cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/d9f3dt8gm8.1
title: Experimental Dataset on Compressive Strength, Electrical Resistivity, and Capillary Water Absorption of Plastic Concrete with Micro Silica under Wastewater Exposure

description: This dataset presents the experimental results of plastic concrete mixtures designed with varying proportions of micro silica and exposed to different concentrations of wastewater containing heavy metals. The study aimed to evaluate the mechanical and durability properties of plastic concrete used in cut-off walls and dam foundations.

The dataset includes measurements of compressive strength (MPa), electrical resistivity (Ω·mm), and capillary water absorption (kg/m²·h⁰·⁵) for concrete mixes prepared with four levels of micro silica replacement (0%, 5%, 10%, and 15% of binder weight). Each mix was subjected to curing in four wastewater concentrations (0%, 30%, 60%, and 100%), simulating aggressive environmental conditions.

The data enable analysis of the effects of micro silica on strength and durability enhancement in plastic concrete, as well as the influence of wastewater-induced corrosion. This dataset can be utilized for:
Evaluating the performance of plastic concrete under aggressive exposure conditions.
Bench marking predictive models such as artificial neural networks.
Supporting mix design optimization for hydraulic structures.
File contents:
Raw data tables of compressive strength, electrical resistivity, and capillary water absorption.
Experimental conditions (micro silica content, wastewater concentration, curing period).
DOI: 10.17632/kcztj9fcgz
title: Climate-Responsive Environmental Theory of Nursing (CRETN): A Systematic Review and Policy-Linked Framework

description: Led by Fernan N. Torreno with Famiela Torreno, this systematic review of 32 studies (n≈6,200 nurses) developed the Climate-Responsive Environmental Theory of Nursing (CRETN). Findings highlight nurses’ roles in adaptive care, resilience, and advocacy, offering a SMART roadmap (2027–2030) to strengthen climate-health equity and system resilience.
DOI: 10.17632/kcztj9fcgz.1
title: Climate-Responsive Environmental Theory of Nursing (CRETN): A Systematic Review and Policy-Linked Framework

description: Led by Fernan N. Torreno with Famiela Torreno, this systematic review of 32 studies (n≈6,200 nurses) developed the Climate-Responsive Environmental Theory of Nursing (CRETN). Findings highlight nurses’ roles in adaptive care, resilience, and advocacy, offering a SMART roadmap (2027–2030) to strengthen climate-health equity and system resilience.
DOI: 10.17632/8xpkgykg2m
title: Impact of Temperature on Rainfall Erosivity on the Loess Plateau: An Innovative EMA-Pix2PixHD Framework

description: This dataset contains the complete research data from the EMA-Pix2PixHD-based prediction of rainfall erosivity (R) over the Loess Plateau. It includes: (1) the trained generator models G1 and G2; (2) generated R images on the training set; (3) monthly R remote sensing images projected under SSP245 and SSP585 scenarios for the years 2040, 2070, and 2100; (4) attention heatmaps from the EMA module for interpretability analysis, revealing model focus on key climate-sensitive regions; and (5) evaluation outputs, including CSV files of MAE and RMSE for each test image, and pixel-wise relative error (RE) maps. All R images are inverse-normalized to physical units (MJ·mm·hm⁻²·h⁻¹), and RE values are expressed as percentages. This dataset supports research on soil erosion risk assessment under climate change, geoscientific applications of deep learning, and the reproducibility and extension of image-to-image translation models.
DOI: 10.17632/8xpkgykg2m.1
title: Impact of Temperature on Rainfall Erosivity on the Loess Plateau: An Innovative EMA-Pix2PixHD Framework

