cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc270w27
title: CCDC 2056418: Experimental Crystal Structure Determination

description: Related Article: Yuji Sumii, Kenta Sasaki, Okiya Matsubara, Norio Shibata|2021|Org.Lett.|23|2777|doi:10.1021/acs.orglett.1c00688
DOI: 10.5517/ccdc.csd.cc270ttx
title: CCDC 2056379: Experimental Crystal Structure Determination

description: Related Article: Lu-Lu Xiao, Ning Wang, Bing Zheng, Ji-Ming Yu, Ji-Peng Yu, Huan Wang, Qi Xu, Fang-Fang Cheng, Wei-Wei Xiong|2021|J.Solid State Chem.|298|122109|doi:10.1016/j.jssc.2021.122109
DOI: 10.5517/ccdc.csd.cc270tsw
title: CCDC 2056378: Experimental Crystal Structure Determination

description: Related Article: Lu-Lu Xiao, Ning Wang, Bing Zheng, Ji-Ming Yu, Ji-Peng Yu, Huan Wang, Qi Xu, Fang-Fang Cheng, Wei-Wei Xiong|2021|J.Solid State Chem.|298|122109|doi:10.1016/j.jssc.2021.122109
DOI: 10.5517/ccdc.csd.cc270tvy
title: CCDC 2056380: Experimental Crystal Structure Determination

description: Related Article: Lu-Lu Xiao, Ning Wang, Bing Zheng, Ji-Ming Yu, Ji-Peng Yu, Huan Wang, Qi Xu, Fang-Fang Cheng, Wei-Wei Xiong|2021|J.Solid State Chem.|298|122109|doi:10.1016/j.jssc.2021.122109
DOI: 10.5066/p9svv311
title: Whooping crane migration habitat selection data and distance to wind-energy infrastructure, 2010-2016

description: These data were developed to support an effort to understand how whooping cranes select stopover habitat in the presence of wind-energy infrastructure. Location and associated data came from whooping cranes from the Aransas-Wood Buffalo Population, 2010-2016. We marked a sample of 57 whooping cranes with leg-mounted transmitters that acquired locations via the global positioning system (GPS) network and transmitted those data through the Argos satellite system. Cranes were captured either at their natal areas in and adjacent to Wood Buffalo National Park in Canada or at their winter terminus along the Texas Gulf Coast. Data herein include 9,347 ground locations used by whooping cranes during migration coupled with 19 potentially available locations for each used location (see processing steps for more information). Predictor variables hypothesized to explain variation in space use were included for all locations (used and available).
DOI: 10.5066/p9gueimd
title: Pesticide and Pharmaceutical Exposure Data for Select Streams within Great Smoky Mountains National Park, 2019

description: This dataset included the concentration results (in nanograms per liter) for 328 pharmaceutical and pesticide compounds analyzed within the Great Smoky Mountain National Park, Tennessee and North Carolina, in 2019. Two samples were collected (July and September) at 15 locations within the park, and one location at the park boundary. Samples were analyzed at the National Water Quality Laboratory (NWQL) in Denver, Colorado.
DOI: 10.5066/p95xkxe1
title: T. bryosalmonae detection in fish and water, DNA sequence, and simple sequence repeat data collected in the Inter-Mountain West from 2011 to 2019

description: This data release contains molecular diagnostic results and molecular detection of the myxozoan parasite Tetracapsuloides byrosalmonae in fish tissue and environmental DNA samples collected from the inter-mountain West, USA.
DOI: 10.5066/p97ukynr
title: Groundwater Quality and Plume Boundaries for Select Contaminants of Concern at Badger Army Ammunition Plant, Wisconsin (2000 - 2018)

description: This dataset describes concentrations of select contaminants in groundwater, collected at monitoring wells in the vicinity of the Badger Army Ammunition Plant in Sauk County, Wisconsin, between 2000 - 2018. The data were used to assess trends in contaminant concentrations over time, delineate plume boundaries at various time intervals, and assess the overall monitoring network at the Badger Army Ammunition Plant. The original water quality data were compiled by the U.S. Army Environmental Command (AEC) and SpecPro Professional Services and provided to the U.S. Geological Survey (USGS). A subset of the data were analyzed by the USGS. This subset of data and additional products derived from these data are provided in this dataset. Further details are also provided in the larger work associated with this dataset (Pajerowski et al., 2020). Users should contact the U.S. AEC for questions related to data not described or provided here.
DOI: 10.5066/p9qfbhz3
title: Post-fire Chondrilla juncea and biocontrol at Boise River Wildlife Management Area 2018-2019

