cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35078/pmqmfw
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Caratinga | Município: Lamim

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.5281/zenodo.7870981
title: desmognathus_fuscus_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7870980
title: desmognathus_fuscus_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7767339
title: Archived Data - Genetic breaks caused by ancient forest fragmentation: phylogeography of Staudtia kamerunensis (Myristicaceae) reveals distinct clusters in the Congo Basin

description: List of the 400 genotyped <em>Staudtia kamerunensis</em><em> </em>accessions from Central Africa included in Vanden Abeele & Matvijev et al. 2023 - Tree Genetics & Genomes, and the corresponding alleles for each of the 14 microsatellite markers (0-0 indicates missing alleles)
DOI: 10.5281/zenodo.7767340
title: Archived Data - Genetic breaks caused by ancient forest fragmentation: phylogeography of Staudtia kamerunensis (Myristicaceae) reveals distinct clusters in the Congo Basin

description: List of the 400 genotyped <em>Staudtia kamerunensis</em><em> </em>accessions from Central Africa included in Vanden Abeele & Matvijev et al. 2023 - Tree Genetics & Genomes, and the corresponding alleles for each of the 14 microsatellite markers (0-0 indicates missing alleles)
DOI: 10.5281/zenodo.7870197
title: Exploring the Impact of Negative Sampling on Patent Citation Recommendation

description: <strong>pcr_patents.csv </strong>is the dataset which is generated by collecting samples randomly from Google Patents by exploiting a Python library. The dataset comprises around 250,000 US patents and their titles, abstracts, and citations. Each patent has roughly on average 27 citations. The zip file contains 3 different datasets for training and testing patent citation recommendation systems. These datasets were generated by utilizing the main dataset. They consist of around 1 million instances which are positive as well as negative samples. <strong>pcr_cpc_negative_sample_data.csv</strong> consists of negative samples that were generated based on CPC subclass codes. <strong>pcr_random_negative_sample_data.csv</strong> consists of negative samples that were generated randomly. <strong>pcr_sem_sim_negative_sample_data_2.csv</strong> consists of negative samples that were generated based on nearest neighbor relation.
DOI: 10.5281/zenodo.7870196
title: Exploring the Impact of Negative Sampling on Patent Citation Recommendation

description: <strong>pcr_patents.csv </strong>is the dataset which is generated by collecting samples randomly from Google Patents by exploiting a Python library. The dataset comprises around 250,000 US patents and their titles, abstracts, and citations. Each patent has roughly on average 27 citations. The zip file contains 3 different datasets for training and testing patent citation recommendation systems. These datasets were generated by utilizing the main dataset. They consist of around 1 million instances which are positive as well as negative samples. <strong>pcr_cpc_negative_sample_data.csv</strong> consists of negative samples that were generated based on CPC subclass codes. <strong>pcr_random_negative_sample_data.csv</strong> consists of negative samples that were generated randomly. <strong>pcr_sem_sim_negative_sample_data_2.csv</strong> consists of negative samples that were generated based on nearest neighbor relation.
DOI: 10.15151/esrf-dc-1183031629
title: NORWAY BAG

description: The fifteen PIs associated to this proposal represent the entire crystallography community in Norway and are affiliated to the major Norwegian universities. The research interests of the PIs and their collaborators revolves around topics linked to structural biology and material sciences. Examples of research projects or topics are carbohydrate-active proteins of medical or bioeconomic relevance, inhibition of DNA repair enzymes, metalloprotein function and catalysis, regulation of cell-cycle processes, enzyme discovery, antibiotic resistance/drug-discovery and neurological diseases. Our overarching aim is to use bright synchrotron sources to produce high quality science.
DOI: 10.34740/kaggle/dsv/5539703
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.7858909
title: Supplementary movies and datasets of the paper: Precise targeting for 3D cryo-correlative light and electron microscopy volume imaging of tissues using a FinderTOP

