cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/snpmrt8fj3.1
title: Negative emotional behavior during fentanyl abstinence is mediated by adaptations to nucleus accumbens neuron subtypes: Gene expression analysis

description: For RNA sequencing, only samples with RNA integrity numbers >8 were used. 6 samples/sex/drug/cell-type were submitted for RNA sequencing at the UMSOM Institute for Genome Sciences (IGS) and processed as described previously (Engeln et al., 2020). Libraries were prepared from 10 ng of RNA from each sample using the Smart-Seq v4 kit (Takara). Samples were sequenced on an Illumina HiSeq 4000 with a 75 bp paired-end read. An average of 64–100 million reads were obtained for each sample. Reads were aligned to the mouse genome (Mus_musculus.GRCm38) using TopHat (version 2.0.8; maximum number of mismatches =  2; segment length =  30; maximum multi-hits per read =  25; maximum intron length =  50,000). The number of reads that aligned to the predicted coding regions was determined using HTSeq. We applied two strategies to characterize gene expression changes in these data. First, we sought to identify individual genes with significant gene expression changes following abstinence from fentanyl. We used limma-trend to fit log2-normalized read counts per million to a linear model and tested for significant effects of fentanyl in each cell type, separately in males and in females, as well as treating sex as a covariate. Second, we characterized the effects of fentanyl on gene co-expression networks. As a starting point for this analysis, we used limma-trend to select the set of genes that exhibited a nominally-significant effect (p-value < 0.05) of fentanyl, sex, or cell type. We then used weighted gene co-expression network analysis (WGCNA) to characterize co-expressed modules among these genes, separately within D1 and D2 MSNs. Module detection was performed with the blockwiseModules() function with power = 10, corType = ‘bicor’, networkType = ‘signed’, minModuleSize = 25, reassignThreshold = 0, mergeCutHeight = 0.25, minMEtoStay = 0, and otherwise default parameters. We tested for differential expression of module eigengenes with limma, using posthoc contrasts to estimate effects of fentanyl while adjusting for sex differences, as above. Hub genes for each module were defined by calculating the Pearson correlation between the eigengene and each gene in the module.
DOI: 10.5281/zenodo.7928514
title: Observed and modelled GPP at 61 eddy covariance sites (2007-2018)

description: In the frame of the ECOPROPHET project, data was collected from in situ observations, remote-sensing sources and models for 61 sites. The objective of this project was to improve our understanding of ecosystem productivity and the role of vegetation phenology as a key determinant of ecosystem carbon, water and energy balances. More info and publications can be found at http://ecoprophet.meteo.be<br> This dataset contains timeseries of observed GPP, modelled GPP (using 15 models), along with key hydrometeorological variables (shortwave radiation, air temperature, vapor pressure deficit and soil moisture).<br> The timeseries are at daily resolution, covering the period 2007-2018 (depending on the data availability per site).<br> The dataset is partly extracted from: FLUXNET2015 dataset (Pastorello et al., 2020) and the ICOS ’2018 drought initiative’ dataset (Drought 2018 Team<br> and ICOS Ecosystem Thematic Centre, 2019). Original dataset available at https://fluxnet.org/ and https://www.icos-cp.eu/data-products/ YVR0-4898 ERA5 product (Hersbach et al., 2020); Original dataset available at https://cds.climate.copernicus.eu/ MODIS: Original dataset available at https://modis.gsfc.nasa.gov/data/ SPOT Vegetation/PROBA V: Original dataset available at https://land.copernicus.eu/global/ Downscaled GOME2 SIF product by Duveiller et al. (2020). Original dataset available at https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1 FluxCom product ensemble (Jung et al., 2020). Original dataset available at http://fluxcom.org/ <strong>File descriptions</strong>:<br> README.pdf : description<br> EcopropheciesMeta.txt : metadata<br> EcopropheciesDataset.txt : data More details and analysis of the data can be found in:<br> De Pue, J., Wieneke, Bastos, A., S., Barrios, J.M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers 2023, Agricultural and Forest Meteorology (submitted)
description: Funding by BELSPO STEREO 3 program: * ECOPROPHET, Web: http://ecoprophet.meteo.be, Award: BELSPO STEREO 3 SR/00/334 * ECOPROPHECIES, Web: http://ecoprophet.meteo.be, Award: BELSPO STEREO 3 SR/34/211
DOI: 10.5281/zenodo.7928513
title: Observed and modelled GPP at 61 eddy covariance sites (2007-2018)

