cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/sh76m2vgbc
title: Objective Neural Face Recognition Neuromodulation within a Single Transcranial Direct Current Stimulation Session

description: Because of substantial technical and methodological difficulties, the cognitive neuromodulatory impact of transcranial direct current stimulation (tDCS), both during and after stimulation, is still uncertain in humans. In this study, we examined these effects using a sensitive, objective, and reliable neural indicator of face identity recognition. Participants first underwent a sham tDCS condition while rapidly individuating images of unfamiliar faces (Phase 1). tDCS was then delivered for 10 minutes over the right occipito-temporal cortex during the same visual stimulation (Phase 2), followed by another sham stimulation period (Phase 3).
The electroencephalographic (EEG) response associated with face individuation, confined to narrow frequency bins (0.014 Hz bandwidth), decreased significantly by 28% during tDCS. After stimulation, the response increased by 66% relative to the during-tDCS level, indicating a rebound effect. These changes were comparable in magnitude across occipito-temporal areas of both hemispheres and were specific to face individuation, while broader neural responses to the periodic visual stimulation remained unchanged.
Taken together, these findings provide evidence of a significant and selective modulation of an essential human cognitive function following a single tDCS session using only two HD-ring electrodes, and they emphasize the usefulness of frequency-tagged electrophysiology for quantifying neuromodulation effects.
DOI: 10.17632/sh76m2vgbc.1
title: Objective Neural Face Recognition Neuromodulation within a Single Transcranial Direct Current Stimulation Session

description: Because of substantial technical and methodological difficulties, the cognitive neuromodulatory impact of transcranial direct current stimulation (tDCS), both during and after stimulation, is still uncertain in humans. In this study, we examined these effects using a sensitive, objective, and reliable neural indicator of face identity recognition. Participants first underwent a sham tDCS condition while rapidly individuating images of unfamiliar faces (Phase 1). tDCS was then delivered for 10 minutes over the right occipito-temporal cortex during the same visual stimulation (Phase 2), followed by another sham stimulation period (Phase 3).
The electroencephalographic (EEG) response associated with face individuation, confined to narrow frequency bins (0.014 Hz bandwidth), decreased significantly by 28% during tDCS. After stimulation, the response increased by 66% relative to the during-tDCS level, indicating a rebound effect. These changes were comparable in magnitude across occipito-temporal areas of both hemispheres and were specific to face individuation, while broader neural responses to the periodic visual stimulation remained unchanged.
Taken together, these findings provide evidence of a significant and selective modulation of an essential human cognitive function following a single tDCS session using only two HD-ring electrodes, and they emphasize the usefulness of frequency-tagged electrophysiology for quantifying neuromodulation effects.
DOI: 10.17632/9sdzgkms72
title: Magnetic Field-Assisted Bundled Capillary Chromatography for Uranium and Lithium Extraction from Salt Lakes

description: Bundled capillary chromatographic columns with methyl vinyl silicone rubber (MVQ) and polytetrafluoroethylene (PTFE) as substrates were fabricated and assisted by a ring magnetic field for the synchronous extraction of uranium and lithium from salt lakes. Through multiple groups of comparative experiments, the optimal peristaltic pump rotational speed was determined to be 1.81 mL/min and the optimal magnetic field-assisted method for separation is when a ring magnet is nested, with its magnetic field lines pointing opposite to the water flow direction (“S-N”). Among them, the MVQ capillary showed better performance. Without an external magnetic field, the uranium-lithium separation factor and magnesium-lithium separation factor of the MVQ capillary chromatographic column were 1.32 and 1.008, respectively; it required 289 stages of separation to reduce the magnesium-lithium ratio from 200 to 20. Under the action of the “S-N” magnetic field, the uranium-lithium separation factor of the MVQ capillary chromatographic column increased to 1.41, the magnesium-lithium separation factor increased to 1.015, and only 155 stages of separation were needed to reduce the magnesium-lithium ratio to 20. Moreover, the action mechanism of the magnetic field was explored, the possible impact of the liquid membrane on the separation process was further verified, and the movement mechanism of ions inside the capillary chromatographic column was analyzed in depth. The results demonstrate that the external magnetic field can be used to improve the separation and extraction efficiency of uranium and lithium from salt lakes, providing new insights for relevant research.
DOI: 10.17632/9sdzgkms72.1
title: Magnetic Field-Assisted Bundled Capillary Chromatography for Uranium and Lithium Extraction from Salt Lakes

