cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/x42jrzkcds.1
title: Dataset on Heavy Metal Contamination of Vegetables and Consumer Perceptions in Lubumbashi, Democratic Republic of Congo

description: In the mining city of Lubumbashi, Democratic Republic of Congo, intensive mining activities have led to heavy metal contamination of vegetables, posing serious risks to public health. This dataset contains chemical analysis data on heavy metals extracted from vegetables using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES), combined with household survey data collected from 353 urban households. The raw chemical dataset quantifies concentrations of key heavy metals in the six most commonly consumed vegetables, while the survey dataset documents consumer exposure, health risk indicators, and perceptions of heavy metal contamination along the food chain. By integrating environmental chemistry and social data, the dataset addresses a critical knowledge gap by enabling the assessment of contamination levels, associated health risks, and consumer awareness in a mining-impacted urban context. This dataset provides a valuable resource for researchers, public health and environmental practitioners, and policymakers seeking to understand the disconnect between contamination levels, consumer behavior, and risk awareness, and to support the design of integrated food safety and environmental policy interventions in mining-affected cities.
DOI: 10.17632/46rdn73gy2
title: A mycovirus switches between endophytic and entomopathogenic lifestyles in a fungal insecticide

description: The dataset consists of three Excel files containing raw data, processed data, and statistical analyses generated during the study. One of the file includes quantitative PCR (qPCR) data used to assess endophytic colonization by Beauveria bassiana in sprayed leaves and unsprayed distant leaves of melon plants. 
Another file contains aphid bioassay data evaluating adult A. gossypii mortality and fungal outgrowth following feeding on colonized melon plants. Mortality was recorded daily over a seven-day period, and data include replicate-level observations, pooled mortality values, and statistical outputs used to compare treatments.Finally, the last file includes transcriptomic data derived from RT-qPCR analyses of plant defense-related genes involved in ethylene, jasmonic acid, and salicylic acid biosynthesis and signaling, as well as pathogenesis-related genes.
DOI: 10.5281/zenodo.18552817
title: Ether Electrolytes Enable High-Rate and Long-Life Sodium-based Energy Storage in Poly(1,4-anthraquinone) Cathodes
DOI: 10.5281/zenodo.18552816
title: Ether Electrolytes Enable High-Rate and Long-Life Sodium-based Energy Storage in Poly(1,4-anthraquinone) Cathodes
DOI: 10.17632/46rdn73gy2.1
title: A mycovirus switches between endophytic and entomopathogenic lifestyles in a fungal insecticide

description: The dataset consists of three Excel files containing raw data, processed data, and statistical analyses generated during the study. One of the file includes quantitative PCR (qPCR) data used to assess endophytic colonization by Beauveria bassiana in sprayed leaves and unsprayed distant leaves of melon plants. 
Another file contains aphid bioassay data evaluating adult A. gossypii mortality and fungal outgrowth following feeding on colonized melon plants. Mortality was recorded daily over a seven-day period, and data include replicate-level observations, pooled mortality values, and statistical outputs used to compare treatments.Finally, the last file includes transcriptomic data derived from RT-qPCR analyses of plant defense-related genes involved in ethylene, jasmonic acid, and salicylic acid biosynthesis and signaling, as well as pathogenesis-related genes.
DOI: 10.17632/3b3gvf2d7m
title: data repository

description: Supplementary data for the manuscript "Are ‘Green’ Silver Nanoparticle Synthesis Routes Really Green? Evaluating True Sustainability Across Traditional, Biogenic, and Biopolymer-Assisted Methods".
DOI: 10.17632/3b3gvf2d7m.1
title: data repository

description: Supplementary data for the manuscript "Are ‘Green’ Silver Nanoparticle Synthesis Routes Really Green? Evaluating True Sustainability Across Traditional, Biogenic, and Biopolymer-Assisted Methods".
DOI: 10.5281/zenodo.18591396
title: Menções a objetos científicos no site Reclame Aqui

