cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/khv55v7gs8
title: Dataset of reclassified national economic accounts and useful exergy prices for Portugal from 1960 to 2014.

description: This dataset supports the article “An aggregate price for energy services: Useful exergy as an intermediate flow in a two-sector model of the economy” published in Ecological Economics (https://doi.org/10.1016/j.ecolecon.2025.108665). It provides a harmonized set of macroeconomic and biophysical time series for Portugal covering the period 1960–2014, constructed to implement a two-sector economic model with an extended energy sector (E-Sector) and a non-energy sector (NE-Sector).

The dataset combines reclassified national accounts with final and useful exergy balances in order to estimate consistent prices for useful exergy (energy services) treated as an intermediate input to production rather than as a primary factor. Macroeconomic variables are derived from official sources (AMECO, EUROSTAT, Banco de Portugal, EU KLEMS) and reallocated across sectors following the accounting framework described in the associated paper. These include sectoral consumption, investment, capital stocks, labor inputs, gross operating surplus, compensation of employees, taxes, trade flows, and gross value added, all expressed in nominal monetary units.

Energy and exergy variables are based on detailed national energy balances and extended exergy accounting, including primary, final, and useful exergy flows by energy carrier, economic activity, and end-use. Useful exergy estimates incorporate second-law (final-to-useful) conversion efficiencies and cover conventional energy carriers as well as food, feed for working animals, and other non-conventional sources, following established societal exergy accounting methods.

The dataset also includes derived indicators, such as aggregate final-to-useful exergy efficiency, sectoral exergy uses, intermediate payments for useful exergy, and demand-side and supply-side prices of useful exergy, enabling replication of all main quantitative results presented in the paper.

All variables are documented with clear definitions, units, and sectoral allocation rules. The dataset is intended for reuse in research on ecological and biophysical economics, energy–economy interactions, growth theory, integrated assessment modeling, and long-run energy service pricing.
DOI: 10.17632/khv55v7gs8.2
title: Dataset of reclassified national economic accounts and useful exergy prices for Portugal from 1960 to 2014.

description: This dataset supports the article “An aggregate price for energy services: Useful exergy as an intermediate flow in a two-sector model of the economy” published in Ecological Economics (https://doi.org/10.1016/j.ecolecon.2025.108665). It provides a harmonized set of macroeconomic and biophysical time series for Portugal covering the period 1960–2014, constructed to implement a two-sector economic model with an extended energy sector (E-Sector) and a non-energy sector (NE-Sector).

The dataset combines reclassified national accounts with final and useful exergy balances in order to estimate consistent prices for useful exergy (energy services) treated as an intermediate input to production rather than as a primary factor. Macroeconomic variables are derived from official sources (AMECO, EUROSTAT, Banco de Portugal, EU KLEMS) and reallocated across sectors following the accounting framework described in the associated paper. These include sectoral consumption, investment, capital stocks, labor inputs, gross operating surplus, compensation of employees, taxes, trade flows, and gross value added, all expressed in nominal monetary units.

Energy and exergy variables are based on detailed national energy balances and extended exergy accounting, including primary, final, and useful exergy flows by energy carrier, economic activity, and end-use. Useful exergy estimates incorporate second-law (final-to-useful) conversion efficiencies and cover conventional energy carriers as well as food, feed for working animals, and other non-conventional sources, following established societal exergy accounting methods.

The dataset also includes derived indicators, such as aggregate final-to-useful exergy efficiency, sectoral exergy uses, intermediate payments for useful exergy, and demand-side and supply-side prices of useful exergy, enabling replication of all main quantitative results presented in the paper.