description: This dataset contains the complete research data from the EMA-Pix2PixHD-based prediction of rainfall erosivity (R) over the Loess Plateau. It includes: (1) the trained generator models G1 and G2; (2) generated R images on the training set; (3) monthly R remote sensing images projected under SSP245 and SSP585 scenarios for the years 2040, 2070, and 2100; (4) attention heatmaps from the EMA module for interpretability analysis, revealing model focus on key climate-sensitive regions; and (5) evaluation outputs, including CSV files of MAE and RMSE for each test image, and pixel-wise relative error (RE) maps. All R images are inverse-normalized to physical units (MJ·mm·hm⁻²·h⁻¹), and RE values are expressed as percentages. This dataset supports research on soil erosion risk assessment under climate change, geoscientific applications of deep learning, and the reproducibility and extension of image-to-image translation models.
DOI: 10.17632/p3ydzv82tt
title: Assessing Digital Banking Adoption by Small-Scale Farmers in Rural Thailand: A 5S Framework based on TAM and UTAUT

description: This dataset, collected in March 2024 from 426 rural farm households in Mae Hong Son province, Thailand, was designed to examine the key factors influencing digital banking adoption among small-scale farmers. Guided by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study tests the hypothesis that the 5S framework—Subsidy, Security, Signal, Satisfaction, and Socio-demographic factors—significantly affects both the likelihood of adoption (analyzed using probit models) and the intra-household adopter ratio (analyzed using tobit models). The file contains two worksheets: one describing the variables and the other presenting the raw data.
DOI: 10.17632/p3ydzv82tt.1
title: Assessing Digital Banking Adoption by Small-Scale Farmers in Rural Thailand: A 5S Framework based on TAM and UTAUT

description: This dataset, collected in March 2024 from 426 rural farm households in Mae Hong Son province, Thailand, was designed to examine the key factors influencing digital banking adoption among small-scale farmers. Guided by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study tests the hypothesis that the 5S framework—Subsidy, Security, Signal, Satisfaction, and Socio-demographic factors—significantly affects both the likelihood of adoption (analyzed using probit models) and the intra-household adopter ratio (analyzed using tobit models). The file contains two worksheets: one describing the variables and the other presenting the raw data.
DOI: 10.5281/zenodo.17222257
title: Title (Formal, Centered, Bold, Larger Font): The Unified Theory, also known as the Theory of Everything: SalehNetBrain Fram  Subtitle (Optional, Italic, Smaller Font): A Cognitive-Cosmological Model for Unifying Consciousness, Meaning, and Reality

description: Title (Formal, Centered, Bold, Larger Font):The Unified Theory, also known as the Theory of Everything: SalehNetBrain Fram

Subtitle (Optional, Italic, Smaller Font):A Cognitive-Cosmological Model for Unifying Consciousness, Meaning, and Reality
DOI: 10.5281/zenodo.17222256
title: Title (Formal, Centered, Bold, Larger Font): The Unified Theory, also known as the Theory of Everything: SalehNetBrain Fram  Subtitle (Optional, Italic, Smaller Font): A Cognitive-Cosmological Model for Unifying Consciousness, Meaning, and Reality

description: Title (Formal, Centered, Bold, Larger Font):The Unified Theory, also known as the Theory of Everything: SalehNetBrain Fram

Subtitle (Optional, Italic, Smaller Font):A Cognitive-Cosmological Model for Unifying Consciousness, Meaning, and Reality
DOI: 10.17632/ng3kvvfgjw
title: Dataset
DOI: 10.17632/ng3kvvfgjw.1
title: Dataset
DOI: 10.17632/kg4kdnr7wf
title: Clients’ personality traits as predictors of preferences for specialist image and satisfaction with psychological help experience

