cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc26j5lj
title: CCDC 2041337: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc26j5mk
title: CCDC 2041338: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc26j5nl
title: CCDC 2041339: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc26j5pm
title: CCDC 2041340: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc26j5rp
title: CCDC 2041342: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc26j8jk
title: CCDC 2041428: Experimental Crystal Structure Determination

description: Related Article: Shan-Shan Yu, Hai-Rong Zhao, Jian-Han Shi, Hui Zhang, Hai-Bao Duan|2021|CrystEngComm|23|8150|doi:10.1039/D1CE00933H
DOI: 10.5517/ccdc.csd.cc2767j7
title: CCDC 2061578: Experimental Crystal Structure Determination

description: Related Article: Fang-Fang Guo, Bei-Bei Wang, Wei-Na Wu, Wen-Yan Bi, Zhi-Hong Xu, Yun-Chang Fan, Lin-Yan Bian, Yuan Wang|2021|J.Mol.Struct.|1251|132073|doi:10.1016/j.molstruc.2021.132073
DOI: 10.5517/ccdc.csd.cc277gkj
title: CCDC 2062757: Experimental Crystal Structure Determination

description: Related Article: Anke Wilhelm, Susanna L. Bonnet, Linette Twigge, Lucie Rarova, Tereza Stenclova, Hendrik G. Visser, Marietjie Schutte-Smith|2021|J.Mol.Struct.|1251|132001|doi:10.1016/j.molstruc.2021.132001
DOI: 10.5517/ccdc.csd.cc277glk
title: CCDC 2062758: Experimental Crystal Structure Determination

description: Related Article: Anke Wilhelm, Susanna L. Bonnet, Linette Twigge, Lucie Rarova, Tereza Stenclova, Hendrik G. Visser, Marietjie Schutte-Smith|2021|J.Mol.Struct.|1251|132001|doi:10.1016/j.molstruc.2021.132001
DOI: 10.5517/ccdc.csd.cc277gml
title: CCDC 2062759: Experimental Crystal Structure Determination

description: Related Article: Anke Wilhelm, Susanna L. Bonnet, Linette Twigge, Lucie Rarova, Tereza Stenclova, Hendrik G. Visser, Marietjie Schutte-Smith|2021|J.Mol.Struct.|1251|132001|doi:10.1016/j.molstruc.2021.132001
DOI: 10.5517/ccdc.csd.cc277gnm
title: CCDC 2062760: Experimental Crystal Structure Determination

description: Related Article: Anke Wilhelm, Susanna L. Bonnet, Linette Twigge, Lucie Rarova, Tereza Stenclova, Hendrik G. Visser, Marietjie Schutte-Smith|2021|J.Mol.Struct.|1251|132001|doi:10.1016/j.molstruc.2021.132001
DOI: 10.5517/ccdc.csd.cc27b9jf
title: CCDC 2065484: Experimental Crystal Structure Determination

description: Related Article: Zhen Liu, Carla Calvó-Tusell, Andrew Z. Zhou, Kai Chen, Marc Garcia-Borràs, Frances H. Arnold|2021|Nature Chemistry|13|1166|doi:10.1038/s41557-021-00794-z
DOI: 10.5517/ccdc.csd.cc27gf9g
title: CCDC 2069445: Experimental Crystal Structure Determination

description: Related Article: V. Siva, A. Chitra Devi, S. Thangarasu, T.M. Viswanathan, S. Athimoolam, S. Asath Bahadur|2021|J.Mol.Struct.|1250|131866|doi:10.1016/j.molstruc.2021.131866
DOI: 10.5517/ccdc.csd.cc27yxpt
title: CCDC 2084337: Experimental Crystal Structure Determination

description: Related Article: Ying Fang, Yuanyuan Meng, Chunming Yuan, Chunhui Du, Kun-Peng Wang, Shaojin Chen, Zhi-Qiang Hu|2021|Spectrochim.Acta,Part A|267|120575|doi:10.1016/j.saa.2021.120575
DOI: 10.5517/ccdc.csd.cc27z64l
title: CCDC 2084599: Experimental Crystal Structure Determination

description: Related Article: Ying Fang, Yuanyuan Meng, Chunming Yuan, Chunhui Du, Kun-Peng Wang, Shaojin Chen, Zhi-Qiang Hu|2021|Spectrochim.Acta,Part A|267|120575|doi:10.1016/j.saa.2021.120575
DOI: 10.5517/ccdc.csd.cc284rck
title: CCDC 2089938: Experimental Crystal Structure Determination

