cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2bnvhc
title: CCDC 2164993: Experimental Crystal Structure Determination

description: Related Article: Futo Morita, Juntaro Nogami, Antônio Junio Araujo Dias, Suzuka Kinoshita, Yuki Nagashima, Ken Tanaka|2023|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: 10.5517/ccdc.csd.cc2cqdk2
title: CCDC 2196274: Experimental Crystal Structure Determination

description: Related Article: Xu-Peng Zhang|2023|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: 10.5517/ccdc.csd.cc2cwbqb
title: CCDC 2201022: Experimental Crystal Structure Determination

description: Related Article: Li Ning, Guisheng Li, Michael Konrad, Christoph Kressierer, Bodo Betzemeier, Stephanie C. Kosnik, Lifen Wu, Scott Pennino, Heewon Lee, Yongda Zhang|2023|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: 10.5517/ccdc.csd.cc2d7vgz
title: CCDC 2212081: Experimental Crystal Structure Determination

description: Related Article: Regina G. Szlag, Marcos R. Imer, Leopoldo Suescun, Federico A. Rabuffetti|2023|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.14061431
title: Supporting data for Detecting initial aragonite and calcite variations in limestone-marl alternations

description: Supporting dataset and code for the manuscript "Detecting initial aragonite and calcite variations in limestone-marl alternations" in revision with Sedimentology<b></b>
DOI: 10.3886/e194857
title: Replication Data for J Atack R Margo P Rhode "Deskilling: Evidence from Late Nineteenth Century American Manufacturing," Explorations in Economic History (2023)

description: This project provides a dataset in STATA format and an associated document with explanatory text and STATA commands sufficient to replicate the tables and Figure 2 in Jeremy Atack, Robert Margo, and Paul Rhode, "Deskilling: Evidence from Late Nineteenth Century Manufacturing," Explorations in Economic History (2023), https://doi.org/10.1016/j.eeh.2023.101554
description: Observations in the replication data are "block-links", which are matched pairs of production operations in the manufacturing of highly specific goods. See section 2 of the published article.
DOI: 10.3886/e194857v1
title: Replication Data for J Atack R Margo P Rhode "Deskilling: Evidence from Late Nineteenth Century American Manufacturing," Explorations in Economic History (2023)

description: This project provides a dataset in STATA format and an associated document with explanatory text and STATA commands sufficient to replicate the tables and Figure 2 in Jeremy Atack, Robert Margo, and Paul Rhode, "Deskilling: Evidence from Late Nineteenth Century Manufacturing," Explorations in Economic History (2023), https://doi.org/10.1016/j.eeh.2023.101554
description: Observations in the replication data are "block-links", which are matched pairs of production operations in the manufacturing of highly specific goods. See section 2 of the published article.
DOI: 10.6084/m9.figshare.23261450
title: MapRios

description: <b>Raster dataset of the following manuscript:</b><b>Looking upstream: </b><b>analyzing</b><b> the protection of </b><b>the drainage area of </b><b>Amazon river</b><b>s</b>.<b>Aim:</b><br>We provide explicit spatial information on accumulated deforestation, mining, and protection across the river network.<b>Input datasets:</b><br>We analyze land use and land cover along Amazonian rivers using several datasets. The adopted Amazon Basin limit is provided by the HydroSHEDS level 2 basin product (Lehner et al., 2008), including the Amazon and Tocantins-Araguaia basins. We used the global HydroSHEDS products at 15 arcsecs spatial resolution, based on elevation data obtained in 2000 by NASA's Shuttle Radar Topography Mission (SRTM). HydroSHEDS provides georeferenced hydrographic information at various scales, including river networks, watershed boundaries, drainage directions, and flow accumulations. The deforestation and mining areas in 2020 were obtained from MapBiomas Amazon Project Collection, which contains annual land use and land cover maps for the region based on automatic classification of satellite imagery. The protected areas were obtained from World Database on Protected Areas (WDPA), updated monthly and managed by the United Nations Environment Programme's World Conservation Monitoring Centre.<br>All non-natural land use and land cover classes were reclassified as deforestation areas, reprojected, and downgraded to the Hydrosheds pixel resolution. For this process, we calculated the fraction of each Hydrosheds pixel covered by the 30 m deforested pixels and multiplied the results by the Hydrosheds pixel areas. The MapBiomas project considers mining as all areas of extraction of minerals with soil exposure without differentiating the type of mining (industrial, artisanal, or illegal). Many overlapping PAs in the WDPA with different categories and designations (national, regional, and international PAs) were maintained in this study.<b>Output dataset:</b><br>From the 15 arc-second (~500 m) flow direction matrix, we calculated the upstream area for each pixel (flow accumulation). The next step was to identify the river network, which is considered the channelized river. For this step, a threshold of 20 km² on the flow accumulation matrix was applied to determine the beginning of the river network. A similar method was used to compute the accumulated area occupied by each land use type upstream of the drainage pixel. The value of each feature (deforested/mining/protected areas) accumulated in a pixel equals the sum of the values of the feature areas in all pixels that drain to it, based on their flow direction information. The final step was determining the percentage between each land use accumulated and the contributing area for each river network pixel.<br>
DOI: 10.6084/m9.figshare.23261450.v1
title: MapRios

