cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6396795
title: Students' Perception towards e-learning during COVID-19 Pandemic in Indonesia

description: The study explores university students' perceptions of e-learning in the context of the ongoing COVID-19 epidemic. The study finds that students prefer e-learning because it enables them to connect with their lecturers and fellow students and engage with their study materials at their leisure, and with the freedom to choose their preferred location and time. One of the key reason students choose e-learning is the ease with which they may obtain study resources. The research methods used with a quantitative model, where the sample tested represented the student of 1137 respondents from 43 universities in Indonesia. The study's findings show the weakness of e-learning is that the majority of respondents responded in turn to interaction with lecturers (52,7%). The study also identified that the majority of respondents have a moderate mastery of technology, 1038 individuals (77.6%), while the remainder has poor knowledge of technology, as many as 52 people (3.9%). According to the study, e-learning technology enables quick access to information, which results in students developing a favorable attitude toward it based on its utility, self-efficacy, the convenience of use, and student behavior related to e-learning. The study verifies the utility of e-learning by demonstrating how it enables students to study from any geographical location, which is not achievable with face-to-face instruction.
DOI: 10.34820/fk2/b1cki0/ojt1ek
title: data penelitian rata rata.tab

description: :unav
DOI: 10.34820/fk2/b1cki0
title: Dataset for clustering of infected covid-19 case in Jakarta

description: Dataset for clustering of infected covid-19 case in jakarta
DOI: 10.34740/kaggle/ds/2045680
title: Moby Dick - Herman Melville
DOI: 10.5281/zenodo.4685964
title: Epidemiological geography at work. An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year (DATASET)

description: <strong>Literature review dataset</strong> This table lists the surveyed papers concerning the application of spatial analysis, GIS (Geographic Information Systems) as well as general geographic approaches and geostatistics, to the assessment of CoViD-19 dynamics. The period of survey is from January 1<sup>st</sup>, 2020 to December 15<sup>th</sup>, 2020. The first column lists the reference. The second lists the date of publication (preferably, the date of online publication). The third column lists the Country or the Countries and/or the subnational entities investigated. The fourth column lists the epidemiological data utilized in each paper. The fifth column lists other types of data utilized for the analysis. The sixth column lists the more traditionally statistically-based methods, if utilized. The seventh column lists the geo-statistical, GIS or geographic methods, if utilized. The eight column sums up the findings of each paper. The papers are also classified within seven thematic categories. The full references are available at the end of the table in alphabetical order. This table was the basis for the realization of a comprehensive geographic literature review. It aims to be a useful tool to ease the "due-diligence" activity of all the researchers interested in the spatial analysis of the pandemic. The reference to cite the related paper is the following: <strong>Pranzo, A.M.R., Dai Prà, E. & Besana, A. Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year. GeoJournal (2022). https://doi.org/10.1007/s10708-022-10601-y</strong> To read the manuscript please follow this link: <strong>https://doi.org/10.1007/s10708-022-10601-y</strong>
DOI: 10.5281/zenodo.4685963
title: Epidemiological geography at work. An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year (DATASET)

description: <strong>Literature review dataset</strong> This table lists the surveyed papers concerning the application of spatial analysis, GIS (Geographic Information Systems) as well as general geographic approaches and geostatistics, to the assessment of CoViD-19 dynamics. The period of survey is from January 1<sup>st</sup>, 2020 to December 15<sup>th</sup>, 2020. The first column lists the reference. The second lists the date of publication (preferably, the date of online publication). The third column lists the Country or the Countries and/or the subnational entities investigated. The fourth column lists the epidemiological data utilized in each paper. The fifth column lists other types of data utilized for the analysis. The sixth column lists the more traditionally statistically-based methods, if utilized. The seventh column lists the geo-statistical, GIS or geographic methods, if utilized. The eight column sums up the findings of each paper. The papers are also classified within seven thematic categories. The full references are available at the end of the table in alphabetical order. This table was the basis for the realization of a comprehensive geographic literature review. It aims to be a useful tool to ease the "due-diligence" activity of all the researchers interested in the spatial analysis of the pandemic. The reference to cite the related paper is the following: <strong>Pranzo, A.M.R., Dai Prà, E. & Besana, A. Epidemiological geography at work: An exploratory review about the overall findings of spatial analysis applied to the study of CoViD-19 propagation along the first pandemic year. GeoJournal (2022). https://doi.org/10.1007/s10708-022-10601-y</strong> To read the manuscript please follow this link: <strong>https://doi.org/10.1007/s10708-022-10601-y</strong>
DOI: 10.6084/m9.figshare.19495001
title: GOterms