description: Related Article: André G. de A. Fernandes, Rommel B. Viana, Rodolfo Moreno-Fuquen, Claudia C. Gatto, Ernesto S. Lang, Marcel Z. Modolo, Amandha K. Silva, Sebastião S. Lemos, Adelheid Hagenbach, Ulrich Abram, Victor M. Deflon|2021|J.Mol.Struct.|1250|131875|doi:10.1016/j.molstruc.2021.131875
DOI: 10.5517/ccdc.csd.cc2859sk
title: CCDC 2090478: Experimental Crystal Structure Determination

description: Related Article: Jesse E. Smith, Haifeng Yang, François P. Gabbaï|2021|Organometallics|40|3886|doi:10.1021/acs.organomet.1c00371
DOI: 10.6084/m9.figshare.17185880
title: Supporting data for "Giant Starship elements mobilize accessory genes in diverse fungal genomes"

description: All associated supplementary data, including predicted protein sequences, genome GFFs, repeat libraries, characterized Starship elements, sequence alignments and newick tree files, generated as part of this study can be downloaded here.
DOI: 10.5066/p90j6l48
title: Occupied Range of the Yellowstone Grizzly Bear 2006-2020

description: The grizzly bear distribution boundary represents the estimated geographic extent of occupied range of the Yellowstone grizzly bear population for the period 2006-2020. The distribution boundary was delineated to provide reliable estimations of grizzly bear occupancy throughout time and for use as a monitoring tool in grizzly bear management and conservation.The boundary was delineated by the Interagency Grizzly Bear Study Team (IGBST) using an interpolation method based on grizzly bear VHF telemetry and GPS locations as well as verified observations and signs of grizzly bears inside the Greater Yellowstone Ecosystem during 2006 to 2020.
DOI: 10.6084/m9.figshare.14832396
title: BookChapter_ExcitedStatePropertyLearning_CaseStudy2

description: Data set and trained ML models for chapter 20 "Learning Excited State Properties" of "Quantum Chemistry in the Age of Machine Learning" edited by Pavlo Dral.
DOI: 10.5281/zenodo.5776541
title: Data, code, and manual for analysis of image heterogeneity in mass spectrometric imaging.

description: This upload contains all replication material for "The software for interactive evaluation of mass spectrometric imaging heterogeneity" (forthcoming). <strong>Authors:</strong> E.S. Zhvansky, E.V. Zhdanova, M.S. Belenikin, M.A. Shamraeva, S.V. Silkin, K.V. Bocharov, A.A. Sorokin. <strong>Code, manual, and data are located within Interactive_CSMM.zip</strong><strong>.</strong> Code is written MATLAB R2019b and Python 3.5.2. Please find the README.md for code using and the code to replicate the main findings of the paper described below: imzml2mat.py in conversion directory for file conversion. CSMM.m for application start. 40TopL,10TopR,30BottomL,20BottomR-centroid.mat - data in conversion/Data directory for reproducing the results. User_manual.pdf - manual. mp4 files - screencasts.
DOI: 10.5281/zenodo.5776540
title: Data, code, and manual for analysis of image heterogeneity in mass spectrometric imaging.

description: This upload contains all replication material for "The software for interactive evaluation of mass spectrometric imaging heterogeneity" (forthcoming). <strong>Authors:</strong> E.S. Zhvansky, E.V. Zhdanova, M.S. Belenikin, M.A. Shamraeva, S.V. Silkin, K.V. Bocharov, A.A. Sorokin. <strong>Code, manual, and data are located within Interactive_CSMM.zip</strong><strong>.</strong> Code is written MATLAB R2019b and Python 3.5.2. Please find the README.md for code using and the code to replicate the main findings of the paper described below: imzml2mat.py in conversion directory for file conversion. CSMM.m for application start. 40TopL,10TopR,30BottomL,20BottomR-centroid.mat - data in conversion/Data directory for reproducing the results. User_manual.pdf - manual. mp4 files - screencasts.
DOI: 10.5281/zenodo.5776521
title: Dataset of plasma non-esterified fatty acid concentrations response of a suckling cow exposed to a feed restriction