description: Este conjunto de dados serviu como base de análise para o Resumo Expandido "A circulação da Informação Científica no Portal Reclame aqui e seu potencial uso altmétrico".Os seguintes termos foram buscados no site Reclame Aqui: “doi.org”, “periódico científico”, “journal”, “editora científica”, “revista científica”, “artigo científico” e “publicação científica”.Os resultados deste levantamento está aprentados neste conjunto de dados, contendo: termo buscado, filtros aplicados, título da reclamação (contendo anonimização quando o nome da empresa foi mencionado), resposta (sim, não ou réplica), Empresa mencionada (com nomes das empresas anonimizados), Categoria/Tipo de empresa, tags, menção ao objeto científico e link da reclamação.
DOI: 10.5281/zenodo.18591395
title: Menções a objetos científicos no site Reclame Aqui

description: Este conjunto de dados serviu como base de análise para o Resumo Expandido "A circulação da Informação Científica no Portal Reclame aqui e seu potencial uso altmétrico".Os seguintes termos foram buscados no site Reclame Aqui: “doi.org”, “periódico científico”, “journal”, “editora científica”, “revista científica”, “artigo científico” e “publicação científica”.Os resultados deste levantamento está aprentados neste conjunto de dados, contendo: termo buscado, filtros aplicados, título da reclamação (contendo anonimização quando o nome da empresa foi mencionado), resposta (sim, não ou réplica), Empresa mencionada (com nomes das empresas anonimizados), Categoria/Tipo de empresa, tags, menção ao objeto científico e link da reclamação.
DOI: 10.6084/m9.figshare.19328939
title: MultiPic: Multilingual Picture Database

description: Database of name agreement and familiarity for a set of 500 colored pictures of concrete objects in 35 different languages (i.e., American English, Australian English, Basque, Belgium Dutch, British English, Cantonese, Catalan, Cypriot Greek, Czech, Finnish, French, Galician, German, Greek, Hebrew, Hungarian, Italian, Korean, Lebanese Arabic, Malay, Malay English, Mandarin Chinese, Netherlands Dutch, Norwegian, Polish, Portuguese, Quebec French, Rioplatense Spanish, Russian, Serbian, Slovak, Spanish, Turkish, Ukrainian, Welsh).
DOI: 10.6084/m9.figshare.19328939.v9
title: MultiPic: Multilingual Picture Database

description: Database of name agreement and familiarity for a set of 500 colored pictures of concrete objects in 35 different languages (i.e., American English, Australian English, Basque, Belgium Dutch, British English, Cantonese, Catalan, Cypriot Greek, Czech, Finnish, French, Galician, German, Greek, Hebrew, Hungarian, Italian, Korean, Lebanese Arabic, Malay, Malay English, Mandarin Chinese, Netherlands Dutch, Norwegian, Polish, Portuguese, Quebec French, Rioplatense Spanish, Russian, Serbian, Slovak, Spanish, Turkish, Ukrainian, Welsh).
DOI: 10.6084/m9.figshare.19328939.v8
title: MultiPic: Multilingual Picture Database

description: Database of name agreement and familiarity for a set of 500 colored pictures of concrete objects in 35 different languages (i.e., American English, Australian English, Basque, Belgium Dutch, British English, Cantonese, Catalan, Cypriot Greek, Czech, Finnish, French, Galician, German, Greek, Hebrew, Hungarian, Italian, Korean, Lebanese Arabic, Malay, Malay English, Mandarin Chinese, Netherlands Dutch, Norwegian, Polish, Portuguese, Quebec French, Rioplatense Spanish, Russian, Serbian, Slovak, Spanish, Turkish, Ukrainian, Welsh).
DOI: 10.15468/dl.takywb
title: Occurrence Download

description: A dataset containing 300 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acmella paniculata",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 300 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005124-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/848krwy32k.1
title: Risk of paradoxical eczema among patients on psoriasis biologics: A Multicenter Cohort Study

description: Supplementary Methods
DOI: 10.15468/dl.ayy44h
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hyphessobrycon weitzmanorum",
 "DecimalLatitude is not null",
 "DecimalLongitude is not null"
 ]
}