description: Imaging data supporting the paper: Precise targeting for 3D cryo-correlative light and electron microscopy volume imaging of tissues using a FinderTOP, containing raw and processed data from fluorescent and electron microscopy.
DOI: 10.5281/zenodo.7858908
title: Supplementary movies and datasets of the paper: Precise targeting for 3D cryo-correlative light and electron microscopy volume imaging of tissues using a FinderTOP

description: Imaging data supporting the paper: Precise targeting for 3D cryo-correlative light and electron microscopy volume imaging of tissues using a FinderTOP, containing raw and processed data from fluorescent and electron microscopy.
DOI: 10.35078/ds0e1w
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Caratinga | Município: Manhumirim

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) ) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.6084/m9.figshare.22708972
title: Rhodesian Bush War - TikTok video and comment data set

description: Rhodesian Bush War TIkTok mp4 videos and comments (in Excel and Word) format
DOI: 10.6084/m9.figshare.22708972.v1
title: Rhodesian Bush War - TikTok video and comment data set

description: Rhodesian Bush War TIkTok mp4 videos and comments (in Excel and Word) format
DOI: 10.5281/zenodo.7870477
title: NCEDs drive Rising but not Peaking abscisic acid profiles in diverging conifer species

description: Datasets supporting experimental results: <strong>MWP data</strong>: Soil water content and Midday water potential readings of experimental trees across three drought trials <strong>ABA data</strong>: Abscisic acid quantitation of experimental trees at selected time points, across three drought trials (species re-tested in trial 2 not included). <strong>Gene expression data</strong>: transcript levels of target ABA-related genes, normalised versus controls and housekeeping genes (first drought trial).
DOI: 10.5281/zenodo.7870476
title: NCEDs drive Rising but not Peaking abscisic acid profiles in diverging conifer species

description: Datasets supporting experimental results: <strong>MWP data</strong>: Soil water content and Midday water potential readings of experimental trees across three drought trials <strong>ABA data</strong>: Abscisic acid quantitation of experimental trees at selected time points, across three drought trials (species re-tested in trial 2 not included). <strong>Gene expression data</strong>: transcript levels of target ABA-related genes, normalised versus controls and housekeeping genes (first drought trial).
DOI: 10.5281/zenodo.7806129
title: Historical (1979 - 2020) data for anthropogenic inputs to a catchment and riverine mainstem exports for carbon, nitrogen, and phosphorus

description: We estimated the difference in Net Anthropogenic Nitrogen and Phosphorus Inputs (NANI-NAPI) at the finest scale possible (the municipality) in the <em>Rivière du Nord</em> watershed (Québec, Canada) between 1981 and 2016. The dataset here reports the delta between those two years for each municipality in the watershed. Three sites along the mainstem of <em>Rivière du Nord </em>have been sampled ~bi-monthly from ~1979 - 2020 for dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP), from which we estimated annual riverine export at each site. We also include annual precipitation (as the sum of rain and snow), and NANI-NAPI interpolated for each sub-watershed for 1981, 1986, 1991, 1996, 2001, 2006, 2011, and 2016.
DOI: 10.5281/zenodo.7871068
title: Data set

description: Data for the article
DOI: 10.5281/zenodo.7871067
title: Data set

description: Data for the article
DOI: 10.5281/zenodo.7871030
title: CHclim25 - aridity index (AI)

description: Aridity index is calculated as in the CGIAR/CSI dataset from CHclim25 sum of precipitation (Prec) and CHclim25 potential evapotranspiration (etp). Yearly individual years, current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.5281/zenodo.7871029
title: CHclim25 - aridity index (AI)

description: Aridity index is calculated as in the CGIAR/CSI dataset from CHclim25 sum of precipitation (Prec) and CHclim25 potential evapotranspiration (etp). Yearly individual years, current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.21954/ou.rd.22659331
title: NGIMU Inertial Sensor Dataset