description: Context and relevance. The establishment of a working alliance is a key factor in the effectiveness of psychological assistance. Client personality traits contribute significantly to this process, beginning as early as the stage of selecting a specialist. Nevertheless, empirical research on clients' perceptions of an "appropriate" psychologist remains fragmented. Grounded in the Five-Factor Model of personality and working alliance theories, the present study aims to address this gap. Objective. Within the context of working alliance formation, this study aims to determine how clients' personality traits and socio-demographic characteristics are associated with their perceptions of an "ideal" professional, as well as with parameters of seeking psychological help and satisfaction with the help-seeking experience. Methods and materials. The study involved 439 participants with prior experience of receiving psychological help. The sample, aged 18 to 56, included 286 women and 153 men. Participants' personality traits and those of their preferred specialists were assessed using the Big Five Inventory-2 Short (BFI-2-S). Socio-demographic variables and help-seeking parameters were assessed using a custom-designed questionnaire, which included items on previous experience with psychological help. Data were analyzed using cluster and regression analyses. Results. Four distinct client profiles and four preferred specialist profiles were identified. A significant association was found between a client's personality profile and their preferred image of a specialist. Satisfaction with the help-seeking experience was positively associated with the client's level of education, employment type, number of previous consultations with psychologists, and selecting a specialist based on personal affinity. Conversely, relying on recommendations when choosing a specialist and high levels of client negative emotionality (neuroticism) were negative predictors of satisfaction. Conclusions. The findings confirm the significance of both personality similarity and complementarity within the client-specialist dyad. It is recommended to consider the personality characteristics of both clients and professionals when matching them to facilitate the formation of an effective working alliance in psychological care. Consequently, the development of assessment tools for preliminary diagnostics of client preferences becomes a relevant task.
DOI: 10.17632/kg4kdnr7wf.1
title: Clients’ personality traits as predictors of preferences for specialist image and satisfaction with psychological help experience

description: Context and relevance. The establishment of a working alliance is a key factor in the effectiveness of psychological assistance. Client personality traits contribute significantly to this process, beginning as early as the stage of selecting a specialist. Nevertheless, empirical research on clients' perceptions of an "appropriate" psychologist remains fragmented. Grounded in the Five-Factor Model of personality and working alliance theories, the present study aims to address this gap. Objective. Within the context of working alliance formation, this study aims to determine how clients' personality traits and socio-demographic characteristics are associated with their perceptions of an "ideal" professional, as well as with parameters of seeking psychological help and satisfaction with the help-seeking experience. Methods and materials. The study involved 439 participants with prior experience of receiving psychological help. The sample, aged 18 to 56, included 286 women and 153 men. Participants' personality traits and those of their preferred specialists were assessed using the Big Five Inventory-2 Short (BFI-2-S). Socio-demographic variables and help-seeking parameters were assessed using a custom-designed questionnaire, which included items on previous experience with psychological help. Data were analyzed using cluster and regression analyses. Results. Four distinct client profiles and four preferred specialist profiles were identified. A significant association was found between a client's personality profile and their preferred image of a specialist. Satisfaction with the help-seeking experience was positively associated with the client's level of education, employment type, number of previous consultations with psychologists, and selecting a specialist based on personal affinity. Conversely, relying on recommendations when choosing a specialist and high levels of client negative emotionality (neuroticism) were negative predictors of satisfaction. Conclusions. The findings confirm the significance of both personality similarity and complementarity within the client-specialist dyad. It is recommended to consider the personality characteristics of both clients and professionals when matching them to facilitate the formation of an effective working alliance in psychological care. Consequently, the development of assessment tools for preliminary diagnostics of client preferences becomes a relevant task.
DOI: 10.17632/ynf5sjhxmj.1
title: Data for: Chemical availability in soils and sediments interpreted by coupled transport–reaction models of DGT fluxes: roles of dissolved ligands and finite sorption capacity.

description: Raw data for all figures in the manuscript "Chemical availability in soils and sediments interpreted by coupled transport–reaction models of DGT fluxes: roles of dissolved ligands and finite sorption capacity" (Josep Galceran, Guanlei Li, Jordi Sans-Duñó, Carlos Rey-Castro, Jaume Puy, Yue Gao and Joan Cecília)
DOI: 10.15468/dl.h6ynxv
title: Occurrence Download

description: A dataset containing 188 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Odontosoria biflora",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 188 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028248-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/c5k7jbg5pm
title: The supplementary table for Comprehensive DIA-MS proteomics of root basal nodes elucidates mechanisms of salt tolerance in rice

