cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7057492
title: Common anti-cancer therapies induce somatic mutations in stem cells of healthy tissue

description: Genome-wide mutation analyses have revealed that specific anti-cancer drugs are highly mutagenic to cancer cells, but the mutational impact of anti-cancer therapies on normal cells is not known. Here, we examine genome-wide somatic mutation patterns in 42 healthy adult stem cells (ASCs) of the colon or the liver from 14 colorectal cancer patients (mean of 3.2 ASC per donor) that received systemic chemotherapy and/or radiotherapy. The platinum-based chemo-drug Oxaliplatin induces on average 535±260 mutations in colon ASC, while 5-FU shows a complete mutagenic absence in most colon ASCs. In contrast with the colon, normal liver ASCs escape mutagenesis from systemic treatment. Radiation results in the accumulation of 50-100 5-10,000bp deletions and structural rearrangements in colon ASCs. Thus, while chemotherapies are highly effective at killing cancer cells, their systemic use also increases the mutational burden of long-lived normal stem cells responsible for tissue renewal thereby increasing the risk for developing second cancers.
DOI: 10.5281/zenodo.3567768
title: A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals

description: A set of controlled terms that define the scope and breadth of Sustainable Development Goals (SDGs) as defined by the United Nations. These terms may be used to tag and index textual records in accordance with SDGs. The vocabulary is constructed by means of the following steps: An initial set of terms per SDG target is built by extracting key terms from the UN official list of Goals, Targets and Indicators The list is manually enriched by performing a review of the literature produced around SDGs and by compiling lists of pertinent words per Target mentioned by the reviewed documents A reference textual corpus is downloaded by searching for the initial set terms defined at step 1. and 2. The corpus is used to train a Word2Vec word embedding model (a machine learning model based on neural networks). The terms’ list is then enriched by means of automatic methods, which are run in parallel: The trained Word2Vec model is used to select, among the indexed keywords of the reference corpus, all terms “semantically close” to the initial set of words. This step is carried out to select terms that might not appear in the texts themselves, but that were deemed pertinent to label the textual records. Further terms that are mentioned in the texts of the reference corpus and that are valued by the trained Word2Vec model as “semantically close” to the initial set of words are also retained. This step is performed to include in the controlled vocabulary a series of terms that are related to the focus of the SDGs and which are used by practitioners. An automated algorithm is used to retrieve, from the APIs of WikiPedia a series of terms that have some categorical relationships (i.e. those that are indexed as “a broader concept of”, or “equivalent to” in DBpedia) with the initial set of words. The final list produced by steps 1-4 s finally manually revised
DOI: 10.5281/zenodo.3567769
title: A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals

description: A set of controlled terms that define the scope and breadth of Sustainable Development Goals (SDGs) as defined by the United Nations. These terms may be used to tag and index textual records in accordance with SDGs. The vocabulary is constructed by means of the following steps: An initial set of terms per SDG target is built by extracting key terms from the UN official list of Goals, Targets and Indicators The list is manually enriched by performing a review of the literature produced around SDGs and by compiling lists of pertinent words per Target mentioned by the reviewed documents A reference textual corpus is downloaded by searching for the initial set terms defined at step 1. and 2. The corpus is used to train a Word2Vec word embedding model (a machine learning model based on neural networks). The terms’ list is then enriched by means of automatic methods, which are run in parallel: The trained Word2Vec model is used to select, among the indexed keywords of the reference corpus, all terms “semantically close” to the initial set of words. This step is carried out to select terms that might not appear in the texts themselves, but that were deemed pertinent to label the textual records. Further terms that are mentioned in the texts of the reference corpus and that are valued by the trained Word2Vec model as “semantically close” to the initial set of words are also retained. This step is performed to include in the controlled vocabulary a series of terms that are related to the focus of the SDGs and which are used by practitioners. An automated algorithm is used to retrieve, from the APIs of WikiPedia a series of terms that have some categorical relationships (i.e. those that are indexed as “a broader concept of”, or “equivalent to” in DBpedia) with the initial set of words. The final list produced by steps 1-4 s finally manually revised
DOI: 10.5281/zenodo.4118028
title: A controlled vocabulary defining the semantic perimeter of Sustainable Development Goals