description: The detaset describes the response of a suckler cow in terms of plasma non-esterified fatty-acids (NEFA) concentrations, that was exposed to a feed restriction that consisted in the reduction of net energy requirements by 50%. The dataset has two columns, one for time (t) in days (d) and another column for plasma NEFA concentrations (g·L<sup>-1</sup>). The feed restriction started at t = 1 d and lasted untill t = 4 d. Negative values for t represent the pre-challenge period.
DOI: 10.5281/zenodo.5776520
title: Dataset of plasma non-esterified fatty acid concentrations response of a suckling cow exposed to a feed restriction

description: The detaset describes the response of a suckler cow in terms of plasma non-esterified fatty-acids (NEFA) concentrations, that was exposed to a feed restriction that consisted in the reduction of net energy requirements by 50%. The dataset has two columns, one for time (t) in days (d) and another column for plasma NEFA concentrations (g·L<sup>-1</sup>). The feed restriction started at t = 1 d and lasted untill t = 4 d. Negative values for t represent the pre-challenge period.
DOI: 10.5281/zenodo.5776439
title: Risk of bias assessments for the Cochrane review 'SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19'

description: Risk of bias assessments and support for judgement with ROB 2 tool for the Cochrane Review: SARS-CoV-2-neutralising monoclonal antibodies to prevent COVID-19.
description: funded by the Federal Ministry of Education and Research, Germany (NaFoUniMedCovid19, funding number: 01KX2021; part of the project "COVIM")
DOI: 10.5281/zenodo.5111402
title: Serial Isomorphous Replacement Data -Pilatus3 2M raw images and meta data

description: Diffraction data collected from the ESRF ID23-EH2 microfocus beamline for the purpose of single isomorphous replacement phasing. These are raw CBF images from a pilatus3 2M detector. The "process" sub directory and CBF headers contain meta data about the experimental setup. Data were collected with the Mesh and Collect workflow and contain partial datasets of ~10 degrees with 0.1 degree oscillations (more detail in the meta data files).
DOI: 10.5281/zenodo.5111401
title: Serial Isomorphous Replacement Data -Pilatus3 2M raw images and meta data

description: Diffraction data collected from the ESRF ID23-EH2 microfocus beamline for the purpose of single isomorphous replacement phasing. These are raw CBF images from a pilatus3 2M detector. The "process" sub directory and CBF headers contain meta data about the experimental setup. Data were collected with the Mesh and Collect workflow and contain partial datasets of ~10 degrees with 0.1 degree oscillations (more detail in the meta data files).
DOI: 10.6084/m9.figshare.13249718
title: μCT dataset for cranial remains of ZIN PH 5/250

description: ZIN PH 5/250 was µ-CT scanned using Phoenix v|tome|x L 240/300 & L 450 (GE Measurement & Control Solutions) at the Skoltech Center for Hydrocarbon Recovery (Moscow, Russia) with the following parameters: voltage of 200 kV, current of 200 µA. The total of 2400 images (2024x2024 pixel in size) were acquired at a resolution of 33.592 µm of an isotropic voxel size.
DOI: 10.6084/m9.figshare.13249718.v1
title: μCT dataset for cranial remains of ZIN PH 5/250

description: ZIN PH 5/250 was µ-CT scanned using Phoenix v|tome|x L 240/300 & L 450 (GE Measurement & Control Solutions) at the Skoltech Center for Hydrocarbon Recovery (Moscow, Russia) with the following parameters: voltage of 200 kV, current of 200 µA. The total of 2400 images (2024x2024 pixel in size) were acquired at a resolution of 33.592 µm of an isotropic voxel size.
DOI: 10.5066/p9vgnfbo
title: Locations of Dams and Basins in South Carolina, derived from U.S. Army Corps Engineers National Inventory of Dams

description: Reliable peak-streamflow information is critical for proper design of stream-related infrastructure, such as bridges, and StreamStats is a Web-based Geographic Information Systems (GIS) application that provides a user-friendly interface to estimate peak flows (https://streamstats.usgs.gov/ss/). StreamStats develops these peak-flow estimates using basin characteristics for the entire contributing area to a user-selected point; however, infrastructure planners often need to estimate flows for an area downstream from a known control such as a reservoir release or a weir. This dataset was compiled in cooperation with the South Carolina Department of Transportation (SCDOT) to provide a GIS layer of filtered regulation points from the U.S. Army Corps Engineers (USACE) National Inventory of Dams and upstream basin polygons for those points, for use within the South Carolina StreamStats client application. A select few characteristics were computed for each basin in the polygon dataset to enable the application to estimate flows above and below each regulation point and better assist SCDOT personnel when designing new or revising existing stream-related infrastructure.
DOI: 10.5281/zenodo.5775149
title: List of all proteins and chemicals mentioned in COVID-19 clinical trials

