cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4y25bd8y5f
title: Telemetry-based PAM

description: This repository contain the data for the paper "Acoustic recordings from narrow-band telemetry arrays allow long-term monitoring of the marine ecological state".
The data consider of environment sound level recorded by TBR-700 from 2017 until 2021.
It also include the data of wide-band recording experiment done at the same site in the folder MothCompareTBR.
DOI: 10.17632/4y25bd8y5f.1
title: Telemetry-based PAM

description: This repository contain the data for the paper "Acoustic recordings from narrow-band telemetry arrays allow long-term monitoring of the marine ecological state".
The data consider of environment sound level recorded by TBR-700 from 2017 until 2021.
It also include the data of wide-band recording experiment done at the same site in the folder MothCompareTBR.
DOI: 10.15468/dl.3qfezs
title: Occurrence Download

description: A dataset containing 134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phractocephalus hemioliopterus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 134 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050184-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/3wvsc4n2c7
title: Iron (Fe) isotopes decipher Fe fate in acid mine drainage within a karst watershed

description: The dataset shows the result of Fe isotope, hydrochemistry, and mineral composition of samples from a karst watershed affected by AMD in southwest China. Table 1 shows water chemistry and Fe isotope compositions in the water samples. Metal concentrations and Fe isotope compositions in the solid samples are shown in Table 2. Mineral compositions of solid samples obtained by XRD are shown in Table S1. Summary of Mössbauer parameters estimated for samples is shown in Table S2 .
DOI: 10.17632/3wvsc4n2c7.1
title: Iron (Fe) isotopes decipher Fe fate in acid mine drainage within a karst watershed

description: The dataset shows the result of Fe isotope, hydrochemistry, and mineral composition of samples from a karst watershed affected by AMD in southwest China. Table 1 shows water chemistry and Fe isotope compositions in the water samples. Metal concentrations and Fe isotope compositions in the solid samples are shown in Table 2. Mineral compositions of solid samples obtained by XRD are shown in Table S1. Summary of Mössbauer parameters estimated for samples is shown in Table S2 .
DOI: 10.17632/7kyvnngh6v
title: Data of silicon isotope of ocean island basalts

description: Table 1 includes Si isotope data for 80 OIB samples from five different regions around the world. Table S1 includes the major and trace element data as well as the radiogenic isotope data of these 80 samples. Among these samples, 37 samples from St. Helena, several Cook-Austral Islands (Rurutu, Tubuai, and Mangaia), and two islands of the Azores archipelago (São Jorge, Terceira) exhibit HIMU characteristics. Thirteen samples from three islands of Samoa (Ta’u, Ofu, and Savai’i) and 14 samples from São Miguel in the Azores exhibit variable EM Ⅱ characteristics (Fig. 1). Additionally, it also includes 16 samples from Hekla, Iceland, with a wide range of SiO2 contents.
DOI: 10.17632/7kyvnngh6v.2
title: Data of silicon isotope of ocean island basalts

description: Table 1 includes Si isotope data for 80 OIB samples from five different regions around the world. Table S1 includes the major and trace element data as well as the radiogenic isotope data of these 80 samples. Among these samples, 37 samples from St. Helena, several Cook-Austral Islands (Rurutu, Tubuai, and Mangaia), and two islands of the Azores archipelago (São Jorge, Terceira) exhibit HIMU characteristics. Thirteen samples from three islands of Samoa (Ta’u, Ofu, and Savai’i) and 14 samples from São Miguel in the Azores exhibit variable EM Ⅱ characteristics (Fig. 1). Additionally, it also includes 16 samples from Hekla, Iceland, with a wide range of SiO2 contents.
DOI: 10.17632/rhpcmk4n9r
title: Data for Steady-state Migration of Barchan Dunes

description: data includes the wind speeds, sand flux from BSNE, and DSM data for the barchan dune.
DOI: 10.17632/rhpcmk4n9r.1
title: Data for Steady-state Migration of Barchan Dunes

description: data includes the wind speeds, sand flux from BSNE, and DSM data for the barchan dune.
DOI: 10.17632/t6mpm52tvc
title: Mitigation strategies reduce CH4 and N2O, but not the CO2 emissions: A Second-Order Meta-Analysis

description: Mitigating greenhouse gas (GHG) emissions from agricultural ecosystems is critical for addressing climate change and fostering sustainable farming advancement. While numerous mitigation strategies have been proposed to mitigate GHG emissions, their effectiveness and applicability remain controversial. Thus, this study generalized 35,060 observation data on the global and national scales to conduct a second-order meta-analysis of the efficacy of 15 mitigation measures in four categories (amendments, high-efficiency fertilizers, protective agriculture, and other measures) on CO2, CH4, and N2O emission reduction.
DOI: 10.17632/t6mpm52tvc.1
title: Mitigation strategies reduce CH4 and N2O, but not the CO2 emissions: A Second-Order Meta-Analysis