description: This dataset contains time series data of human joint angles collected using MoJoXlab sensor systems during various activities such as walking, jumping, squatting, and leg exercises. The dataset includes data for basic activities such as walking, sitting and relaxing, standing, lying down (supine position), jumping, and squatting. Additionally, it includes data for seated active and assisted knee extension/flexion and heel slide exercises. The data were collected at a sampling frequency of 50 Hz and exported as CSV files from both Xsens (https://www.xsens.com/) and NGIMU (https://x-io.co.uk/ngimu/) software. The joint angles were calculated using MoJoXlab software, which utilizes quaternion values to estimate the orientation of the sensors. The dataset consists of time series data collected from 15 participants using two sensor systems, Xsens and NGIMU, during various lower limb movements. The data were collected at a sampling frequency of 50 Hz and exported as CSV files. The dataset includes quaternion values for orientation, specifically for the left thigh (LT), right thigh (RT), left shank (LS), right shank (RS), left foot (LF), right foot (RF), and pelvis. The sensor positions are recommended by Xsens lower limb protocol. The column headers indicate the orientation (i.e., W, X, Y, Z and q0, q1, q2, q3), and P01_LT denotes participant 1 data for the left thigh sensor position. The dataset is useful for researchers and practitioners interested in studying human movement and developing algorithms for joint angle estimation. The data can be used to compare and validate different sensor systems and algorithms for estimating joint angles and develop and test new algorithms. The data can be downloaded and used for non-commercial research purposes with proper attribution to the authors and the data source.
DOI: 10.5281/zenodo.7870918
title: CHclim25 - potential evapotranspiration (etp)

description: Potential evapotranspiration is calculated according to the Turc method from solar radiation, and CHclim25 average temperature (Tave) and CHclim25 relative sunshine duration (Srel) . Monthly and yearly current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.5281/zenodo.7870917
title: CHclim25 - potential evapotranspiration (etp)

description: Potential evapotranspiration is calculated according to the Turc method from solar radiation, and CHclim25 average temperature (Tave) and CHclim25 relative sunshine duration (Srel) . Monthly and yearly current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>layers can be downloaded from separate zip files. Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the CH2018 initiative. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5) The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).
DOI: 10.21954/ou.rd.22659370
title: XSENS Inertial Sensor Dataset

description: This dataset contains time series data of human joint angles collected using MoJoXlab sensor systems during various activities such as walking, jumping, squatting, and leg exercises. The dataset includes data for basic activities such as walking, sitting and relaxing, standing, lying down (supine position), jumping, and squatting. Additionally, it includes data for seated active and assisted knee extension/flexion and heel slide exercises. The data were collected at a sampling frequency of 50 Hz and exported as CSV files from both Xsens (https://www.xsens.com/) and NGIMU (https://x-io.co.uk/ngimu/) software. The joint angles were calculated using MoJoXlab software, which utilizes quaternion values to estimate the orientation of the sensors. The dataset consists of time series data collected from 15 participants using two sensor systems, Xsens and NGIMU, during various lower limb movements. The data were collected at a sampling frequency of 50 Hz and exported as CSV files. The dataset includes quaternion values for orientation, specifically for the left thigh (LT), right thigh (RT), left shank (LS), right shank (RS), left foot (LF), right foot (RF), and pelvis. The sensor positions are recommended by Xsens lower limb protocol. The column headers indicate the orientation (i.e., W, X, Y, Z and q0, q1, q2, q3), and P01_LT denotes participant 1 data for the left thigh sensor position. The dataset is useful for researchers and practitioners interested in studying human movement and developing algorithms for joint angle estimation. The data can be used to compare and validate different sensor systems and algorithms for estimating joint angles and develop and test new algorithms. The data can be downloaded and used for non-commercial research purposes with proper attribution to the authors and the data source.
DOI: 10.5281/zenodo.7870959
title: Carouge pilot: open data for the weather

description: Datasets collected in the NAIADES Carouge pilot and containing all the data related to the weather.
DOI: 10.5281/zenodo.7870958
title: Carouge pilot: open data for the weather