 The dataset includes 12 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005126-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fd5h9s2vbc
title: Coupled-Perception-Framework-for-Road-Condition-Assessment

description: Coupled-Perception-Framework-for-Road-Condition-Assessment
This study introduces an innovative approach for high-precision International Roughness Index (IRI) estimation using low-cost telemetry data, addressing the balance between cost and accuracy in road condition assessment. 
Project Structure
data/: Contains the dataset used in this paper.
optuna/: Includes all base model experiments, enhanced model and ablation study experiments, visualization code, SHAP model interpretation code, and all figures in the paper.
Filter.py: The filter designed in this paper.
environment.yml: Environment configuration file.
Environment Configuration
This project was developed on a workstation with the following specifications:

OS: Windows 11
CPU: Intel Core i7-12700K
GPU: NVIDIA GeForce RTX 3080
RAM: 32GB DDR4
Python: 3.13.5
Key Libraries: PyTorch, Optuna, Scikit-learn, Matplotlib, Pandas, NumPy
DOI: 10.17632/fd5h9s2vbc.1
title: Coupled-Perception-Framework-for-Road-Condition-Assessment

description: Coupled-Perception-Framework-for-Road-Condition-Assessment
This study introduces an innovative approach for high-precision International Roughness Index (IRI) estimation using low-cost telemetry data, addressing the balance between cost and accuracy in road condition assessment. 
Project Structure
data/: Contains the dataset used in this paper.
optuna/: Includes all base model experiments, enhanced model and ablation study experiments, visualization code, SHAP model interpretation code, and all figures in the paper.
Filter.py: The filter designed in this paper.
environment.yml: Environment configuration file.
Environment Configuration
This project was developed on a workstation with the following specifications:

OS: Windows 11
CPU: Intel Core i7-12700K
GPU: NVIDIA GeForce RTX 3080
RAM: 32GB DDR4
Python: 3.13.5
Key Libraries: PyTorch, Optuna, Scikit-learn, Matplotlib, Pandas, NumPy
DOI: 10.17632/hnsb3h9353
title: A GRI-Based ESG Disclosure Dataset for Palm Oil, Pulp and Paper, and Forestry Companies in Indonesia

description: This dataset contains ESG (Environmental, Social, and Governance) disclosure 
data for 41 Indonesian forest-utilizing companies listed on the Indonesia 
Stock Exchange (IDX), covering fiscal years 2023 and 2024.

The dataset encompasses 71 company-year observations across three sectors: 
palm oil (21 companies, 37 observations), pulp and paper (11 companies, 
21 observations), and forestry and wood products (9 companies, 
13 observations).

ESG disclosure was assessed using 144 indicators derived from the 
GRI Standards (GRI 102-103, 201-206, 301-308, 401-419), scored using 
a binary approach (1 = disclosed, 0 = not disclosed) through systematic 
content analysis of annual reports and sustainability reports.

The main file (ESG_Dataset_Final.xlsx) contains 6 sheets:
- README: Dataset documentation
- GRI_Checklist: Raw binary disclosure data (144 indicators x 71 observations)
- ESG_Scores: Aggregated dimension and composite scores
- Company_List: Company identifiers and sector classification
- Descriptive_Stats: Summary statistics by dimension and sector
- Indicator_List: Complete list of 144 GRI indicators with disclosure rates

The supplementary file (ESG_Dataset_Full_Repository.xlsx) contains the 
extended dataset of 108 observations from 63 companies across 7 sectors.
DOI: 10.17632/hnsb3h9353.1
title: A GRI-Based ESG Disclosure Dataset for Palm Oil, Pulp and Paper, and Forestry Companies in Indonesia

description: This dataset contains ESG (Environmental, Social, and Governance) disclosure 
data for 41 Indonesian forest-utilizing companies listed on the Indonesia 
Stock Exchange (IDX), covering fiscal years 2023 and 2024.

The dataset encompasses 71 company-year observations across three sectors: 
palm oil (21 companies, 37 observations), pulp and paper (11 companies, 
21 observations), and forestry and wood products (9 companies, 
13 observations).

