cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.vjzvon
title: Occurrence Download

description: A dataset containing 4065 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-109.42383 48.69096,-112.76367 32.24997,-95.53711 24.20689,-78.13477 24.36711,-67.06055 43.70759,-73.38867 46.31658,-82.35352 42.03297,-82.70508 45.95115,-86.74805 47.87214,-93.25195 49.15297,-109.42383 48.69096))",
 "HasCoordinate is true",
 "TaxonKey is Laterallus jamaicensis (Gmelin, 1789)"
 ]
}

 The dataset includes 4065 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014690-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.78kn7b
title: Occurrence Download

description: A dataset containing 1833 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corylus colurna L."
 ]
}

 The dataset includes 1833 records from 126 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0247555-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qngf8p
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Ligularia lapathifolia (Franch.) Hand.-Mazz."
 ]
}

 The dataset includes 82 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0267543-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dhfgxx
title: Occurrence Download

description: A dataset containing 10609 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Panthera pardus"
 ]
}

 The dataset includes 10609 records from 170 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061754-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/93pm-yqe4
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/3rdk-6p5c
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/8q7w-nhrt
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/g8nb-wxru
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/susb-seh7
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/yz67-y9pr
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.48597/fujx-5jmb
title: Ammonium at Campisabalos

description: Measurement of Ammonium at Campisabalos
DOI: 10.48597/wz9w-q2py
title: Measurement of Ammonium at Campisabalos

description: Measurement of Ammonium at Campisabalos
DOI: 10.48597/anp7-hm8p
title: Measurement of Ammonium at Campisabalos

description: Measurement of Ammonium at Campisabalos
DOI: 10.48597/ayfr-ugb4
title: Measurement of Particle_number_concentration at Boulder Table Mountain

description: Measurement of Particle_number_concentration at Boulder Table Mountain
DOI: 10.15468/dl.k9hq7t
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Global Register of Introduced and Invasive Species - Canada"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003988-250325103851331/datasets/export for details.
DOI: 10.5066/p13jdumh
title: Cladophora biomass and supporting data collected in the Great Lakes, 2022

description: This dataset records Cladophora and associated benthic algae, collectively Cladophora community or submerged aquatic vegetation (SAV), biomass collected during the growing season of 2022 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of PAR, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussels, round goby abundance, and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - nutrient content of SAV, dreissenid mussels, and sediments; - and information about sampling locations and operations. Similar data were collected at several of the same transects within four Great Lakes in 2018, 2019, 2020, and 2021 are available at (2018) https://doi.org/10.5066/P9E570JS, (2019) https://doi.org/10.5066/P99O4QXB, (2020) https://doi.org/10.5066/P9O9FSTT, and (2021) https://doi.org/10.5066/P9449EUF.
DOI: 10.5066/p9449euf
title: Cladophora biomass and supporting data collected in the Great Lakes, 2021

description: This dataset records Cladophora and associated benthic algae, collectively Cladophora community or submerged aquatic vegetation (SAV), biomass collected during the growing season of 2021 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of PAR, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussels, round goby abundance, and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - nutrient content of SAV, dreissenid mussels, and sediments; - and information about sampling locations and operations. Similar data were collected at several of the same transects within four Great Lakes in 2018, 2019, and 2020 are available at (2018) https://doi.org/10.5066/P9E570JS, (2019) https://doi.org/10.5066/P99O4QXB, and (2020) https://doi.org/10.5066/P9O9FSTT.
DOI: 10.5066/p99o4qxb
title: Cladophora biomass and supporting data collected in the Great Lakes, 2019 (ver. 2.0, December 2023)

description: This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2019 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussels, round goby abundance, and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - and information about sampling locations and operations. Similar data were collected in 2018 at seven of the same transects within four Great Lakes and is available at https://doi.org/10.5066/P9E570JS.
DOI: 10.5066/p9e570js
title: Cladophora biomass and supporting data collected in the Great Lakes, 2018 (ver. 2.0, June 2023)

description: This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected approximately monthly during the growing season of 2018 at stations located along the U.S. shoreline of Lakes Michigan, Huron, Erie, and Ontario. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - seasonal time series of light, currents, wave action, temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen from moored sensors at a subset of stations; - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussel, round goby abundance and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - and information about sampling locations and operations. This is a revised version of data release; all changes are pointed out in the ReleaseHistory.txt.  First posted: April 30, 2020 (available from author) Revised: September 30, 2020 (version 1.1)
DOI: 10.5066/p9o9fstt
title: Cladophora biomass and supporting data collected in the Great Lakes, 2020 (ver. 2, May 2023)

