cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/353z4rkwth
title: From Innovation to Impact: How Green Finance and Innovation Drive Carbon Intensity Reduction in Europe

description: This dataset examines the interaction between green finance mechanisms, particularly carbon pricing, and green innovation in reducing carbon intensity across 36 European countries from 2006 to 2022. The research hypothesizes that green finance, when integrated with green innovation, significantly enhances the climate-mitigation effectiveness of technological advancements. The data includes variables such as carbon intensity, green technology adoption, and carbon pricing implementation, along with economic and industrial factors like GDP, foreign direct investment (FDI), and industrialization.
Notable findings reveal that while green innovation alone has a modest impact on carbon intensity, its effectiveness is significantly amplified when supported by green finance, specifically carbon pricing. Cross-country heterogeneity is also evident, indicating that the impact of green finance and innovation on decarbonization varies across different national policy environments and economic structures.
The data was gathered from publicly available sources, including the World Development Indicators (WDI) and OECD databases. It provides annual panel data across 36 European countries and can be used to assess the role of green finance in amplifying the impact of green innovation on emissions reduction. This dataset is essential for policymakers, researchers, and analysts working on climate action, sustainable finance, and decarbonization strategies, offering insights into the synergies between finance and innovation for achieving carbon neutrality.
DOI: 10.17632/353z4rkwth.1
title: From Innovation to Impact: How Green Finance and Innovation Drive Carbon Intensity Reduction in Europe

description: This dataset examines the interaction between green finance mechanisms, particularly carbon pricing, and green innovation in reducing carbon intensity across 36 European countries from 2006 to 2022. The research hypothesizes that green finance, when integrated with green innovation, significantly enhances the climate-mitigation effectiveness of technological advancements. The data includes variables such as carbon intensity, green technology adoption, and carbon pricing implementation, along with economic and industrial factors like GDP, foreign direct investment (FDI), and industrialization.
Notable findings reveal that while green innovation alone has a modest impact on carbon intensity, its effectiveness is significantly amplified when supported by green finance, specifically carbon pricing. Cross-country heterogeneity is also evident, indicating that the impact of green finance and innovation on decarbonization varies across different national policy environments and economic structures.
The data was gathered from publicly available sources, including the World Development Indicators (WDI) and OECD databases. It provides annual panel data across 36 European countries and can be used to assess the role of green finance in amplifying the impact of green innovation on emissions reduction. This dataset is essential for policymakers, researchers, and analysts working on climate action, sustainable finance, and decarbonization strategies, offering insights into the synergies between finance and innovation for achieving carbon neutrality.
DOI: 10.17632/n4hps7y96x.1
title: Empirical Application Data for "Distinguishing Functional Coefficient Models from Time-Varying Coefficient Models"

description: 1. Research Hypothesis and Data Scope
The study investigates the dynamic pricing mechanism of the European Union Allowance (EUA) market using a monthly time-series dataset spanning December 2008 to February 2025 (N=195) sourced from the Wind database and Climate Data Store. The primary research hypothesis examines the nonlinear relationship between carbon prices and their fundamental drivers. Specifically, it tests whether this relationship is state-dependent (governed by specific economic conditions, known as functional-coefficient models) or time-dependent (evolving structurally over time, known as time-varying coefficient models). The data encompasses EUA futures prices, energy markets (gas, coal), macroeconomic indicators, policy uncertainty, and weather conditions.

2. Data Processing Methodology
To ensure stationarity for rigorous regression analysis, the raw time-series data were transformed using two primary statistical methods. First, Logarithmic Differentiation (Returns) was applied to price level variables to calculate growth rates using the formula R(t) = ln[P(t)] - ln[P(t-1)]. Second, First Differencing was applied to percentage indices or rates using the formula D(t) = V(t) - V(t-1). Additionally, weather data underwent a specific pre-processing step using Fourier series regression to remove seasonal components before differencing, ensuring only non-seasonal temperature anomalies were captured.