description: A set of controlled terms that define the scope and breadth of Sustainable Development Goals (SDGs) as defined by the United Nations. These terms may be used to tag and index textual records in accordance with SDGs. The vocabulary is constructed by means of the following steps: An initial set of terms per SDG target is built by extracting key terms from the UN official list of Goals, Targets and Indicators The list is manually enriched by performing a review of the literature produced around SDGs and by compiling lists of pertinent words per Target mentioned by the reviewed documents A reference textual corpus is downloaded by searching for the initial set terms defined at step 1. and 2. The corpus is used to train a Word2Vec word embedding model (a machine learning model based on neural networks). The terms’ list is then enriched by means of automatic methods, which are run in parallel: The trained Word2Vec model is used to select, among the indexed keywords of the reference corpus, all terms “semantically close” to the initial set of words. This step is carried out to select terms that might not appear in the texts themselves, but that were deemed pertinent to label the textual records. Further terms that are mentioned in the texts of the reference corpus and that are valued by the trained Word2Vec model as “semantically close” to the initial set of words are also retained. This step is performed to include in the controlled vocabulary a series of terms that are related to the focus of the SDGs and which are used by practitioners. An automated algorithm is used to retrieve, from the APIs of WikiPedia a series of terms that have some categorical relationships (i.e. those that are indexed as “a broader concept of”, or “equivalent to” in DBpedia) with the initial set of words. The final list produced by steps 1-4 s finally manually revised
DOI: 10.5519/qd.tw62p44i
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (23 records)
DOI: 10.5281/zenodo.7057511
title: Companion data of Detection, Evaluation and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters

description: This is the companion data repository for the paper entitled <strong>Detection, Evaluation, and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters</strong> by Lucas Leandro Nesi and Lucas Mello Schnorr. The manuscript has been accepted for publication in the WSCAD 2020.
DOI: 10.5281/zenodo.7057510
title: Companion data of Detection, Evaluation and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters

description: This is the companion data repository for the paper entitled <strong>Detection, Evaluation, and Mitigation of Resource Affinity and Communication Contention Problems in a Task-Based Runtime over Heterogeneous Clusters</strong> by Lucas Leandro Nesi and Lucas Mello Schnorr. The manuscript has been accepted for publication in the WSCAD 2020.
DOI: 10.5281/zenodo.7057250
title: Simulator data

description: The archive contains simulator data in csv format and routine in python enabling their post traitement and plotting. A "README" file explains how to use these routines. These data have been stored during the final EFAICTS project evaluations and used in a publication also available on zenodo: 10.5281/zenodo.6796534
description: {"references": ["10.5281/zenodo.6796534"]}
DOI: 10.5281/zenodo.7057249
title: Simulator data

description: The archive contains simulator data in csv format and routine in python enabling their post traitement and plotting. A "README" file explains how to use these routines. These data have been stored during the final EFAICTS project evaluations and used in a publication also available on zenodo: 10.5281/zenodo.6796534
description: {"references": ["10.5281/zenodo.6796534"]}
DOI: 10.5519/qd.kub5kgok
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (8 records)
DOI: 10.6084/m9.figshare.21028777
title: Data used.csv

description: Data has been fully explained in the "Data CODEBOOK" file.
DOI: 10.5519/qd.lgk763qc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (49 records)
DOI: 10.6084/m9.figshare.20401047.v1
title: Exploring the Relation Between Spatial Abilities and STEM Expertise

description: The csv file contains all participants' scores in each spatial thinking factor. The R script contains the necessary workflow for reproducing the results reported in the paper.
DOI: 10.5066/p9bbp9ej
title: Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2021

description: This data release is the update of the U.S. Geological Survey - ScienceBase data release by Bera (2021), with the processed data through September 30, 2021. The primary data for water year 2021 (a water year is the 12-month period, October 1 through September 30, in which it ends) is downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2022) and is processed following the guidelines documented in Over and others (2010). Daily potential evapotranspiration (PET) in thousandths of an inch is computed from average daily air temperature in degrees Fahrenheit (�F), average daily dewpoint temperature in degrees Fahrenheit (�F), daily total wind movement in miles (mi), and daily total solar radiation in Langleys [...]
DOI: 10.21223/vxcfji/8ncov5
title: 01-Acaros-revolcaderos.tab

description: :unav
DOI: 10.21223/vxcfji/gobrsx
title: 02-Acaros-raspados.tab

description: :unav
DOI: 10.21223/rngxzn/erjuif
title: 02-Data-Hemograma_Lucanas.tab

description: :unav
DOI: 10.21223/rngxzn/smiv4h
title: 03-Diccionario-Hemogramas.tab

description: :unav
DOI: 10.21223/rngxzn/xpivgl
title: 01-Data-Hemograma_Cercos.tab