description: This dataset records Cladophora and associated submerged aquatic vegetation (SAV) biomass collected during the growing season of 2020 at stations located along the U.S. shoreline of Lakes Michigan, Huron, and Erie. It also records a variety of supporting data collected at Cladophora measurement stations. These supporting data include: - measurements of Secchi disk depth and water chemistry; - water column profiles of temperature, specific conductivity, turbidity, pH, phycocyanin, chlorophyll, and dissolved oxygen; - diver observations of SAV, dreissenid mussels, round goby abundance, and substrate properties; - measurements of dreissenid mussel abundance and size class distribution coincident with SAV biomass; - and information about sampling locations and operations. Similar data were collected at several of the same transects within four Great Lakes in 2018 and 2019 and are available at (2018) https://doi.org/10.5066/P9E570JS and (2019) https://doi.org/10.5066/P99O4QXB.
DOI: 10.25824/redu/yzjfnq
title: Análise dos doentes com tumor de reto e resposta patológica completa após tratamento neoadjuvante e cirurgia

description: Analisar os pacientes que foram operados por suspeita de resposta clínica incompleta após tratamento neoadjuvante, e que apresentaram resposta patológica completa nos estudos anatomopatológicos dos espécimes cirúrgicos. Análise retrospectiva de prontuários médicos (físicos, digitalizados e do sistema eletrônico AGHuse) e dos resultados dos anatomopatológicos de pacientes que foram submetidos à cirurgia com intenção curativa para tratamento de CR após realização de neoadjuvância, operados no período de 2015 a 2023, e que apresentaram RPC.
DOI: 10.5066/p9j9av9v
title: Bottom dissolved oxygen measurements from Lake Erie's Central Basin, 2020

description: This data set, compiled by USGS Lake Erie Biological Station, provides near-bottom measurements of temperature and dissolved oxygen for the Central Basin of Lake Erie. Data were recorded by self-contained environmental data loggers (PME, Inc., MiniDOT data loggers). The data loggers were deployed during the stratified period (i.e., beginning of June 2020 through late October 2020) to better understand how hypoxia develops and influences fish habitat quality. The data loggers were deployed on acoustic telemetry receivers in a network designed to record tagged fish movements (Great Lakes Acoustic Telemetry Observation System, GLATOS). Additional years of data collection are planned, and data release will be updated as necessary.
DOI: 10.5281/zenodo.15090224
title: Datasets for manuscript: "$\Delta$-model correction of Foundation Model based on the models own understanding"

description: Data supporting the findings presented in $\Delta$-model correction of Foundation Model based on the models own understanding.


Contains datasets for


- Cu(111) ultrathin oxides in a c(8x4) surface cell.

- Sulfur on Au(111).


Sets resulting from global optimization, "search"-sets have been constructed by

filtering structures according to their graph representation.


Most of the dataset corresponds to specific figures in the manuscript:


- Figure 3: Files in copper_oxide/chg_search/ and copper_oxide/delta_search/

- Figure 4: Files in copper_oxide/chgnet_best/ and copper_oxide/delta_best/

- Figure 5: Files in gold_sulfide/chg_search/ and gold_sulfide/delta_search/

- Figure 6: Files in gold_sulfide/chg_best and gold_sulfide/delta_best

- Figure 7: Files in metal_sulfides/s7_structures/

- Figure 8 & 9: Files in metal_sulfides/dimer_trajectories/
DOI: 10.5281/zenodo.15090225
title: Datasets for manuscript: "$\Delta$-model correction of Foundation Model based on the models own understanding"

description: Data supporting the findings presented in $\Delta$-model correction of Foundation Model based on the models own understanding.


Contains datasets for


- Cu(111) ultrathin oxides in a c(8x4) surface cell.

- Sulfur on Au(111).


Sets resulting from global optimization, "search"-sets have been constructed by

filtering structures according to their graph representation.


Most of the dataset corresponds to specific figures in the manuscript:


- Figure 3: Files in copper_oxide/chg_search/ and copper_oxide/delta_search/

- Figure 4: Files in copper_oxide/chgnet_best/ and copper_oxide/delta_best/

- Figure 5: Files in gold_sulfide/chg_search/ and gold_sulfide/delta_search/

- Figure 6: Files in gold_sulfide/chg_best and gold_sulfide/delta_best

- Figure 7: Files in metal_sulfides/s7_structures/

- Figure 8 & 9: Files in metal_sulfides/dimer_trajectories/
DOI: 10.15468/dl.x2czdf
title: Occurrence Download

description: A dataset containing 377 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acrobatornis fonsecai Pacheco, B.M.Whitney & Gonzaga, 1996"
 ]
}

 The dataset includes 377 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003990-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dbq2yx
title: Occurrence Download

description: A dataset containing 139526 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample, Occurrence evidence)",
 "Country is Italy",
 "OccurrenceStatus is Present",
 "TaxonKey is Lepidoptera"
 ]
}