description: Top-down and bottom-up factors affecting invasive populations are rarely considered simultaneously, yet their interactive responses to disturbances and management interventions can be essential to understanding invasion patterns. We evaluated post-fire responses of the exotic perennial forb Chondrilla juncea (rush skeletonweed) and its biocontrol agents to landscape factors and a post-fire combined herbicide (imazapic) and bacteria (Pseudomonas fluorescens strain MB906) treatment that targeted invasive annual grasses in a sagebrush steppe ecosystem. Biocontrol agents released against C. juncea in previous decades included Cystiphora schmidti (gall midge), Aceria chondrillae (gall mite), and Puccinia chondrillina (rust fungus). C. juncea abundance was greater in sprayed than unsprayed plots, and where soils were coarser, slopes faced southwest, solar heat loads and topographic water accumulation were greater, and cover of deep-rooted native perennials was lower. Mite infestation was greater in unsprayed plots, midge infestation was greater at higher elevations on steeper slopes, and midges were more abundant while rust was less abundant on gravelly soils. Biocontrol infestation levels varied considerably between years and could not be predicted in 2019 from 2018 infestation levels. Multiple biocontrol species were often present at the same plots but were rarely present on the same C. juncea individuals. These results suggest that spatial patterns of invasion by C. juncea are related to deep-soil water availability, warmer conditions, and alleviation of competition. Treatments designed to reduce invasive annual grasses may inadvertently release C. juncea by both reducing plant competition for soil resources and affecting biocontrol agent (mite) abundance.
DOI: 10.5066/p9g18urx
title: Laboratory data to assess the effect of nanoparticle size and natural organic matter composition on the bioavailability of platinum nanoparticles to a model freshwater invertebrate species

description: Data collected in a series of laboratory experiments conducted with juvenile freshwater snails (Lymnaea stagnalis) reared in the laboratory and exposed to dissolved platinum (Pt), or polyvinylpyrrolidone coated platinum nanoparticles (PtNPs) of five different nominal hydrodynamic diameters in the presence (or absence) of natural organic matter (NOM) are presented in this data release. Files include 1) a data dictionary describing the variables; 2) exposure characteristics of the experimental solutions; 3) Pt concentrations in the experimental organisms; and 4) QA/QC performed during the analysis. Format of the files is comma delimited (*.csv).
DOI: 10.5066/p9l1aylw
title: Habitat and fish assemblages along four river mainstems in Ontario, Canada, 1997 to 2001, with supporting spatial data

description: This dataset includes information about valley segment and catchment summaries, valley characteristics, instream habitat, and fish for valley segments, sites, and transects along four river mainstems in Ontario, Canada. Moving west to east, the rivers include the Grand River which ends in Lake Erie at Port Maitland, the Ganaraska River which ends in Lake Ontario at Port Hope, the Trent River which ends in the Bay of Quinte at Trenton, and the Petawawa River which ends in the Ottawa River at Petawawa. These rivers vary in natural character, anthropogenic development, and fish assemblages. Riverine sites along the mainstems of all four rivers included a total of one hundred and twelve sites. Sampling on the Grand, Trent, and Petawawa Rivers focused on non-wadeable lower river mainstems, whereas all sites on the Ganaraska River mainstem were wadeable and incorporated a wider range of stream sizes. Sites were sampled between 1997 and 2001, with many sites sampled in multiple years. The study design for the Grand, Trent, and Petawawa Rivers include a hierarchical design where data collection was nested at three spatial scales -- shoreline and channel transect data are nested within sites, and sites are nested within valley segments. In the Ganaraska River, data collection was by site and nested within valley segments. A complementary set of shapefiles for each river supports these tabular data and provides items needed to map watersheds, valley segments, and sites, and to calculate additional variables for sites and site catchments. The metadata specific to these spatial data is associated with the shapefiles and is not described here.
DOI: 10.5066/p9rexnq9
title: Data for Specific Gage Analysis on the Patapsco River, 2010-2017