description: :unav
DOI: 10.21223/x5jju1/aludfm
title: 03-Diccionario-Data-Tratamiento-vicuñas.tab

description: :unav
DOI: 10.21223/x5jju1/jjj1u0
title: 01-Data-Tratamientos-vicuñas.tab

description: :unav
DOI: 10.21223/x5jju1/zfyfua
title: 02-Data-Resumen-Tratamientos-vicuñas.tab

description: :unav
DOI: 10.21223/adawwn/bts3i3
title: 1.Base de datos con la determinación de las especies de pastos.tab

description: :unav
DOI: 10.21223/adawwn
title: Dataset for: Determinación de la Diversidad florística de pastizales en los habitat de vicuñas

description: En este dataset se ha evaluado la diversidad de pastos asociados a las zonas de pastizales consumidos por las vicuñas en las zonas de Apurimac, Ayacucho, Cusco, Huancavelica, Junin y Lima. La toma de datos de la vegetación de pastizal, para la estructura y composición florística de los pastizales, se realizó mediante la aplicación del método de transección. En las zonas de estudio se reporto las familias de Cyperaceae, Juncaceae, Plantaginaceae, Poaceae y Rosaceae. Siendo el de mayor porcentaje la familia Asteracea
DOI: 10.21223/adawwn/usyufq
title: 2.Reporte con la descripción botánica de las especies palatables para vicuñas.pdf

description: :unav
DOI: 10.21223/zzam4b/nrwzln
title: 01-Data-Descarte-hemopatogenos-Cerco-Piloto.tab

description: :unav
DOI: 10.21223/zzam4b/fijpgr
title: 02-Data-Descarte-hemopatogenos-Lucanas.tab

description: :unav
DOI: 10.5281/zenodo.7056170
title: SfNet

description: We proposed a novel deep-learning method to invert surface-wave dispersions and obtained an updated <em>Vs</em> model of the Chinese continent. Training a DL inversion network usually requires large amount of complex velocity models, which is labor-intensive and expensive to acquire. Here we relied on synthetics generated automatically from various spline-based <em>Vs</em> models instead of directly using the existing<em> Vs</em> models of an area to build the training dataset, which enhances the generalization of the DL method. In addition, we used a random sampling strategy of the dispersion periods in the training dataset, which alleviates the problem that the real data used must be sampled strictly according to the periods of training dataset.
DOI: 10.5281/zenodo.7056169
title: SfNet

description: We proposed a novel deep-learning method to invert surface-wave dispersions and obtained an updated <em>Vs</em> model of the Chinese continent. Training a DL inversion network usually requires large amount of complex velocity models, which is labor-intensive and expensive to acquire. Here we relied on synthetics generated automatically from various spline-based <em>Vs</em> models instead of directly using the existing<em> Vs</em> models of an area to build the training dataset, which enhances the generalization of the DL method. In addition, we used a random sampling strategy of the dispersion periods in the training dataset, which alleviates the problem that the real data used must be sampled strictly according to the periods of training dataset.
DOI: 10.21223/cyiuhh/6akzge
title: 02-Data-dictionario-EncuestasVicuñas_17-02-22.xlsx

description: :unav
DOI: 10.21223/cyiuhh/twdyxx
title: 01-Data-EncuestasVicuñas_16-02-22.xlsx

description: :unav
DOI: 10.21223/ngvu5n/e2rqmm
title: 01-Data-miembros-hogar-3-8-2022.xlsx

description: :unav
DOI: 10.21223/ohuheq/kyzk1s
title: 04-Datos-herramientas-de-uso-en-la-agricultura.tab

description: :unav
DOI: 10.21223/lnj6hk/uleaf4
title: 01-Encuestas-medios-vida-caracteristicas-del-hogar.tab

description: :unav
DOI: 10.21223/lnj6hk/aqbwtz
title: 02-Diccionario_Encuestas-medios-vida-caracteristicas-del-hogar.xlsx

description: :unav
DOI: 10.5281/zenodo.6541824
title: Dataset_Seeds

description: All data generated and analyzed during the study is available here.
DOI: 10.5281/zenodo.6541825
title: Dataset_Seeds

description: All data generated and analyzed during the study is available here.
DOI: 10.5281/zenodo.6555503
title: Dataset_Seeds

description: All data generated and analyzed during the study is available here.
DOI: 10.5281/zenodo.7057500
title: Dataset_Seeds