description: In the frame of the ECOPROPHET project, data was collected from in situ observations, remote-sensing sources and models for 61 sites. The objective of this project was to improve our understanding of ecosystem productivity and the role of vegetation phenology as a key determinant of ecosystem carbon, water and energy balances. More info and publications can be found at http://ecoprophet.meteo.be<br> This dataset contains timeseries of observed GPP, modelled GPP (using 15 models), along with key hydrometeorological variables (shortwave radiation, air temperature, vapor pressure deficit and soil moisture).<br> The timeseries are at daily resolution, covering the period 2007-2018 (depending on the data availability per site).<br> The dataset is partly extracted from: FLUXNET2015 dataset (Pastorello et al., 2020) and the ICOS ’2018 drought initiative’ dataset (Drought 2018 Team<br> and ICOS Ecosystem Thematic Centre, 2019). Original dataset available at https://fluxnet.org/ and https://www.icos-cp.eu/data-products/ YVR0-4898 ERA5 product (Hersbach et al., 2020); Original dataset available at https://cds.climate.copernicus.eu/ MODIS: Original dataset available at https://modis.gsfc.nasa.gov/data/ SPOT Vegetation/PROBA V: Original dataset available at https://land.copernicus.eu/global/ Downscaled GOME2 SIF product by Duveiller et al. (2020). Original dataset available at https://doi.org/10.2905/21935FFC-B797-4BEE-94DA-8FEC85B3F9E1 FluxCom product ensemble (Jung et al., 2020). Original dataset available at http://fluxcom.org/ <strong>File descriptions</strong>:<br> README.pdf : description<br> EcopropheciesMeta.txt : metadata<br> EcopropheciesDataset.txt : data More details and analysis of the data can be found in:<br> De Pue, J., Wieneke, Bastos, A., S., Barrios, J.M., Liu, L., Ciais, P., Arboleda, A., Hamdi, R., Maleki, M., Maignan, F., Gellens-Meulenberghs, F., Janssens, I., and Balzarolo, M., Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers 2023, Agricultural and Forest Meteorology (submitted)
description: Funding by BELSPO STEREO 3 program: * ECOPROPHET, Web: http://ecoprophet.meteo.be, Award: BELSPO STEREO 3 SR/00/334 * ECOPROPHECIES, Web: http://ecoprophet.meteo.be, Award: BELSPO STEREO 3 SR/34/211
DOI: 10.5517/ccdc.csd.cc2dm7r1
title: CCDC 2223033: Experimental Crystal Structure Determination

description: Related Article: Jinshan Li|2022|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.22810951
title: Matlab code for numerical calculations from Kinematics and dynamics of disclination lines in three-dimensional nematics

description: Code used to perform numerical calculations of disclination lines
DOI: 10.6084/m9.figshare.22810951.v1
title: Matlab code for numerical calculations from Kinematics and dynamics of disclination lines in three-dimensional nematics

description: Code used to perform numerical calculations of disclination lines
DOI: 10.25345/c5t727r8r
title: MassIVE MSV000091924 - GNPS of Turmeric hexane extract positive
title: This is the data of turmeric hexane extract for GNPS networking.
DOI: 10.25403/upresearchdata.22086401
title: Recognition of children's agency in poverty and environmental risk reduction programme

description: This data is aimed at exploring how children's agency is or respected and recognised in a programme directed at reducing poverty and environmental risk at Care- Net Development and Support Organisation.The study adopted a qualitative research approach. Instrumental case study design was utilised to conduct the study, and a purposive sampling of seven child participants (CPs) and three key informant participants (KIs) from the drop-in-centre. Semi-structured, face-to-face interviews were used to collect data, guided by an interview schedule. A six-step thematic analysis was used to analyse the data. Quality of data was ensured through the strategies of credibility, transferability, dependability and confirmability.
DOI: 10.25403/upresearchdata.22086401.v1
title: Recognition of children's agency in poverty and environmental risk reduction programme

description: This data is aimed at exploring how children's agency is or respected and recognised in a programme directed at reducing poverty and environmental risk at Care- Net Development and Support Organisation.The study adopted a qualitative research approach. Instrumental case study design was utilised to conduct the study, and a purposive sampling of seven child participants (CPs) and three key informant participants (KIs) from the drop-in-centre. Semi-structured, face-to-face interviews were used to collect data, guided by an interview schedule. A six-step thematic analysis was used to analyse the data. Quality of data was ensured through the strategies of credibility, transferability, dependability and confirmability.
DOI: 10.6084/m9.figshare.22794359.v1
title: Supplementary Dataset 8 PlasmidReplicons and mlplasmids

description: Supplementary files for a genomic study of OXA-48-producing <em>Klebsiella pneumoniae</em> clinical idoslates.
DOI: 10.5281/zenodo.7928547
title: USEPE Project Scenarios Dataset