description: Bundled capillary chromatographic columns with methyl vinyl silicone rubber (MVQ) and polytetrafluoroethylene (PTFE) as substrates were fabricated and assisted by a ring magnetic field for the synchronous extraction of uranium and lithium from salt lakes. Through multiple groups of comparative experiments, the optimal peristaltic pump rotational speed was determined to be 1.81 mL/min and the optimal magnetic field-assisted method for separation is when a ring magnet is nested, with its magnetic field lines pointing opposite to the water flow direction (“S-N”). Among them, the MVQ capillary showed better performance. Without an external magnetic field, the uranium-lithium separation factor and magnesium-lithium separation factor of the MVQ capillary chromatographic column were 1.32 and 1.008, respectively; it required 289 stages of separation to reduce the magnesium-lithium ratio from 200 to 20. Under the action of the “S-N” magnetic field, the uranium-lithium separation factor of the MVQ capillary chromatographic column increased to 1.41, the magnesium-lithium separation factor increased to 1.015, and only 155 stages of separation were needed to reduce the magnesium-lithium ratio to 20. Moreover, the action mechanism of the magnetic field was explored, the possible impact of the liquid membrane on the separation process was further verified, and the movement mechanism of ions inside the capillary chromatographic column was analyzed in depth. The results demonstrate that the external magnetic field can be used to improve the separation and extraction efficiency of uranium and lithium from salt lakes, providing new insights for relevant research.
DOI: 10.17632/t2jdtnncz4
title: Beyond Outcome Variance: Addressing Ranking Instability via an RSSI-SA-ADF Framework for Adaptive Ecological Restoration Decision-Making

description: Research Hypothesis
This dataset supports the study "Beyond Outcome Variance: Addressing Ranking Instability via an RSSI-SA-ADF Framework for Adaptive Ecological Restoration Decision-Making," which challenges the reliance on variance-based sensitivity analysis (e.g., Sobol indices) in environmental decision-making. We hypothesize that parameters driving numerical outcome variance are distinct from those triggering Ranking Structural Instability (RSI). Minor fluctuations in "structural" parameters (e.g., stakeholder preferences) often cause strategy ranking reversals despite contributing little to total variance.
Data Content and Methodology
The files provide documentation and empirical data from three ecological restoration projects in China (Nanyang, Shangqiu, and Jiaozuo). Key components include:
Frameworks (S2, S3, S6): Mathematical derivations for the MD-LEA evaluation model, the RSSI algorithm, and NSGA-II/TOPSIS optimization procedures.
Parameter Distributions (S7): Probability distributions and sources for inputs like Planting/Maintenance costs and ESV preference weights.
Stakeholder Analysis (S4, S12): Aggregated AHP matrices for risk threshold calibration (τ = 0.15) and post-implementation feedback surveys.
Validation Metrics (S8, S9, S15): Efficiency benchmarks, convergence plots, and ROI calculations comparing SA-ADF against traditional frameworks.
Notable Findings
Risk-Driver Reversal (S10): Technical parameters dominate outcome variance, but social preference parameters are the primary drivers of ranking reversals.
Performance (S3, S4): The RSSI early warning reduced false-positive alerts by 7.0% and plant replanting rates by 68.6%.
Economic Impact (S15): The framework achieved a 109.0% ROI by triggering interventions only when structural instability was detected.
Interpretation and Usage
Replication: Use (S7) distributions to test the MD-LEA model; code is available in the linked GitHub repository.
Calibration: Refer to (S4) to set the risk threshold (τ) based on specific cost ratios of false positives to negatives.
Contextual Analysis: (S10) illustrates how risk structures vary by project type (e.g., preference-driven vs. duration-constrained) to guide sensitivity analysis for new projects.
DOI: 10.17632/t2jdtnncz4.1
title: Beyond Outcome Variance: Addressing Ranking Instability via an RSSI-SA-ADF Framework for Adaptive Ecological Restoration Decision-Making

