cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/cu6dfv
title: Replication Data for: Blowing Snow Contributes to SMB and SEB over Larsen C ice shelf

description: The processed datasets are for the key variables of the history dump from WRF-ice CNTL and Blow-off simulations at 3 km horizontal resolution during the melting season of 2017-18 over Larsen C ice shelf, Antarctic Peninsula. 

The variables include the terms for surface mass balance calculation, i.e., accumulated blowing snow sublimation, blowing snow transport rate in X- and Y- direction, latent heat flux at the surface, surface and underground runoff, accumulated precipitation, and melted snow; the terms for surface energy budget, i.e., ground heat flux, upward heat flux, latent heat flux, downward short wave flux. The surface skin temperature, horizontal wind speed at 10m height, temperature and dew point, and relative humidity at the bottom model level, and sea level pressure from CNTL simulation are also included in the datasets. The differences of the variables mentioned above between CNTL and Blowoff simulations are also added.
DOI: 10.15468/dl.jfndjh
title: Occurrence Download

description: A dataset containing 979 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen, Fossil)",
 "OccurrenceStatus is Present",
 "TaxonKey is Orcinus orca (Linnaeus, 1758)"
 ]
}

 The dataset includes 979 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002044-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/62j3-rz30
title: Senegal Power Compact - Transmission Project Evaluation Design Report (English)
DOI: 10.3886/jdrc-mg72
title: Senegal Power Compact - Transmission Project Evaluation Design Report (English)
DOI: 10.15468/dl.9w34q9
title: Occurrence Download

description: A dataset containing 906837 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hordeum L."
 ]
}

 The dataset includes 906837 records from 2427 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002036-250424135625364/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/dd76nwg83k.1
title: Flake Tool Transformation: Artefact-by-artefact analysis

description: These data comprise a corpus of artefact-by-artefact descriptions of individual transformation histories for a subset of flake tools from Layer I at the Mira site (predominantly excavated in 2000)
DOI: 10.17632/2tr8c4wyy9
title: (Code) Wavelet-Based Detection and Wavelet-Informed Linear Modeling Framework for BOLD Signal Analysis

description: This dataset contains R scripts used to generate the simulation results reported in
“A Wavelet-Based Detection and Wavelet-Informed Linear Modeling Framework for BOLD Signal Analysis.”

The code implements a controlled single-voxel fMRI simulation framework to compare a standard General Linear Model (GLM) with a phase-restricted wavelet-based detection approach and a Wavelet-Informed GLM (W-iGLM). Simulated BOLD time series are generated by convolving event onsets with canonical or latency-shifted hemodynamic response functions (HRFs) and embedding them in structured, non-stationary noise composed of low-frequency drift, 1/f (“pink”) noise, and autoregressive (AR(1)) components.

The scripts include:

Simulation and condition-comparison loops assessing detection sensitivity as a function of
(i) signal-to-noise ratio (SNR),
(ii) hemodynamic latency mismatch, and
(iii) event duration.

Continuous Wavelet Transform (CWT) analysis using a complex Morlet wavelet, with statistical significance masking, cone-of-influence exclusion, and phase-based filtering.

Extraction of band-limited (6–66 s) post-event wavelet power for condition discrimination.

A data-driven latency estimation procedure based on wavelet power peaks, used to realign GLM regressors in the Wavelet-Informed GLM (W-iGLM).

Output of summary statistics (t-values, p-values, regression coefficients, and R²) as spreadsheet files for visualization and reporting.

All analyses were performed in R using publicly available packages (notably biwavelet and fmrihrf). The code is provided to ensure full reproducibility of the simulations and figures reported in the associated manuscript and may be adapted for methodological exploration of temporal uncertainty in fMRI data analysis.
DOI: 10.17632/2tr8c4wyy9.1
title: (Code) Wavelet-Based Detection and Wavelet-Informed Linear Modeling Framework for BOLD Signal Analysis

description: This dataset contains R scripts used to generate the simulation results reported in
“A Wavelet-Based Detection and Wavelet-Informed Linear Modeling Framework for BOLD Signal Analysis.”