description: <strong>Scenarios</strong> Scenario files, with configuration and data, for USEPE simulations, both reference and solution (D2C2) scenarios. <strong>Exercises included</strong> 1. Last Mile Delivery (In directory exercise_1)<br> 2. Emergency Services (In directory exercise_2)<br> 3. Urban Surveillance (In directory exercise_3) Exercise structure: settings file (.cfg) - This file defines the input data to be loaded in a specific experiment. data folder - the input data required for the experiments. Some data is not included due to large size or property restrictions. output - raw outputs obtained from the experiments in the USEPE project scenario - BlueSky scenario files (.scn) required for the experiment <strong>How to</strong><br> See how_to_setup_for_simulations.pptx for step-by-step explanation on how to use these files to create runnable scenarios for BlueSky with the USEPE plugin.<br>
DOI: 10.5281/zenodo.7928546
title: USEPE Project Scenarios Dataset

description: <strong>Scenarios</strong> Scenario files, with configuration and data, for USEPE simulations, both reference and solution (D2C2) scenarios. <strong>Exercises included</strong> 1. Last Mile Delivery (In directory exercise_1)<br> 2. Emergency Services (In directory exercise_2)<br> 3. Urban Surveillance (In directory exercise_3) Exercise structure: settings file (.cfg) - This file defines the input data to be loaded in a specific experiment. data folder - the input data required for the experiments. Some data is not included due to large size or property restrictions. output - raw outputs obtained from the experiments in the USEPE project scenario - BlueSky scenario files (.scn) required for the experiment <strong>How to</strong><br> See how_to_setup_for_simulations.pptx for step-by-step explanation on how to use these files to create runnable scenarios for BlueSky with the USEPE plugin.<br>
DOI: 10.5281/zenodo.7928103
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 1km SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2014. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2013</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.5281/zenodo.7928102
title: MUSES Fractional Vegetation Coverage (FVC) Monthly Global 1km SIN Grid in 2014

description: The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (https://muses.bnu.edu.cn/). This dataset is the MUSES global FVC product at 1 km spatial resolution and monthly temporal resolution. The MUSES FVC product is provided on a Sinusoidal grid and spans from 2000 to 2019 (continuously updated). It was generated from the MUSES LAI product at 1 km resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous. This dataset is the MUSES FVC product in 2014. <em>Please <strong>click here</strong> to download the MUSES FVC product <strong>in 2013</strong></em>, <em>and <strong>click here</strong> to download the MUSES FVC product <strong>in 2015</strong></em>. <strong>Dataset Characteristics:</strong> Spatial Coverage: Global Temporal Coverage: 2014 Spatial Resolution: 1 km Temporal Resolution: 1 month Projection: Sinusoidal Data Format: HDF Scale: 0.004 Valid Range: 0 – 250 <strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong> Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337. If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).
DOI: 10.57841/casdc.0000567
title: 硅基GaN微盘激光器功率-电流曲线数据
DOI: 10.5517/ccdc.csd.cc2bvzhp
title: CCDC 2170883: Experimental Crystal Structure Determination

description: Related Article: Alexis Tigreros, Mario Macías, Jaime Portilla|2022|ChemPhotoChem|6|e202200133|doi:10.1002/cptc.202200133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bvzjq
title: CCDC 2170884: Experimental Crystal Structure Determination

description: Related Article: Alexis Tigreros, Mario Macías, Jaime Portilla|2022|ChemPhotoChem|6|e202200133|doi:10.1002/cptc.202200133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bvzkr
title: CCDC 2170885: Experimental Crystal Structure Determination

description: Related Article: Alexis Tigreros, Mario Macías, Jaime Portilla|2022|ChemPhotoChem|6|e202200133|doi:10.1002/cptc.202200133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bvzls
title: CCDC 2170886: Experimental Crystal Structure Determination

description: Related Article: Alexis Tigreros, Mario Macías, Jaime Portilla|2022|ChemPhotoChem|6|e202200133|doi:10.1002/cptc.202200133
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.57841/casdc.0000568
title: 硅基光调制器数据集
DOI: 10.6084/m9.figshare.22664896.v4
title: Elements and dust input data from Hulugou peat in the northeastern Qinghai-Tibetan Plateau.xlsx

description: The resluts of elements was scanned by X-Ray Fluorescence (XRF) using the Geotek Multi-Sensor Core Loggers (MSCL) XRF core scanner. The grain size distributions of peat samples were determined by a laser-optical particle size analyzer Malvern Mastersizer-2000 and analyzed by parameterization End-member Modelling Analysis (EMA). We stacked a curve with EM1 and Ti components for the reconstructed dust input. The age-depth results are constructed by linear interpolation method, and compared with Bacon age-depth model results.
DOI: 10.6084/m9.figshare.22664896.v3
title: Elements and dust input data from Hulugou peat in the northeastern Qinghai-Tibetan Plateau.xlsx

