cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/hbbtbykt5p.1
title: 2014 and 2019 aerosol field observation dataset in Guangzhou, china

description: This dataset contains comprehensive, high-time-resolution atmospheric measurement data obtained from two field campaigns conducted in 2014 and 2019. It includes detailed aerosol physical properties, chemical composition, and meteorological parameters.

2014 Campaign:
Aerosol Size Distribution: Particle Number Size Distributions (PNSD) in the range of 9.8–414.2 nm were measured at a 5-minute resolution using a Scanning Mobility Particle Sizer (SMPS, TSI 3938) comprising a Differential Mobility Analyzer (DMA, TSI 3081L) and a Condensation Particle Counter (CPC, TSI 3772).
Non-Refractory PM1 Chemical Composition: Mass concentrations of organic matter (Org), nitrate (NO₃⁻), sulfate (SO₄²⁻), and ammonium (NH₄⁺) were quantified using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS, Aerodyne).

2019 Campaign:
Aerosol Size Distribution: Particle size distributions in the range of 11.3–532.8 nm were obtained using an SMPS system identical to the 2014 setup. The data have been corrected for multiple charging and diffusion losses.
Aerosol Hygroscopicity: Hygroscopic growth factors at 90% relative humidity were measured for particles with selected dry diameters (40, 80, 110, 150, and 200 nm) using a Hygroscopicity Tandem Differential Mobility Analyzer (H-TDMA).
Non-Refractory PM2.5 Chemical Composition: Mass concentrations of Org, NO₃⁻, SO₄²⁻, NH₄⁺, and chloride (Chl) were measured with a Quadrupole Aerosol Chemical Speciation Monitor (Q-ACSM).
Black Carbon Mass Concentration: Continuous monitoring was performed using an aethalometer (AE33, Magee Scientific).
Meteorological Data (Both Campaigns):
Wind Speed and Wind Direction data were recorded synchronously, typically at matching high-time-resolution intervals, providing essential context for atmospheric process analysis.

These two comprehensive field investigations at two adjacent sites during two different time periods. One was from 6th to 24th of November in 2019, at the Guangzhou Meteorological Bureau in Panyu, Guangzhou, China (23.01 ° N, 113.32 ° E), and the other was from November 22nd, 2014 to December 31st in 2014, at the Chinese Meteorological Administration (CMA) Atmospheric Watch Network (CAWNET) station in Panyu, Guangzhou, China (23.00 ° N, 133.21 ° E).
DOI: 10.17632/2jgvnhyj87
title: Disintegration Characteristics of a Vegetated Soil

description: Disintegration Characteristics of a Vegetated Soil
DOI: 10.15468/dl.hqe97a
title: Occurrence Download

description: A dataset containing 306 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;= 37.42857426825602
 AND decimallatitude &lt;= 41.89415215079384
 AND decimallongitude &gt;= 51.807709614649205
 AND decimallongitude &lt;= 59.94074752362532
 AND GBIF_Within('POLYGON ((59.940748 37.428574, 59.940748 41.894152, 51.807710 41.894152, 51.807710 37.428574, 59.940748 37.428574))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 306 records were derived from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001987-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2jgvnhyj87.1
title: Disintegration Characteristics of a Vegetated Soil

description: Disintegration Characteristics of a Vegetated Soil
DOI: 10.17632/hh9wr3ydd7
title: Code: Towards Operational Tree-Level Timber Quality and Volume Estimation Using UAV Multi-Sensor Remote Sensing

description: LiDAR-related code for the estimation of stem straightness. Additionally, code for the segmenteation and stem diameter estimation based on previous work added. LiDAR data will be made available in request, due to large file sizes.
DOI: 10.17632/hh9wr3ydd7.3
title: Code: Towards Operational Tree-Level Timber Quality and Volume Estimation Using UAV Multi-Sensor Remote Sensing

description: LiDAR-related code for the estimation of stem straightness. Additionally, code for the segmenteation and stem diameter estimation based on previous work added. LiDAR data will be made available in request, due to large file sizes.
DOI: 10.17632/n4hps7y96x
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/n4hps7y96x.2
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: 10.15468/dl.g9tx9a
title: Occurrence Download

description: A dataset containing 429 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Amaranthus californicus"
 ]
}

