cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/2a16ef16450f37a46f92f7d839648e3a
title: Jornada Basin LTER: Wireless meteorological station at NPP G-IBPE site: 15-minute summary data: 2016 - ongoing

description: 15-minute summary data at NPP G-IBPE met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed; atmospheric pressure; PAR; solar radiation. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-IBPE site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.17007297.v1
title: Additional file 3 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 3. All DEGs Expression
DOI: 10.6084/m9.figshare.17007303.v1
title: Additional file 5 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 5. All DEGs Stats 42 Genes
DOI: 10.6084/m9.figshare.17007306.v1
title: Additional file 6 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 6. CVD Enrichments
DOI: 10.6084/m9.figshare.17007300.v1
title: Additional file 4 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 4. All DEGs Stats
DOI: 10.6084/m9.figshare.17007309.v1
title: Additional file 7 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 7. Original Raw Data
DOI: 10.6084/m9.figshare.17007318.v1
title: Additional file 2 of Father-to-offspring transmission of extremely long NOTCH2NLC repeat expansions with contractions: genetic and epigenetic profiling with long-read sequencing

description: Additional file 2: Table S1. Clinical features of four individuals with disease-causing NOTCH2NLC repeat expansions; Table S2. Summary statistics of Nanopore Cas9-based enrichment sequencing; Table S3. PacBio HiFi-read-based repeat composition; Table S4. Ratio of LCLs with nuclear inclusions in F3 and F4 families; Table S5. Percent methylation score in the F2 family; Table S6. Differentially methylated regions identified by Methylkit.
DOI: 10.5517/ccdc.csd.cc28nddr
title: CCDC 2104974: Experimental Crystal Structure Determination

description: Related Article: Lorenzo Pontini, Pietro Palazzoli, Daniela Maggioni, Giuseppe Damiano, Gianluca Giorgi, Vincenzo Russo, Maura Marinozzi|2021|Chem.Phys.Lipids|241|105151|doi:10.1016/j.chemphyslip.2021.105151
DOI: 10.5517/ccdc.csd.cc28ndfs
title: CCDC 2104975: Experimental Crystal Structure Determination

description: Related Article: Lorenzo Pontini, Pietro Palazzoli, Daniela Maggioni, Giuseppe Damiano, Gianluca Giorgi, Vincenzo Russo, Maura Marinozzi|2021|Chem.Phys.Lipids|241|105151|doi:10.1016/j.chemphyslip.2021.105151
DOI: 10.6084/m9.figshare.17007276.v1
title: Additional file 2 of Do health policies address the availability, accessibility, acceptability, and quality of human resources for health? Analysis over three decades of National Health Policy of India

description: Additional file 2: Table S1. HRH categories with corresponding National Occupation Classification codes (NOC). Legend—HRH: Human Resources for Health, NOC: National Occupation Classification, ANM: Auxiliary Nurse-Midwife, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy. Table S2. Data tables used for extraction of HRH data from Census 1981, 2001, 2011. Legend—HRH: Human Resources for Health. Table S3. Qualifications of qualified HRH. Legend—HRH: Human Resources for Health, ANM: Auxiliary Nurse-Midwife, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy. Table S4a. Coding of HRH-related dimensions of NHPI 1983 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre. Table S4b. Coding of HRH-related dimensions of NHPI-2002 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre. Table S4c. Coding of HRH-related dimensions of NHPI-2017 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre.
DOI: 10.5066/p9woujd3
title: USGS National and Global Oil and Gas Assessment Project-Permian Basin Province, Delaware Basin, Wolfcamp Shale and Bone Spring Assessment Units and Input Data

description: This data release contains the boundaries of assessment units and input data for the assessment of undiscovered oil and gas in the Delaware Basin, Wolfcamp Shale and Bone Spring. 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. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary. This data release also contains comma-separated (CSV) data for assessment input data and area allocation tables (DelawareBasinInputAllocations.xlsx). The input data if formatted in a human-readable format used during assessment meetings and is included (5044DelawareBasinInputForms.pdf). Documentation for these csv is included (Input Forms Colum Descriptions.xlsx). Methodology of assessments are documented in USGS Data Series 547 for continous 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).
DOI: 10.5066/f7x929h9
title: Produced water chemistry data for the Lost Hills, Fruitvale, and North and South Belridge study areas, Southern San Joaquin Valley, California (version 1.1, September 2020)

