cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5285/35fb8318798e437ba5b108e5eca6e92d
title: Monthly Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.1.0.0

description: The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.

These historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).
 
The monthly temperature series are derived as the mean of the daily temperature series values.
 
For mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.

Stations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick
 
Stations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College
 
The current station selection used is Rothamsted, Stonyhurst and Pershore College.
 
The dataset is compiled by the Met Office Hadley Centre.

Latest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html).

The version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.

The CET datasets employ the following version control protocol: 

Version Vx.y.z.a:
• x – major changes – e.g. change in scientific methodology
• y – minor changes – e.g. small bug fixes or updates to diagnostics pages
• z – incremental changes
• a – reserved for use internally

The standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial
changes have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).

This new version of the datasets supersedes the previous version.
DOI: 10.5281/zenodo.15600457
title: Jacobsthal Function Bounds

description: **Title:** Jacobsthal Function Bounds – Analytical Framework and Resolution

**Description:**  This paper presents a comprehensive resolution to the Jacobsthal function bounding problem. By modeling coprime sequences on modular lattice grids and applying number-theoretic sieve theory, we establish a provable upper bound for the Jacobsthal function in terms of Euler’s totient function. Our method applies compactified logarithmic filtering to yield scalable, efficient predictions. The result advances both theoretical insight and practical implications for prime-based number systems, cryptography, and modular arithmetic.

**Tags:** Number Theory, Coprime Sequences, Euler's Totient Function, Jacobsthal Function, Modular Lattice, Prime Gaps, Cryptography
DOI: 10.5281/zenodo.15600458
title: Jacobsthal Function Bounds

description: **Title:** Jacobsthal Function Bounds – Analytical Framework and Resolution

**Description:**  This paper presents a comprehensive resolution to the Jacobsthal function bounding problem. By modeling coprime sequences on modular lattice grids and applying number-theoretic sieve theory, we establish a provable upper bound for the Jacobsthal function in terms of Euler’s totient function. Our method applies compactified logarithmic filtering to yield scalable, efficient predictions. The result advances both theoretical insight and practical implications for prime-based number systems, cryptography, and modular arithmetic.

**Tags:** Number Theory, Coprime Sequences, Euler's Totient Function, Jacobsthal Function, Modular Lattice, Prime Gaps, Cryptography
DOI: 10.5281/zenodo.15148342
title: Research data for the paper Type 1 diabetes mellitus patients had lower total vitamin K levels  and increased sensitivity to direct anticoagulants

description: research data for the paper
DOI: 10.5281/zenodo.15148343
title: Research data for the paper Type 1 diabetes mellitus patients had lower total vitamin K levels  and increased sensitivity to direct anticoagulants

description: research data for the paper
DOI: 10.5281/zenodo.15599935
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250605j Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250605j Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15599936
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250605j Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250605j Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.17632/x4p93tppyz
title: Banco de Dados: Aptidão Física e Estilo de vida

description: Este banco de dados contém informações de 100 participantes avaliados quanto à sua aptidão física e estilo de vida, com o objetivo de investigar a relação entre saúde física e hábitos comportamentais.
DOI: 10.17632/x4p93tppyz.1
title: Banco de Dados: Aptidão Física e Estilo de vida

description: Este banco de dados contém informações de 100 participantes avaliados quanto à sua aptidão física e estilo de vida, com o objetivo de investigar a relação entre saúde física e hábitos comportamentais.
DOI: 10.17632/3h3k58bg2y
title: Plasmid_release_Research Data_EI

description: This dataset “Plasmid_release_Research Data_EI”contains the original data of all the figures and tables in the submitted article“Release and bacterial transformation activity of plasmid-borne antibiotic resistance genes adsorbed on iron nanoparticles as induced by sulfide reduction” for Environment International.
DOI: 10.17632/3h3k58bg2y.1
title: Plasmid_release_Research Data_EI

description: This dataset “Plasmid_release_Research Data_EI”contains the original data of all the figures and tables in the submitted article“Release and bacterial transformation activity of plasmid-borne antibiotic resistance genes adsorbed on iron nanoparticles as induced by sulfide reduction” for Environment International.
DOI: 10.5281/zenodo.13200873
title: Model output used in the manuscript "Micro and macro parametric uncertainty in climate change prediction: a large ensemble perspective"

description: This *.zip file contains the model output from ensemble simulations for the Lorenz 84-Stommel 61 model (hereafter L84-S61; Van Veen et al, 2001; Daron and Stainforth, 2013). To run these simulations, we used the Low-EFFourth ensemble generator (de Melo Viríssimo, 2025a; de Melo Viríssimo, 2025b), which is a MATLAB-based framework that allows for large ensembles of low-dimensional dynamical systems to be run and studied in a systematic way (de Melo Viríssimo and Stainforth, 2023).

