cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/r6z3xydbzz.2
title: Multilingual Image-Text Dataset for Cross-Lingual NLP and Sentiment Analysis

description: Multilingual Image-Text Dataset for Cross-lingual NLP and Sentiment Analysis has 2,860 images with text in Banglish (Romanised Bangla), Romanised Hindi and English. The records have a combination of visual and textual information, which is best suited to multimodal research.Apply to cross-lingual NLP, sentiment analysis, humor and sarcasm detection, political content and social media research. Text only, image only and multimodal learning Supports binary and multi-class binary and multi-class learning.Images are presented in their original form with no preprocessing or annotations and leave a researcher with absolute freedom to extract features and model them in the way they want. The data set is ethical and there is no personal identifiable information.
It is a highly flexible data set that can be used to learn about multimodal understanding, sentiment prediction, cross-lingual AI models, etc.
DOI: 10.17632/6f967y2jyk
title: Are hopeful narratives more convincing? A laboratory experiment

description: This dataset was generated as a result of the experiement described in the paper "Are hopeful narratives more convincing? A laboratory experiment" by Luca Corazzini, Marco Diamante and Valeria Maggian. The folder contains a README file to replicate the results of the paper.
DOI: 10.17632/6f967y2jyk.1
title: Are hopeful narratives more convincing? A laboratory experiment

description: This dataset was generated as a result of the experiement described in the paper "Are hopeful narratives more convincing? A laboratory experiment" by Luca Corazzini, Marco Diamante and Valeria Maggian. The folder contains a README file to replicate the results of the paper.
DOI: 10.17632/yvkwnjj3b4
title: Impact of the Crises on Household Consumption Patterns: an Analysis of Russian Regions

description: The set of codes, datasets and figures presented below allows you to replicate the results of the study "Impact of the Crises on Household Consumption Patterns: an Analysis of Russian Regions".
File named "Guideline.docx" contains extensive information, including details about the data used, step-by-step instructions for execution of all empirical models and statistical tests. This allows for a complete and accurate reproduction of the study's findings.

The set of datasets, stored in Data folder presents unique data collected and calculated from the Household Budget Survey, conducted by the Federal Statistics Service. It contains information on household income and expenditure for three periods: 2007–2010, 2013–2016, and 2019–2021, covering major economic upheavals in Russia and globally. The data is available in .dta (Stata) and .RData formats (for use in R).
DOI: 10.5281/zenodo.15553717
title: Code and Data for "Capturing non-Fickian mesoscale solute transport in porous media: The role of transient storage and mass exchange"

description: This dataset contains experimental breakthrough curve (BTC) data and the associated Python code used to fit solute transport models, as presented in a paper titled "Capturing non-Fickian mesoscale solute transport in porous media: The role of transient storage and mass exchange", published on WRR. The data were collected from controlled column experiments using two different hydrogel sphere diameters (10 mm and 15 mm), designed to explore the influence of porous media on solute transport behavior at the laboratory scale.
DOI: 10.17632/yvkwnjj3b4.2
title: Impact of the Crises on Household Consumption Patterns: an Analysis of Russian Regions

description: The set of codes, datasets and figures presented below allows you to replicate the results of the study "Impact of the Crises on Household Consumption Patterns: an Analysis of Russian Regions".
File named "Guideline.docx" contains extensive information, including details about the data used, step-by-step instructions for execution of all empirical models and statistical tests. This allows for a complete and accurate reproduction of the study's findings.

The set of datasets, stored in Data folder presents unique data collected and calculated from the Household Budget Survey, conducted by the Federal Statistics Service. It contains information on household income and expenditure for three periods: 2007–2010, 2013–2016, and 2019–2021, covering major economic upheavals in Russia and globally. The data is available in .dta (Stata) and .RData formats (for use in R).
DOI: 10.5281/zenodo.18590729
title: Code and Data for "Capturing non-Fickian mesoscale solute transport in porous media: The role of transient storage and mass exchange"

