cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/g3vfxhw6rg
title: INCREASING THE LEVEL OF READING PROFICIENCY OF GRADE 7 STUDENTS THROUGH THE IMPLEMENTATION OF ENGLISH READING PROGRAM

description: This research study quantitatively examines the effectiveness of the English Reading Program in improving the reading proficiency of Grade 7 students at Bucal National Integrated School. Using a pretest–posttest design, the study measures students’ reading proficiency levels before and after the implementation of the program through standardized reading assessments and readability indicators. The analysis focuses on determining the extent of improvement in students’ reading performance and evaluating the appropriateness of the reading materials used during the intervention. The study involves 494 Grade 7 students from eleven (11) sections of Bucal National Integrated School. The findings aim to provide empirical, data-driven evidence to support instructional decision-making and to enhance the implementation of reading interventions within the school context. 
(Note: for the full manuscript see the related links)
DOI: 10.17632/g3vfxhw6rg.2
title: INCREASING THE LEVEL OF READING PROFICIENCY OF GRADE 7 STUDENTS THROUGH THE IMPLEMENTATION OF ENGLISH READING PROGRAM

description: This research study quantitatively examines the effectiveness of the English Reading Program in improving the reading proficiency of Grade 7 students at Bucal National Integrated School. Using a pretest–posttest design, the study measures students’ reading proficiency levels before and after the implementation of the program through standardized reading assessments and readability indicators. The analysis focuses on determining the extent of improvement in students’ reading performance and evaluating the appropriateness of the reading materials used during the intervention. The study involves 494 Grade 7 students from eleven (11) sections of Bucal National Integrated School. The findings aim to provide empirical, data-driven evidence to support instructional decision-making and to enhance the implementation of reading interventions within the school context. 
(Note: for the full manuscript see the related links)
DOI: 10.17632/yn9ptx7mnd.1
title: Dataset on Suicide Risk, Substance Abuse, and Family Functioning Among University Students in a Health Faculty

description: This dataset derives from a cross-sectional public health study aimed at assessing family functioning, substance use, and suicide risk and protective factors among university students.

File structure

The data file is provided in tabular format (rows = participants; columns = variables) and contains approximately 50 columns, organized into four main sections:

Informed consent: a dichotomous variable documenting voluntary agreement to participate in the study.

Mental and social health assessment instruments: items from the Family APGAR (Apgar_1–Apgar_9), the Drug Abuse Screening Test (DAST-10) (DAST_1–DAST_10), and the Positive and Negative Suicide Ideation Inventory (PANSI) (Pansi_1–Pansi_13).

Sociodemographic, academic, and health insurance variables: gender identity, biological sex, age group, relationship status, health insurance scheme, and academic program.

Derived and classification variables: total scores (Family APGAR score and DAST-10 score) and categorical variables for clinical classification and interpretation (Clas_apgar, Inter_apgar, Clas_DAST10, Inter_DAST10).

Variable naming scheme

Variable names follow a standardized structure to facilitate reuse and interpretation:

Instrument-specific prefixes (Apgar_, DAST_, Pansi_) followed by sequential numbering.

Derived variables identified by descriptive prefixes (Puntaje, Clas_, Inter_).

Sociodemographic variables use concise and consistent naming conventions (genero, sexo, rango_edad, sit_sent, reg_salud, prog_acade).

Variable types and encoding

The dataset includes dichotomous categorical, polytomous ordinal categorical, and discrete quantitative variables. Most instrument items use a five-point ordinal scale numerically coded from 0 to 4, with higher values indicating greater frequency or intensity of the assessed construct.