description: The U.S. Geological Survey (USGS) in cooperation with the California State Water Resources Control Board (Water Board) collected produced water and casing gas samples from petroleum wells and other oil-field sites in selected oil fields in the southern San Joaquin Valley in Kern County in 2016 and 2017. The samples were collected as part of the Water Boards Regional Groundwater Monitoring Program (RMP) of Water Quality in Areas of Oil and Gas Production. Samples included produced water and casing gas collected from oil wells, produced water collected from surface produced water disposal ponds, and injectate stored in tanks planned for underground injection. Samples were collected from the Fruitvale oil field on July 26th and July 27th, 2016. Samples were collected from the Lost Hills oil field on October 12th and October 13th, 2016. Samples were collected from the North Belridge oil field on July 25, 2017. Samples were collected from ponds near the South Belridge oil field on October 12, 2017. This digital dataset contains the site information, analyzing laboratories and methods, and water and gas chemistry and quality control results for these samples. Chemistry results include concentrations of dissolved noble and hydrocarbon gases and their isotopic composition; concentrations of inorganic constituents including salinity, major ions, and nutrients; concentrations of dissolved organic constituents; dissolved organic carbon and optical characteristics; and stable isotopes of water and solutes dissolved in water. Samples were analyzed in the field and by twelve laboratories operated or contracted by the USGS.
DOI: 10.6084/m9.figshare.17007237.v1
title: Additional file 2 of Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

description: Additional file 2: Supplementary Figure 2. Bivariate plot of log-transformed read length against base call quality with hexagonal bins and marginal histograms (NanoPlot) of raw reads a) PacBio and b) ONT.
DOI: 10.6073/pasta/5807be8255083a76c837834c3fcd152f
title: Jornada Basin LTER: Wireless meteorological station at NPP G-IBPE site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP G-IBPE met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-IBPE site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.17007234.v1
title: Additional file 23 of Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

description: Additional file 23: Supplementary Table 5. Statistical analysis of hybrid assemblies/ preprocessing effects.
DOI: 10.6084/m9.figshare.17007231.v1
title: Additional file 22 of Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

description: Additional file 22: Supplementary Table 4. Error rates in hybrid assemblies compared to references.
DOI: 10.6084/m9.figshare.17007228.v1
title: Additional file 21 of Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

description: Additional file 21: Supplementary Table 3. Performance of long-read and hybrid assemblers in five isolates of F. tularensis.
DOI: 10.6084/m9.figshare.17007225.v1
title: Additional file 20 of Testing assembly strategies of Francisella tularensis genomes to infer an evolutionary conservation analysis of genomic structures

description: Additional file 20: Supplementary Table 2. Performance of tested eight short-read assemblers in five isolates of F. tularensis.
DOI: 10.6084/m9.figshare.17007140.v1
title: Additional file 1 of In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches

description: Additional file 1.
DOI: 10.6084/m9.figshare.17007318
title: Additional file 2 of Father-to-offspring transmission of extremely long NOTCH2NLC repeat expansions with contractions: genetic and epigenetic profiling with long-read sequencing

description: Additional file 2: Table S1. Clinical features of four individuals with disease-causing NOTCH2NLC repeat expansions; Table S2. Summary statistics of Nanopore Cas9-based enrichment sequencing; Table S3. PacBio HiFi-read-based repeat composition; Table S4. Ratio of LCLs with nuclear inclusions in F3 and F4 families; Table S5. Percent methylation score in the F2 family; Table S6. Differentially methylated regions identified by Methylkit.
DOI: 10.5066/p99ehq8h
title: Water chemistry data for samples collected at groundwater sites near the Oxnard oil field, June 2017-August 2017, Ventura County, California