3. Detailed Variable Descriptions
The specific variables used in the model are defined as follows. The Dependent Variable is REUA (EUA Returns), representing the monthly logarithmic return of the ICE-traded December EUA futures settlement price (continuous contract). The Explanatory Variables include RGS (Gas Returns), the monthly log-return of NYMEX natural gas futures prices; RCL (Coal Returns), the monthly log-return of ARA (Amsterdam-Rotterdam-Antwerp) coal futures settlement prices; RS (Stock Market Returns), the monthly log-return of the STOXX EUROPE 600 index; DIC (Investor Confidence), the first difference of the Sentix Investor Confidence Index for the Eurozone; DEPU (Policy Uncertainty), the first difference of the European Economic Policy Uncertainty index; and TEMP (Temperature Anomalies), the average temperature across 10 major European cities adjusted for seasonality. Furthermore, six State Variables were compiled to test the state-dependent hypothesis, including DS (Default Spread, the yield difference between Moody’s Baa and Aaa corporate bonds), DGBY (the first difference of EU long-term government bond yields), DCPI (the first difference of EU Harmonized Index of Consumer Prices), DESI (the first difference of Eurostat economic sentiment indicator), DIPI (the first difference of Euro area industrial production index), and GPRI (Global geopolitical risk index).
DOI: 10.17632/gdjrrjwgf4
title: M2C: An open-source software for multiphysics simulation of compressible multi-material flows and fluid-structure interactions

description: M2C (Multiphysics Modeling and Computation) is an open-source software for simulating multi-material fluid flows and fluid-structure interactions under extreme conditions, such as high pressures, high temperatures, shock waves, and large interface deformations. It employs a finite volume method to solve the compressible Navier-Stokes equations and supports a wide range of thermodynamic equations of state. M2C incorporates models of laser radiation and absorption, phase transition, and ionization, coupled with continuum dynamics. Multi-material interfaces are evolved using a level set method, while fluid-structure interfaces are tracked using an embedded boundary method. Advective fluxes across interfaces are computed using FIVER (FInite Volume method based on Exact multi-material Riemann problems). For two-way fluid-structure interaction, M2C is coupled with the open-source structural dynamics solver Aero-S using a partitioned procedure. The M2C code is written in C++ and parallelized with MPI for high-performance computing. The source package includes a set of example problems for demonstration and user training. Accuracy is verified through benchmark cases such as Riemann problems, interface evolution, single-bubble dynamics, and ionization response. Several multiphysics applications are also presented, including laser-induced thermal cavitation, explosion and blast mitigation, and hypervelocity impact.
DOI: 10.17632/gdjrrjwgf4.1
title: M2C: An open-source software for multiphysics simulation of compressible multi-material flows and fluid-structure interactions

description: M2C (Multiphysics Modeling and Computation) is an open-source software for simulating multi-material fluid flows and fluid-structure interactions under extreme conditions, such as high pressures, high temperatures, shock waves, and large interface deformations. It employs a finite volume method to solve the compressible Navier-Stokes equations and supports a wide range of thermodynamic equations of state. M2C incorporates models of laser radiation and absorption, phase transition, and ionization, coupled with continuum dynamics. Multi-material interfaces are evolved using a level set method, while fluid-structure interfaces are tracked using an embedded boundary method. Advective fluxes across interfaces are computed using FIVER (FInite Volume method based on Exact multi-material Riemann problems). For two-way fluid-structure interaction, M2C is coupled with the open-source structural dynamics solver Aero-S using a partitioned procedure. The M2C code is written in C++ and parallelized with MPI for high-performance computing. The source package includes a set of example problems for demonstration and user training. Accuracy is verified through benchmark cases such as Riemann problems, interface evolution, single-bubble dynamics, and ionization response. Several multiphysics applications are also presented, including laser-induced thermal cavitation, explosion and blast mitigation, and hypervelocity impact.
DOI: 10.17632/39bd25msbs.1
title: "Puzzle First then Forget Smoothly": Comparison of Puzzle-Based and Coloring-Based Methods for Jockey Silk Identification
DOI: 10.17632/9yvhsccycz
title: Replication package for the paper titled: Demographic change, consumption and equity returns. An international approach

description: This replication package contains all data series and R scripts used in the paper 'Demographic change, consumption and equity returns. An international approach'. The package is organized in two main folders:

- Data: Datasets used as inputs for the empirical analysis.
- Codes: R scripts implementing the full empirical methodology and producing the results.