description: This dataset contains experimental breakthrough curve (BTC) data and the associated Python code used to fit solute transport models, as presented in a paper titled "Capturing non-Fickian mesoscale solute transport in porous media: The role of transient storage and mass exchange", published on WRR. The data were collected from controlled column experiments using two different hydrogel sphere diameters (10 mm and 15 mm), designed to explore the influence of porous media on solute transport behavior at the laboratory scale.
DOI: 10.17632/vzrmtkcs7f
title: Pan-MKK inhibition by myricetin disrupts microglial p38 signaling to rescue sleep deprivation-induced neuropsychiatric disturbances

description: We delineate the molecular pathogenesis of SD-induced neuropsychiatric impairments and establish SX as a multi-target therapeutic intervention. SX corrects behavioral deficits by suppressing hippocampal microglial M1 polarization through inhibition of p38 phosphorylation. Crucially, we identify myricetin as a novel broad-spectrum inhibitor of microglial p38 activation that directly binds p38 and disrupts MKK-mediated phosphorylation, serves as primary active constituent of SX against SD pathology.
DOI: 10.17632/vzrmtkcs7f.1
title: Pan-MKK inhibition by myricetin disrupts microglial p38 signaling to rescue sleep deprivation-induced neuropsychiatric disturbances

description: We delineate the molecular pathogenesis of SD-induced neuropsychiatric impairments and establish SX as a multi-target therapeutic intervention. SX corrects behavioral deficits by suppressing hippocampal microglial M1 polarization through inhibition of p38 phosphorylation. Crucially, we identify myricetin as a novel broad-spectrum inhibitor of microglial p38 activation that directly binds p38 and disrupts MKK-mediated phosphorylation, serves as primary active constituent of SX against SD pathology.
DOI: 10.17632/57bgtkh5mc
title: Targeting SLC16A3 reverses lactate-driven immune dysfunction and immunotherapy resistance in ccRCC

description: Metabolic reprogramming and immune evasion are characteristics of clear cell renal cell carcinoma (ccRCC), but the intrinsic mechanisms of tumor cells in these processes have not been fully determined. Here, through an integrated analysis of 120 publicly available scRNA-seq datasets, spatial transcriptomics, and multiple independent clinical cohorts, we identify SLC16A3 as a major determinant of highly malignant tumor cell status in ccRCC. SLC16A3high cells exhibit enhanced glycolytic activity, increased invasiveness, and strong association with adverse patient outcomes. Mechanistically, SLC16A3-driven glycolysis triggers intracellular and extracellular lactate accumulation, which in turn induces H4K12 lactylation (H4K12la), activates NF-κB, and sustains IL8 expression. This metabolic–epigenetic–cytokine cascade directly impairs CD8⁺ T-cell function, promotes exhaustion, and establishes an immunosuppressive microenvironment. Using molecular docking, biophysical binding assays, tumor organoid–T cell cocultures, orthotopic ccRCC models, and humanized mice, we identify amuvatinib as a potent SLC16A3-targeting small-molecule inhibitor that suppresses tumor progression and restores sensitivity to αPD-1 therapy. Our findings reveal a previously unrecognized mechanism by which SLC16A3 coordinates metabolic and immune reprogramming to drive ccRCC progression and immunotherapy resistance, and highlight SLC16A3 inhibition as a promising therapeutic strategy for metastatic or immune-refractory ccRCC.
DOI: 10.17632/57bgtkh5mc.1
title: Targeting SLC16A3 reverses lactate-driven immune dysfunction and immunotherapy resistance in ccRCC

description: Metabolic reprogramming and immune evasion are characteristics of clear cell renal cell carcinoma (ccRCC), but the intrinsic mechanisms of tumor cells in these processes have not been fully determined. Here, through an integrated analysis of 120 publicly available scRNA-seq datasets, spatial transcriptomics, and multiple independent clinical cohorts, we identify SLC16A3 as a major determinant of highly malignant tumor cell status in ccRCC. SLC16A3high cells exhibit enhanced glycolytic activity, increased invasiveness, and strong association with adverse patient outcomes. Mechanistically, SLC16A3-driven glycolysis triggers intracellular and extracellular lactate accumulation, which in turn induces H4K12 lactylation (H4K12la), activates NF-κB, and sustains IL8 expression. This metabolic–epigenetic–cytokine cascade directly impairs CD8⁺ T-cell function, promotes exhaustion, and establishes an immunosuppressive microenvironment. Using molecular docking, biophysical binding assays, tumor organoid–T cell cocultures, orthotopic ccRCC models, and humanized mice, we identify amuvatinib as a potent SLC16A3-targeting small-molecule inhibitor that suppresses tumor progression and restores sensitivity to αPD-1 therapy. Our findings reveal a previously unrecognized mechanism by which SLC16A3 coordinates metabolic and immune reprogramming to drive ccRCC progression and immunotherapy resistance, and highlight SLC16A3 inhibition as a promising therapeutic strategy for metastatic or immune-refractory ccRCC.
DOI: 10.17632/j8kds94g4t
title: Animations - Mizraim Bessa Doctoral Thesis - UFRN

