cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17927857
title: PUDL Raw EIA Form 930 -- Hourly and Daily Balancing Authority Operations Report

description: The EIA Form 930 provides hourly demand and generation statistics by balancing area (or sub-balancing area in the case of some larger areas). These statistics include a breakdown by energy source (coal, gas, hydro, wind, solar, etc.) as well as interchange between the balancing areas, including international exchanges with Canada and Mexico. Archived from 
https://www.eia.gov/electricity/gridmonitor/

This archive contains raw input data for the Public Utility Data Liberation (PUDL)
software developed by Catalyst Cooperative. It is
organized into Frictionless
Data Packages. For additional information about this data and PUDL, see the
following resources:


  
The PUDL Repository on GitHub
  
PUDL Documentation
  
Other Catalyst Cooperative data archives
DOI: 10.15468/dl.7756gv
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bolitoglossa compacta"
 ]
}

 The dataset includes 24 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064093-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17927872
title: PUDL Raw EIA Form 191 -- Monthly Underground Natural Gas Storage Report

description: The EIA Form 191, also known as the Monthly Underground Natural Gas Storage Report, describes the working and base gas in reservoirs, injections, withdrawals, and location of reservoirs by field monthly. Archived from 
https://www.eia.gov/naturalgas/ngqs/

This archive contains raw input data for the Public Utility Data Liberation (PUDL)
software developed by Catalyst Cooperative. It is
organized into Frictionless
Data Packages. For additional information about this data and PUDL, see the
following resources:


  
The PUDL Repository on GitHub
  
PUDL Documentation
  
Other Catalyst Cooperative data archives
DOI: 10.5281/zenodo.17927850
title: PUDL Raw EIA Bulk API Data

description: All data made available in bulk through the EIA Open Data API, including:



the Annual Energy Outlook, the International Energy Outlook and the Short Term Energy Outlook;

aggregate national, state, and mine-level coal production statistics, including imports and exports, reciepts of coal at electric power plants, consumption and quality, market sales, reserves, and productive capacity;

U.S. electric system operating data;

aggregate national, state, and plant-level electricity generation statistics, including fuel quality and consumption, for grid-connectedplants with nameplate capacity of 1 megawatt or greater;

CO2 emissions aggregates, CO2 emissions and carbon coefficients by fuel, state, and sector;

International Energy System (IES) data containing production, reserves, consumption, capacity, storage, imports, exports, and emissions time series by country for electricity, petroleum, natural gas, coal, nuclear, and renewable energy;

statistics of U.S. natural gas production, imports, exploration, pipelines, exports, prices, consumption, stocks, and reserves;

statistics of U.S. petroleum and other liquid fuel production, imports, refining, exports, prices, consumption, stocks, and reserves;

aggregate national, PADD, state, city, port, and refinery petroleum imports data for various grades of crude oil and country of origin;

state and national energy production and consumption, using survey and estimates to create comprehensive state energy statistics and flows;

U.S. total energy production, prices, carbon dioxide emissions, and consumption of energy from all sources by sector.


Archived from https://www.eia.gov/opendata/bulkfiles.php. The Annual Energy Outlook data is also archived separately here.

This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by Catalyst Cooperative. At present, PUDL integrates only a few specific data series related to fuel receipts and costs figures from the Bulk Electricity API. It is organized into Frictionless Data Packages. For additional information about this data and PUDL, see the following resources:



The PUDL Repository on GitHub

PUDL Documentation

Other Catalyst Cooperative data archives
DOI: 10.6084/m9.figshare.30509165.v5
title: A multi-paradigm and longitudinal EEG dataset including the “sixth-finger” and “affected-hand” motor imagery of stroke patient