description: A record of all COVID-19 related clinical trials is provided in the database hosted at https://ClinicalTrials.gov. This is an important resource that tracks worldwide research efforts directed towards improvements in treating the pandemic. To help unlock the insights buried in this database, in this work we have created an automated text mining pipeline that dynamically tags chemical, protein, and gene names in all COVID-19 related database entries, as the database is updated. We plan to publish further details in a subsequent publication.
DOI: 10.5281/zenodo.5775148
title: List of all proteins and chemicals mentioned in COVID-19 clinical trials

description: A record of all COVID-19 related clinical trials is provided in the database hosted at https://ClinicalTrials.gov. This is an important resource that tracks worldwide research efforts directed towards improvements in treating the pandemic. To help unlock the insights buried in this database, in this work we have created an automated text mining pipeline that dynamically tags chemical, protein, and gene names in all COVID-19 related database entries, as the database is updated. We plan to publish further details in a subsequent publication.
DOI: 10.5281/zenodo.5775095
title: multilabel datasets

description: multilabel datasets
DOI: 10.5281/zenodo.5775094
title: multilabel datasets

description: multilabel datasets
DOI: 10.3886/e113098v1-104480
title: Replication data for: Geographic Dispersion of Economic Shocks: Evidence from the Fracking Revolution

description: We track the geographic and temporal propagation of local economic shocks from new oil and gas production generated by hydrofracturing. Each million dollars of new production produces $80,000 in wage income and $132,000 in royalty and business income within a county. Within 100 miles, one million dollars of new production generates $257,000 in wages and $286,000 in royalty and business income. Roughly two-thirds of the wage income increase persists for two years. Assuming no general equilibrium effects, new extraction increased aggregate US employment by as many as 640,000, and decreased the unemployment rate by 0.43 during the Great Recession.
DOI: 10.7931/h44e-wh90
title: NZGBS 2017 | Trend estimates
DOI: 10.6084/m9.figshare.5545639.v1
title: DLS-100 Solubility Dataset

description: 100 Molecules with measured and reported intrinsic aqueous solubilities, together with a suggested 75-25 training-test split. <br>
DOI: 10.7931/7mqz-sw15
title: NZGBS 2018 | Trend estimates
DOI: 10.7931/eqg5-y240
title: NZGBS 2019 | Trend estimates
DOI: 10.18112/openneuro.ds002814.v1.2.2
title: A Multimodal Neuroimaging Dataset to Study Spatiotemporal Dynamics of Visual Processing in Humans
DOI: 10.5517/ccdc.csd.cc2879g9
title: CCDC 2092390: Experimental Crystal Structure Determination

description: Related Article: André G. de A. Fernandes, Rommel B. Viana, Rodolfo Moreno-Fuquen, Claudia C. Gatto, Ernesto S. Lang, Marcel Z. Modolo, Amandha K. Silva, Sebastião S. Lemos, Adelheid Hagenbach, Ulrich Abram, Victor M. Deflon|2021|J.Mol.Struct.|1250|131875|doi:10.1016/j.molstruc.2021.131875
DOI: 10.5517/ccdc.csd.cc289yn6
title: CCDC 2094938: Experimental Crystal Structure Determination

description: Related Article: Gurjaspreet Singh, Pawan, Mohit, Diksha, Suman, Priyanka, Sushma, Anamika Saini, Amarjit Kaur|2021|J.Mol.Struct.|1250|131858|doi:10.1016/j.molstruc.2021.131858
DOI: 10.5517/ccdc.csd.cc28bq7l
title: CCDC 2095669: Experimental Crystal Structure Determination

description: Related Article: Jérôme Long, Aleksei O. Tolpygin, Anton V. Cherkasov, Yulia V. Nelyubina, Yannick Guari, Joulia Larionova, Alexander A. Trifonov|2021|CrystEngComm|23|8351|doi:10.1039/D1CE01266E
DOI: 10.5517/ccdc.csd.cc28bq8m
title: CCDC 2095670: Experimental Crystal Structure Determination

