cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.9zv9mh
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Italy",
 "DatasetKey is Lepidoptera Eastern Fennoscandia (Luomus) (LEPFEN)"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053707-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fbsjgwp2mg
title: EM_Replication

description: README: Replication Package
Paper Title
Does Public Data Openness Facilitate Corporate ESG Performance? Evidence from China
Authors:
Hongyan Wang (School of Economics, Nankai University)
Guodong Huang (School of Economics and Trade, Hunan University)
Prof. Hui Wang (School of Economics and Trade, Hunan University)
Date: December 13, 2025
1. Overview 
This replication package provides all the publicly available data, code, and instructions required to reproduce the main results of the above-mentioned research paper. The package is designed to facilitate transparncy and enable independent verification of all statistical findings reported in the study.
DOI: 10.17632/fbsjgwp2mg.1
title: EM_Replication

description: README: Replication Package
Paper Title
Does Public Data Openness Facilitate Corporate ESG Performance? Evidence from China
Authors:
Hongyan Wang (School of Economics, Nankai University)
Guodong Huang (School of Economics and Trade, Hunan University)
Prof. Hui Wang (School of Economics and Trade, Hunan University)
Date: December 13, 2025
1. Overview 
This replication package provides all the publicly available data, code, and instructions required to reproduce the main results of the above-mentioned research paper. The package is designed to facilitate transparncy and enable independent verification of all statistical findings reported in the study.
DOI: 10.17632/2m93kp88d5
title: Replication files for: Public Investment and Real Exchange Rate Dynamics: The Role of Public Capital Productivity

description: This replication package contains all codes required to reproduce the figures reported in the paper “Public Investment and Real Exchange Rate Dynamics: The Role of Public Capital Productivity.”
All results are generated using MATLAB scripts.
DOI: 10.17632/2m93kp88d5.1
title: Replication files for: Public Investment and Real Exchange Rate Dynamics: The Role of Public Capital Productivity

description: This replication package contains all codes required to reproduce the figures reported in the paper “Public Investment and Real Exchange Rate Dynamics: The Role of Public Capital Productivity.”
All results are generated using MATLAB scripts.
DOI: 10.15468/dl.n7pbse
title: Occurrence Download

description: A dataset containing 693 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Italy",
 "DatasetKey is ISEA PAS Lepidoptera Collection"
 ]
}

 The dataset includes 693 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053708-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gc3w7d4xtc
title: WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning

description: WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning - Official Reproduction Package

This dataset provides the complete reproduction package for the paper "WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning." It includes source code, experimental data, trained model checkpoints, and scripts to reproduce every table and figure in the manuscript.

RESEARCH BACKGROUND

Complex-valued neural networks (CVNNs) are powerful for processing data with inherent complex structure, such as PolSAR imagery and frequency-domain signals. However, traditional CVNNs impose strict holomorphic constraints that limit expressiveness. This research introduces Wirtinger Derivative Complete Complex Network (WCCN), which relaxes these constraints by processing both the complex signal and its conjugate. This enables capturing richer, non-circular features while maintaining computational efficiency.

KEY CONTRIBUTIONS

1. Superior Parameter Efficiency: WCCN achieves comparable or better accuracy than baselines with significantly fewer parameters.

2. Robust Generalization: WCCN maintains stable performance even with limited training data.

3. Novel Components: The package includes the proposed wcPReLU activation and lightweight heads, with ablation studies confirming their effectiveness.

DATASET CONTENTS

(1) Source Code: PyTorch implementations of WCCN and baselines in "models/". For image classification, baselines include DCN, SurReal, and CDS-I. For PolSAR classification, all models (CV-CNN baseline and WcCvCnn) are implemented in "polsar/models.py".

(2) Configuration Files: JSON files in "configs/" specifying hyperparameters for every experiment.

(3) Training Logs: The "outputs/" directory contains detailed logs recording loss and accuracy for all experiments.

(4) Model Checkpoints: Trained model weights in "checkpoints/" for direct evaluation.

(5) Raw Metrics: JSON and CSV files with exact numerical values from all tables.

(6) Visualization Scripts: Scripts in "scripts/" generate all figures from the paper.