description: Motor imagery-based Brain-computer Interface (MI-BCI) application in stroke rehabilitation aims to match brain activity with real-time feedback, thereby establishing closed-loop neural pathways and providing a basis for evaluating patients’ neuroplasticity changes. Thus, constructing EEG datasets under MI paradigms is crucial for optimizing MI-BCI systems and understanding the neural rehabilitation process. However, the current limitations of single MI paradigms and the lack of relevant EEG datasets may restrict the accurate interpretation and effective application in stroke rehabilitation. This study collected EEG data from 24 stroke patients during MI tasks, including a novel “sixth finger” MI and an affected-hand MI paradigm. The dataset comprehensively covers the complete longitudinal stages of stroke rehabilitation: pre-training, post-training, and follow-up periods. The data materials include: 1) raw EEG data, 2) preprocessed data, and 3) patient clinical information. Preliminary analysis using classical machine learning algorithms (CSP+SVM and CSP+LDA) demonstrated an average classification accuracy between the two MI paradigms maintained at approximately 74% ~ 76%. We anticipate this dataset will advance research on MI-BCI paradigms and neuroplasticity for stroke, and contribute to the development of high-efficiency MI-BCI systems in the field of stroke rehabilitation.
DOI: 10.3886/e241540
title: Dako College of Nursing Sciences, Suleja, 2026/2027 Admission Form/Application Form Is Out Call the Registrar (08058556110) 08058556110 (08058556110) For More Details On How To Apply And Register Online.

description: Dako College of Nursing Sciences, Suleja, 2026/2027 Admission Form/Application Form Is Out Call the Registrar (08058556110) 08058556110 (08058556110) For More Details On How To Apply And Register Online. The Management Of The School Hereby Inform The general Public On The Sales Of The General Nursing Admission Form Into The School Of Nursing, And Also The Sales Of Two (2) Years Post Basic Nursing Program. Contact The Educational Board Admin On (08058556110) For More Details On How To Purchase The Form And Register Online. REQUIREMENT FOR THE THREE YEARS GENERAL NURSING PROGRAMMES1. GENERAL NURSING PROGRAMME Admission Requirements Candidates For Admission Into The General Nursing Program Of The Nursing And Midwifery Council Of Nigeria Must Posses The Senior Secondary School Certificate Or It’s Equivalent With Five Credits To Include English Language And Either Physics, Chemistry, Biology/Health Science At Not More Than Two sittings. Duration Of Training: Three Calendar Years. Registered Nurse (RN) Also POST BASIC NURSING MIDWIFERY PROGRAMME Admission Requirements: The Candidate Must Be a Registered Nurse, Five (O,Level) Credits Not More Two Sittings And Must Also Meet All institutional Requirements. Duration of Training: Two Calendar Year.{08058556110}
DOI: 10.5281/zenodo.17927871
title: EIA STEO -- Short-Term Energy Outlook

description: The Short Term Energy Outlook is a monthly report of the U.S. Energy Information Administration with forecasts and history of energy production, consumption, and trade for electricity, petroleum, natural gas, coal, nuclear, and renewable sources. Archived from 
https://www.eia.gov/outlooks/steo/

This archive contains raw input data for the Public Utility Data Liberation (PUDL)
software developed by Catalyst Cooperative. It is
organized into Frictionless
Data Packages. For additional information about this data and PUDL, see the
following resources:


  
The PUDL Repository on GitHub
  
PUDL Documentation
  
Other Catalyst Cooperative data archives
DOI: 10.5281/zenodo.18036284
title: THE ORIGIN OF LIFE

description: This paper refutes the theory of random evolution (neo-Darwinism) as an explanation for the origin of life. I demonstrate that the irreducible complexity of the genetic code cannot be produced by stochastic processes in finite time. Applying the Pezzotti Method, I identify life not as a chemical accident, but as an "Instant Render": the immediate execution of an information package (Fractal Seed) from the Universal Database.

Introduction: The Failure of Chance

Classical science holds that order arises from chaos through trial and error. However, in a digital system, code does not write itself by shaking the hard drive.

 My theory states that life follows a "Top-Down" logic: the Source Algorithm projects a high-resolution template onto matter.

Methodology: The Seed Principle

Using P=NP logic, I demonstrate that evolution is not a slow process of accumulation, but a rapid process of "Unlocking."

Each species is a compressed file (Seed/Fractal) that already contains its entire evolutionary potential.