The code implements a controlled single-voxel fMRI simulation framework to compare a standard General Linear Model (GLM) with a phase-restricted wavelet-based detection approach and a Wavelet-Informed GLM (W-iGLM). Simulated BOLD time series are generated by convolving event onsets with canonical or latency-shifted hemodynamic response functions (HRFs) and embedding them in structured, non-stationary noise composed of low-frequency drift, 1/f (“pink”) noise, and autoregressive (AR(1)) components.

The scripts include:

Simulation and condition-comparison loops assessing detection sensitivity as a function of
(i) signal-to-noise ratio (SNR),
(ii) hemodynamic latency mismatch, and
(iii) event duration.

Continuous Wavelet Transform (CWT) analysis using a complex Morlet wavelet, with statistical significance masking, cone-of-influence exclusion, and phase-based filtering.

Extraction of band-limited (6–66 s) post-event wavelet power for condition discrimination.

A data-driven latency estimation procedure based on wavelet power peaks, used to realign GLM regressors in the Wavelet-Informed GLM (W-iGLM).

Output of summary statistics (t-values, p-values, regression coefficients, and R²) as spreadsheet files for visualization and reporting.

All analyses were performed in R using publicly available packages (notably biwavelet and fmrihrf). The code is provided to ensure full reproducibility of the simulations and figures reported in the associated manuscript and may be adapted for methodological exploration of temporal uncertainty in fMRI data analysis.
DOI: 10.17632/9rz8rdn659
title: Science of Sacred Alignments: An Archaeoastronomy Inquiry into Mahalaxmi Temple, Kolhapur

description: The study is to establish a conceptual understanding of Archaeo-astronomy that talks about the cosmos and astronomy through global cases and further examining and validating the summer and winter solstice alignment of Mahalaxmi Temple, Kolhapur.
DOI: 10.17632/9rz8rdn659.1
title: Science of Sacred Alignments: An Archaeoastronomy Inquiry into Mahalaxmi Temple, Kolhapur

description: The study is to establish a conceptual understanding of Archaeo-astronomy that talks about the cosmos and astronomy through global cases and further examining and validating the summer and winter solstice alignment of Mahalaxmi Temple, Kolhapur.
DOI: 10.15468/dl.4jhvas
title: Occurrence Download

description: A dataset containing 1606 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sibbaldianthe bifurca",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1606 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005892-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.umggf5
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mullerochloa",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 133 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005891-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18411250
title: Survey Data on Risk Perception and Willingness to Pay for Honeybee Conservation in Italy

description: This dataset comprises individual-level survey data collected from Italian beekeepers to analyze perceived environmental risks, willingness to pay for honeybee conservation, and related policy preferences. The data were collected between January and March 2021 through an original questionnaire and are used to empirically investigate the determinants of environmental valuation under risk.
DOI: 10.5281/zenodo.18411251
title: Survey Data on Risk Perception and Willingness to Pay for Honeybee Conservation in Italy

description: This dataset comprises individual-level survey data collected from Italian beekeepers to analyze perceived environmental risks, willingness to pay for honeybee conservation, and related policy preferences. The data were collected between January and March 2021 through an original questionnaire and are used to empirically investigate the determinants of environmental valuation under risk.
DOI: 10.17632/4chmf48f7m
title: Geomorphology_FlowTransport_FieldData_VegliatoTorrent