ESG disclosure was assessed using 144 indicators derived from the 
GRI Standards (GRI 102-103, 201-206, 301-308, 401-419), scored using 
a binary approach (1 = disclosed, 0 = not disclosed) through systematic 
content analysis of annual reports and sustainability reports.

The main file (ESG_Dataset_Final.xlsx) contains 6 sheets:
- README: Dataset documentation
- GRI_Checklist: Raw binary disclosure data (144 indicators x 71 observations)
- ESG_Scores: Aggregated dimension and composite scores
- Company_List: Company identifiers and sector classification
- Descriptive_Stats: Summary statistics by dimension and sector
- Indicator_List: Complete list of 144 GRI indicators with disclosure rates

The supplementary file (ESG_Dataset_Full_Repository.xlsx) contains the 
extended dataset of 108 observations from 63 companies across 7 sectors.
DOI: 10.17632/rdm7yx5bmm
title: Data and codes of "Human frontopolar cortex plays a causal role in decomposing high-dimensional information during decision making"

description: Dataset of the NeuroImage paper "Human frontopolar cortex plays a causal role in decomposing high-dimensional information during decision making"
DOI: 10.15468/dl.9svnyy
title: Occurrence Download

description: A dataset containing 797 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cnidoscolus quercifolius",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 797 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005128-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/rdm7yx5bmm.1
title: Data and codes of "Human frontopolar cortex plays a causal role in decomposing high-dimensional information during decision making"

description: Dataset of the NeuroImage paper "Human frontopolar cortex plays a causal role in decomposing high-dimensional information during decision making"
DOI: 10.35097/emm4bsvq5vf0c3x6
title: Dynamic Multi-AMR Buffer Reshuffling and Retrieval Dataset

description: Input instances and result data for the Exact Formulation and Heuristic for the Dynamic Multi-AMR Buffer Reshuffling and Retrieval Problem
DOI: 10.15468/dl.yz67aa
title: Occurrence Download

description: A dataset containing 6053 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude 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 "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= 56.135291543055025
 AND decimallatitude &lt;= 61.2993700571118
 AND decimallongitude &gt;= 107.93265282528667
 AND decimallongitude &lt;= 126.56678944754769
 AND GBIF_Within('POLYGON ((126.566789 56.135292, 126.566789 61.299370, 107.932653 61.299370, 107.932653 56.135292, 126.566789 56.135292))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 6053 records were derived from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005108-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/b6p8wz78bx
title: Compatibility of Classical Physics, Relativity, and Quantum Mechanics with the NKTg Law

description: This publication presents a consistent systematization of the compatibility between the pillars of modern physics and the NKTg Law on varying inertia. The NKTg Law is shown to be non-contradictory to classical theories, while allowing their dynamical structures to be abstracted into a unified state relationship among position, velocity, and mass. Scope Statement: This publication focuses on establishing the conceptual consistency and compatibility of the NKTg Law with existing physical theories. The content is not intended to replace, refute, or claim full proof of any established theories.
Theoretical Basis
The NKTg Law describes the tendency of motion of a physical object through the relationship among:
• Position (x)
• Velocity (v)
• Mass (m)
General formulation: NKTg = f(x, v, m) 
The system is characterized by two core product quantities (unit: NKTm):
• NKTg₁ = x • p : positional inertia
• NKTg₂ = (dm/dt) • p : varying inertia
________________________________________
1. With Isaac Newton – Classical Mechanics
When the mass of the system does not vary with time, the NKTg Law reduces to a static inertial state.
• Condition: dm/dt = 0
• Consequence: NKTg₂ = 0
• Remaining expression: NKTg = NKTg₁ = x • p
In the context of classical mechanics and Newtonian gravitation, the quantity x • p preserves the structure of the momentum state, reflecting orbital stability and periodic motion.
In the limit of systems with large mass and velocities much smaller than the speed of light, the NKTg Law is structurally compatible, both in form and physical consequences, with all fundamental laws of classical mechanics.
2. With Albert Einstein – Relativity
In high-energy systems where mass and energy can be converted into one another, the NKTg Law extends into a regime of varying inertia.
• As velocity approaches the speed of light, energy and mass are related by E = mc²
• In this case: dm/dt ≠ 0 ⇒ NKTg₂ emerges and plays a dominant role
The NKTg Law describes the dynamical tendency of the system through changes in mass–energy states, without contradicting the fundamental relations of relativity.
In extreme configurations such as strong gravitational fields, the relative imbalance between NKTg₁ (associated with spatial structure) and NKTg₂ (associated with energy state) consistently reflects the phenomenology of relativistic objects, including systems with event horizons.
3. With Werner Heisenberg – Quantum Mechanics
At the microscopic scale, when considering particles with very small mass or mass approaching zero, the varying inertia component vanishes.
• Condition: m → 0 ⇒ dm/dt = 0 ⇒ NKTg₂ = 0
• Then: NKTg = NKTg₁ = x • p
In the quantum context, x and p are no longer interpreted as definite values, but correspond to uncertainties in position and momentum.
The expression x • p is structurally compatible with the Heisenberg uncertainty inequality (Δx • Δp) and does not violate the foundational mathematical form of quantum mechanics.
DOI: 10.17632/b6p8wz78bx.1
title: Compatibility of Classical Physics, Relativity, and Quantum Mechanics with the NKTg Law