description: GO-term by GOnet
DOI: 10.6084/m9.figshare.19495001.v2
title: GOterms

description: GO-term by GOnet
DOI: 10.6084/m9.figshare.19495001.v1
title: GOterms

description: GO-term by GOnet
DOI: 10.6084/m9.figshare.19495025
title: GOterms

description: Terms
DOI: 10.6084/m9.figshare.19495025.v1
title: GOterms

description: Terms
DOI: 10.5281/zenodo.6406782
title: Data: Human pressure effect on biodiversity-multifunctionality relationship in large Neotropical wetlands

description: Data from manuscript Human pressure drives biodiversity–multifunctionality relationships in neotropical wetlands.<br> Moi et al. This is a dataset compiled from 72 lakes distributed across four neotropical wetlands of Brazil (Amazon, Araguaia, Pantanal, and Paraná). Dataset included single ecosystem functions: nutrient concentrations (in situ measurements of N and P water concentrations), metabolism (daily changes in water O2 concentration), biomass at multiple trophic levels (algae, herbivores, carnivores, detritivores, and omnivores), microorganism abundance (bacterial cell densities), availability of photosynthetically active radiation (light availability underwater), and variation in habitat complexity under water (variation in plant above-bottom cover). Dataset also included measures of aquatic biodiversity, including species richness and functional diversity of seven organismal groups (fish, aquatic macrophytes, microcrustaceans, rotifers, phytoplankton, ciliates, and testate amoebae). Finally, the dataset includes measures of ecosystem multifunctionality, human pressure (Human Footprint), and local environmental covariates (depth, conductivity, pH, precipitation, temperature). All data came from standardized samples.
DOI: 10.5281/zenodo.5764909
title: Data: Human pressure effect on biodiversity-multifunctionality relationship in large Neotropical wetlands

description: Data from manuscript Human pressure drives biodiversity–multifunctionality relationships in neotropical wetlands.<br> Moi et al. This is a dataset compiled from 72 lakes distributed across four neotropical wetlands of Brazil (Amazon, Araguaia, Pantanal, and Paraná). Dataset included single ecosystem functions: nutrient concentrations (in situ measurements of N and P water concentrations), metabolism (daily changes in water O2 concentration), biomass at multiple trophic levels (algae, herbivores, carnivores, detritivores, and omnivores), microorganism abundance (bacterial cell densities), availability of photosynthetically active radiation (light availability underwater), and variation in habitat complexity under water (variation in plant above-bottom cover). Dataset also included measures of aquatic biodiversity, including species richness and functional diversity of seven organismal groups (fish, aquatic macrophytes, microcrustaceans, rotifers, phytoplankton, ciliates, and testate amoebae). Finally, the dataset includes measures of ecosystem multifunctionality, human pressure (Human Footprint), and local environmental covariates (depth, conductivity, pH, precipitation, temperature). All data came from standardized samples.
DOI: 10.34622/datarepositorium/tlsuo1/f6ip6n
title: scrapper_base_gov.py

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/aigx4z
title: scrapper_nifs.py

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/t0caj5
title: Map4Scrutiny_ShEx_Validation_Outputs.txt

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/egc76e
title: AllData.ttl

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/dsf0xz
title: ReadMe_RunShExValidation.txt

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/jw0rqa
title: Map4Scrutiny_ShExC_Shapes.shex

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/wnhpos
title: scrapper_parlamento.py

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/26rxkf
title: Shape_Map_All_Data.txt

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/jz1gnp
title: Map4Scrutiny_OpenRefine_Logs.txt

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/7roovq
title: Map4Scrutiny_Core-1.ttl

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/julkxh
title: Map4Scrutiny_Values-1.ttl