description: The geomorphological settings and the deposits data in the Vegliato Torrent (UD), Italy were sampled during multiple field surveys during late 2024. The Vegliato Torrent main channel was divided into 50 reaches and described by a dataset of four geomorphometric and sedimentological parameters: slope (°), reach width (m), deposit height (m) and largest mobilized clast (mm). The determination of the flow typologies in the main channel was accomplished using the Sediment-Water Flows: Field Survey Worksheet, adapted from Brenna et al. (2020). The worksheets were filled by marking the boxes based on the evidence observed in the field. The worksheets allowed for the determination of four transport typologies: debris flow (DFW), hyperconcentrated flow (HF), debris flood (DFD) and water flow (WF). 
The geomorphological and sedimentological parameters sampled in the field were used to derive the effect of the presence of the control works on the settings of the main channel. The flow transport typologies were analyzed in the reaches where torrent control structures are present to unravel the effects of the structures on sediment dynamics.
DOI: 10.17632/4chmf48f7m.1
title: Geomorphology_FlowTransport_FieldData_VegliatoTorrent

description: The geomorphological settings and the deposits data in the Vegliato Torrent (UD), Italy were sampled during multiple field surveys during late 2024. The Vegliato Torrent main channel was divided into 50 reaches and described by a dataset of four geomorphometric and sedimentological parameters: slope (°), reach width (m), deposit height (m) and largest mobilized clast (mm). The determination of the flow typologies in the main channel was accomplished using the Sediment-Water Flows: Field Survey Worksheet, adapted from Brenna et al. (2020). The worksheets were filled by marking the boxes based on the evidence observed in the field. The worksheets allowed for the determination of four transport typologies: debris flow (DFW), hyperconcentrated flow (HF), debris flood (DFD) and water flow (WF). 
The geomorphological and sedimentological parameters sampled in the field were used to derive the effect of the presence of the control works on the settings of the main channel. The flow transport typologies were analyzed in the reaches where torrent control structures are present to unravel the effects of the structures on sediment dynamics.
DOI: 10.17632/f7m96z8dgm
title: Valorizing palm date wastes for hybrid supercapacitor electrode synthesis and evaluation

description: Climate and energy issues continue to drive researchers to develop fossil-free energy technologies that are both sustainable and scalable. In this work, date seeds (DS) are used to produce activated carbon (DSAC), which is then used as a supercapacitor electrode. The synthesis method uses KOH activation followed by Ar-flow calcination at 950°C. The produced DSAC has a high specific surface area of 1374 m2/g and a turbostratic microporous structure (pore size = 1.14 nm)in addition to oxygen functional groups (-C-O-, -OH). The DSAC electrode demonstrates a hybrid electric double-layer capacitor (EDLC) and pseudocapacitive properties, and produces an impressive specific capacitance of 916 F/g at 10 mV/s. The EDLC contribution of that is 90 F/g while the pseudocapacitive contribution is 826 F/g. Furthermore, it has retained 83.3% of its discharging capacity after 2000 cycles of galvanostatic charge and discharge at 10 A/g. Finally, the DSAC electrode is optimized for the less alkaline KOH 1M rather than the 3M one.
DOI: 10.3886/e244741
title: How do Export Risk Guarantees affect Exports? The Case of Switzerland

description: For the case of Switzerland, this paper endeavours to uncover in how far officially backed
guarantees on trade finance achieve their stipulated goal of promoting exports.The results
of gravity equations suggest that the Swiss Export Risk Insurance scheme increases exports in the manufacturing sector by around 1 per cent. As regards specific destination
countries and industries, this average increase is highly concentrated and accrues primarily with exports towards large emerging markets and of chemical products as well as machinery.
DOI: 10.17632/f7m96z8dgm.1
title: Valorizing palm date wastes for hybrid supercapacitor electrode synthesis and evaluation

description: Climate and energy issues continue to drive researchers to develop fossil-free energy technologies that are both sustainable and scalable. In this work, date seeds (DS) are used to produce activated carbon (DSAC), which is then used as a supercapacitor electrode. The synthesis method uses KOH activation followed by Ar-flow calcination at 950°C. The produced DSAC has a high specific surface area of 1374 m2/g and a turbostratic microporous structure (pore size = 1.14 nm)in addition to oxygen functional groups (-C-O-, -OH). The DSAC electrode demonstrates a hybrid electric double-layer capacitor (EDLC) and pseudocapacitive properties, and produces an impressive specific capacitance of 916 F/g at 10 mV/s. The EDLC contribution of that is 90 F/g while the pseudocapacitive contribution is 826 F/g. Furthermore, it has retained 83.3% of its discharging capacity after 2000 cycles of galvanostatic charge and discharge at 10 A/g. Finally, the DSAC electrode is optimized for the less alkaline KOH 1M rather than the 3M one.
DOI: 10.3886/e244741v1
title: How do Export Risk Guarantees affect Exports? The Case of Switzerland