 The dataset includes 429 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001995-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/v3pkm8sxkk
title: Data for "LW scattering effect on CanAM kernels"

description: This dataset contains the CanAM radiative kernels and the corresponding feedback diagnostics used in the study "LW scattering effects on radiative kernels".
DOI: 10.17632/v3pkm8sxkk.1
title: Data for "LW scattering effect on CanAM kernels"

description: This dataset contains the CanAM radiative kernels and the corresponding feedback diagnostics used in the study "LW scattering effects on radiative kernels".
DOI: 10.17632/c69wx7nk3c
title: Plasma-Stepped Furnaces

description: Data of《Parametric Analysis and Optimization of Plasma-Assisted Combustion in Stepped Furnaces》
DOI: 10.17632/c69wx7nk3c.1
title: Plasma-Stepped Furnaces

description: Data of《Parametric Analysis and Optimization of Plasma-Assisted Combustion in Stepped Furnaces》
DOI: 10.17632/mzz34rgx9k
title: Research Data

description: Raw data on physical, chemical, and biological soil properties.
DOI: 10.17632/mzz34rgx9k.2
title: Research Data

description: Raw data on physical, chemical, and biological soil properties.
DOI: 10.17632/p4w2r4dj9n
title: Georeferenced lichen transplant monitoring dataset from urban environments (2016–2017)

description: This dataset contains georeferenced environmental and visual data from a lichen transplant monitoring study conducted in 2016–2017.
Lichen transplants of Hypogymnia physodes were collected in a forest area outside the city (Mežciems, control site) and installed on trees at multiple urban locations in July 2016. The first field survey was carried out on 1 August 2016, followed by repeated monitoring campaigns until March 2017.
The dataset includes information on the exact location of each sampling site, tree species used as transplant substrates, and surrounding urban land-use structure.
For each sampling site, the dataset provides:
• Geographic coordinates in WGS84 (DMS format),
• Street-based location description,
• Tree species (Latin names) on which lichen transplants were installed,
• Urban land-use composition (%) within the surrounding area, including residential, industrial, commercial, green, and water-related land-use types,
• Photographic documentation from repeated field surveys, including:
Close-range images of lichen transplants showing visual condition and necrosis,
360-degree panoramic images documenting the surrounding environment at each site.
The dataset includes multiple monitoring campaigns carried out between August 2016 and March 2017. Notes on transplant degradation, loss, replacement, and physical disturbances (e.g., branch cutting) are included in the metadata tables where applicable.
The dataset is intended for reuse in urban environmental studies, lichen bioindication research, spatial analysis, and visual assessment of urban impact gradients. Detailed methodological descriptions are not included in this dataset and will be provided in a separate scientific publication.
DOI: 10.17632/p4w2r4dj9n.2
title: Georeferenced lichen transplant monitoring dataset from urban environments (2016–2017)

description: This dataset contains georeferenced environmental and visual data from a lichen transplant monitoring study conducted in 2016–2017.
Lichen transplants of Hypogymnia physodes were collected in a forest area outside the city (Mežciems, control site) and installed on trees at multiple urban locations in July 2016. The first field survey was carried out on 1 August 2016, followed by repeated monitoring campaigns until March 2017.
The dataset includes information on the exact location of each sampling site, tree species used as transplant substrates, and surrounding urban land-use structure.
For each sampling site, the dataset provides:
• Geographic coordinates in WGS84 (DMS format),
• Street-based location description,
• Tree species (Latin names) on which lichen transplants were installed,
• Urban land-use composition (%) within the surrounding area, including residential, industrial, commercial, green, and water-related land-use types,
• Photographic documentation from repeated field surveys, including:
Close-range images of lichen transplants showing visual condition and necrosis,
360-degree panoramic images documenting the surrounding environment at each site.
The dataset includes multiple monitoring campaigns carried out between August 2016 and March 2017. Notes on transplant degradation, loss, replacement, and physical disturbances (e.g., branch cutting) are included in the metadata tables where applicable.
The dataset is intended for reuse in urban environmental studies, lichen bioindication research, spatial analysis, and visual assessment of urban impact gradients. Detailed methodological descriptions are not included in this dataset and will be provided in a separate scientific publication.
DOI: 10.17632/s6skkpwzs6
title: Using beneficial ownership data for large-scale risk assessment in public procurement. The example of 6 European countries.