description: Research Hypothesis
This dataset supports the study "Beyond Outcome Variance: Addressing Ranking Instability via an RSSI-SA-ADF Framework for Adaptive Ecological Restoration Decision-Making," which challenges the reliance on variance-based sensitivity analysis (e.g., Sobol indices) in environmental decision-making. We hypothesize that parameters driving numerical outcome variance are distinct from those triggering Ranking Structural Instability (RSI). Minor fluctuations in "structural" parameters (e.g., stakeholder preferences) often cause strategy ranking reversals despite contributing little to total variance.
Data Content and Methodology
The files provide documentation and empirical data from three ecological restoration projects in China (Nanyang, Shangqiu, and Jiaozuo). Key components include:
Frameworks (S2, S3, S6): Mathematical derivations for the MD-LEA evaluation model, the RSSI algorithm, and NSGA-II/TOPSIS optimization procedures.
Parameter Distributions (S7): Probability distributions and sources for inputs like Planting/Maintenance costs and ESV preference weights.
Stakeholder Analysis (S4, S12): Aggregated AHP matrices for risk threshold calibration (τ = 0.15) and post-implementation feedback surveys.
Validation Metrics (S8, S9, S15): Efficiency benchmarks, convergence plots, and ROI calculations comparing SA-ADF against traditional frameworks.
Notable Findings
Risk-Driver Reversal (S10): Technical parameters dominate outcome variance, but social preference parameters are the primary drivers of ranking reversals.
Performance (S3, S4): The RSSI early warning reduced false-positive alerts by 7.0% and plant replanting rates by 68.6%.
Economic Impact (S15): The framework achieved a 109.0% ROI by triggering interventions only when structural instability was detected.
Interpretation and Usage
Replication: Use (S7) distributions to test the MD-LEA model; code is available in the linked GitHub repository.
Calibration: Refer to (S4) to set the risk threshold (τ) based on specific cost ratios of false positives to negatives.
Contextual Analysis: (S10) illustrates how risk structures vary by project type (e.g., preference-driven vs. duration-constrained) to guide sensitivity analysis for new projects.
DOI: 10.18758/74y0x62y
title: Regional weighted means of groundbased ozone (O3) anomalies timeseries in the Arctic, 2000-2024

description: Total and partial columns of ozone (O3) relative anomalies created by averaging with a weighted mean ozone relative anomalies timeseries of different groundbased instruments in the Arctic region (60-90°N) for the 2000-2024 time period. 

Types of instruments used: Brewer and Dobson spectrophotometers from WOUDC (https://woudc.org/en/data/data-search-and-download) for the total column of ozone only, FTIR spectrometers from NDACC (https://ndacc.larc.nasa.gov/) for all columns and ozonesondes from HEGIFTOM (https://hegiftom.meteo.be/datasets/ozonesondes) for the troposphere, lower and mid stratosphere. 
Each individual dataset used to create the present merged datasets are under the responsibility of their respective PIs. 
Further details on how the merged datasets are obtained (i.e., definition of regions, list of instruments merged for each timeseries, anomalies calculation, weighting calculation, trends calculated from these columns, etc.) are given in https://doi.org/10.5194/egusphere-2025-6473.
DOI: 10.17632/x4kh298ndx
title: Development of a novel clinical decision support tool for determining the need for whole-body computed tomography in pediatric trauma patients: the WHOLE score

description: The aim of this study was to investigate the association between injury mechanism, physical examination findings, and laboratory parameters, and the presence of injuries involving multiple CT regions on whole-body computed tomography (WBCT) in trauma patients under 18 years of age. Additionally, this study sought to develop a clinical risk assessment score to assist emergency medicine specialists in decision-making, with the goal of reducing unnecessary WBCT utilization.
DOI: 10.17632/x4kh298ndx.1
title: Development of a novel clinical decision support tool for determining the need for whole-body computed tomography in pediatric trauma patients: the WHOLE score

description: The aim of this study was to investigate the association between injury mechanism, physical examination findings, and laboratory parameters, and the presence of injuries involving multiple CT regions on whole-body computed tomography (WBCT) in trauma patients under 18 years of age. Additionally, this study sought to develop a clinical risk assessment score to assist emergency medicine specialists in decision-making, with the goal of reducing unnecessary WBCT utilization.
DOI: 10.17632/m5h64j94zg
title: Dataset Description: Panel Data of Digital Infrastructure and Regional Economic Integration in the Yangtze River Delta Region (2013-2022)