description: The supplementary table for Comprehensive DIA-MS proteomics of root basal nodes elucidates mechanisms of salt tolerance in rice.
These data include the supplementary tables listed below
Supplementary table. List of identified significant proteins
DOI: 10.17632/c5k7jbg5pm.2
title: The supplementary table for Comprehensive DIA-MS proteomics of root basal nodes elucidates mechanisms of salt tolerance in rice

description: The supplementary table for Comprehensive DIA-MS proteomics of root basal nodes elucidates mechanisms of salt tolerance in rice.
These data include the supplementary tables listed below
Supplementary table. List of identified significant proteins
DOI: 10.17632/33j33cr7m9
title: Detailed Optimisation Results for a Batch Extractive Distillation Process Obtained by Hybrid Optimisation Methods

description: The data presented in the four Excel files were used in the paper "Laszlo Hegely: Optimisation of a Batch Extractive Distillation Process with Hybrid Methods, 2025". They show the data points in which the simulation of the batch extractive distillation process was performed, as well as the simulation results. By the data points, we refer to points in the seven-dimensional space of the optimisation variables, which were the reflux ratios of Steps 1-3 of the procedure (R1, R2, R3), the stopping criteria of Steps 1 and 2 (Cr1 and Cr2), and the flow rate (FE) and duration (tF) of the water feeding. (Values of tF/2 are given in the files.) The stopping criteria are the values of tetrahydrofuran concentration (in mass fraction) in the (instantaneous) distillate when the given step is finished. Selected simulation results, the ones necessary to calculate the profit of the process, are also shown: duration of the process (t), mass of the Fore-cut 1 (mfc1) and of the main cut (mmc), the concentration of methanol, THF and toluene in Fore-cut 2 (xfc2,B, xfc2,C and xfc2,E, respectively), the final (xmc,B) and maximal (xmc,B,max) concentration of methanol in the main cut, as well as the profit (OF).
The different files correspond to the different optimisation methods used. They contain various sheets that correspond to different optimisation runs; they are identified with the notation used in the corresponding paper. 
The file “GA run data.xlsx” contains the data of the best individual of each generation when only the genetic algorithm is used, with the first line being the first generation. Apart from the data mentioned above, it also contains the ratios C1=xfc2,C/xfc2,B and C2=xfc2,E/xfc2,B, which served as constraints. The elements of profit, the income, incineration and steam cost are also given.
The results of Latin hypercube sampling are in the file “LHS run data.xlsx”. Simulations prematurely terminated are indicated with the symbol “x” in the column “t, min”.
The file “Simplex run data.xlsx” contains the results of the optimisation performed with the Nelder-Mead simplex algorithm. Each run has two sheets. The one whose name starts with “History” contains the initial simplex, including its side length (a), and the list of new points generated by the algorithm. In the latter list, the average (Avg. OF) and standard deviation of the OF values (SD OF) of the points in the simplex are also given. The sheet with the name starting with “AS” shows all the simplexes in sequence, the average and standard deviation of OF (columns Q and R), the simplex size (column S) and the operation performed.
The file “Complex run data.xlsx” presents the data of the current best point of the complex in the rows of each sheet. “n” is the number of simulations performed, “d_avg” is the average scaled distance between the point of the complex.
DOI: 10.15468/dl.avzrrm
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Curruca subcoerulea",
 "Country is one of (Brunei Darussalam, Indonesia, Philippines, Timor-Leste, Singapore)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028249-250920141307145/datasets/export for details.
DOI: 10.17632/33j33cr7m9.1
title: Detailed Optimisation Results for a Batch Extractive Distillation Process Obtained by Hybrid Optimisation Methods