description: The resluts of elements was scanned by X-Ray Fluorescence (XRF) using the Geotek Multi-Sensor Core Loggers (MSCL) XRF core scanner. The grain size distributions of peat samples were determined by a laser-optical particle size analyzer Malvern Mastersizer-2000 and analyzed by parameterization End-member Modelling Analysis (EMA). We stacked a curve with EM1 and Ti components for the reconstructed dust input. The age-depth results are constructed by linear interpolation method, and compared with Bacon age-depth model results.
DOI: 10.5281/zenodo.7928598
title: Data for "The use of bibliometrics in nursing research: topics, data sources and applications"

description: Dataset to reproduce the analysis of the paper "The use of bibliometrics in nursing research: topics, data sources and applications". It contains a list of 129 nursing bibliometric articles and, or each article, the topic of the study, the data source employed to gather the literature, the time frame, the number of records considered, and whether the article analysed, or not, fourteen variables.
DOI: 10.57841/casdc.0000569
title: 应变锗材料制备及测试性能数据
DOI: 10.6084/m9.figshare.22250185
title: Arabidopsis repeats with templates

description: TRASH run using default settings and sequence templates for CEN178 CEN159 and 5s rDNA
DOI: 10.6084/m9.figshare.22810997
title: Supplementary_Material

description: The three-dimensional structure of AP-III-a4 and ENO1, and PROCHECK assessment results <strong>Supplementary Fig. 1</strong>. Haematological changes after AP-III-a4 treatment in mice
DOI: 10.6084/m9.figshare.22810997.v1
title: Supplementary_Material

description: The three-dimensional structure of AP-III-a4 and ENO1, and PROCHECK assessment results <strong>Supplementary Fig. 1</strong>. Haematological changes after AP-III-a4 treatment in mice
DOI: 10.11583/dtu.22740191
title: Collaboration of Ph.D. fellows in data-intensive research networks: The case of wind energy

description: This metadata record consists of 23 interview transcripts with Ph.D. fellows, who are members of the following four data-intensive wind-energy Innovative Training Networks (ITNs): FLOating Wind Energy NetwoRk (FLOAWER) Lidar Knowledge Europe (LIKE) Novel deSign, producTion and opEration aPproaches for floating WIND turbine farms (STEP4WIND) TRAINing school analysing enTRAINment in offshore WIND farms (Train2Wind) The qualitative interviews are about scientific collaboration within these networks. The Interviewees were assured that the interview transcripts would not be shared in publications. The related journal manuscript has not been submitted yet.
DOI: 10.6084/m9.figshare.22250191
title: Human repeats de novo

description: TRASH run using default settings for human assembly CHM13v2
DOI: 10.6084/m9.figshare.22250191.v1
title: Human repeats de novo

description: TRASH run using default settings for human assembly CHM13v2
DOI: 10.57841/casdc.0000570
title: 低损耗（10dB)单片集成激光器/硅光芯片耦合器的集成
DOI: 10.6084/m9.figshare.22250209
title: Human Higher Order Repeats

description: TRASH HOR output for the CHM13v2 alpha satellite repeats
DOI: 10.6084/m9.figshare.22250326
title: Arabidopsis higher order repeats

description: TRASH HOR output for the <em>Arabidopsis thaliana</em> colCEN CEN178 satellite repeats
DOI: 10.6084/m9.figshare.22250326.v1
title: Arabidopsis higher order repeats

description: TRASH HOR output for the <em>Arabidopsis thaliana</em> colCEN CEN178 satellite repeats
DOI: 10.57841/casdc.0000572
title: GeSn合金生长数据
DOI: 10.5281/zenodo.7928669
title: BLASTDB UniRef100 Virus Sequences 2023/03/01

description: BLASTDB Version: 5<br> UniRef100 Viral Sequences 2023_03_01<br> 3,091,814 sequences; 1,162,982,857 residues; 1 volume
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
description: {"references": ["https://doi.org/10.1093/ve/veaa091", "https://doi.org/10.3390/v15020431"]}
DOI: 10.5281/zenodo.7928668
title: BLASTDB UniRef100 Virus Sequences 2023/03/01

description: BLASTDB Version: 5<br> UniRef100 Viral Sequences 2023_03_01<br> 3,091,814 sequences; 1,162,982,857 residues; 1 volume
description: This database is part of https://bitbucket.org/plyusnin/lazypipe project
description: {"references": ["https://doi.org/10.1093/ve/veaa091", "https://doi.org/10.3390/v15020431"]}