description: Main Variables Dataset.xlsx: 2013-2022 panel data of 41 Yangtze River Delta cities (410 observations, no missing values), including core variables (digital_infra, integration_level) and 7 control variables (urban_rate, gov_intervention, etc.).
Indicators and Scores of Digital Infrastructure.xlsx: 410 rows of data covering 6 secondary indicators (X1-X6), composite scores (digital_infra) and standardized scores (stand_digital_infra), enabling traceability of digital infrastructure calculation.
Indicators and Scores of Regional Economic Integration.xlsx: 409 rows of raw data on 21 basic indicators (regional GDP, fixed asset investment, fiscal revenue/expenditure, etc.) to support measuring regional economic integration.
Indicators and Scores of Controlled Variable.xlsx: 410 rows of raw/standardized control variables (population, core_dummy, etc.), consistent with the main dataset in time and regional scope.
DOI: 10.17632/m5h64j94zg.1
title: Dataset Description: Panel Data of Digital Infrastructure and Regional Economic Integration in the Yangtze River Delta Region (2013-2022)

description: Main Variables Dataset.xlsx: 2013-2022 panel data of 41 Yangtze River Delta cities (410 observations, no missing values), including core variables (digital_infra, integration_level) and 7 control variables (urban_rate, gov_intervention, etc.).
Indicators and Scores of Digital Infrastructure.xlsx: 410 rows of data covering 6 secondary indicators (X1-X6), composite scores (digital_infra) and standardized scores (stand_digital_infra), enabling traceability of digital infrastructure calculation.
Indicators and Scores of Regional Economic Integration.xlsx: 409 rows of raw data on 21 basic indicators (regional GDP, fixed asset investment, fiscal revenue/expenditure, etc.) to support measuring regional economic integration.
Indicators and Scores of Controlled Variable.xlsx: 410 rows of raw/standardized control variables (population, core_dummy, etc.), consistent with the main dataset in time and regional scope.
DOI: 10.35097/1405
title: Search for alternative two-step-absorption photoinitiators for 3D laser nanoprinting

description: Research data corresponding to the publication "Search for alternative two-step-absorption photoinitiators for 3D laser nanoprinting".
DOI: 10.5281/zenodo.18484633
title: Preprocessed GEOM-Drugs Dataset

description: Preprocessed GEOM-Drugs dataset from MiDi (Vignac et al, 2025) for fast loading. Intended for use with the atomic-datasets library.
DOI: 10.5281/zenodo.18484634
title: Preprocessed GEOM-Drugs Dataset

description: Preprocessed GEOM-Drugs dataset from MiDi (Vignac et al, 2025) for fast loading. Intended for use with the atomic-datasets library.
DOI: 10.35097/1n8u3z4zvh9w76ch
title: Simultaneously improving sodium ionic conductivity and dendrite behaviour of NaSICON ceramics by grain-boundary modification

description: The TEM data can be open and analysis through Velox (Thermofisher).
DOI: 10.17632/6wt6t9kswt
title: Dataset on the enthalpy of mixing in binary liquids

description: Two versions of the dataset are available:
- Version 1 includes data on 375 binary liquids and machine learning predictions in 2415 binary systems, as detailed in our 2024 publication [1].
- Version 2 expands on this with data on 433 binary liquids, including 29 data obtained from ab initio molecular dynamics simulations. It also includes the updated predictions in 2415 binary liquids. Further details can be found in our 2026 publication [2].

Both versions are organized as follows:
- The "Dataset" folder contains data on the enthalpy of mixing collected from Calphad assessments in composition domains where the models are supported by experimental measurements, as well as additional data from ab initio molecular dynamics for Version 2.
- The "Predictions" folder contains machine learning predictions given as Redlich-Kister polynomials in 2415 binary liquids generated by 70 elements. These predictions are compared with those from the Miedema model in both tables and figures where data are also plotted when available.