description: The data presented in the four Excel files were used in the paper "Laszlo Hegely: Optimisation of a Batch Extractive Distillation Process with Hybrid Methods, 2025". They show the data points in which the simulation of the batch extractive distillation process was performed, as well as the simulation results. By the data points, we refer to points in the seven-dimensional space of the optimisation variables, which were the reflux ratios of Steps 1-3 of the procedure (R1, R2, R3), the stopping criteria of Steps 1 and 2 (Cr1 and Cr2), and the flow rate (FE) and duration (tF) of the water feeding. (Values of tF/2 are given in the files.) The stopping criteria are the values of tetrahydrofuran concentration (in mass fraction) in the (instantaneous) distillate when the given step is finished. Selected simulation results, the ones necessary to calculate the profit of the process, are also shown: duration of the process (t), mass of the Fore-cut 1 (mfc1) and of the main cut (mmc), the concentration of methanol, THF and toluene in Fore-cut 2 (xfc2,B, xfc2,C and xfc2,E, respectively), the final (xmc,B) and maximal (xmc,B,max) concentration of methanol in the main cut, as well as the profit (OF).
The different files correspond to the different optimisation methods used. They contain various sheets that correspond to different optimisation runs; they are identified with the notation used in the corresponding paper. 
The file “GA run data.xlsx” contains the data of the best individual of each generation when only the genetic algorithm is used, with the first line being the first generation. Apart from the data mentioned above, it also contains the ratios C1=xfc2,C/xfc2,B and C2=xfc2,E/xfc2,B, which served as constraints. The elements of profit, the income, incineration and steam cost are also given.
The results of Latin hypercube sampling are in the file “LHS run data.xlsx”. Simulations prematurely terminated are indicated with the symbol “x” in the column “t, min”.
The file “Simplex run data.xlsx” contains the results of the optimisation performed with the Nelder-Mead simplex algorithm. Each run has two sheets. The one whose name starts with “History” contains the initial simplex, including its side length (a), and the list of new points generated by the algorithm. In the latter list, the average (Avg. OF) and standard deviation of the OF values (SD OF) of the points in the simplex are also given. The sheet with the name starting with “AS” shows all the simplexes in sequence, the average and standard deviation of OF (columns Q and R), the simplex size (column S) and the operation performed.
The file “Complex run data.xlsx” presents the data of the current best point of the complex in the rows of each sheet. “n” is the number of simulations performed, “d_avg” is the average scaled distance between the point of the complex.
DOI: 10.17632/j8735gv8f5
title: pH/enzyme dual-responsive colon-targeted dropping pills loaded with naringin

description: It includes experimental data on the preparation of pH and enzyme dual-targeted naringin capsules for the colon.
DOI: 10.17632/j8735gv8f5.1
title: pH/enzyme dual-responsive colon-targeted dropping pills loaded with naringin

description: It includes experimental data on the preparation of pH and enzyme dual-targeted naringin capsules for the colon.
DOI: 10.17632/8vvb2s9y5c
title: Dynamic Prediction Model Based on Relational Heterogeneous Graph Neural Networks

description: The data was mainly obtained from the website of China Health and Retirement Longitudinal Study. Regarding the clinical and behavioral habit factors related to sarcopenia, after cleaning and integration, the final clean data was obtained. Using these data, a dynamic prediction model for sarcopenia based on graph neural networks was constructed to achieve early warning of sarcopenia.
DOI: 10.17632/8vvb2s9y5c.1
title: Dynamic Prediction Model Based on Relational Heterogeneous Graph Neural Networks

description: The data was mainly obtained from the website of China Health and Retirement Longitudinal Study. Regarding the clinical and behavioral habit factors related to sarcopenia, after cleaning and integration, the final clean data was obtained. Using these data, a dynamic prediction model for sarcopenia based on graph neural networks was constructed to achieve early warning of sarcopenia.
DOI: 10.15468/dl.rqfb7c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Herniaria glabra",
 "Country is Japan",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028253-250920141307145/datasets/export for details.
DOI: 10.15468/dl.ksfyj8
title: Occurrence Download

description: A dataset containing 273 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Aster tongolensis)"
 ]
}

 The dataset includes 273 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028250-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.