These model outputs are presented and discussed in the manuscript "Micro and macro parametric uncertainty in climate change prediction: a large ensemble perspective", published by the Bulletin of the American Meteorological Society (de Melo Viríssimo and Stainforth, 2025). The manuscript describes the experiments performed, the parameter values used and the modifications done to the original L84-S61 model. For this matter, we also refer you to Daron and Stainforth (2013) and de Melo Viríssimo et al. (2024).

All files uploaded were generated from simulations run by the lead author.

For specific information about each file uploaded, please refer to the README file. The details of each experiment are also presented in the supplementary materials of the manuscript. If you have any questions, please feel free to contact me.
DOI: 10.5281/zenodo.13200874
title: Model output used in the manuscript "Micro and macro parametric uncertainty in climate change prediction: a large ensemble perspective"

description: This *.zip file contains the model output from ensemble simulations for the Lorenz 84-Stommel 61 model (hereafter L84-S61; Van Veen et al, 2001; Daron and Stainforth, 2013). To run these simulations, we used the Low-EFFourth ensemble generator (de Melo Viríssimo, 2025a; de Melo Viríssimo, 2025b), which is a MATLAB-based framework that allows for large ensembles of low-dimensional dynamical systems to be run and studied in a systematic way (de Melo Viríssimo and Stainforth, 2023).

These model outputs are presented and discussed in the manuscript "Micro and macro parametric uncertainty in climate change prediction: a large ensemble perspective", published by the Bulletin of the American Meteorological Society (de Melo Viríssimo and Stainforth, 2025). The manuscript describes the experiments performed, the parameter values used and the modifications done to the original L84-S61 model. For this matter, we also refer you to Daron and Stainforth (2013) and de Melo Viríssimo et al. (2024).

All files uploaded were generated from simulations run by the lead author.

For specific information about each file uploaded, please refer to the README file. The details of each experiment are also presented in the supplementary materials of the manuscript. If you have any questions, please feel free to contact me.
DOI: 10.6084/m9.figshare.29243660
title: The Regulation of Lysosomal TRPML1 Channels on Insulin Secretion raw data.7z

description: The Regulation of Lysosomal TRPML1 Channels on Insulin Secretion raw data.
DOI: 10.6084/m9.figshare.29243660.v1
title: The Regulation of Lysosomal TRPML1 Channels on Insulin Secretion raw data.7z

description: The Regulation of Lysosomal TRPML1 Channels on Insulin Secretion raw data.
DOI: 10.7910/dvn/ftwygr
title: Streptococcus pyogenes Surveillance Through Surface Swab Samples to Track the Emergence of Streptococcal Toxic Shock Syndrome in Rural Japan

description: Sequence FASTA data set related to emm genotype
DOI: 10.15468/dl.8xmmff
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ricinus communis",
 "Country is Lebanon",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025180-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15599897
title: GSA data from the paper: Harnessing small RNAs as synthetic post-transcriptional regulators in prokaryotes

description: Dataset from a Global Sensitivity Analysis (GSA) of an Ordinary Differential Equation (ODE) model simulating sRNA-mediated regulation of protein expression. It includes 1.5000.000 input parameter sets (kinetic rates for processes like transcription, translation, degradation, and sRNA-target interaction) generated via Sobol' sampling from defined ranges using uniform and log-uniform distributions. The corresponding model output for each set is the 'Protein Regulation Strength,' calculated as a log2 fold change. This dataset is provided for re-analysis of parameter sensitivities, interactions, and further model exploration. The R scripts for the GSA and model are available in the associated GitHub repository: https://github.com/JensGeorg/GSA-sRNA-RNA-interaction-.git
DOI: 10.5281/zenodo.15599898
title: GSA data from the paper: Harnessing small RNAs as synthetic post-transcriptional regulators in prokaryotes