description: Mitigating greenhouse gas (GHG) emissions from agricultural ecosystems is critical for addressing climate change and fostering sustainable farming advancement. While numerous mitigation strategies have been proposed to mitigate GHG emissions, their effectiveness and applicability remain controversial. Thus, this study generalized 35,060 observation data on the global and national scales to conduct a second-order meta-analysis of the efficacy of 15 mitigation measures in four categories (amendments, high-efficiency fertilizers, protective agriculture, and other measures) on CO2, CH4, and N2O emission reduction.
DOI: 10.17632/h473ddnn3f
title: Experimental Study on Seepage at the Soil-Structure Interface

description: To investigate the seepage erosion failure mechanism at the interface between earth-rock dams and culverts, this study systematically examined three key factors—clay content, compaction degree, and duration of hydraulic gradient—and their influence on interface stability. Seepage erosion tests were conducted using clay-sand mixed soil in contact with structural interfaces.
Three soil sample types with varying clay contents were prepared, and their specific particle size distributions are detailed in Data 1. By applying different hydraulic gradients, the dynamic flow velocity and mass loss of particles during seepage were recorded. Representative data from three typical experimental conditions are presented in Data 2. Data 3, 4, and 5 respectively illustrate how clay content, compaction degree, and duration of hydraulic gradient affect seepage velocity and hydraulic conductivity. These datasets provide insights into the macroscopic seepage characteristics and the progression of erosion within the interface zone.
To further elucidate the erosion mechanisms at the mesoscopic scale, nuclear magnetic resonance (NMR) technology was employed to monitor pore structure evolution before and after the application of hydraulic gradients. This included changes in pore distribution, porosity, free water, and NMR permeability. The corresponding mesoscopic data are detailed in Data 6 (Sheet 2) and Data 7 (Sheet 3).
Collectively, these datasets capture the multi-scale erosion process, ranging from macroscopic seepage behavior to mesoscopic pore evolution. They not only support the validation of existing seepage erosion models but also serve as a critical foundation for safety assessments and numerical simulations of soil-structure interfaces.
DOI: 10.17632/h473ddnn3f.1
title: Experimental Study on Seepage at the Soil-Structure Interface

description: To investigate the seepage erosion failure mechanism at the interface between earth-rock dams and culverts, this study systematically examined three key factors—clay content, compaction degree, and duration of hydraulic gradient—and their influence on interface stability. Seepage erosion tests were conducted using clay-sand mixed soil in contact with structural interfaces.
Three soil sample types with varying clay contents were prepared, and their specific particle size distributions are detailed in Data 1. By applying different hydraulic gradients, the dynamic flow velocity and mass loss of particles during seepage were recorded. Representative data from three typical experimental conditions are presented in Data 2. Data 3, 4, and 5 respectively illustrate how clay content, compaction degree, and duration of hydraulic gradient affect seepage velocity and hydraulic conductivity. These datasets provide insights into the macroscopic seepage characteristics and the progression of erosion within the interface zone.
To further elucidate the erosion mechanisms at the mesoscopic scale, nuclear magnetic resonance (NMR) technology was employed to monitor pore structure evolution before and after the application of hydraulic gradients. This included changes in pore distribution, porosity, free water, and NMR permeability. The corresponding mesoscopic data are detailed in Data 6 (Sheet 2) and Data 7 (Sheet 3).
Collectively, these datasets capture the multi-scale erosion process, ranging from macroscopic seepage behavior to mesoscopic pore evolution. They not only support the validation of existing seepage erosion models but also serve as a critical foundation for safety assessments and numerical simulations of soil-structure interfaces.
DOI: 10.5281/zenodo.17094494
title: Trilateral Security Nexus Framework (TSNF): India's Transformative Treaty Model Integrating Law, Technology, and Development for Global Cooperative Security

description: This work presents the Trilateral Security Nexus Framework (TSNF) — a groundbreaking, treaty-level model designed to address India’s border and internal security challenges while pioneering an internationally replicable architecture for cooperative security governance.

 

Unlike traditional security treaties limited to defense or intelligence-sharing, TSNF integrates four core dimensions:

 

Legal enforceability → A binding trilateral treaty between India, selected neighboring states, and an international security organization.

 

Operational innovation → Establishment of the Trilateral Security Coordination Council (TSCC), Joint Intelligence Fusion Centre (JIFC), Border Activation Zones (BAZs), and Rapid Response Cells (RRCs).