The file uses UTF-8 character encoding, ensuring proper representation of Spanish-language characters. Missing values are represented by empty cells or instrument-specific codes.
DOI: 10.17632/njb5pjm2bb
title: AI Self-Efficacy, Innovative Work Behavior, Work Engagement, Schedule Idiosyncratic Deals

description: AI Self-Efficacy, Innovative Work Behavior, Work Engagement, Schedule Idiosyncratic Deals
DOI: 10.17632/njb5pjm2bb.1
title: AI Self-Efficacy, Innovative Work Behavior, Work Engagement, Schedule Idiosyncratic Deals

description: AI Self-Efficacy, Innovative Work Behavior, Work Engagement, Schedule Idiosyncratic Deals
DOI: 10.6084/m9.figshare.30885299.v1
title: Diversification within the epizoic habitat in diatoms of the genus <i>Achnanthes</i> (Bacillariophyceae)

description: As we continue to document the diversity of epizoic diatoms, we can channel greater effort into understanding the nature of the interaction between the diatoms and their host organisms. Among diatoms, the genus <i>Achnanthes</i> Bory is unique in that it contains taxa which grow opportunistically on both epizoic and non-epizoic benthic habitats as well as taxa which are restricted to epizoic habitats. One of these latter taxa, <i>Achnanthes elongata</i>, stands out as a more ecologically flexible species, having been documented on a variety of marine vertebrates, including manatees, diamondback terrapins and four species of sea turtles. We isolated, cultured and documented morphology and DNA data from <i>Achnanthes</i> cells from manatees, dolphins, sea turtles, terrapins and sea snakes from multiple locations on both sides of the Atlantic Ocean and from the Indian Ocean. Molecular phylogenetic inference of the DNA sequence data from these strains implied a single transition to an exclusively epizoic habitat (in <i>Achnanthes elongata</i> and <i>Achnanthes squaliformis</i>) but could not resolve any fine population-level patterns regarding host specificity or biogeography. We also take the opportunity here to describe a novel taxon of <i>Achnanthes</i>, <i>Achnanthes angustelliptica</i> sp. nov., which was collected from a manatee but has been documented in other habitats as well.
DOI: 10.6084/m9.figshare.30885299
title: Diversification within the epizoic habitat in diatoms of the genus <i>Achnanthes</i> (Bacillariophyceae)

description: As we continue to document the diversity of epizoic diatoms, we can channel greater effort into understanding the nature of the interaction between the diatoms and their host organisms. Among diatoms, the genus <i>Achnanthes</i> Bory is unique in that it contains taxa which grow opportunistically on both epizoic and non-epizoic benthic habitats as well as taxa which are restricted to epizoic habitats. One of these latter taxa, <i>Achnanthes elongata</i>, stands out as a more ecologically flexible species, having been documented on a variety of marine vertebrates, including manatees, diamondback terrapins and four species of sea turtles. We isolated, cultured and documented morphology and DNA data from <i>Achnanthes</i> cells from manatees, dolphins, sea turtles, terrapins and sea snakes from multiple locations on both sides of the Atlantic Ocean and from the Indian Ocean. Molecular phylogenetic inference of the DNA sequence data from these strains implied a single transition to an exclusively epizoic habitat (in <i>Achnanthes elongata</i> and <i>Achnanthes squaliformis</i>) but could not resolve any fine population-level patterns regarding host specificity or biogeography. We also take the opportunity here to describe a novel taxon of <i>Achnanthes</i>, <i>Achnanthes angustelliptica</i> sp. nov., which was collected from a manatee but has been documented in other habitats as well.
DOI: 10.5281/zenodo.17931169
title: Comparison of frame-based vs. event-based vision systems

description: This repository contains experimental datasets used for a comparative study of frame-based and event-based vision systems in industrial inspection scenarios relevant to flexible manufacturing systems (FMS). The datasets were acquired under controlled laboratory conditions designed to emulate real-world industrial environments, including variable illumination, conveyor speed, and object geometry.
DOI: 10.6084/m9.figshare.30885301.v1
title: A Comprehensive Study of Grey Wolf Optimizer Variants for Optimizing Feature Selection in High-Dimensional Data