description: For the case of Switzerland, this paper endeavours to uncover in how far officially backed
guarantees on trade finance achieve their stipulated goal of promoting exports.The results
of gravity equations suggest that the Swiss Export Risk Insurance scheme increases exports in the manufacturing sector by around 1 per cent. As regards specific destination
countries and industries, this average increase is highly concentrated and accrues primarily with exports towards large emerging markets and of chemical products as well as machinery.
DOI: 10.11588/duerer.online.697b588c8f85d
title: Betende Maria, https://d-nb.info/gnd/1184444412
DOI: 10.15468/dl.25x9t5
title: Occurrence Download

description: A dataset containing 5637 records in GBIF matching the query:
SELECT
 '585' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 61.2993700571118
 AND decimalLatitude &lt;= 66.79314043790278
 AND decimalLongitude &gt;= 55.37297038330212
 AND decimalLongitude &lt;= 71.84031383705663
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 5637 records were derived from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005878-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/yr9r2gxmrw
title: Three-frame-sequence synthetic PIV (TFS-S-PIV) dataset 1

description: Three-frame-sequence synthetic PIV (TFS-S-PIV) dataset for deep learning models for PIV tasks training, each flow type includes two subfolders, png and flo, the sequence pair is {flow_type}_{%05d}_flow_img1.png, {flow_type}_{%05d}_flow_img2.png, and {flow_type}_{%05d}_flow_img3.png to {flow_type}_{%05d}_flow.flo and {flow_type}_{%05d+1}_flow.flo
DOI: 10.17632/yr9r2gxmrw.1
title: Three-frame-sequence synthetic PIV (TFS-S-PIV) dataset 1

description: Three-frame-sequence synthetic PIV (TFS-S-PIV) dataset for deep learning models for PIV tasks training, each flow type includes two subfolders, png and flo, the sequence pair is {flow_type}_{%05d}_flow_img1.png, {flow_type}_{%05d}_flow_img2.png, and {flow_type}_{%05d}_flow_img3.png to {flow_type}_{%05d}_flow.flo and {flow_type}_{%05d+1}_flow.flo
DOI: 10.6084/m9.figshare.31187908
title: Supplementary Material for: Machine learning models for Disease-free survival analysis after liver resection for hepatocellular carcinoma: a multicentric French collaborative study

description: Introduction
Liver resection (LR) is a potentially curative treatment of hepatocellular carcinoma (HCC) but early recurrence rates remain high reaching as high as 70%. Accurate prediction of disease-free survival (DFS) after LR is crucial to optimize patients’ selection for clinical trials evaluating adjuvant strategies. This study assessed machine learning (ML) models for predicting DFS after LR for HCC. 
Methods
A total of 663 patients who underwent LR between 2010 and 2020 in 3 French HPB referral centers were analyzed. Three ML models —random survival forest (RSF), gradient boosting survival (GBS), and fast survival support vector machine (FSSVM) —were compared with the Cox proportional hazards regression model. Model performance was assessed using C-index and time-dependent area under the curve (AUC). External validation was performed using an independent cohort from a fourth center. Statistical comparisons between models were conducted using paired t-tests. 
Results
After a median follow up of 52 months, recurrence occurred in 43 % of patients and median DFS was 15 months. In the training cohort, RSF achieved the highest discrimination (C-index = 0.721 ± 0.027) and predictive accuracy (AUC = 0.768 ± 0.039) among the four evaluated models. Cox, GBS, and FSSVM showed comparable performance (C-index = 0.684–0.699; AUC = 0.718–0.745). Paired t-tests demonstrated that RSF significantly outperformed Cox for both C-index (p=0.023) and AUC (p = 0.039). In the external validation cohort, all ML models outperformed Cox regression, with RSF showing the highest performance (C-index 0.817, AUC 0.863), suggesting strong generalizability.
Conclusions
RSF significantly improved DFS prediction compared with Cox regression and yielded the best discriminatory performance in both training and external validation cohorts. These findings highlight the value of ML-based survival models, particularly RSF, for enhancing individualized postoperative prognostication and refining patient selection for clinical trials evaluating adjuvant treatment to surveillance after LR for HCC.
DOI: 10.6084/m9.figshare.31187908.v1
title: Supplementary Material for: Machine learning models for Disease-free survival analysis after liver resection for hepatocellular carcinoma: a multicentric French collaborative study

