cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25921/fxjn-r752
title: National Coral Reef Monitoring Program: Dissolved inorganic carbon, total alkalinity, pH and other variables collected from surface discrete measurements using Coulometer, alkalinity titrator and other instruments from the Hawaiian Archipelago, from 2019-04-21 to 2019-09-05 (NCEI Accession 0226794)

description: This dataset contains the National Coral Reef Monitoring Program carbonate chemistry data from the Hawaiian Archipelago, including the Main and Northwest Hawaiian Islands, from 2019-04-21 to 2019-09-05. The project monitors changes to coral reef carbonate chemistry over time, at U.S.-affiliated Pacific coral reef sites, through quantifying key chemical parameters that are expected to change with ocean acidification. This effort addresses multiple OAP programmatic mission areas by maintaining the coral reef portion of the OA monitoring network and developing a procedure for data synthesis, assimilation, and distribution. Incorporating an interdisciplinary approach, this project collects, processes, analyzes, and stewards dissolved inorganic carbon (DIC) and total alkalinity (TA) water sample data to document seawater carbonate chemistry at Class 0, I, II, and III climate monitoring sites in coral reef areas of the U.S. Pacific region.
DOI: 10.14278/rodare.4137
title: Data publication: Synthetic Optical Imaging in PIConGPU

description: Data to create figures for "Synthetic Optical Imaging in PIConGPU" and source code to rerun simulations. 


 `cryojet_openpmd_data.zip`: Simulation with cryojet density slice (Fig 4a), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `cryojet_shadowgram_plugin_data.zip`: Simulation with cryojet shadowgram (Fig 4b, 4c, 4d), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_openpmd_data_setup.zip`: Simulation with double slit setup picture (Fig. 2), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_shadowgram_openpmd_data.zip`: Simulation with double slit shadowgram made with openPMD time integration (Fig. 3b), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_shadowgram_plugin_data.zip`: Simulation with double slit shadowgram made with plugin (Fig. 3a and 3b), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `picongpu-cryojet.zip`: PIConGPU source code for cryojet simulations
 `picongpu-doubleslit.zip`: PIConGPU source code for double slit simulations
DOI: 10.14278/rodare.4136
title: Data publication: Synthetic Optical Imaging in PIConGPU

description: Data to create figures for "Synthetic Optical Imaging in PIConGPU" and source code to rerun simulations. 


 `cryojet_openpmd_data.zip`: Simulation with cryojet density slice (Fig 4a), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `cryojet_shadowgram_plugin_data.zip`: Simulation with cryojet shadowgram (Fig 4b, 4c, 4d), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_openpmd_data_setup.zip`: Simulation with double slit setup picture (Fig. 2), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_shadowgram_openpmd_data.zip`: Simulation with double slit shadowgram made with openPMD time integration (Fig. 3b), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `doubleslit_shadowgram_plugin_data.zip`: Simulation with double slit shadowgram made with plugin (Fig. 3a and 3b), input files to rebuild and rerun simulation are in `input/include` and `input/etc`
 `picongpu-cryojet.zip`: PIConGPU source code for cryojet simulations
 `picongpu-doubleslit.zip`: PIConGPU source code for double slit simulations
DOI: 10.25921/s4f4-ye35
title: Compilation of dissolved organic matter (DOM) data obtained from global ocean observations from 1994 to 2021, Version 2 (NCEI Accession 0227166)