EXPERIMENTAL SCOPE

- Image Classification: CIFAR-10/100 with multiple input encodings (RGB, LAB, Sliding, RTC6).
- PolSAR Classification: Flevoland, San Francisco, and Oberpfaffenhofen datasets, comparing CV-CNN baseline with WcCvCnn.

NOTE ON OUTPUTS.ZIP: Mendeley Data restricts folder depth to 7 levels. The "outputs/" directory exceeds this limit, so it is provided as outputs.zip containing complete training logs, process files, and experimental results. Extract to root before use.

This dataset enables full reproducibility of the research findings.
DOI: 10.17632/gc3w7d4xtc.1
title: WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning

description: WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning - Official Reproduction Package

This dataset provides the complete reproduction package for the paper "WCCN: A Parameter and Computationally Efficient Framework for Complex-Valued Deep Learning." It includes source code, experimental data, trained model checkpoints, and scripts to reproduce every table and figure in the manuscript.

RESEARCH BACKGROUND

Complex-valued neural networks (CVNNs) are powerful for processing data with inherent complex structure, such as PolSAR imagery and frequency-domain signals. However, traditional CVNNs impose strict holomorphic constraints that limit expressiveness. This research introduces Wirtinger Derivative Complete Complex Network (WCCN), which relaxes these constraints by processing both the complex signal and its conjugate. This enables capturing richer, non-circular features while maintaining computational efficiency.

KEY CONTRIBUTIONS

1. Superior Parameter Efficiency: WCCN achieves comparable or better accuracy than baselines with significantly fewer parameters.

2. Robust Generalization: WCCN maintains stable performance even with limited training data.

3. Novel Components: The package includes the proposed wcPReLU activation and lightweight heads, with ablation studies confirming their effectiveness.

DATASET CONTENTS

(1) Source Code: PyTorch implementations of WCCN and baselines in "models/". For image classification, baselines include DCN, SurReal, and CDS-I. For PolSAR classification, all models (CV-CNN baseline and WcCvCnn) are implemented in "polsar/models.py".

(2) Configuration Files: JSON files in "configs/" specifying hyperparameters for every experiment.

(3) Training Logs: The "outputs/" directory contains detailed logs recording loss and accuracy for all experiments.

(4) Model Checkpoints: Trained model weights in "checkpoints/" for direct evaluation.

(5) Raw Metrics: JSON and CSV files with exact numerical values from all tables.

(6) Visualization Scripts: Scripts in "scripts/" generate all figures from the paper.

EXPERIMENTAL SCOPE

- Image Classification: CIFAR-10/100 with multiple input encodings (RGB, LAB, Sliding, RTC6).
- PolSAR Classification: Flevoland, San Francisco, and Oberpfaffenhofen datasets, comparing CV-CNN baseline with WcCvCnn.

NOTE ON OUTPUTS.ZIP: Mendeley Data restricts folder depth to 7 levels. The "outputs/" directory exceeds this limit, so it is provided as outputs.zip containing complete training logs, process files, and experimental results. Extract to root before use.

This dataset enables full reproducibility of the research findings.
DOI: 10.17632/3rkj78f3vp
title: Supplement 1: Risk of Malignancies and All-Cause Mortality in Patients with Pemphigus

description: Supplement 1: Risk of Malignancies and All-Cause Mortality in Patients with Pemphigus
DOI: 10.17632/3rkj78f3vp.4
title: Supplement 1: Risk of Malignancies and All-Cause Mortality in Patients with Pemphigus

description: Supplement 1: Risk of Malignancies and All-Cause Mortality in Patients with Pemphigus
DOI: 10.7929/issda/hsbncu
title: The Irish Longitudinal Study on Ageing (TILDA) Wave 2, 2012-2013

