cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.33435
title: MuSyQ SHG-LCC: A high-resolution global leaf chlorophyll content dataset derived from Sentinel-2 imagery
title: MuSyQ SHG-LCC:全球高分辨率叶片叶绿素含量产品

description: Leaf chlorophyll content (LCC) is a critical indicator of plant photosynthetic capacity and plays a key role in understanding the terrestrial carbon cycle. However, existing global LCC products, primarily derived from coarse-resolution remote sensing data, are unable to accurately capture the spatiotemporal variations of LCC in heterogeneous regions. Currently, high-resolution global LCC products remain limited, significantly constraining their application at fine scales. To address this gap, this dataset developed a high-resolution global LCC product (MuSyQ SHG-LCC) with 100-meter/10-day resolution from Sentinel-2 MSI data for the 2019-2023. The dataset was generated using the leaf-scale MERIS Terrestrial Chlorophyll Index (MTCIleaf), which effectively corrects for canopy structural effects on LCC retrieval. Validation results demonstrated that the dataset achieved high retrieval accuracy across various vegetation types, providing important data support for global carbon cycle and ecological research.
description: Leaf chlorophyll content (LCC) is a critical indicator of plant photosynthetic capacity and plays a key role in understanding the terrestrial carbon cycle. However, existing global LCC products, primarily derived from coarse-resolution remote sensing data, are unable to accurately capture the spatiotemporal variations of LCC in heterogeneous regions. Currently, high-resolution global LCC products remain limited, significantly constraining their application at fine scales. To address this gap, this dataset developed a high-resolution global LCC product (MuSyQ SHG-LCC) with 100-meter/10-day resolution from Sentinel-2 MSI data for the 2019-2023. The dataset was generated using the leaf-scale MERIS Terrestrial Chlorophyll Index (MTCIleaf), which effectively corrects for canopy structural effects on LCC retrieval. Validation results demonstrated that the dataset achieved high retrieval accuracy across various vegetation types, providing important data support for global carbon cycle and ecological research.
DOI: 10.17026/ar/ptm4tn
title: PAN-00134524 - arrowhead (stone)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00134524&lt;/p&gt;
description: Modified: 2025-07-04T16:25:08+02:00
DOI: 10.5281/zenodo.17898796
title: Lipidomics analysis of MDA-MB-231 cells upon WMK-1 treatment

description: MDA-MB-231 cells were treated with compounds, including DMSO (Vehicle), ML210 (for 2h, 3 μM), WMK-1 (5 μM, for 3h or 6h), ZL-1-180 (20 μM, for 7h), in the presence or absence of Lip-1 (1 μM).

For lipidomic analysis, 1 µL of the prepared tissue lipidomics samples were loaded into an ACQUITY UPLC BEH C8 column (100 × 2.1 mm,1.7 μm, 130 Å, Waters, Cat# 186002878), and separated chromatographically with a 25-min gradient elution at a flow rate of 0.3 mL/min. The mobile phase for the positive ion acquisition mode contains H2O with 0.1% (v/v) FA and 10 mM ammonium acetate for Phase A, and ACN/IPA (80:20) with 0.1% (v/v) FA for Phase B. The mobile phase for the negative ion mode is similar to the ones for the positive ion mode except excluding formic acid in the buffer. The LipidSearch software (v4.2.21, Thermo Fisher Scientific) was used for lipidomics peak detection, peak alignment, and compound annotation. Specifically, we used a 0.5-min retention time interval for peak detection with the isotope compositions recalculated. 5 ppm and 8 ppm deviations were employed as tolerance ranges for precursor and product ions, respectively, during Database searches. The minimum relative fragment ion intensity threshold was set at 1%. Isomer peaks were filtered out. In parallel, the precursor ion quantitation was performed with a 5 ppm tolerance and a 0.5-min retention time range. 

Lipidomics data normalization:Before downstream analysis of lipidomics data, the following criteria was employed to exclude unreliable ion peaks: 1) exclusion of peaks with a peak-quality (PQ) score < 0.9 or peak area score < 0.7; 2) manual inspection of peak shapes, excluding those with abnormal shapes or insufficient data points; 3) filtering out ions with a relative standard deviation (RSD) > 0.3 across all QC samples in each experimental set; 4) exclusion of lipid species with intensity lower than five times of that of blank samples;

For downstream analysis, the raw intensity data were normalized by dividing by the median intensity of the corresponding sample and scaled by a scaling factor, 10^6. Then, the fold change of each lipid ion between compound treatment (ML210, WMK-1, ZL-1-180 or Lip-1 rescue) and Vehicle treatment was calculated. P value was calculated using two-tailed, non-parametric, unpaired Student’s t-test. Lipid species with fold change >= 1.5 and P value <= 0.05 were considered as significantly changed lipid species after WMK-1 treatment and were then used for plotting
DOI: 10.5281/zenodo.17898797
title: Lipidomics analysis of MDA-MB-231 cells upon WMK-1 treatment

description: MDA-MB-231 cells were treated with compounds, including DMSO (Vehicle), ML210 (for 2h, 3 μM), WMK-1 (5 μM, for 3h or 6h), ZL-1-180 (20 μM, for 7h), in the presence or absence of Lip-1 (1 μM).