description: Metaheuristic algorithms, notably the Grey Wolf Optimizer (GWO), are widely used for wrapper-based feature selection due to their superior ability to balance exploration and exploitation. We conduct a comparative evaluation of the original GWO and eight established variants on ten benchmark datasets from diverse domains. All nine selectors are tested under a unified wrapper protocol. The evaluation encompasses accuracy, composite fitness, feature-reduction rate, runtime, Fisher index, and selection consistency. Statistical significance is assessed using the Friedman test with Nemenyi post-hoc comparisons. Multi-Swarm GWO (MS-GWO) achieves the highest average classification accuracy on most datasets and the best overall optimization quality, ranking first with a mean rank of 2.55 across all metrics. Chaotic GWO (CGWO) delivers the strongest dimensionality reduction and the lowest average runtime, indicating superior computational efficiency. Adaptive GWO (AGWO) performs worst in accuracy and feature reduction, limiting its utility in high-dimensional settings. The original GWO offers balanced performance and serves as a stable baseline. On average, MS-GWO’s fitness is 23.21% lower than the pooled mean of the other variants, indicating superior optimization performance. These results guide the selection of GWO variants, with MS-GWO recommended for accuracy and overall optimization, and CGWO for dimensionality reduction and speed.
DOI: 10.6084/m9.figshare.30885301
title: A Comprehensive Study of Grey Wolf Optimizer Variants for Optimizing Feature Selection in High-Dimensional Data

description: Metaheuristic algorithms, notably the Grey Wolf Optimizer (GWO), are widely used for wrapper-based feature selection due to their superior ability to balance exploration and exploitation. We conduct a comparative evaluation of the original GWO and eight established variants on ten benchmark datasets from diverse domains. All nine selectors are tested under a unified wrapper protocol. The evaluation encompasses accuracy, composite fitness, feature-reduction rate, runtime, Fisher index, and selection consistency. Statistical significance is assessed using the Friedman test with Nemenyi post-hoc comparisons. Multi-Swarm GWO (MS-GWO) achieves the highest average classification accuracy on most datasets and the best overall optimization quality, ranking first with a mean rank of 2.55 across all metrics. Chaotic GWO (CGWO) delivers the strongest dimensionality reduction and the lowest average runtime, indicating superior computational efficiency. Adaptive GWO (AGWO) performs worst in accuracy and feature reduction, limiting its utility in high-dimensional settings. The original GWO offers balanced performance and serves as a stable baseline. On average, MS-GWO’s fitness is 23.21% lower than the pooled mean of the other variants, indicating superior optimization performance. These results guide the selection of GWO variants, with MS-GWO recommended for accuracy and overall optimization, and CGWO for dimensionality reduction and speed.
DOI: 10.17632/xtg72yf9rh
title: Replication Package for article "A Co-Jump Network Approach to Systemic Risk Measurement: Evidence from the U.S. Financial Market"

description: Replication Package for article "A Co-Jump Network Approach to Systemic Risk Measurement: Evidence from the U.S. Financial Market", includes readme file, main code and data.
DOI: 10.17632/xtg72yf9rh.1
title: Replication Package for article "A Co-Jump Network Approach to Systemic Risk Measurement: Evidence from the U.S. Financial Market"

description: Replication Package for article "A Co-Jump Network Approach to Systemic Risk Measurement: Evidence from the U.S. Financial Market", includes readme file, main code and data.
DOI: 10.17632/88r8dcffzg
title: Database of Occupational Benefits Costs in Brazil (Period from March 2022 to March 2024)

description: We used the Knowledge Discovery in Databases (KDD) method to create the database. 
In the first KDD stage, we selected 25 files containing benefit data issued by INSS (National Social Security Institute). These files cover March 2022 to March 2024, representing the only period available for download on the Brazilian Open Data portal at the time of our research. We exported all these data files to the SQL Server 2020 database using the Microsoft SQL Server Management Studio's import and export wizard. Each file generated a distinct table.
A query to the tables revealed they contained all social security benefits issued by INSS. For this research, we only focused on occupational benefits (B91, B92, B93, and B94). Thus, in the first step of the second KDD stage, we excluded benefits not related to work-related diseases and accidents. Still, within data preprocessing, we equalized the number of columns in each table. To do this, we removed columns not present in all tables or those irrelevant for analysis, such as "Meio pagamento" and "Banco."
In the data transformation stage, we created columns for the country's region and the benefit code. We populated the region column based on the benefit's state of issuance. Subsequently, we filled the benefit code column according to the benefit's name.
Finally, we exported all tables into a single table, "tbbeneficios," within the DBCustos database. This resulted in a table with over 18 million rows and a backup file of approximately 5 GB. The Table 1 presents the structure of the "tbbeneficios" table.
DOI: 10.5281/zenodo.16745417
title: A wavelet-based method for the assessment of hydrodynamic model behaviour against observed sea level variability

description: Accompanying data for the submission "A wavelet-based method for the assessment of hydrodynamic model behaviour against observed sea level variability" to Limnology and Oceanography: Methods.