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1/kytfle
title: DCTAP.tab

description: :unav
DOI: 10.34622/datarepositorium/tlsuo1
title: Map4Scrutiny: a Linked Open Data approach on politicians interest registers - support files

description: This dataset includes all the files mentioned in the dissertation: "Map4Scrutiny: a Linked Open Data Prototype for Politicians Interest Registers". These include the code used to scrap and source the original files, the vocabularies created, the data itself, and the shapes of the data in ShExC together with the Shape Map to run validation.
DOI: 10.5281/zenodo.6406706
title: SocialDisNER corpus: gold standard annotations for detection of disease mentions in Spanish tweets

description: Gold Standard annotations for <strong>SocialDisNER </strong>(SMM4H 2022 – Task 10) shared task. <strong>Introduction:</strong><br> The <strong>SocialDisNER corpus</strong> of the SMM4H 2022 – Task 10 task will focus on the recognition of disease mentions in tweets written in Spanish after selecting primarily<strong><em> first-hand experience of diseases</em></strong> and other health-relevant content (from patient associations, professional healthcare institutions, and through followers of patient association accounts of a <em>diversity of pathologies</em> including rare diseases, mental health, cancer, etc..). The corpus was manually annotated by medical experts following the SMM4H-SocialDisNER guidelines. These guidelines were adapted from previous efforts used to annotate patient clinical records and medical literature. It covers rules for annotating <strong>mentions of diseases</strong> in health-related tweets in Spanish, The current training set consists of 2415 tweets written in Spanish, the annotated validation set and the unannotated test set will be published shortly. The structure of the dataset is: socialdisner.zip: <strong><em>train-valid-txt-files</em></strong>: folder with training and validation text files. One text file per tweet, he file name corresponds to the tweet id.. One sub-directory per corpus split (train and valid). Validation tweets have not yet been included. <strong><em>mentions.tsv</em></strong>: This file contains the manually annotated disease mentions. The file has the following fields: <em>tweets_id</em>: This is the id of the tweet, using Twitter API you can query the content of the tweet. <em>Begin</em>: This is the position in the tweet where the annotation was found. <em>End</em>: This is the position of the last character of the annotation in the tweet. <em>Type: </em>This is the type of entity found, in our case "ENFERMEDAD". <em>Extraction</em>: This is the literal extraction, in other words, the fragment of text which refers to the annotation. For further information, please visit https://temu.bsc.es/socialdisner/ Do not share the data with other individuals/teams without permission from the task organizer. Tweets IDs are the primary source of information. Tweet texts are provided as support material. By downloading this resource, you agree to the Twitter Terms of Service, Privacy Policy, Developer Agreement, and Developer Policy.
DOI: 10.34740/kaggle/dsv/3393492
title: Mahanagar Yatayat Dataset
DOI: 10.34622/datarepositorium/iyovcc/9jvtfr
title: scrapper_base_gov.py

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/52d3b3
title: scrapper_nifs.py

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/zcusve
title: Map4Scrutiny_ShEx_Validation_Outputs.txt

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/qykttx
title: AllData.ttl

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/eciasq
title: ReadMe_RunShExValidation.txt

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/miqcog
title: Map4Scrutiny_ShExC_Shapes.shex

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/l3e4qb
title: scrapper_parlamento.py

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/zhcbps
title: Shape_Map_All_Data.txt

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/ruj1cs
title: Map4Scrutiny_OpenRefine_Logs.txt

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/jzkwas
title: Map4Scrutiny_Core-1.ttl

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/md1z2m
title: Map4Scrutiny_Values-1.ttl

description: :unav
DOI: 10.34622/datarepositorium/iyovcc/xy6eb3
title: DCTAP.tab

description: :unav
DOI: 10.34622/datarepositorium/iyovcc
title: Map4Scrutiny: a Linked Open Data approach on politicians interest registers - support files

description: This dataset includes all the files mentioned in the dissertation: "Map4Scrutiny: a Linked Open Data Prototype for Politicians Interest Registers". These include the code used to scrap and source the original files, the vocabularies created, the data itself, and the shapes of the data in ShExC together with the Shape Map to run validation.
DOI: 10.5281/zenodo.6406797
title: The Extreme Mechanics of Viscoelastic Metamaterials