The code implements the econometric procedures used in the paper, including estimation routines, GMM-based inference, and model evaluation tests.
DOI: 10.17632/9yvhsccycz.1
title: Replication package for the paper titled: Demographic change, consumption and equity returns. An international approach

description: This replication package contains all data series and R scripts used in the paper 'Demographic change, consumption and equity returns. An international approach'. The package is organized in two main folders:

- Data: Datasets used as inputs for the empirical analysis.
- Codes: R scripts implementing the full empirical methodology and producing the results.

The code implements the econometric procedures used in the paper, including estimation routines, GMM-based inference, and model evaluation tests.
DOI: 10.17632/3bp796fp29
title: Dede Korkut Stories

description: Character Strengths in Cultural Narratives: A Positive Psychology Analysis of the Dede Korkut Stories
DOI: 10.17632/3bp796fp29.1
title: Dede Korkut Stories

description: Character Strengths in Cultural Narratives: A Positive Psychology Analysis of the Dede Korkut Stories
DOI: 10.6084/m9.figshare.31258546
title: 5-Hydroxymethylfurfural and furfural levels in non-alcoholic beverages: a survey of product types

description: Toxic furanic compounds such as 5-hydroxymethylfurfural (HMF) and 2-furfural (F) can form during the processing and storage of non-alcoholic beverages (NABs). This study aimed to determine the levels of HMF and F in a wide range of NAB categories, including fruit juices and nectars, carbonated soft drinks, non-carbonated soft drinks, energy drinks, and coffee with milk drinks. The levels of HMF and F were determined using a validated analytical method. The HMF and F levels of the studied samples varied depending on the type of product. The coffee with milk drinks exhibited the highest levels, while the carbonated soft drinks exhibited the lowest. Notably, the HMF levels of most of the coffee with milk drinks exceeded 10 mg L<sup>−1</sup>. The findings provide novel insights into the presence of furanic compounds in NABs and emphasise the importance of raising consumer awareness regarding potential dietary exposure to furanic compounds, particularly from coffee drinks.
DOI: 10.6084/m9.figshare.31258546.v1
title: 5-Hydroxymethylfurfural and furfural levels in non-alcoholic beverages: a survey of product types

description: Toxic furanic compounds such as 5-hydroxymethylfurfural (HMF) and 2-furfural (F) can form during the processing and storage of non-alcoholic beverages (NABs). This study aimed to determine the levels of HMF and F in a wide range of NAB categories, including fruit juices and nectars, carbonated soft drinks, non-carbonated soft drinks, energy drinks, and coffee with milk drinks. The levels of HMF and F were determined using a validated analytical method. The HMF and F levels of the studied samples varied depending on the type of product. The coffee with milk drinks exhibited the highest levels, while the carbonated soft drinks exhibited the lowest. Notably, the HMF levels of most of the coffee with milk drinks exceeded 10 mg L<sup>−1</sup>. The findings provide novel insights into the presence of furanic compounds in NABs and emphasise the importance of raising consumer awareness regarding potential dietary exposure to furanic compounds, particularly from coffee drinks.
DOI: 10.17632/3y5bkfs6fg
title: Genetic basis for convergent evolution of compound leaves over deep time

description: The compressed file Leaf_Complexity_Convergence.zip contains the specified directories and relevant files detailed below:

1. all_TF_family
The gene list of all transcription factor gene families in the 414 plants studied.