description: The U.S. Geological Survey, in collaboration with American Rivers and other partners, conducted a monitoring program beginning in 2010 to track river response to a series of dam removals on the Patapsco River intended to restore anadromous fish habitat in the watershed. Dam removals included the November 2010 removal of the Simkins dam, a 3.3 m tall and 66 m wide dam, with a reservoir sediment volume of ~67,000 cubic meters. As part of the dam removal monitoring program, three USGS streamgaging stations were established in late 2010 along the mainstem of the Patapsco River to estimate flow and suspended sediment-transport for constraining sediment budgets. USGS 01589000 Patapsco River at Hollofield, MD was reestablished 6 km upstream of the former Simkins dam at a gage location with flow records dating from 1944 and was intended as an upstream reference for the effects of the dam removal sediment pulse. USGS 01589025 Patapsco River near Catonsville, MD was newly constructed at a location ~ 0.5 km downriver of the Simkins dam and was installed to measure sediment released by the Simkins removal. USGS 01589035 Patapsco River near Elkridge, MD was constructed ~5.5 km downstream of the Simkins dam, ~4.2 km downstream of the Bloede dam, and at a lower-gradient reach of the lower Patapsco in the transition from the Piedmont physiographic province into the Coastal Plain. Data collected at the three USGS streamgages were then examined with Specific Stage Analysis, Specific Discharge Analysis, and Field Measurement Analysis, collectively termed Specific Gage Analyses, to track the sediment pulse and changes to river condition through time following the Simkins dam removal. This data release contains five tabular datasets covering the raw snapshot of data obtained from the National Water Information System (NWIS) at the three gages at unit-value (uv_data.csv) and daily-value (dv_data.csv) time scales, results of Specific Stage (Specific_Stage_results.csv) and Specific Discharge Analyses (Specific_Discharge_results.csv), and combined input and results of the Field Measurement Analysis (meas_data_analysis.csv). Data of surveyed field cross sections collected by collaborative research partners (NOAA_CrossSections_Combined.csv) are also provided as ground-truth validation for the Specific Gage Analyses.
DOI: 10.5066/p923xb6l
title: USGS National and Global Oil and Gas Assessment Project -- Horn River Basin, Cordova Embayment, and Liard Basin, Canada, Assessment Unit Boundaries and Assessment Input Forms

description: This data release contains the boundaries of assessment units for the assessment of undiscovered oil and gas resources in the Horn River Basin, Cordova Embayment and Liard Basin in Alberta Basin Province, Canada. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf). See supplemental information for a detailed list of files included this data release.
DOI: 10.6084/m9.figshare.14370011.v1
title: New gene

description: New genes response to CSS
DOI: 10.6084/m9.figshare.14370011.v2
title: New gene

description: New genes response to CSS
DOI: 10.14457/cu.the.1982.2
title: ผลของตัวแปรต่ออัตราการระเหยในเครื่องระเหยแบบแผ่นฟิล์มบางหมุน
DOI: 10.14457/cu.the.1982.3
title: การศึกษาการเสริมธาตุเหล็กในน้ำปลา
DOI: 10.6084/m9.figshare.14370035.v1
title: Gut microbiota OTU Front Immunol 669672.xlsx

description: Gut microbiota of OTUs.3003-3005: HFHSD3013-3015: HTHSD3021-3023: ND
DOI: 10.6084/m9.figshare.14370035
title: Gut microbiota OTU Front Immunol 669672.xlsx

description: Gut microbiota of OTUs.3003-3005: HFHSD3013-3015: HTHSD3021-3023: ND
DOI: 10.6084/m9.figshare.14369555
title: Monodisperse and size-tunable high quality factor microsphere biolasers

description: This is the dataset for the paper entitled "Monodisperse and size-tunable high quality factor microsphere biolasers" submitted to Optics Letters.
DOI: 10.5281/zenodo.4661775
title: Pokemon dataset

description: Pokémon data extrated from the pokedex
DOI: 10.5281/zenodo.4661774
title: Pokemon dataset

description: Pokémon data extrated from the pokedex
DOI: 10.5281/zenodo.4564182
title: NGS Sequencing data from samples derived from the Thessaloniki municipality sewage, across three different time periods

description: The data were produced by targeted sequencing, based on the ARTIC v3 protocol developed by Wellcome Sanger Institute. The samples are paired‐end (Illumina MiSeq platform) with a read length of 2 × 300 bp.
DOI: 10.5281/zenodo.4564181
title: NGS Sequencing data from samples derived from the Thessaloniki municipality sewage, across three different time periods

description: The data were produced by targeted sequencing, based on the ARTIC v3 protocol developed by Wellcome Sanger Institute. The samples are paired‐end (Illumina MiSeq platform) with a read length of 2 × 300 bp.
DOI: 10.6084/m9.figshare.14370275.v1
title: Coronavac vaccinated health-care workers