description: This dataset contains all data as used for the paper 'The Extreme Mechanics of Viscoelastic Metamaterials'. It provides example files on viscoelastic modelling in Abaqus and on deriving viscoelastic material properties, <strong>Abstract:</strong> Mechanical metamaterials made of flexible building blocks can exhibit a plethora of extreme mechanical responses, such as negative elastic constants, shape-changes, programmability and memory. To date, dissipation has largely remained overlooked for such flexible metamaterials. As a matter of fact, extensive care has often been devoted in the constitutive materials’ choice to avoid strong dissipative effects. However, in an increasing number of scenarios, where metamaterials are loaded dynamically, dissipation can not be ignored. In this review, we show that the interplay between mechanical instabilities and viscoelasticity can be crucial and can be harnessed to obtain new functionalities. We first show that this interplay is key to understanding the dynamical behaviour of flexible dissipative metamaterials that use buckling and snapping as functional mechanisms. We further discuss the new opportunities that spatial patterning of viscoelastic properties offer for the design of mechanical metamaterials with properties that depend on loading rate.
description: We acknowledge funding from the European Research Council under grant agreement 852587 and the Netherlands Organization for Scientific Research under grant agreement NWO TTW 17883.
DOI: 10.34703/gzx1-9v95/zw5rim/bgweoh
title: ESI_neg_4MW_HR-4_TIMS_FT_ICR_MS.d.zip.zip

description: :unav
DOI: 10.34703/gzx1-9v95/zw5rim/c0x0lv
title: ESI_neg_4MW_HR-3_TIMS__FT_ICR_MS.d.zip.zip

description: :unav
DOI: 10.34703/gzx1-9v95/zw5rim/ee0a2x
title: ESI_neg_4MW_HR-2_TIMS_FT_ICR_MS.d.zip.zip

description: :unav
DOI: 10.34703/gzx1-9v95/zw5rim/aqkrcm
title: ESI_neg_4MW_HR-1_TIMS_FT_ICR_MS.d.zip

description: :unav
DOI: 10.34703/gzx1-9v95/zw5rim/083mbz
title: ESI_neg_4MW_HR-5_TIMS_FT_ICR_MS.d.zip

description: :unav
DOI: 10.34703/gzx1-9v95/zw5rim
title: ESI-TIMS-FT-ICR-MS data of the Harney River SPE-DOM samples

description: This dataset comprises the raw files generated from ESI-TIMS-FT ICR MS analysis of SPE-DOM samples from the Harney River, Florida Everglades.
DOI: 10.6084/m9.figshare.19495100
title: OQMD-mix, MP-mix, ICSD-mix datasets

description: Datasets with mixed samples, some are charge neutral, some are not. Some are electroneativity balanced. Some are not. <br>
DOI: 10.6084/m9.figshare.19495064
title: OQMD-pure, ICSD-pure, MP-pure

description: the datasets with charge neutral and balanced electronegativity samples for training BLMM generator
DOI: 10.5281/zenodo.6406818
title: Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks

description: Supplementary Tables - Version 2
DOI: 10.5281/zenodo.5758217
title: Predicting methane emission in Canadian Holstein dairy cattle using milk mid-infrared reflectance spectroscopy and other commonly available predictors via artificial neural networks

description: Supplementary Tables - Version 2
DOI: 10.34820/fk2/3pwbxi/oejmwi
title: Assesment of Spatial Water Quality variation on Citarum River-IJASEIT_2018-7parm.pdf

description: :unav
DOI: 10.34820/fk2/3pwbxi
title: Assessment of Spatial Water Quality Observation of Citarum River Bandung Regency Using Multivariate Statistical Methods

description: Assessment of Spatial Water Quality Observation of Citarum River Bandung Regency Using Multivariate Statistical Methods
DOI: 10.5281/zenodo.6383269
title: SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data

description: Processed data for the manuscript "" available on bioRxiv at "" Data is available for the following samples CD34+ Multiome data : 2 replicates T-cell depleted bone marrow Multiome data: 2 replicates The following counts and fragments files are available for each replicate &lt;sample&gt;_filtered_feature_bc_matrix.h5: Feature counts from CellRanger ARC &lt;sample&gt;_atac_fragments.tsv.gz: ATAC fragments file from Cellranger ARC &lt;sample&gt;_atac_fragments.tsv.gz.tbi: Index files for ATAC fragments file from Cellranger ARC The following scanpy anndata objects are also available cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of CD34+ hematopoietic stem and progenitor cells cd34_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of of CD34+ hematopoietic stem and progenitor cells. cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of T-cell depleted bone marrow dataset. bm_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of T-cell depleted bone marrow dataset.
DOI: 10.5281/zenodo.6383268
title: SEACells: Inference of transcriptional and epigenomic cellular states from single-cell genomics data