2. KNOX_pep
The protein sequences of the KNOX gene family in all studied species.

3. threeSubClasses
The gene list of three KNOX subclasses (KNOXI, KNOXII, and KNOXM) in the 414 plants studied.

4. KNOX_gene_duplication_modes
Gene duplication modes of KNOX gene family in the 414 plants studied.
DOI: 10.17632/3y5bkfs6fg.2
title: Genetic basis for convergent evolution of compound leaves over deep time

description: The compressed file Leaf_Complexity_Convergence.zip contains the specified directories and relevant files detailed below:

1. all_TF_family
The gene list of all transcription factor gene families in the 414 plants studied.

2. KNOX_pep
The protein sequences of the KNOX gene family in all studied species.

3. threeSubClasses
The gene list of three KNOX subclasses (KNOXI, KNOXII, and KNOXM) in the 414 plants studied.

4. KNOX_gene_duplication_modes
Gene duplication modes of KNOX gene family in the 414 plants studied.
DOI: 10.15468/dl.ersg7y
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is SBBG - Clifton Smith Herbarium, Santa Barbara Botanic Garden",
 "TaxonKey is Fungi"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012517-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9zcvpw
title: Occurrence Download

description: A dataset containing 1450 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Angola",
 "GadmGid is AGO.5_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae",
 "Year 1990-2026"
 ]
}

 The dataset includes 1450 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012518-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z42jte
title: Occurrence Download

description: A dataset containing 4116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (iNaturalist Research-grade Observations, Marine mammal aerial surveys in the Bering, Chukchi and Beaufort Seas 1979-2010, USGS Alaska Science Center Polar Bear Maternal Dens, DFO Arctic Metabarcoding (COI) 2015-2019, ICES contaminants and biological effects, Observation.org, Nature data from around the World, UAM Mammal Collection (Arctos), NHMD Mammalogy Collection, Arctic Species Trend Index (ASTI) : Marine, Macaulay Library Audio and Video Collection)",
 "TaxonKey is Ursus maritimus",
 "Year 1980-2020"
 ]
}

 The dataset includes 4116 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012516-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6cu3tu
title: Occurrence Download

description: A dataset listing the 17 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Inventaires Aéro Biodiversité - UIP - Quimper-Inventaires Aéro Biodiversité - UIP - Point d'EPOC 1"
 ]
}

 The dataset's 17 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012513-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vgt2h6
title: Occurrence Download

description: A dataset containing 628701 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (North America, South America)",
 "TaxonKey is Myiopsitta monachus"
 ]
}

 The dataset includes 628701 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012492-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.71819/v3h4rw
title: Coleção de Herpetologia (Serpentes) do MZUSP

description: A coleção herpetológica do Museu de Zoologia reúne o maior acervo de répteis e anfíbios sul-americanos do mundo, figurando entre as seis maiores coleções herpetológicas existentes. Conta atualmente com cerca de 260.000 exemplares (120.000 répteis e 140.000 anfíbios) sendo que 468 deles são espécies-tipo, uma coleção de tecidos com aproximadamente 6.850 amostras e uma coleção de esqueletos com mais de 1.000 exemplares preparados a seco ou diafanizados. Suas coleções vêm sendo digitalizadas para permitir seu melhor gerenciamento. Tem sido continuamente usada por especialistas do Brasil e do exterior como base indispensável para pesquisas e na formação de recursos humanos na pós-graduação. Recebe, anualmente, mais de 30 visitantes do Brasil e do exterior. Incontáveis alunos de iniciação, aperfeiçoamento, mestrado e doutorado, hoje trabalhando nas mais diversas instituições brasileiras, também visitam a coleção de Herpetologia para ali complementarem suas pesquisas. Atualmente, a coleção de Herpetologia do MZUSP representa referência incontornável para qualquer pesquisador que realize trabalho revisionário sobre a herpetofauna Neotropical. O papel de destaque da coleção contribui também para que esta seja escolhida preferencialmente pelos pesquisadores que queiram depositar grandes coleções e material-tipo oriundo de suas pesquisas.