description: All data generated and analyzed during the study is available here.
DOI: 10.21223/bgagdn/ihemrk
title: 03-Data-Animales-Crianza-3-7-2022.xlsx

description: :unav
DOI: 10.5281/zenodo.7057563
title: Autonomous Self-burying Seed Carriers for Aerial Seeding

description: The datasets
DOI: 10.5281/zenodo.7057562
title: Autonomous Self-burying Seed Carriers for Aerial Seeding

description: The datasets
DOI: 10.5281/zenodo.6799639
title: Registros notáveis de lagartos através da ciência cidadã

description: Tabela suplementar referente ao artigo: Novos registros dos lagartos <em>Ameivula cipoensis</em> Arias et al., 2014, <em>Enyalius capetinga</em> Breitman et al., 2018, <em>Psilops paeminosus</em> (Rodrigues, 1991) e <em>Tupinambis quadrilineatus</em> Manzani & Abe, 1997 (Squamata) para o estado de Minas Gerais, Brasil, através da ciência cidadã
DOI: 10.5281/zenodo.6799638
title: Registros notáveis de lagartos através da ciência cidadã

description: Tabela suplementar referente ao artigo: Novos registros dos lagartos <em>Ameivula cipoensis</em> Arias et al., 2014, <em>Enyalius capetinga</em> Breitman et al., 2018, <em>Psilops paeminosus</em> (Rodrigues, 1991) e <em>Tupinambis quadrilineatus</em> Manzani & Abe, 1997 (Squamata) para o estado de Minas Gerais, Brasil, através da ciência cidadã
DOI: 10.5066/p9rzpnjr
title: Channel geometry, banklines and floodplain inundation over a range of discharges in two segments of the Missouri National Recreational River, South Dakota and Nebraska, 1955-2018

description: These datasets describe channel adjustments over a 60-year period to dams in the Missouri National Recreational River (MNRR), South Dakota and Nebraska. Datasets include a channel geometry analysis from cross-sections, banklines digitized and interpreted to predict future bank erosion sites from aerial photography, and models of floodplain inundation over a range of discharges. There are two MNRR segments, a 39-mile segment downstream from Fort Randall Dam, and a 59-mile segment downstream from Gavins Point Dam. Similar datasets were analyzed for each MNRR segment using similar methods.
DOI: 10.34740/kaggle/dsv/4172965
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.7057497
title: 50 SERVICIOS ECOSISTEMICOS (Según CICES V5.1) Y 50 STAKEHOLDERS EN RIO TAJO, T.M. DE ARANJUEZ (MADRID)

description: 50 SERVICIOS ECOSISTEMICOS (Según CICES V5.1) Y 50 STAKEHOLDERS EN RIO TAJO, T.M. DE ARANJUEZ (MADRID) para Resumen de XII Congreso Ibérico de Gestión y Planificación del Agua
DOI: 10.5281/zenodo.7057496
title: 50 SERVICIOS ECOSISTEMICOS (Según CICES V5.1) Y 50 STAKEHOLDERS EN RIO TAJO, T.M. DE ARANJUEZ (MADRID)

description: 50 SERVICIOS ECOSISTEMICOS (Según CICES V5.1) Y 50 STAKEHOLDERS EN RIO TAJO, T.M. DE ARANJUEZ (MADRID) para Resumen de XII Congreso Ibérico de Gestión y Planificación del Agua
DOI: 10.6084/m9.figshare.17190167
title: Dados Fenologia - Dalbergia nigra.xlsx

description: Dados enológicos de 4 subpopulações de Dalbergia nigra, observados por 24 meses (julho de 2014-junho de 2016) no Recôncavo da Bahia (Mata Atlântica).Planilha contendo abas com informações das plantas marcadas (matrizes) e avaliadas (Altura das plantas, Altura do fuste, Diâmetro de copa, Diâmetro à altura do peito, Forma da Copa e do Tronco). Dados do ambiente (Fotoperíodo, Temperatura, Chuvas, Solos, Tipo de vegetação) e de variáveis fenógicas vegetativas (Brotação, Queda de Folhas) e reprodutivas (Botão Floral, Flores, Fruto Imaturo, Fruto Maduro e Dispersão de frutos maduros).
DOI: 10.6084/m9.figshare.17190167.v1
title: Untitled Item