The equation of Life L is:

L = Download(Divine_Seed)

There is no assembly "time," only loading time (Boot).
DOI: 10.5281/zenodo.18036211
title: Extended data for 'Hydrogen and biomass-based carbon source integration for iron and steel manufacturing: A systematic review of Life Cycle Assessment studies'
DOI: 10.5281/zenodo.18036212
title: Extended data for 'Hydrogen and biomass-based carbon source integration for iron and steel manufacturing: A systematic review of Life Cycle Assessment studies'
DOI: 10.5281/zenodo.18036290
title: Synthetic datasets for Make - Single Machine Scheduling Problem / Mathematical Programming / Total Weighted Completion Time
DOI: 10.5281/zenodo.18036289
title: Synthetic datasets for Make - Single Machine Scheduling Problem / Mathematical Programming / Total Weighted Completion Time
DOI: 10.15468/dl.2qjmaw
title: Occurrence Download

description: A dataset containing 62659 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "DatasetKey is Fungal Records Database of Britain and Ireland",
 "Geometry POLYGON((-7.28443 51.67425,-3.92725 48.52885,3.53636 51.67425,3.53636 56.17549,-7.28443 56.17549,-7.28443 51.67425))",
 "HasGeospatialIssue is false",
 "Month is October",
 "TaxonKey is Basidiomycota",
 "Year 2000-2025"
 ]
}

 The dataset includes 62659 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064090-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18036231
title: Synthetic datasets for Deliver - Multiple Traveling Salesman Problem / Mathematical Programming / Miller–Tucker–Zemlin Model
DOI: 10.5281/zenodo.18036232
title: Synthetic datasets for Deliver - Multiple Traveling Salesman Problem / Mathematical Programming / Miller–Tucker–Zemlin Model
DOI: 10.15468/dl.9ks2yq
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.19649 41.22494,13.72972 41.23206,13.72423 41.51365,13.1887 41.50646,13.19649 41.22494))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Myocastor coypus",
 "Year 1990-2025"
 ]
}

 The dataset includes 10 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064094-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18036235
title: A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption

description: Zenodo Repository Metadata and Description

Title: Supplemental Material for "A Systematic Literature Review on Machine Learning Techniques for Predicting Household Water Consumption"

Description

This repository contains the dataset and methodological artifacts developed for a Systematic Literature Review (SLR) investigating Machine Learning (ML) applications in residential water demand forecasting. The review synthesizes evidence from 80 primary studies published between 2009 and 2024, following the PRISMA-2020 guidelines.

Repository Contents





DataExtraction.csv: The master evidence matrix containing metadata, objectives, and findings for all 80 primary studies.




Taxonomy Maps: Standardized mapping files that document how raw textual terms from the literature were normalized into canonical categories.




Supplementary Material: The file provides detailed methodological documentation and extended analyses that support the results reported in the main manuscript, while preserving conciseness in the primary text.

The supplementary material includes:





A detailed methodological workflow and execution timeline, describing the implementation of the seven-step SLR protocol in accordance with PRISMA guidelines, including database search, screening, quality assessment, data consolidation, and analysis.




A complete list of the 80 primary studies analyzed in the review, including publication type and reference identifiers.




An extended characterization of machine learning model properties (RQ1), documenting the conceptual taxonomy used to classify model capabilities and methodological features across studies.




A qualitative synthesis of reported benefits associated with evaluation metrics (RQ3), complementing the quantitative results presented in the main article.




A citation-based contextual analysis, including total citations and citations per year (CPY), stratified by model families, to identify influential studies and thematic trends within the literature.



All quantitative mappings, cross-references, and classifications described in this document are aligned with the evidence matrix made publicly available alongside this repository. This supplementary file is intended to enhance transparency, reproducibility, and methodological rigor for researchers interested in machine-learning-based residential water demand forecasting.



Key Research Insights





Methodological Evolution: A capability shift around 2020 where Deep Learning models (notably LSTM) displaced traditional methods.




Predictor Patterns: Climatic and historical consumption dominate, with limited use of socio-economic variables due to privacy constraints.




Evaluation Standards: RMSE and MAE are the most widely used evaluation metrics.



Practical Tools for Researchers





Model-Predictor Crosswalk: A co-occurrence matrix of model families and predictor categories.