description: In cooperation with the California State Water Resources Control Board's oil and gas Regional Monitoring Program, the U.S. Geological Survey collected and analyzed groundwater and associated quality control (QC) samples during June 2017 - August 2017. Groundwater samples were collected from one public supply well, four monitoring wells, and nine irrigation wells located within a three- mile buffer zone overlying and surrounding the Oxnard oil field administrative boundary in Ventura County, California. Samples were collected using established groundwater data-collection protocols and procedures. Samples were analyzed for water-quality indicators, major and minor ions, nutrients, trace elements, volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), naturally occurring radioactive material, geochemical and age-dating tracers, dissolved organic carbon (DOC), low molecular weight organic acids, dissolved standard and hydrocarbon gases, and dissolved noble and atmospheric gases. Approximately 280 constituents and water-quality indicators were measured. Quality-control samples including replicates; source-solution, equipment, and field blanks; laboratory spikes; and split samples for inter-laboratory comparisons were collected and summarized in this data release. A data dictionary was created to describe the data tables and is provided with this data release. Please refer to this data dictionary file called COGG_Data_Dictionary_OxnardGW for definitions of fields within these data files.
DOI: 10.6084/m9.figshare.17007309
title: Additional file 7 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 7. Original Raw Data
DOI: 10.6084/m9.figshare.17007306
title: Additional file 6 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 6. CVD Enrichments
DOI: 10.6084/m9.figshare.17007303
title: Additional file 5 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 5. All DEGs Stats 42 Genes
DOI: 10.5066/f7qn65nj
title: Topographic Survey Data of Fountain Creek between Colorado Springs and the Confluence of Fountain Creek at the Arkansas River, Colorado, 2012 to 2017

description: In 2012, the U.S. Geological Survey (USGS) in cooperation with Colorado Springs Utilities selected 10 reaches or study area along Fountain Creek between Colorado Springs and the confluence of Fountain Creek at the Arkansas River for annual bed and bank characterization and topographic surveys. The selected 10 study areas are approximately 5 to 20 bank-full channel widths in length. The topographic surveys collected point data of location and elevation in the active channel and along both left and right banks and flood plains. Starting in 2012, USGS personnel have collected topographic survey data annually during the winter, spring, or summer using real-time kinematic Global Navigation Satellite Systems. These point data are converted to a grid which generates annual digital elevation maps of each study area which are used to develop elevation change maps at each study area. The topographic survey data provide an annual assessment of the geomorphic change at each study area.
DOI: 10.6084/m9.figshare.17007300
title: Additional file 4 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 4. All DEGs Stats
DOI: 10.6084/m9.figshare.17007297
title: Additional file 3 of RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

description: Additional file 3. All DEGs Expression
DOI: 10.5066/p9v18tm9
title: A summary of CMIP3 and CMIP5 climate change projections for the conterminous U.S.

description: This dataset includes model projections of seasonal temperature (T), precipitation (P), and runoff (R) from 214 climate simulations from coupled model intercomparison project (CMIP) 3 and CMIP5 scenarios for 19-year periods centered on 2030, 2060, and 2090. The summaries of the climate model projections are presented as percentiles (5th, 25th, 50th, 75th, and 95th) of seasonal (October through March, January through March, April through June, and July through September) changes in T, P, and R for the 214 climate models. The metrics are calculated from variables previously summarized across the conterminous United States for hydrologic response units of the Geospatial Fabric for National Hydrologic Modeling (Viger and Bock, 2014). T, P, and R were previously derived using a monthly water balance model (Bock and others, 2016; 2017). Names, sources, and references of the climate inputs are described in Bock and others (2017).
DOI: 10.6084/m9.figshare.17007276
title: Additional file 2 of Do health policies address the availability, accessibility, acceptability, and quality of human resources for health? Analysis over three decades of National Health Policy of India