description: This dataset consists of measurements of dissolved organic matter (DOM) and other chemical and hydrographic parameters obtained during the global ocean observations from 1994-01-01 to 2021-05-29. Measurements of dissolved organic matter (DOM) in the open ocean have increased greatly since the late 1980's, spurred by the growth in scientific interest directed at the ocean carbon cycle. Analytical quality for determining the elemental concentrations of DOM was commonly low in those early years, but through great effort and use of consensus reference materials its quality has improved with time. The data in this compilation should be used with the trajectory of improved analytical quality with time in mind. DOM data generated by many laboratories around the world are typically made available in diverse, regional data archives, making them less available than necessary for the data value to be maximized. The effort here was to make ship-collected bottle data accessible more directly and in uniform format. The emphasis was on spatial coverage of the global ocean, so the well-known and ongoing time-series data (such as the Bermuda Atlantic Time-series Study and Hawaiian Ocean Time-series) are not included; nor are coastal waters well represented in this first version. While the focus of this compilation is largely on dissolved organic carbon (DOC) and total dissolved nitrogen (TDN), we extended coverage to include the less frequently determined DOM isotopes (13C, 14C, 15N), select wavelengths and a single spectral slope of colored dissolved organic matter (CDOM), and DOM composition (i.e., dissolved combined neutral sugars). To the extent possible, the DOM data have been complemented with hydrographic data (e.g, temperature and salinity), other biogeochemical variables (e.g., oxygen, nutrients), the inorganic carbon system [e.g., dissolved organic carbon (with isotopes when available), pH, and total alkalinity], and anthropogenic (chlorofluorocarbons, sulfur hexafluoride, carbon tetrachloride) and natural tracers (neon, helium, tritium). A very few data are included for biological variables such as bacterial abundance and chlorophyll a concentrations. These data are from all ocean basins taken from 224 cruises in the global ocean, providing DOC concentrations largely from the full water column and TDN concentrations in the surface 250 m.
DOI: 10.15468/dl.3822cc
title: Occurrence Download

description: A dataset containing 363563 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "Elevation 323.0-968.0m",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 363563 records from 307 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009761-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/2zej-bq50
title: Dissolved inorganic carbon, total alkalinity, water temperature, salinity, dissolved oxygen, nutrients and other variables collected from discrete samples and profile observations during the R/V L'Atalante PANDORA cruise (EXPOCODE 35A320120628) in the South Pacific Ocean, Bismarck Sea, Coral Sea and Solomon Sea from 2012-06-28 to 2012-08-06 (NCEI Accession 0232898)

description: This dataset includes discrete sample and profile observations, collected during the R/V L'Atalante PANDORA cruise (EXPOCODE 35A320120628) in the South Pacific Ocean, Bismarck Sea, Coral Sea and Solomon Sea from 2012-06-28 to 2012-08-06. These data include Dissolved inorganic carbon, total alkalinity, water temperature, salinity, dissolved oxygen and nutrients. The instruments used to collect these data include CTD and Niskin bottles.
DOI: 10.15468/dl.ckrjd2
title: Occurrence Download

description: A dataset containing 98554 records in GBIF matching the query:
SELECT
 '24' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)) AS cell,
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= -33.06103686093294
 AND decimalLatitude &lt;= -28.773895969281842
 AND decimalLongitude &gt;= 146.15102397859218
 AND decimalLongitude &lt;= 155.85126321428865
 AND "year" &gt;= 2015
 AND "year" &lt;= 2025
 AND (coordinateUncertaintyInMeters &lt;= 1000 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 98554 records were derived from 171 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009763-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.21315.05928
title: English CarniForeGraze Comics2
DOI: 10.6084/m9.figshare.30090436
title: Supplementary data from Garcia et al., 2025

description: Supplementary data of the manuscript entitled "Ancient origin, evolution and diversity of oxidoreductases involved inredox balance and energy conservation" by Garcia et al., 2025
DOI: 10.6084/m9.figshare.30090436.v1
title: Supplementary data from Garcia et al., 2025

description: Supplementary data of the manuscript entitled "Ancient origin, evolution and diversity of oxidoreductases involved inredox balance and energy conservation" by Garcia et al., 2025
DOI: 10.15468/dl.r9ntdz
title: Occurrence Download