description: <b>Raster dataset of the following manuscript:</b><b>Looking upstream: </b><b>analyzing</b><b> the protection of </b><b>the drainage area of </b><b>Amazon river</b><b>s</b>.<b>Aim:</b><br>We provide explicit spatial information on accumulated deforestation, mining, and protection across the river network.<b>Input datasets:</b><br>We analyze land use and land cover along Amazonian rivers using several datasets. The adopted Amazon Basin limit is provided by the HydroSHEDS level 2 basin product (Lehner et al., 2008), including the Amazon and Tocantins-Araguaia basins. We used the global HydroSHEDS products at 15 arcsecs spatial resolution, based on elevation data obtained in 2000 by NASA's Shuttle Radar Topography Mission (SRTM). HydroSHEDS provides georeferenced hydrographic information at various scales, including river networks, watershed boundaries, drainage directions, and flow accumulations. The deforestation and mining areas in 2020 were obtained from MapBiomas Amazon Project Collection, which contains annual land use and land cover maps for the region based on automatic classification of satellite imagery. The protected areas were obtained from World Database on Protected Areas (WDPA), updated monthly and managed by the United Nations Environment Programme's World Conservation Monitoring Centre.<br>All non-natural land use and land cover classes were reclassified as deforestation areas, reprojected, and downgraded to the Hydrosheds pixel resolution. For this process, we calculated the fraction of each Hydrosheds pixel covered by the 30 m deforested pixels and multiplied the results by the Hydrosheds pixel areas. The MapBiomas project considers mining as all areas of extraction of minerals with soil exposure without differentiating the type of mining (industrial, artisanal, or illegal). Many overlapping PAs in the WDPA with different categories and designations (national, regional, and international PAs) were maintained in this study.<b>Output dataset:</b><br>From the 15 arc-second (~500 m) flow direction matrix, we calculated the upstream area for each pixel (flow accumulation). The next step was to identify the river network, which is considered the channelized river. For this step, a threshold of 20 km² on the flow accumulation matrix was applied to determine the beginning of the river network. A similar method was used to compute the accumulated area occupied by each land use type upstream of the drainage pixel. The value of each feature (deforested/mining/protected areas) accumulated in a pixel equals the sum of the values of the feature areas in all pixels that drain to it, based on their flow direction information. The final step was determining the percentage between each land use accumulated and the contributing area for each river network pixel.<br>
DOI: 10.6084/m9.figshare.24201603
title: <b>MD package of wtXPD-damaged-ssDNA</b>