description: Processed data for the manuscript "" available on bioRxiv at "" Data is available for the following samples CD34+ Multiome data : 2 replicates T-cell depleted bone marrow Multiome data: 2 replicates The following counts and fragments files are available for each replicate &lt;sample&gt;_filtered_feature_bc_matrix.h5: Feature counts from CellRanger ARC &lt;sample&gt;_atac_fragments.tsv.gz: ATAC fragments file from Cellranger ARC &lt;sample&gt;_atac_fragments.tsv.gz.tbi: Index files for ATAC fragments file from Cellranger ARC The following scanpy anndata objects are also available cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of CD34+ hematopoietic stem and progenitor cells cd34_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of of CD34+ hematopoietic stem and progenitor cells. cd34_multiome_rna.h5ad: Anndata object with normalized data, cell type annotations and clusters for the RNA modality of T-cell depleted bone marrow dataset. bm_multiome_atac.h5ad: Anndata object with peak counts, cell type annotations and clusters for the ATAC modality of T-cell depleted bone marrow dataset.
DOI: 10.5281/zenodo.6406830
title: Adebiyi etal: absorption of shortwave radiation by North African dust

description: The codes and datasets contained here are for the paper with the information below<br> Titled: "North African dust absorbs substantially less solar radiation than estimated by climate models and remote-sensing retrievals"<br> Author: Adeyemi A. Adebiyi, Yue Huang, Bjørn H. Samset and Jasper F. Kok Please see the ReadMe.txt for additional details. ------------------------<br> Corresponding Authors:<br> Adeyemi Adebiyi<br> Email: aaadebiyi@ucmerced.edu;<br> Department of Life and Environmental Sciences,<br> University of California-Merced,<br> 5200 North Lake Road Merced, CA 95343.
DOI: 10.3886/e166584
title: Happy At Work: Possible at Any Age

description: This study uses several recent years of the General Social Survey to examine Job Satisfaction for older workers, controlling for gender and work arrangement. Older workers are divided into two categories; those close to retirement age, 55 -64, and those who continue to work post the traditional retirement age (65-80). This study is particularly interested in examining job satisfaction for these older workers in various work arrangements in addition to those in regular jobs.
DOI: 10.3886/e166584v1
title: Happy At Work: Possible at Any Age

description: This study uses several recent years of the General Social Survey to examine Job Satisfaction for older workers, controlling for gender and work arrangement. Older workers are divided into two categories; those close to retirement age, 55 -64, and those who continue to work post the traditional retirement age (65-80). This study is particularly interested in examining job satisfaction for these older workers in various work arrangements in addition to those in regular jobs.
DOI: 10.5517/ccdc.csd.cc1yvb37
title: CCDC 1812759: Experimental Crystal Structure Determination

description: Related Article: Zhenbo Guo, Yiming Xu, Yujie Peng, Haroon ur Rashid, Wei Quan, Peng Xie, Lichuan Wu, Jun Jiang, Lisheng Wang, Xu Liu|2019|Bioorg.Med.Chem.Lett.|29|1133|doi:10.1016/j.bmcl.2019.02.023
DOI: 10.5517/ccdc.csd.cc20j25t
title: CCDC 1862485: Experimental Crystal Structure Determination

description: Related Article: Balendra Kumar|2018|CSD Communication|||
description: Related Article: Balendra, Azeem Banday, Shailabh Tewari, Bharti Singh, Sevi Murugavel, Arunachalam Ramanan|2019|Inorg.Chim.Acta|495|118940|doi:10.1016/j.ica.2019.05.039
DOI: 10.5517/ccdc.csd.cc20j2xk
title: CCDC 1862508: Experimental Crystal Structure Determination

description: Related Article: Balendra, Azeem Banday, Shailabh Tewari, Bharti Singh, Sevi Murugavel, Arunachalam Ramanan|2019|Inorg.Chim.Acta|495|118940|doi:10.1016/j.ica.2019.05.039