All variables are documented with clear definitions, units, and sectoral allocation rules. The dataset is intended for reuse in research on ecological and biophysical economics, energy–economy interactions, growth theory, integrated assessment modeling, and long-run energy service pricing.
DOI: 10.25549/examiner-c44-42947
title: Baseball -- Los Angeles Dodgers, 1958

description: 9 images. Baseball -- Los Angeles Dodgers, 13 January 1958. A.E. Patterson' Walter O'Malley; Pan view of Wrigley Field seen from behind home plate in the stands; View toward left field stands; View across the diamond toward right field stands. "Sports". (Sleeve reads: SP-12288).; Caption slip reads: "Photographer: Wyman. Date: 1958-01-13. Reporter: McKinney. Assignment: Dodgers announcement, Wrigley Field. 37-38, 7-8: L - R: A.E. 'Red' Patterson (publicity dept.) & Walter O'Malley, making announcement Dodgers won't play in Pasadena".
DOI: 10.17632/9gyft37fm7
title: Genome-wide Study Identifies a Locus Associated with Atopic Dermatitis Severity in a Canine Model

description: Genotype data, phenotype data, and summary statistics for genome-wide association study aimed to identify loci associated with dermatitis severity in a colony of laboratory beagles validated as a model for atopic dermatitis. The study population included 41 dogs from the colony and six unrelated unaffected laboratory beagles as controls. The overall severity for each dog was determined by evaluating flare severity at the peak of a standardized allergen challenge using the Canine Atopic Dermatitis Extent and Severity Index (CADESI-03). Genotyping was performed using the Illumina 230K CanineHD BeadChip array. CADESI-03 scores from the 47 dogs were transformed from a scale of zero to three to a scale of one to four by adding one to each score. Excluding values of zero prevents scores from being mistaken as missing phenotypes, commonly defined by -9 or zero in Plink.
DOI: 10.25549/examiner-c44-42950
title: Baseball -- Los Angeles Dodgers, 1958

description: 9 images. Baseball -- Los Angeles Dodgers, 13 January 1958. A.E. Patterson' Walter O'Malley; Pan view of Wrigley Field seen from behind home plate in the stands; View toward left field stands; View across the diamond toward right field stands. "Sports". (Sleeve reads: SP-12288).; Caption slip reads: "Photographer: Wyman. Date: 1958-01-13. Reporter: McKinney. Assignment: Dodgers announcement, Wrigley Field. 37-38, 7-8: L - R: A.E. 'Red' Patterson (publicity dept.) & Walter O'Malley, making announcement Dodgers won't play in Pasadena".
DOI: 10.17632/9gyft37fm7.2
title: Genome-wide Study Identifies a Locus Associated with Atopic Dermatitis Severity in a Canine Model

description: Genotype data, phenotype data, and summary statistics for genome-wide association study aimed to identify loci associated with dermatitis severity in a colony of laboratory beagles validated as a model for atopic dermatitis. The study population included 41 dogs from the colony and six unrelated unaffected laboratory beagles as controls. The overall severity for each dog was determined by evaluating flare severity at the peak of a standardized allergen challenge using the Canine Atopic Dermatitis Extent and Severity Index (CADESI-03). Genotyping was performed using the Illumina 230K CanineHD BeadChip array. CADESI-03 scores from the 47 dogs were transformed from a scale of zero to three to a scale of one to four by adding one to each score. Excluding values of zero prevents scores from being mistaken as missing phenotypes, commonly defined by -9 or zero in Plink.
DOI: 10.25549/examiner-c44-42951
title: Baseball -- Los Angeles Dodgers, 1958

description: 9 images. Baseball -- Los Angeles Dodgers, 13 January 1958. A.E. Patterson' Walter O'Malley; Pan view of Wrigley Field seen from behind home plate in the stands; View toward left field stands; View across the diamond toward right field stands. "Sports". (Sleeve reads: SP-12288).; Caption slip reads: "Photographer: Wyman. Date: 1958-01-13. Reporter: McKinney. Assignment: Dodgers announcement, Wrigley Field. 37-38, 7-8: L - R: A.E. 'Red' Patterson (publicity dept.) & Walter O'Malley, making announcement Dodgers won't play in Pasadena".
DOI: 10.17632/znxmwxrbsp
title: Shelf life determination of Hypophthalmicthys molitrix ( Silver Carp )