Seu início deu-se a partir de coletas esporádicas de E. Garbe, ainda no Museu Paulista. Em 1918, José Florêncio Gomes, do Instituto Butantan, identificou as serpentes. No começo da década de 20, Alípio de Miranda Ribeiro, do Museu Nacional do Rio de Janeiro, identificou os anfíbios e publicou os resultados das suas pesquisas na Revista do Museu Paulista. Já na década de 30, Afrânio do Amaral, também do Instituto Butantan, identificou parte dos lagartos, publicando também os seus resultados.
Em 1940, na passagem das coleções para o prédio atual, o Padre D. José Kretz, contratado pelo Museu para cuidar das coleções, resolveu tirar os rótulos dos vidros e colá-los num caderno, o que causou grande confusão.

Em 1946, Paulo Emílio Vanzolini assumiu a curadoria da coleção com aproximadamente 1.200 números, correspondentes a exemplares ou lotes. P.E. Vanzolini ampliou as coleções de Herpetologia para as suas dimensões de hoje. Miguel T. U. Rodrigues, pesquisador do Instituto de Biociências da USP e diretor do MZUSP entre 2000 e 2004, teve também um papel fundamental nesta expansão, com contribuição proveniente de coletas por todo o Brasil. Recentemente, enormes séries oriundas de resgates de fauna realizados em empreendimentos hidrelétricos vêm sendo incorporadas ao acervo, tendo como destaques, importantes séries de anfíbios e répteis do Brasil central e do sul da Amazônia. P.E. Vanzolini foi responsável pelas coleções de Herpetologia do MZUSP até Marco de 2002, quando foi substituído por Hussam El Dine Zaher.
DOI: 10.5281/zenodo.18487992
title: IODP Expedition 355 Rig instrumentation

description: Operational rig information data were measured using a variety of sensors and compiled using the RigWatch software package. Approximately 50 channels of drilling/coring data are captured in real time during the expedition. Data are presented as ASCII files extracted from the proprietary RigWatch data files and are presented by expedition. RigWatch data in time or depth domain can be imported into graphics and analysis programs to be merged and correlated with core physical properties data to enhance assessment of poor core recovery intervals.
DOI: 10.5281/zenodo.18487993
title: IODP Expedition 355 Rig instrumentation

description: Operational rig information data were measured using a variety of sensors and compiled using the RigWatch software package. Approximately 50 channels of drilling/coring data are captured in real time during the expedition. Data are presented as ASCII files extracted from the proprietary RigWatch data files and are presented by expedition. RigWatch data in time or depth domain can be imported into graphics and analysis programs to be merged and correlated with core physical properties data to enhance assessment of poor core recovery intervals.
DOI: 10.17632/rzjzb4bxz7
title: Using Sentiment Analysis to investigate Sandro Abruzzese's literary works

description: The dataset was created to support a comparative geo-affective analysis of Sandro Abruzzese’s literary works, with a focus on Casa per casa and Niente da vedere. Starting from digitized and normalized texts (typographic cleaning, diacritic and punctuation harmonization, and segmentation), place names (toponyms) were extracted and their occurrences were counted by work and in the aggregated corpus (ALL). Each toponym was then enriched with geographic information (latitude/longitude coordinates, when available) and with a semantic–affective profile computed through SenticNet, including polarity and the Hourglass dimensions (attitude, introspection, sensitivity, temper). In parallel, toponyms were embedded in AffectiveSpace and summarized via Principal Component Analysis (PCA) to obtain a compact 2D representation (PC1–PC2) suitable for cross-text comparison. Finally, clustering was performed on the geo-affective feature set (k = 5), generating cluster labels and interpretable descriptors for each group. The resulting dataset is delivered in a tabular format (CSV), ready for statistical exploration, visualization, and GIS integration.