description: Dados enológicos de 4 subpopulações de Dalbergia nigra, observados por 24 meses (julho de 2014-junho de 2016) no Recôncavo da Bahia (Mata Atlântica).Planilha contendo abas com informações das plantas marcadas (matrizes) e avaliadas (Altura das plantas, Altura do fuste, Diâmetro de copa, Diâmetro à altura do peito, Forma da Copa e do Tronco). Dados do ambiente (Fotoperíodo, Temperatura, Chuvas, Solos, Tipo de vegetação) e de variáveis fenógicas vegetativas (Brotação, Queda de Folhas) e reprodutivas (Botão Floral, Flores, Fruto Imaturo, Fruto Maduro e Dispersão de frutos maduros).
DOI: 10.6084/m9.figshare.21029482
title: erythroxylum_oxycarpum_decontaminated_FSCR.fasta.gz

description: .......
DOI: 10.6084/m9.figshare.21029482.v1
title: erythroxylum_oxycarpum_decontaminated_FSCR.fasta.gz

description: .......
DOI: 10.6084/m9.figshare.12965270.v4
title: Wind data repository

description: This is a comprehensive repository of spatially and temporally correlated wind velocity samples. The samples are classified based on the maximum sustained wind speed (maximum 1-min average) and the 3-sec gust wind speed (maximum 3-sec average), which are the intensity measures commonly used for structural analysis. The repository consists of 58,000 wind samples with 1-hour duration, as well as 110,847 samples with 2-min and 87,257 wind samples with10-min durations. This database is meant to facilitate researchers and engineers in readily selecting and using wind velocity time histories for many applications, such as the analysis of tall structures located in open terrain areas.
DOI: 10.6084/m9.figshare.12965270.v5
title: Wind data repository

description: This is a comprehensive repository of spatially and temporally correlated wind velocity samples. The samples are classified based on the maximum sustained wind speed (maximum 1-min average) and the 3-sec gust wind speed (maximum 3-sec average), which are the intensity measures commonly used for structural analysis. The repository consists of 58,000 wind samples with 1-hour duration, as well as 110,847 samples with 2-min and 87,257 wind samples with10-min durations. This database is meant to facilitate researchers and engineers in readily selecting and using wind velocity time histories for many applications, such as the analysis of tall structures located in open terrain areas. <br> Preferred citation: Khazaali, M., Christou, V., Bocchini, P. (2022). Classification Protocol and Comprehensive Database of Vertically Correlated Longitudinal Wind Velocities for Structural Analysis and Risk Assessment. <em>Journal of Structural Engineering, ASCE</em>, 148(1), https://doi.org/10.1061/(ASCE)ST.1943-541X.0003227
DOI: 10.6084/m9.figshare.12965270
title: Wind data repository

description: This is a comprehensive repository of spatially and temporally correlated wind velocity samples. The samples are classified based on the maximum sustained wind speed (maximum 1-min average) and the 3-sec gust wind speed (maximum 3-sec average), which are the intensity measures commonly used for structural analysis. The repository consists of 58,000 wind samples with 1-hour duration, as well as 110,847 samples with 2-min and 87,257 wind samples with10-min durations. This database is meant to facilitate researchers and engineers in readily selecting and using wind velocity time histories for many applications, such as the analysis of tall structures located in open terrain areas. <br> Preferred citation: Khazaali, M., Christou, V., Bocchini, P. (2022). Classification Protocol and Comprehensive Database of Vertically Correlated Longitudinal Wind Velocities for Structural Analysis and Risk Assessment. <em>Journal of Structural Engineering, ASCE</em>, 148(1), https://doi.org/10.1061/(ASCE)ST.1943-541X.0003227
DOI: 10.6084/m9.figshare.12965270.v6
title: Wind data repository

description: This is a comprehensive repository of spatially and temporally correlated wind velocity samples. The samples are classified based on the maximum sustained wind speed (maximum 1-min average) and the 3-sec gust wind speed (maximum 3-sec average), which are the intensity measures commonly used for structural analysis. The repository consists of 58,000 wind samples with 1-hour duration, as well as 110,847 samples with 2-min and 87,257 wind samples with10-min durations. This database is meant to facilitate researchers and engineers in readily selecting and using wind velocity time histories for many applications, such as the analysis of tall structures located in open terrain areas. <br> Preferred citation: Khazaali, M., Christou, V., Bocchini, P. (2022). Classification Protocol and Comprehensive Database of Vertically Correlated Longitudinal Wind Velocities for Structural Analysis and Risk Assessment. <em>Journal of Structural Engineering, ASCE</em>, 148(1), https://doi.org/10.1061/(ASCE)ST.1943-541X.0003227