description: Additional file 2: Table S1. HRH categories with corresponding National Occupation Classification codes (NOC). Legend—HRH: Human Resources for Health, NOC: National Occupation Classification, ANM: Auxiliary Nurse-Midwife, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy. Table S2. Data tables used for extraction of HRH data from Census 1981, 2001, 2011. Legend—HRH: Human Resources for Health. Table S3. Qualifications of qualified HRH. Legend—HRH: Human Resources for Health, ANM: Auxiliary Nurse-Midwife, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy. Table S4a. Coding of HRH-related dimensions of NHPI 1983 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre. Table S4b. Coding of HRH-related dimensions of NHPI-2002 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre. Table S4c. Coding of HRH-related dimensions of NHPI-2017 into dimension, cadre, action, and strategy using the framework for HRH strengthening. Legend—NHPI: National Health Policy of India, HRH: Human Resources for Health, AYUSH: Ayurveda, Yoga and Naturopathy, Unani, Siddha and Homeopathy, CHW: Community Health Worker. Other includes mid-level practitioners, community health workers, and multi-purpose workers. Non-cadre-specific recommendations are the ones that are not specific to any cadre.
DOI: 10.5066/p9mjy24n
title: Lava level and crater geometry data during the 2018 lava lake draining at Kilauea Volcano, Hawaii

description: In May 2018, the onset of new eruptive activity on the lower flank of K&amp;#299;lauea Volcano, Hawai&amp;#699;i, accompanied the draining of the lava lake at the summit, 40 km upslope. The lava lake draining lasted over seven days, and transitioned into the largest collapse event at the summit of K&amp;#299;lauea in over 200 years, with the paired flank and summit activity marking a historic episode in the modern record of K&amp;#299;lauea. We present two important datasets that characterize draining of the K&amp;#299;lauea summit lava lake in 2018. First, we present high-precision elevation data of the lava lake surface measured by an industrial laser rangefinder. To our knowledge, this is the highest-precision lava lake elevation data ever collected over a sustained period. Second, we present three-dimensional models of the drained crater on three dates during the draining sequence. The models were constructed from oblique airborne thermal images using structure-from-motion processing. These models constrain the crater geometry and can be used for measuring the volume of the lava lake during its draining. This combined dataset may be useful for future research on the 2018 eruption.
DOI: 10.5066/f73r0rr3
title: Data to support modeling of the 2015 Tyndall Glacier landslide, Alaska

description: Landslide-generated tsunamis pose significant hazards, but developing models to assess these hazards presents unique challenges. George and others (2017) present a new methodology in which a depth-averaged two-phase landslide model (D-Claw) is used to simulate all stages of landslide dynamics and subsequent tsunami generation, propagation, and inundation. Because the model describes the evolution of solid and fluid volume fractions, it treats both landslides and tsunamis as special cases of a more general class of phenomena. Therefore, the landslide and tsunami can be seamlessly and efficiently simulated as a single-layer continuum with evolving solid-grain concentrations, and with wave generation via mass displacement and direct longitudinal momentum transfer: dominant physical mechanisms that are unresolved with traditional modeling approaches. To test their methodology, George and others (2017) used D-Claw to model a large subaerial landslide and resulting tsunami that occurred on October, 17, 2015, in Taan Fiord near the terminus of Tyndall Glacier, Alaska. Modeled shoreline inundation patterns compare well with observations derived from satellite imagery. This data release contains topographic datasets used to model the landslide and a Normalized difference vegetation index (NDVI) change image used to assess the model results. These data are intended to accompany the journal article by George and others (2017): George, D.L., Iverson, R.M., and Cannon, C.M., 2017, New methodology for computing tsunami generation by subaerial landslides: application to the 2015 Tyndall Glacier Landslide, Alaska, Geophysical Research Letters, 44, doi:10.1002/2017GL074341.
DOI: 10.6073/pasta/bdc7059fcb7ada01418e4dee341b2d67
title: Jornada Basin LTER: Wireless meteorological station at NPP G-IBPE site: 30-minute summary data: 2013 - ongoing

description: 30-minute summary data at NPP G-IBPE met station. Average air temperature, relative humidity, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP G-IBPE site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.