description: Dataset from a Global Sensitivity Analysis (GSA) of an Ordinary Differential Equation (ODE) model simulating sRNA-mediated regulation of protein expression. It includes 1.5000.000 input parameter sets (kinetic rates for processes like transcription, translation, degradation, and sRNA-target interaction) generated via Sobol' sampling from defined ranges using uniform and log-uniform distributions. The corresponding model output for each set is the 'Protein Regulation Strength,' calculated as a log2 fold change. This dataset is provided for re-analysis of parameter sensitivities, interactions, and further model exploration. The R scripts for the GSA and model are available in the associated GitHub repository: https://github.com/JensGeorg/GSA-sRNA-RNA-interaction-.git
DOI: 10.17632/v63vrhgwxy
title: Dates related to the research results presented in the article: Conceptual Framework for Clustering, Labeling, and Evaluating Scientific Articles with Embedding Models and Bibliometric Analysis

description: Dataset Description for the Article:
"Conceptual Framework for Clustering, Labeling, and Evaluating Scientific Articles with Embedding Models and Bibliometric Analysis"

The dataset underpins the experiments described in the article, which proposes a framework for clustering, labeling, and evaluating scientific publications using both statistical and bibliometric indicators. It consists of three CSV files, each corresponding to a different collection of scholarly publications (small, medium, and large). All publications were retrieved from the Scopus database based on specific search queries.

CSV Files (3 in total) - Each CSV file contains:
Ranked lists of scholarly articles retrieved from Scopus, supplemented with computed vectors.
Embedding vectors representing article content (title + abstract).
Distance metrics (e.g., cosine distance) to enable quick similarity comparisons.

Together, these CSV files mirror the experimental setup discussed in the article, allowing reproduction of the clustering and labeling processes, as well as subsequent evaluations via bibliometric and statistical approaches.

Data Structure:
Standard Metadata Columns (from Scopus export):
These include typical bibliographic information such as:

Title, Authors, Year, DOI, Source title, Abstract, Keywords, Affiliations, Document Type, Cited by, and others.

Computed Columns (for experimentation):

combined_embeddings or article_embedding:
A list of numeric values representing the semantic embedding vector generated from the concatenated title and abstract of the publication.

distance_cosine:
The cosine distance between the publication’s embedding and a reference embedding (e.g., based on a user query).
Values range from 0 to 1, where lower values indicate higher semantic similarity.

Purpose and Use:
These data support the evaluation of embedding-based clustering, labeling, and bibliometric methods for automating systematic literature reviews. They serve as reproducible material for the experiments described in the paper.
DOI: 10.17632/v63vrhgwxy.1
title: Dates related to the research results presented in the article: Conceptual Framework for Clustering, Labeling, and Evaluating Scientific Articles with Embedding Models and Bibliometric Analysis

description: Dataset Description for the Article:
"Conceptual Framework for Clustering, Labeling, and Evaluating Scientific Articles with Embedding Models and Bibliometric Analysis"

The dataset underpins the experiments described in the article, which proposes a framework for clustering, labeling, and evaluating scientific publications using both statistical and bibliometric indicators. It consists of three CSV files, each corresponding to a different collection of scholarly publications (small, medium, and large). All publications were retrieved from the Scopus database based on specific search queries.

CSV Files (3 in total) - Each CSV file contains:
Ranked lists of scholarly articles retrieved from Scopus, supplemented with computed vectors.
Embedding vectors representing article content (title + abstract).
Distance metrics (e.g., cosine distance) to enable quick similarity comparisons.

Together, these CSV files mirror the experimental setup discussed in the article, allowing reproduction of the clustering and labeling processes, as well as subsequent evaluations via bibliometric and statistical approaches.

Data Structure:
Standard Metadata Columns (from Scopus export):
These include typical bibliographic information such as:

Title, Authors, Year, DOI, Source title, Abstract, Keywords, Affiliations, Document Type, Cited by, and others.

Computed Columns (for experimentation):

combined_embeddings or article_embedding:
A list of numeric values representing the semantic embedding vector generated from the concatenated title and abstract of the publication.

distance_cosine:
The cosine distance between the publication’s embedding and a reference embedding (e.g., based on a user query).
Values range from 0 to 1, where lower values indicate higher semantic similarity.