description: Animations from my PhD Thesis, defended at the Federal University of Rio Grande do Norte - UFRN, Natal - Brazil, in February 06, 2026. In addition, some animations also exhibited during the last presentation/defense.

The Thesis can be found at https://repositorio.ufrn.br/home.
Tittle: Structural, optical, electronic and mechanical properties of two-dimensional BxCyNz based materials.
DOI: 10.17632/j8kds94g4t.1
title: Animations - Mizraim Bessa Doctoral Thesis - UFRN

description: Animations from my PhD Thesis, defended at the Federal University of Rio Grande do Norte - UFRN, Natal - Brazil, in February 06, 2026. In addition, some animations also exhibited during the last presentation/defense.

The Thesis can be found at https://repositorio.ufrn.br/home.
Tittle: Structural, optical, electronic and mechanical properties of two-dimensional BxCyNz based materials.
DOI: 10.17632/dwdjxvkmhc
title: Data for: Spatiotemporal evolution and driving mechanisms of flood resilience in the Beijing–Tianjin–Hebei Urban Agglomeration: An interpretable machine learning approach

description: Data for: Spatiotemporal evolution and driving mechanisms of flood resilience in the Beijing–Tianjin–Hebei Urban Agglomeration: An interpretable machine learning approach
DOI: 10.17632/dwdjxvkmhc.1
title: Data for: Spatiotemporal evolution and driving mechanisms of flood resilience in the Beijing–Tianjin–Hebei Urban Agglomeration: An interpretable machine learning approach

description: Data for: Spatiotemporal evolution and driving mechanisms of flood resilience in the Beijing–Tianjin–Hebei Urban Agglomeration: An interpretable machine learning approach
DOI: 10.17632/w3g2gjbp4t
title: Soil, microbial abundance and enzymatic activities to asymmetrical warming and N-inputs from a dry tropical grassland

description: In the present Anthropocene, climate change has been felt as a serious threat to nutrient cycling and ecosystem functioning. Soil microbial communities and enzymatic activity are crucial for nutrient cycling, although the effects of asymmetric warming and nitrogen (N) input are still unclear. A three-year field experiment (2021-2023) at Banaras Hindu University, Varanasi, India, examined the effects of daytime and nighttime warming and N inputs (0, 30, and 60 kg N ha⁻¹ yr⁻¹) on soil temperature, moisture, pH, C:N, microbial abundance, β1,4-glucosidase (BG), urease (URE), and dehydrogenase (DHA) activities in tropical grassland. Data were statistically analyzed. Asymmetrical warming and N inputs changed soil moisture, temperature, pH, and C:N. These changes affected microbial community structure. Asymmetric warming reduced soil moisture, especially during the night, impacting BG, URE, and DHA activities. N inputs lowered soil pH while enhancing microbial biomass and enzyme activity by alleviating nutritional constraints. Nighttime warming benefited Gram-positive bacteria, but daytime warmings promoted fungi. N input boosted bacterial populations and reduced the fungi-to-bacteria ratio, signifying copiotrophic communities. Microbial and enzymatic activities reached their peak during the wet season and declined in the arid summer. Structural equation modeling and stepwise regression indicated that soil moisture influenced BG and URE, but soil pH impacted DHA. Our results suggested that asymmetrical warming and nitrogen input may influence soil carbon and the nitrogen cycles through moisture and pH pathways and pointed to the incorporation of seasonal hydrothermal dynamics and asymmetrical warming into projections of nitrogen and carbon cycles in arid regions.
DOI: 10.17632/w3g2gjbp4t.1
title: Soil, microbial abundance and enzymatic activities to asymmetrical warming and N-inputs from a dry tropical grassland