For lipidomic analysis, 1 µL of the prepared tissue lipidomics samples were loaded into an ACQUITY UPLC BEH C8 column (100 × 2.1 mm,1.7 μm, 130 Å, Waters, Cat# 186002878), and separated chromatographically with a 25-min gradient elution at a flow rate of 0.3 mL/min. The mobile phase for the positive ion acquisition mode contains H2O with 0.1% (v/v) FA and 10 mM ammonium acetate for Phase A, and ACN/IPA (80:20) with 0.1% (v/v) FA for Phase B. The mobile phase for the negative ion mode is similar to the ones for the positive ion mode except excluding formic acid in the buffer. The LipidSearch software (v4.2.21, Thermo Fisher Scientific) was used for lipidomics peak detection, peak alignment, and compound annotation. Specifically, we used a 0.5-min retention time interval for peak detection with the isotope compositions recalculated. 5 ppm and 8 ppm deviations were employed as tolerance ranges for precursor and product ions, respectively, during Database searches. The minimum relative fragment ion intensity threshold was set at 1%. Isomer peaks were filtered out. In parallel, the precursor ion quantitation was performed with a 5 ppm tolerance and a 0.5-min retention time range. 

Lipidomics data normalization:Before downstream analysis of lipidomics data, the following criteria was employed to exclude unreliable ion peaks: 1) exclusion of peaks with a peak-quality (PQ) score < 0.9 or peak area score < 0.7; 2) manual inspection of peak shapes, excluding those with abnormal shapes or insufficient data points; 3) filtering out ions with a relative standard deviation (RSD) > 0.3 across all QC samples in each experimental set; 4) exclusion of lipid species with intensity lower than five times of that of blank samples;

For downstream analysis, the raw intensity data were normalized by dividing by the median intensity of the corresponding sample and scaled by a scaling factor, 10^6. Then, the fold change of each lipid ion between compound treatment (ML210, WMK-1, ZL-1-180 or Lip-1 rescue) and Vehicle treatment was calculated. P value was calculated using two-tailed, non-parametric, unpaired Student’s t-test. Lipid species with fold change >= 1.5 and P value <= 0.05 were considered as significantly changed lipid species after WMK-1 treatment and were then used for plotting
DOI: 10.6084/m9.figshare.30866411
title: A harmonised 0.1-degree annual dataset of forest gross primary productivity and environmental drivers for China, 1990–2018

description: This dataset provides a harmonised, multi-variable record of gross primary productivity (GPP) and its environmental drivers across mainland China from 1990 to 2018 at 0.1° spatial resolution. It supports reproducible analyses of vegetation productivity, climate–biosphere interactions, and forest ecosystem dynamics at national scale.Annual GPP derived from near-infrared reflectance is integrated with climate variables (temperature, precipitation, shortwave radiation, and soil moisture), nighttime lights as a proxy for anthropogenic pressure, and static topographic attributes (elevation, slope, and aspect). All variables are temporally aggregated to annual values and spatially harmonised to a fixed WGS84 0.1° grid with identical extent and alignment across all years.A forest mask derived from the 2018 China Land-Use/Land-Cover Dataset is provided to enable forest-focused analyses, together with an annual forest fragmentation index (FFI) computed from high-resolution land-cover data using landscape metrics. Climate-zone identifiers based on an aggregated Köppen classification allow stratified analyses across China’s major bioclimatic regions.The dataset is distributed as annual GeoTIFF layers with comprehensive metadata and example Python and R workflows. All processing scripts are openly released, ensuring full reproducibility and compliance with FAIR data principles.
DOI: 10.6084/m9.figshare.30866411.v1
title: A harmonised 0.1-degree annual dataset of forest gross primary productivity and environmental drivers for China, 1990–2018