 

Technological empowerment → AI-driven predictive intelligence, blockchain-based transparency, biometric and satellite–drone surveillance, and robust cybersecurity safeguards.

 

Socio-economic and ethical governance → Development programs in BAZs, human rights compliance, independent oversight, and community engagement to transform borders into corridors of opportunity.

 

 

The framework is supported by comparative analysis (India–Bangladesh, Nepal, Myanmar, NATO, Schengen, SCO), operational manuals, model domestic legislation, financial/resource mobilization plans, KPIs, and geopolitical assessments. Through this comprehensive design, TSNF provides both a blueprint for India’s national resilience and a Global South-led model of cooperative, transparent, and people-centered security governance.

 

By combining law + technology + development + diplomacy, TSNF positions India as a civilizational leader and norm-setter in shaping 21st-century global security. Its emphasis on transparency, socio-economic upliftment, and ethical governance distinguishes it from NATO or SCO, making it both globally scalable and uniquely India-centric.

 

Keywords: India, Border Security, Trilateral Treaty, AI Governance, Blockchain Transparency, Cooperative Security, Civilizational Diplomacy, Global South, International Law, Human Rights, Development–Security Nexus.
DOI: 10.15468/dl.6z2kze
title: Occurrence Download

description: A dataset containing 109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Machine Observation",
 "Continent is North America",
 "Country is United States of America",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Absent",
 "TaxonKey is Spionidae"
 ]
}

 The dataset includes 109 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050185-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gkba4q
title: Occurrence Download

description: A dataset containing 534 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Heliconia irrasa"
 ]
}

 The dataset includes 534 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050187-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2jj5v3
title: CCDC 2339255: Experimental Crystal Structure Determination

description: Related Article: Maria A. Gromova, Yurii V. Kharitonov, Tatyana S. Golubeva, Tatyana V. Rybalova, Elvira E. Shults|2024|Steroids|208|109457|doi:10.1016/j.steroids.2024.109457
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.25574/13414
title: Chandra X-ray Observatory ObsId 13414

description: Mapping the Spatial Distribution of the ACIS Contaminant
DOI: 10.15468/dl.kvug33
title: Occurrence Download

description: A dataset containing 4731 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Ecological typology of waterways, vegetation surveys"
 ]
}

 The dataset includes 4731 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050188-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/13417
title: Chandra X-ray Observatory ObsId 13417

description: Mapping the Spatial Distribution of the ACIS Contaminant
DOI: 10.15468/dl.8aa9df
title: Occurrence Download

description: A dataset containing 2073 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-105.52477 22.53718,-104.89272 22.53718,-104.89272 22.99108,-105.52477 22.99108,-105.52477 22.53718))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Aves, Mammalia, Amphibia, Squamata, Testudines, Crocodylia)"
 ]
}

 The dataset includes 2073 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050190-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uttpte
title: Occurrence Download

description: A dataset containing 4657 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is European stag beetle monitoring network: transect observations"
 ]
}

 The dataset includes 4657 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050189-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/14273
title: Chandra X-ray Observatory ObsId 14273

description: AO-13 Calibration Observations of A1795
DOI: 10.25574/14274
title: Chandra X-ray Observatory ObsId 14274

description: AO-13 Calibration Observations of A1795
DOI: 10.15468/dl.5a27ht
title: Occurrence Download

description: A dataset containing 1596580 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is DELTATRACK - Herring gulls (Larus argentatus, Laridae) and lesser black-backed gulls (Larus fuscus, Laridae) breeding at Neeltje Jans (Netherlands)"
 ]
}

 The dataset includes 1596580 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050159-250827131500795/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.30096346
title: <b>Wind speed manipulation experimental data from the Community Land Model version 5 (CLM5)</b>