description: TILDA collects information on all aspects of health, economic and social circumstances from adults aged 50 years and over resident in Ireland. Waves of data collection take place every two years. TILDA provides a comprehensive and accurate picture of the characteristics, needs and contributions of older persons in Ireland to inform and support improvements in policy and practice; advancements in technology and innovation; tailored education and training through an enhanced ageing research infrastructure; harmonisation with leading international research to ensure adoption of best policy and practice and comparability of results. TILDA is necessary to act as the foundation on which we can plan appropriate health, medical, social and economic policies for our older adults. Wave 2 dataset: version 2.8The version 2.8 PMF dataset includes data from 7,206 TILDA respondents who completed a second self-interview during the Wave 2 fieldwork. Data from any respondents who were new at Wave 2, respondents who had passed away between the waves and data from returning respondents who required a proxy interview have been removed (n=408) to protect anonymity. The dataset includes data from the home interview, the self-completion questionnaire and certain other variables derived from this data. More information on these derived variables can be found in the ‘Wave 2 Derived Variable Codebook’.
DOI: 10.17632/22jp2xv46c
title: Data for Article "Optimizing Lightweight Convolutional Networks via Topo-logical Attention and Entropy-Constrained Distillation: A Spectral-Topological Approach for Robust Facial Expression Recognition"

description: These files are output results of our experments in article.
DOI: 10.17632/22jp2xv46c.1
title: Data for Article "Optimizing Lightweight Convolutional Networks via Topo-logical Attention and Entropy-Constrained Distillation: A Spectral-Topological Approach for Robust Facial Expression Recognition"

description: These files are output results of our experments in article.
DOI: 10.17632/nc7dsgtvkk
title: Whole-genome sequencing and integrative genomic data-driven profiling of Carbapenems-resistant Klebsiella pneumoniae isolated from human urine samples in the Iraq

description: This dataset contains supplementary tables and figures related to the study on Klebsiella pneumoniae whole genome sequencing. 
It includes 1 Word file with all tables and figures. 
The raw sequencing data are publicly available in the NCBI Sequence Read Archive under BioProject accession PRJNA1371618 with run accession number SRR27266164. 
Researchers can use this dataset to access the sequencing data, examine the tables and figures, and perform genome analysis, annotation, and comparative studies. 
The dataset is intended to support transparency and reproducibility of the study findings
DOI: 10.17632/nc7dsgtvkk.1
title: Whole-genome sequencing and integrative genomic data-driven profiling of Carbapenems-resistant Klebsiella pneumoniae isolated from human urine samples in the Iraq

description: This dataset contains supplementary tables and figures related to the study on Klebsiella pneumoniae whole genome sequencing. 
It includes 1 Word file with all tables and figures. 
The raw sequencing data are publicly available in the NCBI Sequence Read Archive under BioProject accession PRJNA1371618 with run accession number SRR27266164. 
Researchers can use this dataset to access the sequencing data, examine the tables and figures, and perform genome analysis, annotation, and comparative studies. 
The dataset is intended to support transparency and reproducibility of the study findings
DOI: 10.6084/m9.figshare.30885308
title: Assessment of Subjective Well-Being, Quality of Life, and Successful Aging in Older Adults

description: A cross-sectional study was conducted with 403 adults aged 60 years and older in Eastern Croatia. Data were collected using a sociodemographic questionnaire, the Self-assessment of Successful Ageing Scale (SSAS), and the Personal Wellbeing Index (PWI).
DOI: 10.6084/m9.figshare.30885308.v1
title: Assessment of Subjective Well-Being, Quality of Life, and Successful Aging in Older Adults

description: A cross-sectional study was conducted with 403 adults aged 60 years and older in Eastern Croatia. Data were collected using a sociodemographic questionnaire, the Self-assessment of Successful Ageing Scale (SSAS), and the Personal Wellbeing Index (PWI).
DOI: 10.17632/hhcmsd7kg9
title: Morphological and geochemical variation in framboidal pyrite aggregates and its implications for paleoenvironmental reconstruction

description: Table S1 Framboid size distributions in various aggregate morphotypes
Table S2 Trace-elemental concentrations and δ34S of pyrite aggregates
DOI: 10.17632/hhcmsd7kg9.1
title: Morphological and geochemical variation in framboidal pyrite aggregates and its implications for paleoenvironmental reconstruction

description: Table S1 Framboid size distributions in various aggregate morphotypes
Table S2 Trace-elemental concentrations and δ34S of pyrite aggregates
DOI: 10.17632/6rw37shr2t
title: AGU_SuppInfo_Word_13-12