description: Introduction
Liver resection (LR) is a potentially curative treatment of hepatocellular carcinoma (HCC) but early recurrence rates remain high reaching as high as 70%. Accurate prediction of disease-free survival (DFS) after LR is crucial to optimize patients’ selection for clinical trials evaluating adjuvant strategies. This study assessed machine learning (ML) models for predicting DFS after LR for HCC. 
Methods
A total of 663 patients who underwent LR between 2010 and 2020 in 3 French HPB referral centers were analyzed. Three ML models —random survival forest (RSF), gradient boosting survival (GBS), and fast survival support vector machine (FSSVM) —were compared with the Cox proportional hazards regression model. Model performance was assessed using C-index and time-dependent area under the curve (AUC). External validation was performed using an independent cohort from a fourth center. Statistical comparisons between models were conducted using paired t-tests. 
Results
After a median follow up of 52 months, recurrence occurred in 43 % of patients and median DFS was 15 months. In the training cohort, RSF achieved the highest discrimination (C-index = 0.721 ± 0.027) and predictive accuracy (AUC = 0.768 ± 0.039) among the four evaluated models. Cox, GBS, and FSSVM showed comparable performance (C-index = 0.684–0.699; AUC = 0.718–0.745). Paired t-tests demonstrated that RSF significantly outperformed Cox for both C-index (p=0.023) and AUC (p = 0.039). In the external validation cohort, all ML models outperformed Cox regression, with RSF showing the highest performance (C-index 0.817, AUC 0.863), suggesting strong generalizability.
Conclusions
RSF significantly improved DFS prediction compared with Cox regression and yielded the best discriminatory performance in both training and external validation cohorts. These findings highlight the value of ML-based survival models, particularly RSF, for enhancing individualized postoperative prognostication and refining patient selection for clinical trials evaluating adjuvant treatment to surveillance after LR for HCC.
DOI: 10.6084/m9.figshare.31187911
title: Supplementary Material for: Rheology of Twin Anaemia Polycythaemia Sequence – Insights from haemoglobin electrophoresis: a case report

description: Introduction: Twin Anaemia Polycythaemia Sequence (TAPS) is a recognised complication of monochorionic (MC) twins due to abnormal placental vasculature. Determining the rheology involved within the abnormal placental vasculature may help in identifying the optimum treatment option.
Case Presentation: We describe a case of TAPS which was treated via intrauterine transfusions (IUTs) with partial exchange transfusions (PETs) in which additional haemoglobin electrophoresis (HbEp) testing was performed on cordocentesis samples taken before and after intrauterine transfusions and partial exchange transfusions for the donor and recipient twin, respectively. The aim was to assess the flow dynamics from the donor to recipient twin. No differences in hemoglobin A were found in the polycythemic twin after 30 minutes of IUT of the anemic co-twin but within 13 days of first transfusion greater than a 3-fold rise in adult Hemoglobin A was apparent. Within 5 days of second treatment a further 9% rise in Adult Hemoglobin A was encountered.
Conclusion: The use of HbEp testing in this case provided preliminary insights into the fluid dynamics involved in TAPS, however, further studies are required to achieve better understanding.