description: In this study, the CLM was run in the offline mode. To achieve carbon, water and energy steady state at the start of the simulations<sup>62</sup>, CLM5 was run for 400 years in the “spin‐up” mode with accelerated decomposition rates of soil organic matters, followed by an additional 800 years’ run in the “normal mode”. By the end of the spin‐up, the total ecosystem C was drifting by less than 0.02 Pg C year<sup>–1</sup> at global scale, much lower than the 0.1 Pg C yr<sup>-1</sup> threshold recommended for the C4MIP by Jones et al.<sup>63</sup>. Then, experimental simulations were conducted using CLM5 for varying wind speed scenarios for the period of 1983 – 2014, including:i) Control run: The simulation was forced by the default air forcing dataset of CLM5 – CRUNCEP version 7 meteorological data (6-hourly data; https://rda.ucar.edu/datasets), except for wind speed, which was replaced by data from the CRU JRA version 2.2 dataset, because the CRUNCEP7 wind speed revealed widespread increasing trend of terrestrial wind speed during 1983 – 2014, inconsistent with observations; in contrast, CRU JRA2.2 wind speed showed overall decreasing trend of terrestrial wind speed during the same period. All air forcing data had a temporal resolution of 6-hourly and a spatial resolution of 0.5° × 0.5°, and the simulation was conducted at 0.9° × 1.25° resolution. The atmospheric CO<sub>2</sub> concentration in the simulation was set to a constant value of 367 ppm (default value in the model) to exclude effects of the rising CO<sub>2</sub> concentration on GPP.ii) Sensitivity run: All model settings and drivers were the same as the control run, except that the wind speed was uniformly increased / decreased by 1% and 8% respectively throughout the simulation period. The extracted declining trends in spatially-averaged terrestrial wind speed during 1983–2014 were -1.48% and -1.95% per decade from CRU dataset and CESM2 simulation, respectively (Fig. 1a). Previous studies reported an averaged terrestrial wind speed decline of up to 8% over the past three decades<sup>3</sup>. Adjustments of 1% and 8% were determined to cover the range of the terrestrial wind speed changes. We haven’t further manipulated wind speed within the range of 1%– 8%, because the responses of GPP to wind speed changes (ΔGPP) from -8% to +8% are essentially linear (Fig. S12).iii) Detrended wind speed run: All model settings were the same as the control run, except that the long-term trend in wind speed was eliminated. The singular spectrum analysis<sup>64</sup> was used to extract and remove the long-term trend in wind speed, and the extraction was carried out on a 5-day scale, instead of 6-hour or daily scale, to deal with the requirements of substantial computational resources. Specifically, trend extraction was implemented using function ‘trenddecomp’ in MATLAB for each terrestrial grid.
DOI: 10.6084/m9.figshare.30096346.v1
title: CLM5 experimental simulations

description: In this study, the CLM was run in the offline mode. To achieve carbon, water and energy steady state at the start of the simulations<sup>62</sup>, CLM5 was run for 400 years in the “spin‐up” mode with accelerated decomposition rates of soil organic matters, followed by an additional 800 years’ run in the “normal mode”. By the end of the spin‐up, the total ecosystem C was drifting by less than 0.02 Pg C year<sup>–1</sup> at global scale, much lower than the 0.1 Pg C yr<sup>-1</sup> threshold recommended for the C4MIP by Jones et al.<sup>63</sup>. Then, experimental simulations were conducted using CLM5 for varying wind speed scenarios for the period of 1983 – 2014, including:i) Control run: The simulation was forced by the default air forcing dataset of CLM5 – CRUNCEP version 7 meteorological data (6-hourly data; https://rda.ucar.edu/datasets), except for wind speed, which was replaced by data from the CRU JRA version 2.2 dataset, because the CRUNCEP7 wind speed revealed widespread increasing trend of terrestrial wind speed during 1983 – 2014, inconsistent with observations; in contrast, CRU JRA2.2 wind speed showed overall decreasing trend of terrestrial wind speed during the same period. All air forcing data had a temporal resolution of 6-hourly and a spatial resolution of 0.5° × 0.5°, and the simulation was conducted at 0.9° × 1.25° resolution. The atmospheric CO<sub>2</sub> concentration in the simulation was set to a constant value of 367 ppm (default value in the model) to exclude effects of the rising CO<sub>2</sub> concentration on GPP.ii) Sensitivity run: All model settings and drivers were the same as the control run, except that the wind speed was uniformly increased / decreased by 1% and 8% respectively throughout the simulation period. The extracted declining trends in spatially-averaged terrestrial wind speed during 1983–2014 were -1.48% and -1.95% per decade from CRU dataset and CESM2 simulation, respectively (Fig. 1a). Previous studies reported an averaged terrestrial wind speed decline of up to 8% over the past three decades<sup>3</sup>. Adjustments of 1% and 8% were determined to cover the range of the terrestrial wind speed changes. We haven’t further manipulated wind speed within the range of 1%– 8%, because the responses of GPP to wind speed changes (ΔGPP) from -8% to +8% are essentially linear (Fig. S12).iii) Detrended wind speed run: All model settings were the same as the control run, except that the long-term trend in wind speed was eliminated. The singular spectrum analysis<sup>64</sup> was used to extract and remove the long-term trend in wind speed, and the extraction was carried out on a 5-day scale, instead of 6-hour or daily scale, to deal with the requirements of substantial computational resources. Specifically, trend extraction was implemented using function ‘trenddecomp’ in MATLAB for each terrestrial grid.