Consists of



NEMO 1-hourly sea level output for the whole domain (compressed, full_output.tar.gz)

NEMO sea level outputs extracted at the grid locations closest to the locations of the corresponding tide gauges (BO_TS_TG_[station name]_processed_UNFILTERED.nc)

Wavelet transforms of extracted NEMO sea level outputs and corresponding tide gauges (compressed, [station name]_transforms.tar.gz)



Transforms of tide gauge series in mesoscale range: [station name]_obs_meso_*.nc

Transforms of tide gauge series in synoptic range: [station name]_obs_syno_*.nc

Transforms of model output series in mesoscale range: [station name]_mod_meso_*.nc

Transforms of model output series in synoptic range: [station name]_mod_syno_*.nc




The tide gauge data itself is avaliable at https://en.ilmatieteenlaitos.fi/open-data
DOI: 10.5281/zenodo.17940537
title: A wavelet-based method for the assessment of hydrodynamic model behaviour against observed sea level variability

description: Accompanying data for the submission "A wavelet-based method for the assessment of hydrodynamic model behaviour against observed sea level variability" to Limnology and Oceanography: Methods.

Consists of



NEMO 1-hourly sea level output for the whole domain (compressed, full_output.tar.gz)

NEMO sea level outputs extracted at the grid locations closest to the locations of the corresponding tide gauges (BO_TS_TG_[station name]_processed_UNFILTERED.nc)

Wavelet transforms of extracted NEMO sea level outputs and corresponding tide gauges (compressed, [station name]_transforms.tar.gz)



Transforms of tide gauge series in mesoscale range: [station name]_obs_meso_*.nc

Transforms of tide gauge series in synoptic range: [station name]_obs_syno_*.nc

Transforms of model output series in mesoscale range: [station name]_mod_meso_*.nc

Transforms of model output series in synoptic range: [station name]_mod_syno_*.nc




The tide gauge data itself is avaliable at https://en.ilmatieteenlaitos.fi/open-data
DOI: 10.17632/88r8dcffzg.1
title: Database of Occupational Benefits Costs in Brazil (Period from March 2022 to March 2024)

description: We used the Knowledge Discovery in Databases (KDD) method to create the database. 
In the first KDD stage, we selected 25 files containing benefit data issued by INSS (National Social Security Institute). These files cover March 2022 to March 2024, representing the only period available for download on the Brazilian Open Data portal at the time of our research. We exported all these data files to the SQL Server 2020 database using the Microsoft SQL Server Management Studio's import and export wizard. Each file generated a distinct table.
A query to the tables revealed they contained all social security benefits issued by INSS. For this research, we only focused on occupational benefits (B91, B92, B93, and B94). Thus, in the first step of the second KDD stage, we excluded benefits not related to work-related diseases and accidents. Still, within data preprocessing, we equalized the number of columns in each table. To do this, we removed columns not present in all tables or those irrelevant for analysis, such as "Meio pagamento" and "Banco."
In the data transformation stage, we created columns for the country's region and the benefit code. We populated the region column based on the benefit's state of issuance. Subsequently, we filled the benefit code column according to the benefit's name.
Finally, we exported all tables into a single table, "tbbeneficios," within the DBCustos database. This resulted in a table with over 18 million rows and a backup file of approximately 5 GB. The Table 1 presents the structure of the "tbbeneficios" table.
DOI: 10.15468/dl.kyep6f
title: Occurrence Download

description: A dataset containing 3569 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rubus hirsutus"
 ]
}