description: This database is a compilation of datasets of matched public procurement with beneficial ownership (BO) records by country. The database was used to conduct a systematic assessment of corruption risks in government contracting in the academic article: Arista, Irene Tello; Fazekas, Mihály & Volkotrub, Antonina (2026), Using beneficial ownership data for large-scale risk assessment in public procurement. The example of 6 European countries. European Journal of Criminal Policy and Research. Overall, it contains approximately 8 million public procurement contracts with beneficial ownership information for 11 million companies across Denmark, Estonia, Latvia, Slovakia, Ukraine, and the United Kingdom. The dataset includes tender-level corruption risk indicators, buyer and contract characteristics, and several BO-based risk indicators capturing ownership structure, as well as political exposure, nationality, and residence of beneficial owners. Several variables were constructed to identify unusual or outlier BO features –such as high ownership concentration of firms under one person, frequent BO changes, and absence of BO data– and other commonly used firm-level risk indicators, including company age and political connections, were included. The database was designed to test non-linear and fixed-effects analyses of the relationship between beneficial ownership characteristics and corruption risks in public procurement, and to facilitate the validation and practical use of BO-based risk indicators for research, policy analysis, and investigative purposes.
DOI: 10.17632/s6skkpwzs6.2
title: Using beneficial ownership data for large-scale risk assessment in public procurement. The example of 6 European countries.

description: This database is a compilation of datasets of matched public procurement with beneficial ownership (BO) records by country. The database was used to conduct a systematic assessment of corruption risks in government contracting in the academic article: Arista, Irene Tello; Fazekas, Mihály & Volkotrub, Antonina (2026), Using beneficial ownership data for large-scale risk assessment in public procurement. The example of 6 European countries. European Journal of Criminal Policy and Research. Overall, it contains approximately 8 million public procurement contracts with beneficial ownership information for 11 million companies across Denmark, Estonia, Latvia, Slovakia, Ukraine, and the United Kingdom. The dataset includes tender-level corruption risk indicators, buyer and contract characteristics, and several BO-based risk indicators capturing ownership structure, as well as political exposure, nationality, and residence of beneficial owners. Several variables were constructed to identify unusual or outlier BO features –such as high ownership concentration of firms under one person, frequent BO changes, and absence of BO data– and other commonly used firm-level risk indicators, including company age and political connections, were included. The database was designed to test non-linear and fixed-effects analyses of the relationship between beneficial ownership characteristics and corruption risks in public procurement, and to facilitate the validation and practical use of BO-based risk indicators for research, policy analysis, and investigative purposes.
DOI: 10.17632/r54hpjjwv3
title: Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle - dataset

description: The data associated with the figures presented in the article: Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle - dataset

Konopińska, N., Walkowiak-Nowicka, K., Chowański, S., Nowicki, G., Urbański, A. (2025). Effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor females: implications for insect breeding and pest control. bioRxiv, 2025-08.

 and

Konopińska, N., Walkowiak-Nowicka, K., Chowański, S., Nowicki, G., Urbański, A. (2026). Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle. Journal of Stored Products Research (2026) 102966
DOI: 10.17632/r54hpjjwv3.1
title: Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle - dataset

description: The data associated with the figures presented in the article: Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle - dataset

Konopińska, N., Walkowiak-Nowicka, K., Chowański, S., Nowicki, G., Urbański, A. (2025). Effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor females: implications for insect breeding and pest control. bioRxiv, 2025-08.

 and

Konopińska, N., Walkowiak-Nowicka, K., Chowański, S., Nowicki, G., Urbański, A. (2026). Physiological effects of tachykinin-related peptides on the reproductive system of Tenebrio molitor L. (Coleoptera: Tenebrionidae) females: an important pest and mass-reared beetle. Journal of Stored Products Research (2026) 102966
DOI: 10.17632/ydj35kx7d7
title: Dataset for SPM of "QUADRICEPS OXYGEN SATURATION RESPONSES IN ONE-DAY RECOVERING PHASE FOLLOWING HIGH INTENSITY SIMULATED MILITARY COMBAT EXERCISE PROTOCOL"

description: Dataset used for SPM analysis. In this study, The SmO₂ of the vastus lateralis in the preferred leg was measured using near-infrared spectroscopy during an isometric squat protocol before exercise (Pre), 4 hours post-exercise (post-4h), and 24 hours post-exercise (post-24h) in 10 trained male soldiers. Each column represents each percentage of time, with 0% representing the beginning of the isometric test and 100% its end.
DOI: 10.17632/ydj35kx7d7.1
title: Dataset for SPM of "QUADRICEPS OXYGEN SATURATION RESPONSES IN ONE-DAY RECOVERING PHASE FOLLOWING HIGH INTENSITY SIMULATED MILITARY COMBAT EXERCISE PROTOCOL"

description: Dataset used for SPM analysis. In this study, The SmO₂ of the vastus lateralis in the preferred leg was measured using near-infrared spectroscopy during an isometric squat protocol before exercise (Pre), 4 hours post-exercise (post-4h), and 24 hours post-exercise (post-24h) in 10 trained male soldiers. Each column represents each percentage of time, with 0% representing the beginning of the isometric test and 100% its end.