description: Day 1, day 14 and day 21 antibody responses of Coronavac COVID-19 vaccine
DOI: 10.6084/m9.figshare.14370275
title: Coronavac vaccinated health-care workers

description: Day 1, day 14 and day 21 antibody responses of Coronavac COVID-19 vaccine
DOI: 10.6084/m9.figshare.14370275.v3
title: Coronavac vaccinated health-care workers

description: Day 1, day 14 and day 21 antibody responses of Coronavac COVID-19 vaccine
DOI: 10.6084/m9.figshare.14370275.v2
title: Coronavac vaccinated health-care workers

description: Day 1, day 14 and day 21 antibody responses of Coronavac COVID-19 vaccine
DOI: 10.5281/zenodo.4661779
title: Datasets and R script - Writing process data of typed intransitive, monotransitive and ditransitive sentences of 90 elderly

description: Writing process data of 90 healthy elderly (50 - 90 years) were obtained. Each of them completed a typed sentence production task that consisted of 40 trials. Time on task, production time, and pause times before sentences, between words and within words were logged with a keystroke logging tool (ScriptLog). The data were used to examine the influences of normal ageing and verb transitivity on sentence production. The underlying aim was to provide a foundation for further research on sentence production in Alzheimer's disease (AD). This dataset contains the data that remained after eliminating the first trial of each participant and the trials during which participants did not use the correct target sentence structure (intransitive, monotransitive, ditransitive) or made revisions. The R script that was used for the analyses is also available. The paper is currently under review. The data will be available as soon as it is accepted for publication.
description: This work was supported by the Research Foundation – Flanders [Aspirant 2016, reference number: 1173617N, PS ID: 3330].
DOI: 10.5517/ccdc.csd.cc1pkjzr
title: CCDC 1565995: Experimental Crystal Structure Determination

description: Related Article: Sundarraman Balaji, Gunasekaran Balamurugan, Rengan Ramesh, David Semeril|2021|Organometallics|40|725|doi:10.1021/acs.organomet.0c00814
DOI: 10.5517/ccdc.csd.cc1zjkhk
title: CCDC 1833169: Experimental Crystal Structure Determination

description: Related Article: Sundarraman Balaji, Gunasekaran Balamurugan, Rengan Ramesh, David Semeril|2021|Organometallics|40|725|doi:10.1021/acs.organomet.0c00814
DOI: 10.5517/ccdc.csd.cc257w0b
title: CCDC 2003561: Experimental Crystal Structure Determination

description: Related Article: Yixian Pan, Marc Schnierle, Daniel Auweiler, Mark R. Ringenberg|2021|Organometallics|40|760|doi:10.1021/acs.organomet.1c00010
DOI: 10.5517/ccdc.csd.cc26p121
title: CCDC 2046002: Experimental Crystal Structure Determination

description: Related Article: Hui-Hui Wu, Xiao-Zu Fan, Zhe Tang, Heng Zhang, Lu-Yu Cai, Xiao-Fan Bi, Hong-Wu Zhao|2021|Org.Lett.|23|2802|doi:10.1021/acs.orglett.1c00729
DOI: 10.5517/ccdc.csd.cc26plj1
title: CCDC 2046543: Experimental Crystal Structure Determination

description: Related Article: Jinlei Zhou, Wen Li, Huitao Zheng, Yongyan Pei, Xiang Liu, Hua Cao|2021|Org.Lett.|23|2754|doi:10.1021/acs.orglett.1c00664
DOI: 10.5517/ccdc.csd.cc275tdn
title: CCDC 2061171: Experimental Crystal Structure Determination

description: Related Article: Daniel S. Brandes, Ana Sirvent, Brandon Q. Mercado, Jonathan A. Ellman|2021|Org.Lett.|23|2836|doi:10.1021/acs.orglett.1c00851
DOI: 10.5517/ccdc.csd.cc27683v
title: CCDC 2061596: Experimental Crystal Structure Determination

description: Related Article: Yongjie Chen, Yingqi Zheng, Yuanyuan Jiang, Haijun Fan, Xiaozhang Zhu|2021|J.Am.Chem.Soc.|143|4281|doi:10.1021/jacs.0c12818
DOI: 10.5517/ccdc.csd.cc27684w
title: CCDC 2061597: Experimental Crystal Structure Determination