description: In the present Anthropocene, climate change has been felt as a serious threat to nutrient cycling and ecosystem functioning. Soil microbial communities and enzymatic activity are crucial for nutrient cycling, although the effects of asymmetric warming and nitrogen (N) input are still unclear. A three-year field experiment (2021-2023) at Banaras Hindu University, Varanasi, India, examined the effects of daytime and nighttime warming and N inputs (0, 30, and 60 kg N ha⁻¹ yr⁻¹) on soil temperature, moisture, pH, C:N, microbial abundance, β1,4-glucosidase (BG), urease (URE), and dehydrogenase (DHA) activities in tropical grassland. Data were statistically analyzed. Asymmetrical warming and N inputs changed soil moisture, temperature, pH, and C:N. These changes affected microbial community structure. Asymmetric warming reduced soil moisture, especially during the night, impacting BG, URE, and DHA activities. N inputs lowered soil pH while enhancing microbial biomass and enzyme activity by alleviating nutritional constraints. Nighttime warming benefited Gram-positive bacteria, but daytime warmings promoted fungi. N input boosted bacterial populations and reduced the fungi-to-bacteria ratio, signifying copiotrophic communities. Microbial and enzymatic activities reached their peak during the wet season and declined in the arid summer. Structural equation modeling and stepwise regression indicated that soil moisture influenced BG and URE, but soil pH impacted DHA. Our results suggested that asymmetrical warming and nitrogen input may influence soil carbon and the nitrogen cycles through moisture and pH pathways and pointed to the incorporation of seasonal hydrothermal dynamics and asymmetrical warming into projections of nitrogen and carbon cycles in arid regions.
DOI: 10.17632/t7ntk649xv
title: Data for: Visibility and Citation in the Scientific Ecosystem: How Persistent Identifiers are Transforming Science

description: This dataset contains semi-structured survey data collected as part of the exploratory study “Visibility and Citation in the Scientific Ecosystem: How Persistent Identifiers are Transforming Science.” The study investigates how the adoption of persistent identifiers (PIDs), such as DOIs and ORCID iDs, is reshaping the landscape of scientific communication by enhancing the discoverability, attribution, and citation of research outputs. The data include responses capturing researchers’ awareness, use, and perceptions of PIDs within the scientific community. These data provide valuable insights into the evolving role of PIDs in research ecosystems and contribute to a better understanding of how these tools influence academic visibility and impact. The dataset supports further research on digital identity management, scholarly communication practices, and metrics of scientific influence.
DOI: 10.17632/t7ntk649xv.4
title: Data for: Visibility and Citation in the Scientific Ecosystem: How Persistent Identifiers are Transforming Science

description: This dataset contains semi-structured survey data collected as part of the exploratory study “Visibility and Citation in the Scientific Ecosystem: How Persistent Identifiers are Transforming Science.” The study investigates how the adoption of persistent identifiers (PIDs), such as DOIs and ORCID iDs, is reshaping the landscape of scientific communication by enhancing the discoverability, attribution, and citation of research outputs. The data include responses capturing researchers’ awareness, use, and perceptions of PIDs within the scientific community. These data provide valuable insights into the evolving role of PIDs in research ecosystems and contribute to a better understanding of how these tools influence academic visibility and impact. The dataset supports further research on digital identity management, scholarly communication practices, and metrics of scientific influence.
DOI: 10.15468/dl.hh95am
title: Occurrence Download

description: A dataset containing 157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pilosocereus pachycladus pernambucoensis",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 157 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005097-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18591205
title: ARCHITECTING DIGITAL TRANSFORMATION: STRATEGIES FOR ENTERPRISE SYSTEM