description: Related Article: Jérôme Long, Aleksei O. Tolpygin, Anton V. Cherkasov, Yulia V. Nelyubina, Yannick Guari, Joulia Larionova, Alexander A. Trifonov|2021|CrystEngComm|23|8351|doi:10.1039/D1CE01266E
DOI: 10.5517/ccdc.csd.cc28bq9n
title: CCDC 2095671: Experimental Crystal Structure Determination

description: Related Article: Jérôme Long, Aleksei O. Tolpygin, Anton V. Cherkasov, Yulia V. Nelyubina, Yannick Guari, Joulia Larionova, Alexander A. Trifonov|2021|CrystEngComm|23|8351|doi:10.1039/D1CE01266E
DOI: 10.5517/ccdc.csd.cc28d573
title: CCDC 2097064: Experimental Crystal Structure Determination

description: Related Article: Ruslan V. Fauziev, Roman E. Ivanov, Ilya V. Kuchurov, Sergei G. Zlotin|2021|Green Chemistry|23|10137|doi:10.1039/D1GC03161A
DOI: 10.5517/ccdc.csd.cc28jrp8
title: CCDC 2101480: Experimental Crystal Structure Determination

description: Related Article: Jean-Baptiste Garsi, Pedro M. Aguiar, Stephen Hanessian|2021|J.Org.Chem.|86|16834|doi:10.1021/acs.joc.1c02061
DOI: 10.5517/ccdc.csd.cc28jrq9
title: CCDC 2101481: Experimental Crystal Structure Determination

description: Related Article: Jean-Baptiste Garsi, Pedro M. Aguiar, Stephen Hanessian|2021|J.Org.Chem.|86|16834|doi:10.1021/acs.joc.1c02061
DOI: 10.5517/ccdc.csd.cc28jrrb
title: CCDC 2101482: Experimental Crystal Structure Determination

description: Related Article: Jean-Baptiste Garsi, Pedro M. Aguiar, Stephen Hanessian|2021|J.Org.Chem.|86|16834|doi:10.1021/acs.joc.1c02061
DOI: 10.5281/zenodo.5722347
title: Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill Protected Area funding gaps

description: Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction. Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD &gt;$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M–$1.7 B/year (at USD $13/ton). We highlighted variable but significant PCR for savanna PAs from USD $1.5–$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators. <br> <br> Open Access article: https://doi.org/10.1016/j.oneear.2021.11.013
description: Provided here are two tables and five zipped shapefiles and associated readme files. The tables expand on the information provided in the publication (https://doi.org/10.1016/j.oneear.2021.11.013). The shapefiles include the data used to produce figures 1 and 2 in the publication and figure S1 in the supplementary information. Table columns are often labeled as Mt for metric tonnes, not megatonnes. All emissions data expressed as tCO2eq/yr. Read the methods section in the publication for more details.
DOI: 10.5281/zenodo.5722346
title: Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill Protected Area funding gaps

description: Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction. Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD &gt;$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M–$1.7 B/year (at USD $13/ton). We highlighted variable but significant PCR for savanna PAs from USD $1.5–$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators. <br> <br> Open Access article: https://doi.org/10.1016/j.oneear.2021.11.013
description: Provided here are two tables and five zipped shapefiles and associated readme files. The tables expand on the information provided in the publication (https://doi.org/10.1016/j.oneear.2021.11.013). The shapefiles include the data used to produce figures 1 and 2 in the publication and figure S1 in the supplementary information. Table columns are often labeled as Mt for metric tonnes, not megatonnes. All emissions data expressed as tCO2eq/yr. Read the methods section in the publication for more details.
DOI: 10.25345/c5rp20
title: MassIVE MSV000088554 - A Comparative Study of Human Testes and Epididymis through the Proteomics and RNA-seq Methods
title: A Comparative Study of Human Testes and Epididymis through the Proteomics and RNA-seq Methods &lt;ul&gt;&lt;li&gt;Dataset imported into MassIVE from &lt;a href="https://www.iprox.cn/page/project.html?id=IPX0003098000"&gt;https://www.iprox.cn/page/project.html?id=IPX0003098000&lt;/a&gt; on 12/10/21&lt;/li&gt;&lt;/ul&gt;