description: This publication presents a consistent systematization of the compatibility between the pillars of modern physics and the NKTg Law on varying inertia. The NKTg Law is shown to be non-contradictory to classical theories, while allowing their dynamical structures to be abstracted into a unified state relationship among position, velocity, and mass. Scope Statement: This publication focuses on establishing the conceptual consistency and compatibility of the NKTg Law with existing physical theories. The content is not intended to replace, refute, or claim full proof of any established theories.
Theoretical Basis
The NKTg Law describes the tendency of motion of a physical object through the relationship among:
• Position (x)
• Velocity (v)
• Mass (m)
General formulation: NKTg = f(x, v, m) 
The system is characterized by two core product quantities (unit: NKTm):
• NKTg₁ = x • p : positional inertia
• NKTg₂ = (dm/dt) • p : varying inertia
________________________________________
1. With Isaac Newton – Classical Mechanics
When the mass of the system does not vary with time, the NKTg Law reduces to a static inertial state.
• Condition: dm/dt = 0
• Consequence: NKTg₂ = 0
• Remaining expression: NKTg = NKTg₁ = x • p
In the context of classical mechanics and Newtonian gravitation, the quantity x • p preserves the structure of the momentum state, reflecting orbital stability and periodic motion.
In the limit of systems with large mass and velocities much smaller than the speed of light, the NKTg Law is structurally compatible, both in form and physical consequences, with all fundamental laws of classical mechanics.
2. With Albert Einstein – Relativity
In high-energy systems where mass and energy can be converted into one another, the NKTg Law extends into a regime of varying inertia.
• As velocity approaches the speed of light, energy and mass are related by E = mc²
• In this case: dm/dt ≠ 0 ⇒ NKTg₂ emerges and plays a dominant role
The NKTg Law describes the dynamical tendency of the system through changes in mass–energy states, without contradicting the fundamental relations of relativity.
In extreme configurations such as strong gravitational fields, the relative imbalance between NKTg₁ (associated with spatial structure) and NKTg₂ (associated with energy state) consistently reflects the phenomenology of relativistic objects, including systems with event horizons.
3. With Werner Heisenberg – Quantum Mechanics
At the microscopic scale, when considering particles with very small mass or mass approaching zero, the varying inertia component vanishes.
• Condition: m → 0 ⇒ dm/dt = 0 ⇒ NKTg₂ = 0
• Then: NKTg = NKTg₁ = x • p
In the quantum context, x and p are no longer interpreted as definite values, but correspond to uncertainties in position and momentum.
The expression x • p is structurally compatible with the Heisenberg uncertainty inequality (Δx • Δp) and does not violate the foundational mathematical form of quantum mechanics.