description: A dataset listing the 150 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.13504 41.43479,2.14026 41.43479,2.14026 41.43856,2.13504 41.43856,2.13504 41.43479))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset's 150 records were derived from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009765-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.34736.83200
title: Francais CarniForeGraze Comics2
DOI: 10.25921/yrpd-vp53
title: Dissolved inorganic carbon (DIC), total alkalinity, water temperature, salinity, dissolved oxygen, phosphate, silicate, nitrate, nitrite and other measurements collected from profile and discrete sample observations during the RRS James Cook GEOTRACES cruise JC068 (EXPOCODE 740H20111224) in the South Atlantic Ocean from 2011-12-24 to 2012-01-27 (NCEI Accession 0253907)

description: This dataset includes discrete profile measurements of Dissolved inorganic carbon (DIC), total alkalinity, water temperature, salinity, dissolved oxygen, phosphate, silicate, nitrate, nitrite and other measurements collected during the RRS James Cook GEOTRACES cruise JC068 (EXPOCODE 740H20111224) in the South Atlantic Ocean from 2011-12-24 to 2012-01-27.
DOI: 10.34740/kaggle/dsv/13879320
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.13140/rg.2.2.19637.33761
title: Deutsch CarniForeGraze Comics2
DOI: 10.25921/jacg-ts70
title: Temperature, Salinity, pH, Oxygen, Inorganic and Organic Nitrogen, Phosphorus and Carbon, Suspended Sediments and Chlorophyll-a data for the Mobile Bay and Mississippi Sound from 2020-05-28 to present (NCEI Accession 0277234)

description: Twenty-six surveys were carried out under the NOAA “RESTORE” project from 2020-present. The main objective of this project was to determine the spatial and temporal variability of parameters in Mobile Bay based on river discharge and seasonal variation. During these surveys, temperature, salinity, pH, oxygen, nutrients, chlorophyll, inorganic and organic carbon, and suspended sediments were measured at thirty different stations across Mobile Bay and the Mississippi Sound.
DOI: 10.13140/rg.2.2.16281.89443
title: Norsk CarniForeGraze Comics2
DOI: 10.15468/dl.yupjap
title: Occurrence Download

description: A dataset containing 89 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 countrycode countrycode,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, countrycode, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'CH'
 AND GBIF_WITHIN('POLYGON((-35.88793 29.16548,80.88793 29.16548,80.88793 75.83452,-35.88793 75.83452,-35.88793 29.16548))', occurrence.decimallatitude, occurrence.decimallongitude) = TRUE
 AND occurrence.hascoordinate = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (CAST(occurrence.taxonkey AS INTEGER) = 2468095 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 2468095 OR CAST(occurrence.kingdomkey AS INTEGER) = 2468095 OR CAST(occurrence.phylumkey AS INTEGER) = 2468095 OR CAST(occurrence.classkey AS INTEGER) = 2468095 OR CAST(occurrence.orderkey AS INTEGER) = 2468095 OR CAST(occurrence.familykey AS INTEGER) = 2468095 OR CAST(occurrence.genuskey AS INTEGER) = 2468095 OR CAST(occurrence.specieskey AS INTEGER) = 2468095)
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year",
 occurrence.countrycode

 The dataset's 89 records were derived from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009766-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30720401
title: Comprehensive Surveillance of Pemivibart (VYD2311) Escape Mutations in 9,398,268 SARS-CoV-2 Spike Protein Sequences 2020 up to 2025 Q3