description: This project, titled "Good and Bad Classification of Silver Carp(Hypophthalmichthys molitrix) is designed to develop an image classification system that distinguishes between healthy (good) and unhealthy (bad) Silver Carp fish (Hypophthalmichthys molitrix). The dataset consists of approximately 2000 images, evenly distributed between good and bad samples. All images were captured using a Realme 5i mobile camera, providing high-resolution visual data suitable for machine learning applications. The fish were photographed against a black background in daylight conditions to ensure consistency, clarity, and accurate feature capture.
Dataset Composition
Good Samples (Healthy)
The dataset includes approximately 1000 images of healthy Silver Carp fish. These images show fish with:
Bright, shiny, and intact scales
Clear, transparent eyes
Proper body shape without deformities
Natural coloration and smooth texture
These samples represent the positive class and help train the model to recognize healthy fish conditions.
Bad Samples (Unhealthy)
The dataset also contains approximately 1000 images of unhealthy Silver Carp fish. These fish may exhibit:
Dull or discolored scales
Cloudy or damaged eyes
Physical deformities
Visible injuries or infections
Poor overall physical condition
These images represent the negative class, enabling the model to identify unhealthy fish accurately.
Data Collection Setup
All images were captured using a Realme 5i smartphone camera, known for its reliable image quality and resolution. A black background was used intentionally to:
Enhance contrast between the fish and the background
Reduce noise and unwanted visual distractions
Highlight important visual features such as scales, eyes, and body structure
Images were taken under natural daylight conditions, ensuring consistent illumination and accurate representation of color and texture.
Image Characteristics
The dataset includes variations in:
Fish size
Body orientation
Color intensity
Health condition
This diversity improves the robustness of the machine learning model and ensures better performance in real-world scenarios.
Data Annotation
Each image is carefully labeled as either:
"Good" (Healthy)
"Bad" (Unhealthy)
These labels serve as the ground truth, allowing the machine learning model to learn the differences between healthy and unhealthy fish accurately.
DOI: 10.25549/examiner-c44-42972
title: Baseball -- Dodgers in Coliseum, 1958

description: 10 images. Baseball -- Dodgers in Coliseum, 17 January 1958. Kenneth Hahn; William S. Hughes; David Lamon; Vierling Kersey; Warren Dorn; Walter O'Malley; Don Loker; Jim Smith; Burton Chace. "Sports". (Sleeve reads: SP-12288).; Caption slip reads: "Photographer: Lapp. Date: 1958-01-17. Reporter: Davis. Assignment: Baseball & Coliseum Commission. 27-28: Dr. Vierling Kersey, City; Warren Dorn, County; Walter O'Malley; Don Loker; Kenneth Hahn, County. 23-24: Baseball Committee talk over deal drop out. Don Loker, Walter O'Malley listening to Commission. 33: Jim Smith read announcement. 16: Walter O'Malley shaking hands of Burton Chace and Kenneth Hahn. 39: L to R: William S. Hughes, President of Wagenseller & Durst, Inc. & David Lamon, representative of Blythe & Co. 40: L to R: David Lamon & William S. Hughes".
DOI: 10.17632/znxmwxrbsp.1
title: Shelf life determination of Hypophthalmicthys molitrix ( Silver Carp )