description: This dataset provides a harmonised, multi-variable record of gross primary productivity (GPP) and its environmental drivers across mainland China from 1990 to 2018 at 0.1° spatial resolution. It supports reproducible analyses of vegetation productivity, climate–biosphere interactions, and forest ecosystem dynamics at national scale.Annual GPP derived from near-infrared reflectance is integrated with climate variables (temperature, precipitation, shortwave radiation, and soil moisture), nighttime lights as a proxy for anthropogenic pressure, and static topographic attributes (elevation, slope, and aspect). All variables are temporally aggregated to annual values and spatially harmonised to a fixed WGS84 0.1° grid with identical extent and alignment across all years.A forest mask derived from the 2018 China Land-Use/Land-Cover Dataset is provided to enable forest-focused analyses, together with an annual forest fragmentation index (FFI) computed from high-resolution land-cover data using landscape metrics. Climate-zone identifiers based on an aggregated Köppen classification allow stratified analyses across China’s major bioclimatic regions.The dataset is distributed as annual GeoTIFF layers with comprehensive metadata and example Python and R workflows. All processing scripts are openly released, ensuring full reproducibility and compliance with FAIR data principles.
DOI: 10.17026/ar/tvnj1l
title: PAN-00171913 - lower pump box

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00171913&lt;/p&gt;
description: Modified: 2025-09-17T10:39:54+02:00
DOI: 10.5281/zenodo.17860206
title: Efeitos da temperatura e da umidade no desenvolvimento e consumo alimentar de Bombyx mori em Sirgaria no Mato Grosso do Sul

description: Dataset associated with the article: “Efeitos da temperatura e da umidade no desenvolvimento e consumo alimentar de Bombyx mori em sirgarias no Mato Grosso do Sul”.

This dataset contains the raw environmental and biometric data used to evaluate the influence of air temperature, relative humidity and food availability on the larval development of Bombyx mori under real sericulture conditions in Itaquiraí–MS, Brazil.

Data were obtained during three production periods:

- May 2008 (Autumn)

- November 2008 (Spring)

- January 2009 (Summer)

Included data:

- Individual larval measurements (length, weight, instar, replicate bed and quadrant)

- Temperature and relative humidity inside and outside the sericulture shed (initial and final readings)

- Feeding information (fresh leaves supplied, residues)

- Aggregated environmental means used in Table 1 of the manuscript

-  Intermediate organization sheets for complete transparency

All data derive from in-field measurements conducted in commercial sirgarias, following the methodology described in the manuscript.

The dataset supports all results, figures, tables and statistical analyses (ANOVA and Tukey tests) presented in the study.

File formats: xlsx (multi-sheet), containing raw measurements and aggregated values.

Corresponding author: Marcos Massuo Kashiwaqui (mkashiwaqui@yahoo.com.br)
DOI: 10.5281/zenodo.17860205
title: Efeitos da temperatura e da umidade no desenvolvimento e consumo alimentar de Bombyx mori em Sirgaria no Mato Grosso do Sul

description: Dataset associated with the article: “Efeitos da temperatura e da umidade no desenvolvimento e consumo alimentar de Bombyx mori em sirgarias no Mato Grosso do Sul”.

This dataset contains the raw environmental and biometric data used to evaluate the influence of air temperature, relative humidity and food availability on the larval development of Bombyx mori under real sericulture conditions in Itaquiraí–MS, Brazil.

Data were obtained during three production periods:

- May 2008 (Autumn)

- November 2008 (Spring)

- January 2009 (Summer)

Included data:

- Individual larval measurements (length, weight, instar, replicate bed and quadrant)

- Temperature and relative humidity inside and outside the sericulture shed (initial and final readings)

- Feeding information (fresh leaves supplied, residues)

- Aggregated environmental means used in Table 1 of the manuscript

-  Intermediate organization sheets for complete transparency

All data derive from in-field measurements conducted in commercial sirgarias, following the methodology described in the manuscript.

The dataset supports all results, figures, tables and statistical analyses (ANOVA and Tukey tests) presented in the study.

File formats: xlsx (multi-sheet), containing raw measurements and aggregated values.

Corresponding author: Marcos Massuo Kashiwaqui (mkashiwaqui@yahoo.com.br)
DOI: 10.17026/ar/c26j3r
title: PAN-00105057 - coin/coin-related, Constantinus I (306-337), nummus

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00105057&lt;/p&gt;
description: Modified: 2025-05-12T08:48:28+02:00
DOI: 10.17026/dans-xqn-rg8e
title: PAN-00141523 - plate (type unknown; South-Gaulish terra sigillata)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00141523&lt;/p&gt;
description: Modified: 2025-09-09T17:33:31+02:00
DOI: 10.15468/dl.wsjnu8
title: Occurrence Download

description: A dataset containing 1650150 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 34.085278",
 "DecimalLatitude is less than or equal to 39.085278",
 "DecimalLongitude is greater than or equal to -120.0",
 "DecimalLongitude is less than or equal to -115.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 1650150 records from 318 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048335-251120083545085/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.30866420
title: Análise quantitativa - ferramentas digitais