description: This dataset presents a large-scale genomic surveillance analysis of selected spike mutations which may or may not disrupt pemivibart (VYD2311) monoclonal antibody binding. We analyzed 9,398,268 SARS-CoV-2 spike protein sequences. Pemivibart is a next-generation monoclonal antibody therapy for COVID-19, and understanding potential escape mutations is crucial for monitoring therapeutic efficacy.<b>Methods:</b>Analyzed 9,398,268 SARS-CoV-2 spike protein sequences from global databases.We employed position-based mutation detection against Wuhan-Hu-1 reference (YP_009724390.1) We systematically scanned for 11 known pemivibart escape mutations: R346T, K444T, F456L, F486P, S371F, N460K, S417T, S501T, S446A, S444T, S500TIdentified both individual mutations and mutation constellations (combinations)Data provided in compressed TSV format with comprehensive metadata<b>Results:</b>8,913,005 sequences (94.84%) contained at least one pemivibart escape mutationIdentified 116 distinct mutation constellationsMutation distribution: single mutations to 8-mutation combinationsMost prevalent mutations: <b>S500T, R346T, F486P, F456L</b>Constellation analysis reveals complex mutation patterns that may disrupt pemivibart binding epitopes.<b>Data Contents:</b>Individual mutation files for all 11 target mutations116 constellation files showing mutation combinationsFiles provided in both Zstandard (.zst) and Gzip (.gz) formatsComplete summary statistics and metadataSequence accessions, collection years, and geographic origins<b>Potential Impact:</b>The identified single and multiple mutation constellations may disrupt pemivibart epitopes and impact therapeutic efficacy. This comprehensive dataset enables researchers to monitor resistance emergence, inform treatment guidelines, and support public health surveillance.<b>Usage Notes:</b>Files are provided in tab-separated format with sequence headers, accession numbers, collection metadata, and mutation information. Compressed formats ensure efficient storage while maintaining data accessibility.<b>Study by</b>: TahirHB@Hotmail.Com
DOI: 10.6084/m9.figshare.30720401.v1
title: Comprehensive Surveillance of Pemivibart (VYD2311) Escape Mutations in 9,398,268 SARS-CoV-2 Spike Protein Sequences 2020 up to 2025 Q3

description: This dataset presents a large-scale genomic surveillance analysis of selected spike mutations which may or may not disrupt pemivibart (VYD2311) monoclonal antibody binding. We analyzed 9,398,268 SARS-CoV-2 spike protein sequences. Pemivibart is a next-generation monoclonal antibody therapy for COVID-19, and understanding potential escape mutations is crucial for monitoring therapeutic efficacy.<b>Methods:</b>Analyzed 9,398,268 SARS-CoV-2 spike protein sequences from global databases.We employed position-based mutation detection against Wuhan-Hu-1 reference (YP_009724390.1) We systematically scanned for 11 known pemivibart escape mutations: R346T, K444T, F456L, F486P, S371F, N460K, S417T, S501T, S446A, S444T, S500TIdentified both individual mutations and mutation constellations (combinations)Data provided in compressed TSV format with comprehensive metadata<b>Results:</b>8,913,005 sequences (94.84%) contained at least one pemivibart escape mutationIdentified 116 distinct mutation constellationsMutation distribution: single mutations to 8-mutation combinationsMost prevalent mutations: <b>S500T, R346T, F486P, F456L</b>Constellation analysis reveals complex mutation patterns that may disrupt pemivibart binding epitopes.<b>Data Contents:</b>Individual mutation files for all 11 target mutations116 constellation files showing mutation combinationsFiles provided in both Zstandard (.zst) and Gzip (.gz) formatsComplete summary statistics and metadataSequence accessions, collection years, and geographic origins<b>Potential Impact:</b>The identified single and multiple mutation constellations may disrupt pemivibart epitopes and impact therapeutic efficacy. This comprehensive dataset enables researchers to monitor resistance emergence, inform treatment guidelines, and support public health surveillance.<b>Usage Notes:</b>Files are provided in tab-separated format with sequence headers, accession numbers, collection metadata, and mutation information. Compressed formats ensure efficient storage while maintaining data accessibility.<b>Study by</b>: TahirHB@Hotmail.Com
DOI: 10.25921/haac-g960
title: Cetacean visual observations using line-transect survey methods onboard the NOAA Ship Gordon Gunter (GU) in the Gulf of America (survey GU0402) from 2004-04-15 to 2004-06-10 (NCEI Accession 0284773)