 The dataset includes 3569 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053703-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/drj89cs69h
title: Development and application of a barcoded rabies viral tracing method for mapping brain-wide inputs to single neurons

description: While whole-brain connectome mapping has been achieved at both macroscopic (tract tracing) and microscopic (electron microscopy) scales, existing methods—such as conventional rabies virus tracing or sequencing-based projection mapping—cannot simultaneously capture both local and long-range inputs to single neurons while integrating transcriptomic identities. Furthermore, prior barcoded rabies approaches faced challenges such as barcode sharing between starter cells, low barcode/cell recovery rates, and an inability to link connectivity to gene expression. The Barcoded Rabies Viral Tracing (BRT) method was engineered to address these gaps by combining high-diversity barcoded rabies viruses with single-cell RNA sequencing of the starter region and bulk barcode sequencing of input regions, enabling the reconstruction of comprehensive inputomes for transcriptome-defined neurons.
DOI: 10.17632/drj89cs69h.2
title: Development and application of a barcoded rabies viral tracing method for mapping brain-wide inputs to single neurons

description: While whole-brain connectome mapping has been achieved at both macroscopic (tract tracing) and microscopic (electron microscopy) scales, existing methods—such as conventional rabies virus tracing or sequencing-based projection mapping—cannot simultaneously capture both local and long-range inputs to single neurons while integrating transcriptomic identities. Furthermore, prior barcoded rabies approaches faced challenges such as barcode sharing between starter cells, low barcode/cell recovery rates, and an inability to link connectivity to gene expression. The Barcoded Rabies Viral Tracing (BRT) method was engineered to address these gaps by combining high-diversity barcoded rabies viruses with single-cell RNA sequencing of the starter region and bulk barcode sequencing of input regions, enabling the reconstruction of comprehensive inputomes for transcriptome-defined neurons.
DOI: 10.17632/2scppydzt3
title: Data and codes for: The long-run relationship between labour force participation rate and unemployment rate for Türkiye: COVID-19 matters

description: This file contains the dataset and program files for the article:
Sivri, U. (202?). The long-run relationship between labour force participation rate and unemployment rate for Türkiye: COVID-19 matters. Applied Economics Letters, DOI: 10.1080/13504851.2025.2603671
The link of the article will be: https://doi.org/10.1080/13504851.2025.2603671
The original data are obtained from Turkish Statistical Institute. 
“Data” and “Data_SA” are data files used in the analyses. 
SA abbreviation means seasonally adjusted.
Analysis.wf1 is a EViews file that also includes all data. EViews12 software is used in unit root tests withous structural breaks and producing the Figure 1. 
LS_One_unemployment is a Gauss file. Gauss software is used in unit root tests with structural breaks.
“Analysis_Before”, “Analysis_After”, “Analysis_Before_SA” and “Analysis_After_SA” are WinRATS files. The Johansen cointegration and related analysis are carried out by WinRATS Pro (v. 6.35) and CATS in RATS (v. 2). Before and after denote to pre- and post-COVID19 periods, respectively. 
“Results” and “Results_SA” are the results prepared for seeing and comparing the results at each stage of the analysis. In addition to the results reported and discussed in the paper, these files also include nonreported and non-discussed results such as structural break results.
DOI: 10.17632/2scppydzt3.1
title: Data and codes for: The long-run relationship between labour force participation rate and unemployment rate for Türkiye: COVID-19 matters

description: This file contains the dataset and program files for the article:
Sivri, U. (202?). The long-run relationship between labour force participation rate and unemployment rate for Türkiye: COVID-19 matters. Applied Economics Letters, DOI: 10.1080/13504851.2025.2603671
The link of the article will be: https://doi.org/10.1080/13504851.2025.2603671
The original data are obtained from Turkish Statistical Institute. 
“Data” and “Data_SA” are data files used in the analyses. 
SA abbreviation means seasonally adjusted.
Analysis.wf1 is a EViews file that also includes all data. EViews12 software is used in unit root tests withous structural breaks and producing the Figure 1. 
LS_One_unemployment is a Gauss file. Gauss software is used in unit root tests with structural breaks.
“Analysis_Before”, “Analysis_After”, “Analysis_Before_SA” and “Analysis_After_SA” are WinRATS files. The Johansen cointegration and related analysis are carried out by WinRATS Pro (v. 6.35) and CATS in RATS (v. 2). Before and after denote to pre- and post-COVID19 periods, respectively. 
“Results” and “Results_SA” are the results prepared for seeing and comparing the results at each stage of the analysis. In addition to the results reported and discussed in the paper, these files also include nonreported and non-discussed results such as structural break results.