description: Related Article: Yongjie Chen, Yingqi Zheng, Yuanyuan Jiang, Haijun Fan, Xiaozhang Zhu|2021|J.Am.Chem.Soc.|143|4281|doi:10.1021/jacs.0c12818
DOI: 10.6084/m9.figshare.14221985
title: Data supporting Kuppler & Kotowska (2021) in Global Change Biology

description: This data set & R Code supports the following publication:<br>Kuppler J & Kotowska MM (2021) A meta-analysis of floral trait responses and flower-visitor interaction to water deficit. Global Change Biology, https://doi.org/10.1111/gcb.15621<br>See readme file for further explanation<br>ORCID id <br>Jonas Kuppler: https://orcid.org/0000-0003-4409-9367Martyna M Kotowska: <br>https://orcid.org/0000-0002-2283-5979
DOI: 10.15161/oar.it/73626
title: CovidStat project data

description: This record contains the daily updated data of the CovidStat project. CovidStat is a project carried out by the CovidStat Working Group at INFN, whose creation was promoted within the Italian National Institute of Nuclear Physics with the aim of making a statistical analysis of the data provided daily by the Civil Protection on the spread of the pandemic in Italy. CovidStat data can interactively be browsed at https://covid19.infn.it.
description: The software to process this Root TTree is in the related identifier. Be sure to use the right corresponding version, based on the data in which Root TTree was generated.
DOI: 10.5281/zenodo.4661790
title: City of Trees - Canopy Cover and Treelines of Manchester

description: Canopy cover of Manchester using LIDAR data from Manchester City of Trees. Includes treelines for areas of trees that cannot be measuring using LIDAR
DOI: 10.5281/zenodo.4657023
title: City of Trees - Canopy Cover and Treelines of Manchester

description: Canopy cover of Manchester using LIDAR data from Manchester City of Trees. Includes treelines for areas of trees that cannot be measuring using LIDAR
DOI: 10.5281/zenodo.4661826
title: prism_meta + supporting files

description: Prism meta files for DDH project + supporting files: prism_meta.Rds compound_mesh.Rds compound_descriptions.Rds
DOI: 10.25646/8271
title: Tagesdaten-CSV aus dem DIVI-Intensivregister

description: Die Tagesdaten-CSV entspricht einem Auszug der Daten des DIVI-Intensivregisters. Die Datei enthält eine Aggregation der aktuellsten Meldungen pro Landkreis. Es werden die aktuell gemeldeten Anzahlen der COVID-19 Intensivfälle sowie die gemeldeten intensivmedizinischen Behandlungskapazitäten angezeigt. Die Tagesdaten-CSV liefert dabei ausschließlich einen Blick auf die Daten gemäß dem Stand des betrachteten Tages. Die Daten sind im situationsbedingten Kontext aufbereitet, damit sind verschiedene Tagesdaten-CSVs u.U. nicht direkt miteinander vergleichbar. Die aktuellsten Meldungen werden im gewählten Betrachtungszeitfenster über alle Meldebereiche und Standorte aufsummiert. Weitere Informationen sind zu finden unter https://www.intensivregister.de/#/faq
DOI: 10.21227/0svz-tc51
title: February-6-Basu-Sukanta

description: February-6-Basu-Sukanta
DOI: 10.34740/kaggle/dsv/1617305
title: Aviation Accident Database & Synopses
DOI: 10.5281/zenodo.4661849
title: Galaxy history for the ToolFactory in Planemo.

description: Import this history into the planemo tool_factory Galaxy It contains a variety of simple demonstrations of ToolFactory generated tools
DOI: 10.21227/xggk-cm50
title: Load forecasting

description: Submission 06 Feb
DOI: 10.34740/kaggle/dsv/1491
title: Solar Flares from RHESSI Mission
DOI: 10.21227/7cq1-s059
title: Day-Ahead Forecasting using LSTM with rolling windows

description: The project involves day-ahead forecasting which takes a model fit into historical data and predicts future demand of electricity. Time series forecasting methods are used as the dataset contains an explicit order dependence between observations, i.e. a time dimension which makes the problem difficult to handle but makes the prediction more accurate. Various machine learning and deep learning algorithms were used to accomplish this work. Results obtained by autoregressive integrated moving average(ARIMA), autoregressive moving average with explanatory variable(ARIMAX), seasonal autoregressive moving average(SARIMA), seasonal autoregressive moving average(SARIMAX) and long short term memory(LSTM) recurrent neural networks with rolling windows were compared and the one with least error, i.e. LSTM with rolling windows was used for time series prediction.