description: <b>MD simulation: wtXPD-damaged-ssDNA</b><b>XPD-64PP.tgz</b> and <b>XPD-CPD.tgz</b><br>The 8 µs MD simulations of human XPD bound to damaged ssDNA, containing a 6−4PP (XPD-64PP) or a CPD (XPD-CPD) lesion right outside the entry pore of XPD, are provided.<br><br><b>Descriptions of each simulations</b><br>1. Simulation of XPD-64PP reveals that 6−4PP initially positioned outside the entry pore is translocated in the 3' to 5' direction as its bases flip into the unoccupied space within the pore.<br>2. Simulation of XPD-CPD reveals that CPD initially positioned outside the DNA entry pore undergoes a backbone-translocation into the pore, but its bases are blocked from entering.<br><br><b>Files included</b><br>For each system, the trajectory files are presented in binary NETCDF format, *.nc, a corresponding topology PRMTOP files, *.top, and the coordinates of the initial structure in PDB files, *.pdb are also provided, where * = XPD-64PP, XPD-CPD.<br><br><b>Note</b><br>1. Water molecules and ions are not included in all files.<br>2. The trajectories were saved every 1 ns.<b>Coordinates of the model of XPG-XPD-XPB bound to the open bubble substrate </b><b>XPG-XPD-XPB-initial.pdb</b> and <b>XPG-XPD-XPB-final.pdb</b>XPG-XPD-XPB-initial.pdb: XPD prior to the shift of the Arch domain within the XPG-XPD-XPB-DNA complex. XPG-XPD-XPB-final.pdb: XPD after the shift of the Arch domain within the XPG-XPD-XPB-DNA complex.<b>Note</b><br>This model is derived from the structural model provided by Bralic <i>et al.</i> In this model, XPB and XPD helicase were replaced with those in the exiting cryo-EM structure of TFIIH-XPA-DNA; XPG was replaced with the existing XPG crystal structure PDB 3Q8K.
DOI: 10.6084/m9.figshare.24201603.v1
title: <b>MD package of wtXPD-damaged-ssDNA</b>

description: <b>MD simulation: wtXPD-damaged-ssDNA</b><b>XPD-64PP.tgz</b> and <b>XPD-CPD.tgz</b><br>The 8 µs MD simulations of human XPD bound to damaged ssDNA, containing a 6−4PP (XPD-64PP) or a CPD (XPD-CPD) lesion right outside the entry pore of XPD, are provided.<br><br><b>Descriptions of each simulations</b><br>1. Simulation of XPD-64PP reveals that 6−4PP initially positioned outside the entry pore is translocated in the 3' to 5' direction as its bases flip into the unoccupied space within the pore.<br>2. Simulation of XPD-CPD reveals that CPD initially positioned outside the DNA entry pore undergoes a backbone-translocation into the pore, but its bases are blocked from entering.<br><br><b>Files included</b><br>For each system, the trajectory files are presented in binary NETCDF format, *.nc, a corresponding topology PRMTOP files, *.top, and the coordinates of the initial structure in PDB files, *.pdb are also provided, where * = XPD-64PP, XPD-CPD.<br><br><b>Note</b><br>1. Water molecules and ions are not included in all files.<br>2. The trajectories were saved every 1 ns.
DOI: 10.5281/zenodo.10048442
title: Regridded KNMI-RACMO-ECEARTH pr

description: Dataset KNMI-RACMO-ECEARTH (Bias-adjusted parameters (pr, tas, evappot) for the Netherlands (gridded) from KNMI-RACMO-ECEARTH) regridded to 0.1 degrees on a regular grid using xesmf.
DOI: 10.5281/zenodo.10063412
title: Regridded KNMI-RACMO-ECEARTH pr (missing files)

description: Missing files from Regridded KNMI-RACMO-ECEARTH pr (zenodo.org)
DOI: 10.5281/zenodo.10063413
title: Regridded KNMI-RACMO-ECEARTH pr (missing files)

description: Missing files from Regridded KNMI-RACMO-ECEARTH pr (zenodo.org)
DOI: 10.5281/zenodo.10063500
title: Regridded KNMI-RACMO-ECEARTH evappot

description: Dataset KNMI-RACMO-ECEARTH (Bias-adjusted parameters (pr, tas, evappot) for the Netherlands (gridded) from KNMI-RACMO-ECEARTH) regridded to 0.1 degrees on a regular grid using xesmf.
DOI: 10.5281/zenodo.10063501
title: Regridded KNMI-RACMO-ECEARTH evappot