Purpose and Use:
These data support the evaluation of embedding-based clustering, labeling, and bibliometric methods for automating systematic literature reviews. They serve as reproducible material for the experiments described in the paper.
DOI: 10.17632/w5gnr5wk7f.1
title: Catfish Cultivation Biofloc Pond in Integrated Agricultural System

description: This dataset offers a comprehensive glimpse into the growth of catfish within biofloc ponds, which are standardized at dimensions of 1.5 meters in both diameter and height. The primary focus of this study lies in meticulously assessing water quality, facilitated by the deployment of sensors designed to measure critical parameters such as water temperature, pH levels, total dissolved solids, electrical conductivity, and turbidity. Moreover, external sensors for temperature and relative humidity are strategically positioned to capture environmental conditions within the biofloc pond accurately. Data collection is conducted at three distinct times during the day—morning, afternoon, and evening—to ensure thorough representation of daily fluctuations. The process of obtaining data on catfish growth entails a systematic approach, involving regular weighing of catfish specimens and manual calculations of both living and deceased individuals on a weekly basis. Covering a duration of 69 days and spanning 11 weeks from June 1, 2023, to August 8, 2023, the dataset encompasses observations from three separate biofloc ponds. The deliberate integration of methodologies for environmental monitoring and growth assessment forms the bedrock of this dataset, offering valuable insights into the dynamic interplay between biofloc pond conditions and catfish growth over a specific timeframe. With its potential for reuse across diverse research domains such as aquaculture, environmental science, and data-driven modeling, this dataset serves as a pivotal resource for researchers delving into the intricate relationship between biofloc pond dynamics and catfish development.
DOI: 10.17632/w5gnr5wk7f
title: Catfish Cultivation Biofloc Pond in Integrated Agricultural System

description: This dataset offers a comprehensive glimpse into the growth of catfish within biofloc ponds, which are standardized at dimensions of 1.5 meters in both diameter and height. The primary focus of this study lies in meticulously assessing water quality, facilitated by the deployment of sensors designed to measure critical parameters such as water temperature, pH levels, total dissolved solids, electrical conductivity, and turbidity. Moreover, external sensors for temperature and relative humidity are strategically positioned to capture environmental conditions within the biofloc pond accurately. Data collection is conducted at three distinct times during the day—morning, afternoon, and evening—to ensure thorough representation of daily fluctuations. The process of obtaining data on catfish growth entails a systematic approach, involving regular weighing of catfish specimens and manual calculations of both living and deceased individuals on a weekly basis. Covering a duration of 69 days and spanning 11 weeks from June 1, 2023, to August 8, 2023, the dataset encompasses observations from three separate biofloc ponds. The deliberate integration of methodologies for environmental monitoring and growth assessment forms the bedrock of this dataset, offering valuable insights into the dynamic interplay between biofloc pond conditions and catfish growth over a specific timeframe. With its potential for reuse across diverse research domains such as aquaculture, environmental science, and data-driven modeling, this dataset serves as a pivotal resource for researchers delving into the intricate relationship between biofloc pond dynamics and catfish development.
DOI: 10.17632/w5gnr5wk7f.2
title: Catfish Cultivation Biofloc Pond in Integrated Agricultural System

description: This dataset offers a comprehensive glimpse into the growth of catfish within biofloc ponds, which are standardized at dimensions of 1.5 meters in both diameter and height. The primary focus of this study lies in meticulously assessing water quality, facilitated by the deployment of sensors designed to measure critical parameters such as water temperature, pH levels, total dissolved solids, electrical conductivity, and turbidity. Moreover, external sensors for temperature and relative humidity are strategically positioned to capture environmental conditions within the biofloc pond accurately. Data collection is conducted at three distinct times during the day—morning, afternoon, and evening—to ensure thorough representation of daily fluctuations. The process of obtaining data on catfish growth entails a systematic approach, involving regular weighing of catfish specimens and manual calculations of both living and deceased individuals on a weekly basis. Covering a duration of 69 days and spanning 11 weeks from June 1, 2023, to August 8, 2023, the dataset encompasses observations from three separate biofloc ponds. The deliberate integration of methodologies for environmental monitoring and growth assessment forms the bedrock of this dataset, offering valuable insights into the dynamic interplay between biofloc pond conditions and catfish growth over a specific timeframe. With its potential for reuse across diverse research domains such as aquaculture, environmental science, and data-driven modeling, this dataset serves as a pivotal resource for researchers delving into the intricate relationship between biofloc pond dynamics and catfish development.
DOI: 10.15468/dl.pv4dps
title: Occurrence Download

description: A dataset containing 137 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schizanthus laetus Phil."
 ]
}

 The dataset includes 137 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022372-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.