: xxxxxxx
DOI: 10.6084/m9.figshare.14785107.v1
title: Phrvla_v2.0.cds

description: CDS file of the <i>Phrynocephalus vlangalii</i> genome.
DOI: 10.6084/m9.figshare.14785098
title: .annotation.xls

description: xxxxx
DOI: 10.6084/m9.figshare.14785098.v2
title: .annotation.xls

description: xxxxx
DOI: 10.6084/m9.figshare.14785098.v1
title: Phrvla_v2.0.annotation.xls

description: Functional annotation file of <i>Phrynocephalus vlangalii</i> genome.
DOI: 10.6084/m9.figshare.14785068
title: 0.gff

description: xxxx
DOI: 10.6084/m9.figshare.14785068.v2
title: 0.gff

description: xxxx
DOI: 10.6084/m9.figshare.14785068.v1
title: Phrvla_v2.0.gff

description: GFF file of the <i>Phrynocephalus vlangalii </i>genome.
DOI: 10.21223/jfnqhm/hokm7c
title: 01_Laboratory_data_K_2_35_2020.tab
DOI: 10.21223/jfnqhm/3jur7t
title: 02_Sprecta_data_K_2_35_2020.xlsx
DOI: 10.21223/jfnqhm/jgy3os
title: 05_Dictionary_K_2_35_2020.tab
DOI: 10.21223/jfnqhm/6zga1a
title: 03_Calibration_Validation_K_2_35_2020.tab
DOI: 10.21223/jfnqhm/pcyewo
title: 04_Description_data_K_2_35_2020.tab
DOI: 10.21223/jfnqhm/o6dyw0
title: 05_Dictionary_K_2_35_2020.tab

description: :unav
DOI: 10.21223/jfnqhm
title: Dataset for: RTBfoods K.2.35- Spectral database on NIRS on raw freeze dried sweetpotato

description: Up to 4 SP roots per genotype were cut longitudinal, sliced, mixed, freeze-dried, and milled before NIRS scanning. SP root samples harvested in 2 locations in Uganda and processed in Namulonge on 11/2019 (60 genotypes). NIR instrument used was Foss XDS, serial number 30101714, and analysis 60 spectra (1 representing 1 genotype). All traits were analyzed on freeze-dried material. All quantitative traits are calculated on the Dry Weight Basis of flour.