For more information, and to use this dataset, please refer to these publications:
[1] G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, Calphad 87 (2024) 102745, https://doi.org/10.1016/j.calphad.2024.102745
[2] Q. Bizot, R. Tamura, G. Deffrennes, Active Learning for Predicting the Enthalpy of Mixing in Binary Liquids Based on Ab Initio Molecular Dynamics, Comput. Mater. Sci. 266 (2026), 114568, https://doi.org/10.1016/j.commatsci.2026.114568
DOI: 10.17632/6wt6t9kswt.4
title: Dataset on the enthalpy of mixing in binary liquids

description: Two versions of the dataset are available:
- Version 1 includes data on 375 binary liquids and machine learning predictions in 2415 binary systems, as detailed in our 2024 publication [1].
- Version 2 expands on this with data on 433 binary liquids, including 29 data obtained from ab initio molecular dynamics simulations. It also includes the updated predictions in 2415 binary liquids. Further details can be found in our 2026 publication [2].

Both versions are organized as follows:
- The "Dataset" folder contains data on the enthalpy of mixing collected from Calphad assessments in composition domains where the models are supported by experimental measurements, as well as additional data from ab initio molecular dynamics for Version 2.
- The "Predictions" folder contains machine learning predictions given as Redlich-Kister polynomials in 2415 binary liquids generated by 70 elements. These predictions are compared with those from the Miedema model in both tables and figures where data are also plotted when available.

For more information, and to use this dataset, please refer to these publications:
[1] G. Deffrennes, B. Hallstedt, T. Abe, Q. Bizot, E. Fischer, J-M. Joubert, K. Terayama, and R. Tamura, Data-driven study of the enthalpy of mixing in the liquid phase, Calphad 87 (2024) 102745, https://doi.org/10.1016/j.calphad.2024.102745
[2] Q. Bizot, R. Tamura, G. Deffrennes, Active Learning for Predicting the Enthalpy of Mixing in Binary Liquids Based on Ab Initio Molecular Dynamics, Comput. Mater. Sci. 266 (2026), 114568, https://doi.org/10.1016/j.commatsci.2026.114568
DOI: 10.5281/zenodo.18584578
title: Preprocessed CrossDocked dataset

description: Preprocessed CrossDocked dataset for fast loading without PyTorch dependencies. Intended for use with the atomic-datasets library.
DOI: 10.5281/zenodo.18584577
title: Preprocessed CrossDocked dataset

description: Preprocessed CrossDocked dataset for fast loading without PyTorch dependencies. Intended for use with the atomic-datasets library.
DOI: 10.15468/dl.zpw7hz
title: Occurrence Download

description: A dataset containing 1267 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Phyllostachys edulis"
 ]
}

 The dataset includes 1267 records from 131 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005155-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/bp46tt93dg
title: Variable environmental effects on nutrient availability in temperate forest soils during period 1961–2020

description: The data package contains ESRI shapefile and table summarizing canonical correlation analyses between environmental predictors (X) and forest soil fertility features (Y) during normal periods 1961-2020 in the Czech Republic. Environmental predictors were defined by climatic, pollution and subsoil properties, while soil fertility was indicated through pH, organic carbon, total nitrogen and exchangeable cations from sorption complex. The tables and shapefile database are connective via primary key of rocky geomorphological units (RGMU). The shapefile contains multipolygons of the RGMUs defined on the basis of overlays between relief and bedrock types in biogeographical division of the Czech Republic under coordination system Greenwich/Křovák East North (102067).
DOI: 10.17632/bp46tt93dg.2
title: Variable environmental effects on nutrient availability in temperate forest soils during period 1961–2020

description: The data package contains ESRI shapefile and table summarizing canonical correlation analyses between environmental predictors (X) and forest soil fertility features (Y) during normal periods 1961-2020 in the Czech Republic. Environmental predictors were defined by climatic, pollution and subsoil properties, while soil fertility was indicated through pH, organic carbon, total nitrogen and exchangeable cations from sorption complex. The tables and shapefile database are connective via primary key of rocky geomorphological units (RGMU). The shapefile contains multipolygons of the RGMUs defined on the basis of overlays between relief and bedrock types in biogeographical division of the Czech Republic under coordination system Greenwich/Křovák East North (102067).