description: The study really emphasizes how crucial modern enterprise architecture (EA) is for digital transformation, especially with older systems like ERP and ECM getting outdated. By looking at real-life examples from different industries in China, the research found four main points: modular EA frameworks help with making changes on a bigger scale; agile strategies using APIs make it easier for systems to work together smoothly. Proper management and risk assessment play a key role in meeting regulations. Issues like exceeding budgets often result from inconsistent management practices. In general, breaking things down into smaller parts and being flexible lead to better results, with efficiency getting a boost of around 15–30%.
DOI: 10.5281/zenodo.18591206
title: ARCHITECTING DIGITAL TRANSFORMATION: STRATEGIES FOR ENTERPRISE SYSTEM

description: The study really emphasizes how crucial modern enterprise architecture (EA) is for digital transformation, especially with older systems like ERP and ECM getting outdated. By looking at real-life examples from different industries in China, the research found four main points: modular EA frameworks help with making changes on a bigger scale; agile strategies using APIs make it easier for systems to work together smoothly. Proper management and risk assessment play a key role in meeting regulations. Issues like exceeding budgets often result from inconsistent management practices. In general, breaking things down into smaller parts and being flexible lead to better results, with efficiency getting a boost of around 15–30%.
DOI: 10.15468/dl.pds4ke
title: Occurrence Download

description: A dataset containing 557 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Syagrus coronata",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 557 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005098-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hdypcn78xp
title: Data Vulnerability & Privacy Literacy in FinTech Application Usage: An extended APBO framework

description: We surveyed 350 fintech application users using 33 validated 5 point Likert-scale items measuring five constructs. The constructs are namely Data Vulnerability, Privacy Concern, Trustworthiness, Privacy Protection Behaviour, and Privacy Literacy.
DOI: 10.17632/hdypcn78xp.1
title: Data Vulnerability & Privacy Literacy in FinTech Application Usage: An extended APBO framework

description: We surveyed 350 fintech application users using 33 validated 5 point Likert-scale items measuring five constructs. The constructs are namely Data Vulnerability, Privacy Concern, Trustworthiness, Privacy Protection Behaviour, and Privacy Literacy.
DOI: 10.5281/zenodo.18591162
title: Wildfire shape various disturbed types of forest in a distinct way a medium-term perspective from ground beetles.
DOI: 10.5281/zenodo.18591161
title: Wildfire shape various disturbed types of forest in a distinct way a medium-term perspective from ground beetles.
DOI: 10.6084/m9.figshare.31304878
title: <b>Corrosion of carbon steel in heterogeneous argillite/cement grout environment</b>

description: The corrosion processes of carbon steel electrodes embedded in a specific cement grout were studied at 25°C (56 days) and at 25°C and 80°C (55 + 57 days). Two situations were addressed, A: steel in contact with cement grout, and B: steel in contact with both cement grout and argillite. The corrosion processes were studied via electrochemical measurements and the corrosion product layer was characterized using µ-Raman spectroscopy, XRD and SEM. For experiment A, the carbon steel electrodes, entirely covered with cement grout, remained passive at 25°C. However, the increase in temperature to 80°C induced a passive to active transition, leading to the formation of a thin corrosion product layer mainly composed of FeS. For experiment B, the part of the carbon steel surface covered with argillite presented a more severe localized degradation. The corrosion mechanisms could be linked to the cement composition and properties. The pH of the considered cement grout proved too low, and its sulfide content too high, for the envisioned application.
DOI: 10.6084/m9.figshare.31304878.v1
title: <b>Corrosion of carbon steel in heterogeneous argillite/cement grout environment</b>

description: The corrosion processes of carbon steel electrodes embedded in a specific cement grout were studied at 25°C (56 days) and at 25°C and 80°C (55 + 57 days). Two situations were addressed, A: steel in contact with cement grout, and B: steel in contact with both cement grout and argillite. The corrosion processes were studied via electrochemical measurements and the corrosion product layer was characterized using µ-Raman spectroscopy, XRD and SEM. For experiment A, the carbon steel electrodes, entirely covered with cement grout, remained passive at 25°C. However, the increase in temperature to 80°C induced a passive to active transition, leading to the formation of a thin corrosion product layer mainly composed of FeS. For experiment B, the part of the carbon steel surface covered with argillite presented a more severe localized degradation. The corrosion mechanisms could be linked to the cement composition and properties. The pH of the considered cement grout proved too low, and its sulfide content too high, for the envisioned application.