description: Dataset KNMI-RACMO-ECEARTH (Bias-adjusted parameters (pr, tas, evappot) for the Netherlands (gridded) from KNMI-RACMO-ECEARTH) regridded to 0.1 degrees on a regular grid using xesmf.
DOI: 10.25934/pr00008728
title: Disease modifying anti-rheumatic drugs for rheumatoid arthritis: A network meta-analysis incorporating individual patient data

description: Rheumatoid arthritis (RA) is an autoimmune disease that affects between 0.2% to 0.4% of adults [1]. People living with rheumatoid arthritis experience joint pain, stiffness, impaired function, fatigue and significantly decreased quality of life. While rheumatoid arthritis cannot be cured, there are now many effective medications available. These medications are referred to as disease-modifying antirheumatic drugs (DMARDS) and are the mainstay of RA treatment. They work to control the underlying inflammation that is responsible for peoples’ symptoms. In doing so, they also protect the joints from damage. 

There are now over 20 different DMARDs available for RA. DMARDs can be divided into different categories, based on how they are made and what parts of the immune system they target [2]. Conventional synthetic DMARDs and targeted synthetic DMARDs are both ‘traditional’ medications, in the sense that they are synthetically made. The difference is that the latter were developed with a specific target of the immune system (e.g. cell type or protein) in mind. These medications contrast with biologic DMARDs, which are made biologically (e.g. antibodies) and are much more complex in their structure. Given their complex structure, it is not possible to exactly reproduce biologics. As such, biologics are typically divided into biologic originator or biosimilar DMARDs, according to whether they were the first or subsequent manufacturers. 

Given the many different choices of DMARDs available, we need high-quality evidence that compares the benefits and harms. Network meta-analysis is a method whereby every randomized trial that has been conducted on these treatments is analyzed together as a ‘network’ [3]. A main benefit of network meta-analysis is that it allows all treatments to be compared against one another. Our research group has published several Cochrane reviews of network meta-analyses comparing DMARD treatments in rheumatoid arthritis [4-8]. Recently, we have transitioned these reviews to a ‘living’ mode, whereby the evidence will be updated continuously over time, to take into account new trials that are published [9]. 

While our network meta-analyses allow comparisons between treatments, the comparisons are made using average (group-level) data from the trials. In this study, we will conduct a network meta-analysis using the raw (individual level) data from the clinical trials, where this data is available. This has two main advantages. First, it will allow us to determine whether patients with certain characteristics may respond better to one drug or another. Second, it will allow us to ensure each trial is analyzed using similar approaches. Overall, this will allow us to more robust and personalized data to help patients and their physicians choose between all the DMARD options available.
DOI: 10.5519/qd.ylgwv29c
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (85 records)
DOI: 10.5281/zenodo.10064315
title: Bats generate lower affinity, but higher diversity antibody responses compared to mice, an effect that can be  manipulated with diet
DOI: 10.5281/zenodo.10064314
title: Bats generate lower affinity, but higher diversity antibody responses compared to mice, an effect that can be  manipulated with diet
DOI: 10.6084/m9.figshare.19898048
title: Implementing night light data as auxiliary variable of small area estimation

description: Along with the growing popularity of the small area estimation method, the need to utilize good auxiliary variables also increases. Remote sensing data, such as night light imagery, offers advantages such as time-cost efficiency and global coverage but is easily accessible. This research aims to implement night light intensity as an auxiliary variable for the EBLUP model to estimate per capita consumption expenditure at West Java in 2018. This research employs three scenarios of auxiliary variables usage in EBLUP model construction: official data, night light intensity, and the combination between both data. The results show that night light intensity is an efficient auxiliary variable for estimating per capita consumption expenditure. Furthermore, the EBLUP model with a combination of official data and night light as auxiliary variables gives the best accuracy with coefficient of variation (CV) as evaluation.
DOI: 10.6084/m9.figshare.19898048.v1
title: Implementing night light data as auxiliary variable of small area estimation