description: The U.S. National Marine Fisheries Service (NMFS) is required to prepare an annual Stock Assessment Report (SAR) for each marine mammal stock to update abundance, stock structure, maximum net productivity, human-caused mortality, potential biological removal (PBR), and status. In the summer of 2004, the Southeast Fisheries Science Center (SEFSC) conducted a marine mammal survey in the northern Gulf of America. Operations occurred in the waters from 200 m deep seaward to the Exclusive Economic Zone (EEZ) from Brownsville, Texas east into the Straights of Florida. The survey was designed using ship-based, line-transect methods in which experienced marine mammal observers visually located marine mammals, identified the species (to the lowest taxonomic level possible) and counted the number of whales and dolphins sighted along predetermined track-lines. A sighting constitutes a group of marine mammals (whales and dolphins) seen at the same location and time. This dataset includes marine mammal visual observation data and effort points with surveying conditions that can be used in abundance and density modeling per visual line-transect survey protocols. This dataset also includes opportunistic marine mammal photographs and information on biopsy samples collected during the survey.
DOI: 10.13140/rg.2.2.36414.55369
title: Svensk CarniForeGraze Comics2
DOI: 10.5281/zenodo.17723274
title: Unlocking Bank Performance: How Institutional Quality Shapes the Impact of Financial Inclusion in Nigerian Deposit Money Banks
title: How Institutional Quality Shapes the Impact of Financial Inclusion in Nigerian Deposit Money Banks

description: This study examined the moderating effect of Institutional quality (henceforth IQ) on relationships between financial inclusion (henceforth FINC) and financial performance(henceforth Perf) among deposit money banks in Nigeria. The study used 13 deposit money banks that are listed on the stock exchange. The panel ARDL approach was used to establish the short- and long-run moderating effect of IQ on the relationships between FINC and PERF among deposit money banks in Nigeria. Looking at the long- and short-run dimensions of the moderating effect of IQ on the relationship between FINC and the PERF, the study found mixed results. The study found that IQ variables significantly moderate the relationship between FINC variables and the PERF of deposit money banks in Nigeria in both the long and short run. These suggest that the moderating effects of IQ are more pronounced in the long run than in the short run. The study found that IQ has a more pronounced moderating impact on the commercial bank branches than other measures of FINC used. Lastly, the study established that the rule of law and corruption perception have the most pronounced moderating effects on the relationship between FINC and PERF among deposit money banks in Nigeria.
DOI: 10.5281/zenodo.17723275
title: Unlocking Bank Performance: How Institutional Quality Shapes the Impact of Financial Inclusion in Nigerian Deposit Money Banks
title: How Institutional Quality Shapes the Impact of Financial Inclusion in Nigerian Deposit Money Banks

description: This study examined the moderating effect of Institutional quality (henceforth IQ) on relationships between financial inclusion (henceforth FINC) and financial performance(henceforth Perf) among deposit money banks in Nigeria. The study used 13 deposit money banks that are listed on the stock exchange. The panel ARDL approach was used to establish the short- and long-run moderating effect of IQ on the relationships between FINC and PERF among deposit money banks in Nigeria. Looking at the long- and short-run dimensions of the moderating effect of IQ on the relationship between FINC and the PERF, the study found mixed results. The study found that IQ variables significantly moderate the relationship between FINC variables and the PERF of deposit money banks in Nigeria in both the long and short run. These suggest that the moderating effects of IQ are more pronounced in the long run than in the short run. The study found that IQ has a more pronounced moderating impact on the commercial bank branches than other measures of FINC used. Lastly, the study established that the rule of law and corruption perception have the most pronounced moderating effects on the relationship between FINC and PERF among deposit money banks in Nigeria.
DOI: 10.17605/osf.io/swbck
title: Monkeypox_data

description: Output data for monkeypox model
DOI: 10.15468/dl.ayzwv7
title: Occurrence Download

description: A dataset containing 123177 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ara ararauna"
 ]
}

 The dataset includes 123177 records from 231 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009754-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.