Prescriptive Decision Tree: A heuristic framework guiding model selection based on data and computational constraints.
DOI: 10.5281/zenodo.18036288
title: INTEGRATED MANAGEMENT MODEL FOR ENSURING BORDER SECURITY
DOI: 10.5281/zenodo.18036287
title: INTEGRATED MANAGEMENT MODEL FOR ENSURING BORDER SECURITY
DOI: 10.15468/dl.9k4fvx
title: Occurrence Download

description: A dataset containing 62659 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "DatasetKey is Fungal Records Database of Britain and Ireland",
 "Geometry POLYGON((-7.28443 51.67425,-3.92725 48.52885,3.53636 51.67425,3.53636 56.17549,-7.28443 56.17549,-7.28443 51.67425))",
 "HasGeospatialIssue is false",
 "Month is October",
 "TaxonKey is Basidiomycota",
 "Year 2000-2025"
 ]
}

 The dataset includes 62659 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064091-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17927855
title: EPA MATS -- Mercury and Air Toxics Standards

description: The EPA Mercury and Air Toxics Standards (MATS) dataset provides detailed information on emissions of hazardous air pollutants, specifically mercury and other toxic substances, from power plants in the United States. Established by the U.S. Environmental Protection Agency (EPA) under the Clean Air Act, MATS aims to reduce air pollution and its associated health risks by setting limits on the emissions of mercury, arsenic, acid gases, and other pollutants from coal- and oil-fired power plants. The dataset typically includes metrics such as emission levels, compliance testing results, facility locations, and operational data. It serves as a critical resource for policymakers, researchers, and environmental organizations to assess the effectiveness of pollution control measures, monitor compliance, and evaluate the environmental and public health impacts of power plant emissions. Archived from 
https://www.epa.gov/stationary-sources-air-pollution/mercury-and-air-toxics-standards

This archive contains raw input data for the Public Utility Data Liberation (PUDL)
software developed by Catalyst Cooperative. It is
organized into Frictionless
Data Packages. For additional information about this data and PUDL, see the
following resources:


  
The PUDL Repository on GitHub
  
PUDL Documentation
  
Other Catalyst Cooperative data archives
DOI: 10.6084/m9.figshare.29945330
title: Supplementary data for Blais et al. 2025. "Insights into the thermal ecology, physiology, and behavior of a threatened ectothermic specialist from a warming and drying ecoregion." Biology Open. https://doi.org/10.1242/bio.062264

description: Supplementary information for "Insights into the thermal ecology, physiology, and behavior of a threatened ectothermic specialist from a warming and drying ecoregion." Attached files include 1) data as a .xlsx spreadsheet ("Dataset 1") with a key and two dataframes as tabs (these can be converted to .csv); and 2) R code ("code_THRU-thermal-ecology") for analysis of two dataframes.
DOI: 10.6084/m9.figshare.29945330.v1
title: Supplementary data for Blais et al. 2025. "Insights into the thermal ecology, physiology, and behavior of a threatened ectothermic specialist from a warming and drying ecoregion." Biology Open. https://doi.org/10.1242/bio.062264

description: Supplementary information for "Insights into the thermal ecology, physiology, and behavior of a threatened ectothermic specialist from a warming and drying ecoregion." Attached files include 1) data as a .xlsx spreadsheet ("Dataset 1") with a key and two dataframes as tabs (these can be converted to .csv); and 2) R code ("code_THRU-thermal-ecology") for analysis of two dataframes.
DOI: 10.3886/e241540v1
title: Dako College of Nursing Sciences, Suleja, 2026/2027 Admission Form/Application Form Is Out Call the Registrar (08058556110) 08058556110 (08058556110) For More Details On How To Apply And Register Online.