 The dataset includes 139526 records from 145 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003982-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u5y239
title: Occurrence Download

description: A dataset containing 1373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "OccurrenceStatus is Present",
 "TaxonKey is Melaleuca quinquenervia (Cav.) S.T.Blake"
 ]
}

 The dataset includes 1373 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003991-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9ffzwni
title: Bottom dissolved oxygen measurements from Lake Erie's Central Basin, 2021-2022

description: This data set, compiled by the USGS Lake Erie Biological Station, provides near-bottom measurements of temperature and dissolved oxygen for the Central Basin of Lake Erie. Data were recorded by self-contained environmental data loggers (PME, Inc., MiniDOT data loggers). The data loggers were deployed to collect data during August 2021 through November 2022 to better understand how hypoxia develops and influences fish habitat quality during lake stratification. The data loggers were deployed on acoustic telemetry receivers in a network designed to record tagged fish movements (Great Lakes Acoustic Telemetry Observation System, GLATOS). Additional years of data collection are planned, and data release will be updated as necessary.
DOI: 10.17632/3rrtjfrx4j.1
title: RRD Supplemental Text

description: Supplemental Text for Radiation recall dermatitis triggered by COVID-19 vaccination: A systematic review of a skin reaction following cancer radiotherapy
DOI: 10.17632/xh6jvwsjd3.1
title: Articles analyzing the concept of nursing care

description: Article extraction matrix for the analysis of the concept of prenatal nursing care
DOI: 10.17632/63szk8jfth.1
title: The Relationship Between School’s Emotional Climate and Organizational Happiness: The Parallel Mediating Role of Harmonic and Obsessive Job Passion

description: The Relationship Between School’s Emotional Climate and Organizational Happiness: The Parallel Mediating Role of Harmonic and Obsessive Job Passion
DOI: 10.17632/t7ffy2dfcw.1
title: Surviving the Fintech Disruption (Replication package)

description: Replication files for "Surviving the Fintech Disruption" by Wei Jiang, Yuehua Tang, Rachel Xiao, and Vincent Yao. Additional information and instructions are provided in the Readme file.
DOI: 10.17632/tvnbvzy4hb.1
title: Rapid reductions of multidrug-resistant Salmonella enterica on foods using novel photocatalytic films

description: This dataset includes antibacterial property assessment of the developed conjugate film against multidrug-resistant bacteria, absorbance range of conjugates, and EPR data. The absorbance range shows that TcPP expands the effective photocatalytic range of TiO2 into the visible spectra. The antibacterial property assessments show that higher light intensity kills bacteria more quickly. EPR data shows that higher light intensity promotes the generation of reactive oxygen species. Moreover, conjugate films have a better antibacterial effect on mango surfaces than chicken breast.
DOI: 10.5281/zenodo.14808057
title: Beach-imaging derived beach wracks

description: This is a draft-dataset providing a time series of beach wrack coverage (COVR) at Cala Millor beach, derived from imagery captured by the SIRENA beach video-monitoring system. SIRENA's cameras acquire overlapping, hourly, oblique images at a resolution of 1280×960 pixels. A deep learning-based object detection and segmentation model identifies seagrass wracks in these images. Photogrammetric techniques then rectify the images to a terrain coordinate system, and seagrass wrack coverage is calculated as the area fraction per 5 m grid cell. To ensure data validity, a preliminary quality control step filters out detections landwards from the promenade seawall.
description: This work was supported by ‘FOCCUS’ (Grant Agreement No.101133911) and ‘iMagine’ (Grant Agreement No.101058625) European Union funded projects. The deep learning model for beach wrack identification from oblique imagery was developed in the context of iMagine. The FOCCUS project focused on designing and crafting the final data product, encompassing metadata structuring, model implementation, photogrammetric transformations, and netCDF data generation.
DOI: 10.5281/zenodo.14808058
title: Beach-imaging derived beach wracks

description: This is a draft-dataset providing a time series of beach wrack coverage (COVR) at Cala Millor beach, derived from imagery captured by the SIRENA beach video-monitoring system. SIRENA's cameras acquire overlapping, hourly, oblique images at a resolution of 1280×960 pixels. A deep learning-based object detection and segmentation model identifies seagrass wracks in these images. Photogrammetric techniques then rectify the images to a terrain coordinate system, and seagrass wrack coverage is calculated as the area fraction per 5 m grid cell. To ensure data validity, a preliminary quality control step filters out detections landwards from the promenade seawall.
description: This work was supported by ‘FOCCUS’ (Grant Agreement No.101133911) and ‘iMagine’ (Grant Agreement No.101058625) European Union funded projects. The deep learning model for beach wrack identification from oblique imagery was developed in the context of iMagine. The FOCCUS project focused on designing and crafting the final data product, encompassing metadata structuring, model implementation, photogrammetric transformations, and netCDF data generation.