description: This document includes the supporting information, associated figures, and data files for the paper entitled 
‘Constraining the mechanisms of early Cenozoic cooling and denudation on the Outer Hebrides, northwest Scotland, using joint apatite fission-track and (U–Th–Sm)/He data.’”
DOI: 10.17632/6rw37shr2t.1
title: AGU_SuppInfo_Word_13-12

description: This document includes the supporting information, associated figures, and data files for the paper entitled 
‘Constraining the mechanisms of early Cenozoic cooling and denudation on the Outer Hebrides, northwest Scotland, using joint apatite fission-track and (U–Th–Sm)/He data.’”
DOI: 10.17632/dmpf5hksjz
title: Parcel-Level Land Titling, Oil Palm, and Deforestation Data from Ucayali, Peru

description: This dataset contains parcel-level spatial data for titled land in Ucayali, Peru, combined with information on land cover, deforestation, and oil palm cultivation. Parcel boundaries are derived from the publicly available regional cadastral database for Ucayali and are linked to land titling records from SUNARP, annual deforestation data from GeoBosques, land-cover classifications from MapBiomas, and oil palm plantation data from Descals et al 2021. The dataset supports analysis of the relationships between land titling, agricultural expansion, and forest loss in a rapidly changing Amazonian frontier. To protect confidential information, this dataset uses the publicly available version of the regional parcel database and may differ slightly from the version used in the associated publication.
DOI: 10.17632/dmpf5hksjz.1
title: Parcel-Level Land Titling, Oil Palm, and Deforestation Data from Ucayali, Peru

description: This dataset contains parcel-level spatial data for titled land in Ucayali, Peru, combined with information on land cover, deforestation, and oil palm cultivation. Parcel boundaries are derived from the publicly available regional cadastral database for Ucayali and are linked to land titling records from SUNARP, annual deforestation data from GeoBosques, land-cover classifications from MapBiomas, and oil palm plantation data from Descals et al 2021. The dataset supports analysis of the relationships between land titling, agricultural expansion, and forest loss in a rapidly changing Amazonian frontier. To protect confidential information, this dataset uses the publicly available version of the regional parcel database and may differ slightly from the version used in the associated publication.
DOI: 10.17632/dbwfcf3bzm
title: Persian Gulf AIS-like Dataset for Risk-Aware Navigation

description: Synthetic AIS-like dataset comprising 30,000 records for Persian Gulf maritime traffic analysis (25-28°N, 50-54°E). Features: MMSI, timestamp, lat/lon (w/ GPS noise), speed (5-20 knots), wind speed (9-20 knots), current speed (0.3-0.6 knots), obstacle distance (20-600m), risk labels (21.7% high-risk ratio). JSON format, S-100 compliant structure. Used for LSTM risk/trajectory prediction and risk-aware A* path planning.
DOI: 10.17632/dbwfcf3bzm.1
title: Persian Gulf AIS-like Dataset for Risk-Aware Navigation

description: Synthetic AIS-like dataset comprising 30,000 records for Persian Gulf maritime traffic analysis (25-28°N, 50-54°E). Features: MMSI, timestamp, lat/lon (w/ GPS noise), speed (5-20 knots), wind speed (9-20 knots), current speed (0.3-0.6 knots), obstacle distance (20-600m), risk labels (21.7% high-risk ratio). JSON format, S-100 compliant structure. Used for LSTM risk/trajectory prediction and risk-aware A* path planning.
DOI: 10.57702/a32v5ubu
title: CARE Score and Care2CompareDataset usage

description: A Jupyter Notebook describing usage of the Care2Compare Dataset.
DOI: 10.17632/6d4y69dv9x.1
title: A Comprehensive Real-World Dataset of Jackfruit Leaf Diseases and Growth Stages for Intelligent Crop Health Monitoring

description: This dataset presents a high-quality and visually diverse collection of jackfruit (Artocarpus heterophyllus) leaf images captured in real agricultural environments across Savar and Rajbari, Bangladesh. It includes eight curated classes—Blight, Dried, Fungal_Spot, Healthy, Leaf_Miner, Pest_Damage, Senescence, and Young—covering both disease conditions and leaf growth stages, along with a structured CSV metadata file containing image names, labels, and location information. Designed for machine learning and deep learning applications, the dataset supports disease detection, growth-stage classification, and intelligent crop health monitoring, making it a valuable resource for precision agriculture and sustainable jackfruit cultivation.