description: Dako College of Nursing Sciences, Suleja, 2026/2027 Admission Form/Application Form Is Out Call the Registrar (08058556110) 08058556110 (08058556110) For More Details On How To Apply And Register Online. The Management Of The School Hereby Inform The general Public On The Sales Of The General Nursing Admission Form Into The School Of Nursing, And Also The Sales Of Two (2) Years Post Basic Nursing Program. Contact The Educational Board Admin On (08058556110) For More Details On How To Purchase The Form And Register Online. REQUIREMENT FOR THE THREE YEARS GENERAL NURSING PROGRAMMES1. GENERAL NURSING PROGRAMME Admission Requirements Candidates For Admission Into The General Nursing Program Of The Nursing And Midwifery Council Of Nigeria Must Posses The Senior Secondary School Certificate Or It’s Equivalent With Five Credits To Include English Language And Either Physics, Chemistry, Biology/Health Science At Not More Than Two sittings. Duration Of Training: Three Calendar Years. Registered Nurse (RN) Also POST BASIC NURSING MIDWIFERY PROGRAMME Admission Requirements: The Candidate Must Be a Registered Nurse, Five (O,Level) Credits Not More Two Sittings And Must Also Meet All institutional Requirements. Duration of Training: Two Calendar Year.{08058556110}
DOI: 10.5281/zenodo.17927853
title: PUDL Raw Mine Safety and Health Administration (MSHA) Mines

description: The Mine dataset lists all Coal and Metal/Non-Metal mines under MSHA's jurisdiction. It includes such information as the current status of each mine (Active, Abandoned, NonProducing, etc.), the current owner and operating company, commodity codes and physical attributes of the mine. Archived from 
https://arlweb.msha.gov/OpenGovernmentData/OGIMSHA.asp

This archive contains raw input data for the Public Utility Data Liberation (PUDL)
software developed by Catalyst Cooperative. It is
organized into Frictionless
Data Packages. For additional information about this data and PUDL, see the
following resources:


  
The PUDL Repository on GitHub
  
PUDL Documentation
  
Other Catalyst Cooperative data archives
DOI: 10.34770/m5g3-nf94
title: Data for 'Soil texture regulates bacterial motility and chemotactic recruitment to plant roots'

description: Imaging data underscoring all the figures and findings of the article
 titled 'Soil texture regulates bacterial motility and chemotactic
 recruitment to plant roots' by Al Harraq, Choi, Datta, and Shaevitz.
DOI: 10.34740/kaggle/dsv/14270766
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.5281/zenodo.18036321
title: THE ORIGIN OF LIFE

description: This paper refutes the theory of random evolution (neo-Darwinism) as an explanation for the origin of life. I demonstrate that the irreducible complexity of the genetic code cannot be produced by stochastic processes in finite time. Applying the Pezzotti Method, I identify life not as a chemical accident, but as an "Instant Render": the immediate execution of an information package (Fractal Seed) from the Universal Database.

Introduction: The Failure of Chance

Classical science holds that order arises from chaos through trial and error. However, in a digital system, code does not write itself by shaking the hard drive.

 My theory states that life follows a "Top-Down" logic: the Source Algorithm projects a high-resolution template onto matter.

Methodology: The Seed Principle

Using P=NP logic, I demonstrate that evolution is not a slow process of accumulation, but a rapid process of "Unlocking."

Each species is a compressed file (Seed/Fractal) that already contains its entire evolutionary potential.

The equation of Life L is:

L = Download(Divine_Seed)

There is no assembly "time," only loading time (Boot).
DOI: 10.5281/zenodo.18036283
title: THE ORIGIN OF LIFE

description: This paper refutes the theory of random evolution (neo-Darwinism) as an explanation for the origin of life. I demonstrate that the irreducible complexity of the genetic code cannot be produced by stochastic processes in finite time. Applying the Pezzotti Method, I identify life not as a chemical accident, but as an "Instant Render": the immediate execution of an information package (Fractal Seed) from the Universal Database.

Introduction: The Failure of Chance

Classical science holds that order arises from chaos through trial and error. However, in a digital system, code does not write itself by shaking the hard drive.

 My theory states that life follows a "Top-Down" logic: the Source Algorithm projects a high-resolution template onto matter.

Methodology: The Seed Principle

Using P=NP logic, I demonstrate that evolution is not a slow process of accumulation, but a rapid process of "Unlocking."

Each species is a compressed file (Seed/Fractal) that already contains its entire evolutionary potential.

The equation of Life L is:

L = Download(Divine_Seed)

There is no assembly "time," only loading time (Boot).