description: Datasets collected in the NAIADES Carouge pilot and containing all the data related to the weather.
DOI: 10.5281/zenodo.7870528
title: NAIADES Dynamical Treatments Suggestion Tool Modelling Dataset

description: This data was generated within the European NAIADES project (grant agreement No 820985) for the development of the Dynamical Treatments Suggestion (DTS) Service. The DTS purpose is the estimation of the most efficient treatments (dosage of coagulant and chlorine) for drinking Water Treatment Plants (dWTPs) whose configuration is: coagulation/sedimentation, filtration and chlorination. The inlet water quality (pH, conductivity and turbidity) of the dWTP is used as input of the service. Then, it suggests the most efficient treatments that guarantee good drinking water quality at the outlet of the dWTP, based on WHO recommendations (turbidity below 5 NTU and chlorine concentration between 0.5 and 1 mg/L). The dataset includes data generated with Stimela, an open source water treatments processes simulation SW; and data collected in a scaled down replica of a real dWTP.
DOI: 10.5281/zenodo.7870529
title: NAIADES Dynamical Treatments Suggestion Tool Modelling Dataset

description: This data was generated within the European NAIADES project (grant agreement No 820985) for the development of the Dynamical Treatments Suggestion (DTS) Service. The DTS purpose is the estimation of the most efficient treatments (dosage of coagulant and chlorine) for drinking Water Treatment Plants (dWTPs) whose configuration is: coagulation/sedimentation, filtration and chlorination. The inlet water quality (pH, conductivity and turbidity) of the dWTP is used as input of the service. Then, it suggests the most efficient treatments that guarantee good drinking water quality at the outlet of the dWTP, based on WHO recommendations (turbidity below 5 NTU and chlorine concentration between 0.5 and 1 mg/L). The dataset includes data generated with Stimela, an open source water treatments processes simulation SW; and data collected in a scaled down replica of a real dWTP.
DOI: 10.5281/zenodo.7826506
title: The relationship between the clinical course of SARS-CoV-2 infection with ACE2 and TMPRSS2 expression and polymorphisms

description: Background<br> The viral S protein and host ACE2 and TMPRSS2 genetic variations may act as a barrier to viral<br> infection or determine susceptibility to COVID-19 infection.<br> Objectives<br> We investigated the relationship between the expression patterns and polymorphisms of the ACE2<br> and TMPRSS2 receptor genes associated with COVID-19 and the clinical course of COVID-19<br> infection.<br> Material and methods<br> We studied 147 COVID-19 patients (41 asymptomatic, 53 symptomatic and 53 treated in intensive<br> care unit (ICU) cases) and 33 healthy controls. ACE2 and TMPRSS2 expressions were determined<br> using the One-Run RT Q-PCR kit. Genotypic distributions of Single Nucleotide Polymorphisms (SNP)<br> of ACE2 and TMPRSS2 were obtained by RT-PCR.<br> Results<br> The expressions of ACE2 and TMPRSS2 were different between SARS-CoV-2 positive and negative<br> groups. ACE2 rs714205GG genotype and G-allele showed significant differences in the SARS-CoV-2<br> positive asymptomatic group. A significant correlation was found between TMPRSS2 rs8134378GA,<br> rs2070788GA, rs7364083GA and rs9974589AC genotypes and SARS-CoV-2 positivity. The<br> rs1978124 C-allele and rs8134378 A-allele were significant in the SARS-CoV-2 positive symptomatic<br> group. TMPRSS2 rs2070788GA was different in all patient groups from the control group. There was a<br> difference between SARS-CoV-2 positive and negative groups for the CTTA haplotype formed by<br> ACE2 variants. The AGCAG and AGAAG haplotypes formed by TMPRSS2 variants were more<br> common in the asymptomatic patient group than in other patient groups.<br> Conclusions<br> Identifying the relationship between host genetic variants and COVID-19 susceptibility will contribute to<br> further studies that will enable new vaccines and potential therapeutic approaches to be applicable.