Dataset Classes and Image Counts:
Blight:500 images
Dried:500 images
Fungal_Spot:500 images
Healthy:500 images
Leaf_Miner:500 images
Pest_Damage:500 images
Senescence:500 images
Young:500 images


Image Details:
Original image resolution:3072 x 4096 
Resized image resolution:480 x 560
Image format: JPG
Color mode: RGB
Collection device: Smartphone camera
Location: Savar and Rajbari districts, Bangladesh
DOI: 10.17632/sjt79hnb2f
title: 3D Mexican Sign Language Static Alphabet

description: This dataset is about Mexican Sign Language (MSL) static alphabet. The 21 sign letters were acquired in 3D using a MS Kinect v1 sensor. Fifteen persons participated to perform each of the signs once. Therefore, 315 files were captured.
DOI: 10.17632/sjt79hnb2f.1
title: 3D Mexican Sign Language Static Alphabet

description: This dataset is about Mexican Sign Language (MSL) static alphabet. The 21 sign letters were acquired in 3D using a MS Kinect v1 sensor. Fifteen persons participated to perform each of the signs once. Therefore, 315 files were captured.
DOI: 10.17632/wzrmntwr3f
title: A Dataset on Research Excellence and Technology Commercialization Success in Southeast Asia under the impact of Artificial Intelligence Application and Governance.

description: This dataset is designed to study the application of generative AI in scientific research at universities in Southeast Asia, focusing on:
- The level of generative AI use in research
- The influence of organizational, governance, legal, and individual capabilities factors
- The impact on research collaboration, adaptability, and research outcomes

The dataset consists of 4 worksheets:
- Questionnaire: Survey questionnaire
- Data_Individual Level: Aggregated data at the individual level
- Data_Organization Level: Aggregated data at the organizational level
- List of School: List of educational institutions within the scope of the study

The main variable groups include:
- Demographic questions (8): Role, Exp, Qual, Disc, Country, Type, Name, Involve
- Independent variables (69) coded with the prefix IV
- Mediating variables (28) coded with the prefix MV
- Dependent variables (32) is encoded with the prefix DV

The measurement questionnaire uses a 5-point Likert scale, from "1 = Strongly disagree" to "5 = Strongly agree"
DOI: 10.17632/wzrmntwr3f.1
title: A Dataset on Research Excellence and Technology Commercialization Success in Southeast Asia under the impact of Artificial Intelligence Application and Governance.

description: This dataset is designed to study the application of generative AI in scientific research at universities in Southeast Asia, focusing on:
- The level of generative AI use in research
- The influence of organizational, governance, legal, and individual capabilities factors
- The impact on research collaboration, adaptability, and research outcomes

The dataset consists of 4 worksheets:
- Questionnaire: Survey questionnaire
- Data_Individual Level: Aggregated data at the individual level
- Data_Organization Level: Aggregated data at the organizational level
- List of School: List of educational institutions within the scope of the study

The main variable groups include:
- Demographic questions (8): Role, Exp, Qual, Disc, Country, Type, Name, Involve
- Independent variables (69) coded with the prefix IV
- Mediating variables (28) coded with the prefix MV
- Dependent variables (32) is encoded with the prefix DV

The measurement questionnaire uses a 5-point Likert scale, from "1 = Strongly disagree" to "5 = Strongly agree"
DOI: 10.15468/dl.brzhma
title: Occurrence Download

description: A dataset containing 2040 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Hohenbergia"
 ]
}

 The dataset includes 2040 records from 115 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053709-251120083545085/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.cc2mjrdb
title: CCDC 2429172: Experimental Crystal Structure Determination

description: Related Article: Ashutosh Nath, John Mark Award, Wei Zhang|2025|CSD Communication|||
description: Related Article: Ashutosh Nath, John Mark Awad and Wei Zhang
|2025|Beilstein J.Org.Chem.|21|1161|doi:10.3762/bjoc.21.92
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.