description: Along with the growing popularity of the small area estimation method, the need to utilize good auxiliary variables also increases. Remote sensing data, such as night light imagery, offers advantages such as time-cost efficiency and global coverage but is easily accessible. This research aims to implement night light intensity as an auxiliary variable for the EBLUP model to estimate per capita consumption expenditure at West Java in 2018. This research employs three scenarios of auxiliary variables usage in EBLUP model construction: official data, night light intensity, and the combination between both data. The results show that night light intensity is an efficient auxiliary variable for estimating per capita consumption expenditure. Furthermore, the EBLUP model with a combination of official data and night light as auxiliary variables gives the best accuracy with coefficient of variation (CV) as evaluation.
DOI: 10.25573/data.24476686.v1
title: BHL Image Data

description: This data set is a compilation of image data from several sources including:BHL title-levelBHL item-levelBHL page-levelBHL namesBHL Flickr harvestsThis dataset was created for an event held on October 23, 2023 entitled <b><i>Transforming Biodiversity Heritage Library Images - Data Modeling with</i></b><b><i> </i></b><b><i>Open</i></b><b><i>Refine. </i></b>Combined, the 4 files comprise approximately 65MB zipped, and 1.4GB expanded. Each unzipped file is roughly 350MB.<b>Data Dictionary: </b><b>BHL Flickr Images to Wiki Structured Data Commons</b><b>Release Date: </b>23-10-2023<b>Frequency: </b>Infrequent<b>bureauCode:</b> 452:11<b>Access Level:</b> public<b>Rights:</b> http://rightsstatements.org/vocab/NoC-US/<br>
DOI: 10.3886/e113617v1-142779
title: Replication data for: Racial Discrimination in Grading: Evidence from Brazil

description: We investigate whether racial discrimination in the form of biased assessment of students is prevalent within Brazilian schools. Evidence is drawn from unique administrative data pertaining to eighth-grade students and educators. Holding constant performance in blindly-scored tests of proficiency and behavioral traits we find that blacks have lower teacher-assigned math grades than their white classmates. Heterogeneity in differentials provides evidence both of robustness with respect to omission biases and of compatibility with predictions from models of statistical discrimination. (JEL I21, I24, J15, O15)
DOI: 10.5281/zenodo.10051462
title: Phonon-induced geometric chirality - Supporting Data

description: Abinit DFT input and output files used to calculate 3-phonon couplings and nonlinear phonon driving in LiB3O5. See https://github.com/cpromao/phonondriving for post-processing scripts.
DOI: 10.5281/zenodo.10051463
title: Phonon-induced geometric chirality - Supporting Data

description: Abinit DFT input and output files used to calculate 3-phonon couplings and nonlinear phonon driving in LiB3O5. See https://github.com/cpromao/phonondriving for post-processing scripts.
DOI: 10.6073/pasta/a9f0987969d0cff81e2fcfc2f51e5762
title: SBC LTER: Beach: Time series of abundance of birds and stranded kelp on selected beaches, ongoing since 2008

description: Dataset contains the distribution, abundance and seasonal occurrence of birds, humans, dogs, and of freshly stranded giant kelp (Macrocystis pyrifera) plants and holdfasts present during monthly low-tide (&lt;= 2.5 ft) weekday surveys of standard 1 km long transects on selected sandy beaches of the mainland coast of the Santa Barbara Channel. The abundance of humans, dogs, marine mammals and dead or oiled wildlife is also recorded during each survey. Sampling began in 2008 and is ongoing. See Methods for more information.
DOI: 10.5517/ccdc.csd.cc2djsb2
title: CCDC 2220664: Experimental Crystal Structure Determination

description: Related Article: Philipp Royla, Kai Schwedtmann, Zeyu Han, Jannis Fidelius, Derek P. Gates, Rosa M. Gomila, Antonio Frontera, Jan J. Weigand|2023|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: 10.5517/ccdc.csd.cc2djznl
title: CCDC 2220860: Experimental Crystal Structure Determination

description: Related Article: Xiaojun Ding|2023|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: 10.5517/ccdc.csd.cc2f228w
title: CCDC 2236317: Experimental Crystal Structure Determination

description: Related Article: Jinfang Zhang, Quan Chen, Ling Chen, Shunchang Zhao, Chi Zhang|2023|J.Cluster Sci.|34|2891|doi:10.1007/s10876-023-02440-9
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.