description: Os dados coletados foram utilizados para uma atividade avaliativa na disciplina de Ferramentas Digitais para a Pesquisa Acadêmica, da Universidade Federal da Bahia - UFBA. É uma pesquisa de análise quantitativa, que buscou compreender o uso de tecnologias emergentes no ensino superior e seus impactos (sendo eles positivos ou negativos) através de informações coletadas de um questionário respondido por discentes de diferentes instituições de ensino superior.
DOI: 10.6084/m9.figshare.30866420.v1
title: Análise quantitativa - ferramentas digitais

description: Os dados coletados foram utilizados para uma atividade avaliativa na disciplina de Ferramentas Digitais para a Pesquisa Acadêmica, da Universidade Federal da Bahia - UFBA. É uma pesquisa de análise quantitativa, que buscou compreender o uso de tecnologias emergentes no ensino superior e seus impactos (sendo eles positivos ou negativos) através de informações coletadas de um questionário respondido por discentes de diferentes instituições de ensino superior.
DOI: 10.17026/ar/komdga
title: PAN-00175692 - marking lead

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00175692&lt;/p&gt;
description: Modified: 2025-10-28T11:39:51+01:00
DOI: 10.15468/dl.76dbbg
title: Occurrence Download

description: A dataset containing 111640 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Piranga flava)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1951",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to April",
 "Month is less than or equal to July",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 111640 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048334-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/ne6hwk
title: PAN-00179392 - clod (ball)

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00179392&lt;/p&gt;
description: Modified: 2025-09-04T11:37:08+02:00
DOI: 10.34740/kaggle/dsv/14118792
title: Garbage Dataset
DOI: 10.15468/dl.v59zjc
title: Occurrence Download

description: A dataset containing 37924 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Picoides dorsalis)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1951",
 "Year is less than or equal to 2024",
 "Month is greater than or equal to April",
 "Month is less than or equal to July",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 37924 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048347-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xq5e3a
title: Occurrence Download

description: A dataset containing 1316088 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "DatasetKey is iNaturalist Research-grade Observations",
 "Country is United States of America",
 "Year is greater than or equal to 1995",
 "Year is less than or equal to 2014"
 ]
}

 The dataset includes 1316088 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048343-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/f6if9p
title: PAN-00136877 - arched bow brooch A1/B

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00136877&lt;/p&gt;
description: Modified: 2025-06-03T12:15:15+02:00
DOI: 10.15468/dl.mswh56
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-117.2444 33.0092,-117.23931 33.0092,-117.23931 33.00926,-117.24028 33.01055,-117.24351 33.01063,-117.2444 33.00926,-117.2444 33.0092))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is December",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 21 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048348-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j4m8n3
title: Occurrence Download

description: A dataset containing 1908 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-117.2444 33.0092,-117.23931 33.0092,-117.23931 33.00926,-117.24028 33.01055,-117.24351 33.01063,-117.2444 33.00926,-117.2444 33.0092))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1908 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048350-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17905487
title: Focus and Distraction 2025 (Dataset, n = 790)

description: This dataset is part of the Human Clarity Institute’s AI–Human Experience 2025 data series. It examines digital focus, distraction triggers, and the emotional experience of losing focus, including task-sustainability duration, primary sources of digital distraction, and self-reported emotional states linked to focus loss.

The dataset includes:• validated 1–7 Likert-scale items• categorical measures of single-task focus duration and perceived focus quality• behavioural indicators such as distraction sources, coping strategies, and focus-maintenance habits• multi-select variables stored as canonical semicolon-delimited snake_case tokens• open-text reflections with minimal safe cleaning (trim + newline removal only)• demographic variables across six English-speaking countries• digital life exposure (daily hours online) and AI-tool usage frequency

Data were collected on 3 September 2025 via Prolific from adults in the UK, US, Australia, Canada, New Zealand, and Ireland.All data were cleaned, anonymised, and processed under the Human Clarity Institute’s machine-readable dataset protocol, which includes:

• canonical snake_case variable naming• validated numeric and categorical ranges• standardised multi-select formats• minimal safe text cleaning• full alignment with the accompanying data dictionary• removal of Prolific IDs, timestamps, and indirect identifiers• SHA-256 checksums for all files• removal of 6 duplicate submissions (final n = 790)

This dataset contributes to understanding how digital environments shape human focus, attention sustainability, and subjective distraction experience, supporting longitudinal tracking of how cognitive load, distraction patterns, and self-regulation behaviours evolve as AI and digital tools become more embedded in everyday life.
DOI: 10.15468/dl.q6f3gy
title: Occurrence Download

description: A dataset containing 156972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Psittacara leucophthalmus"
 ]
}

 The dataset includes 156972 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048311-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mzscv8
title: Occurrence Download

description: A dataset containing 1061 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Gabon",
 "OccurrenceStatus is Present",
 "TaxonKey is Gypohierax angolensis"
 ]
}

 The dataset includes 1061 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048353-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.