description: This project, titled "Good and Bad Classification of Silver Carp(Hypophthalmichthys molitrix) is designed to develop an image classification system that distinguishes between healthy (good) and unhealthy (bad) Silver Carp fish (Hypophthalmichthys molitrix). The dataset consists of approximately 2000 images, evenly distributed between good and bad samples. All images were captured using a Realme 5i mobile camera, providing high-resolution visual data suitable for machine learning applications. The fish were photographed against a black background in daylight conditions to ensure consistency, clarity, and accurate feature capture.
Dataset Composition
Good Samples (Healthy)
The dataset includes approximately 1000 images of healthy Silver Carp fish. These images show fish with:
Bright, shiny, and intact scales
Clear, transparent eyes
Proper body shape without deformities
Natural coloration and smooth texture
These samples represent the positive class and help train the model to recognize healthy fish conditions.
Bad Samples (Unhealthy)
The dataset also contains approximately 1000 images of unhealthy Silver Carp fish. These fish may exhibit:
Dull or discolored scales
Cloudy or damaged eyes
Physical deformities
Visible injuries or infections
Poor overall physical condition
These images represent the negative class, enabling the model to identify unhealthy fish accurately.
Data Collection Setup
All images were captured using a Realme 5i smartphone camera, known for its reliable image quality and resolution. A black background was used intentionally to:
Enhance contrast between the fish and the background
Reduce noise and unwanted visual distractions
Highlight important visual features such as scales, eyes, and body structure
Images were taken under natural daylight conditions, ensuring consistent illumination and accurate representation of color and texture.
Image Characteristics
The dataset includes variations in:
Fish size
Body orientation
Color intensity
Health condition
This diversity improves the robustness of the machine learning model and ensures better performance in real-world scenarios.
Data Annotation
Each image is carefully labeled as either:
"Good" (Healthy)
"Bad" (Unhealthy)
These labels serve as the ground truth, allowing the machine learning model to learn the differences between healthy and unhealthy fish accurately.
DOI: 10.25549/examiner-c44-42979
title: Baseball -- Dodgers press conference, 1958

description: 5 images. Baseball -- Dodgers press conference, 18 January 1958. Harold Parrott; Walter O'Malley; Fresco Thompson. "Sports". (Sleeve reads: SP-12288).; Caption slip reads: "Photographer: Monteverde. Date: 1958-01-18. Assignment: O'Malley press".
DOI: 10.5281/zenodo.18762369
title: PERSONAL INCOME LAND TAX: DIGITIZATION AND CADASTRE INTEGRATION MECHANISMS

description: This article provides a systematic analysis of the existing challenges in the calculation and payment of land tax by individuals in Uzbekistan. The relevance of the study is determined by the growing importance of land tax in the formation of local budget revenues and the need to ensure efficient and rational use of land resources.
DOI: 10.17632/9sd8mk6mfn
title: Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing

description: Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing
This repository contains the reference implementation of the framework proposed in the research article: "Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing".
Overview
Current Computational Models of Emotion (CMEs) often operate as isolated systems characterized by architectural rigidity and fixed execution cycles. This framework serves as a mediating core designed to integrate heterogeneous affective components into unified, theoretically coherent processes. By decoupling domain-specific implementations, the system employs an ontology-based semantic controller to align disparate terminologies and a dependency coordinator to enable configurable execution sequences.
Key Features
Ontology-Based Semantic Alignment: Resolves terminological inconsistencies using a formal affective ontology comprising 139 elements.
Dynamic Execution Orchestration: Employs a dependency-aware execution planner that identifies independent component groups for parallel execution while managing sequential data flow.
Machine-Readable Traceability: Enriches every affective output with formal metadata and ontological provenance, yielding a semantic trace suitable for explainability analysis.
Architectural Extensibility: Supports the modular integration of diverse third-party components (e.g., appraisal evaluation, mood dynamics, behavioral generators) without requiring structural redesigns.
Repository Contents
FRAMEWORKV7_(English).py: The main Python implementation containing the core modules (Central Executive, Semantic Controller, and Execution Coordinator).
CMEs_ontology.owl: The formal OWL ontology file containing the 139 affective elements used for semantic alignment.
Supplementary_Material_Tables.pdf: This document includes:
Table I: Comprehensive listings of affective labels and theories extracted per model (ALMA, EEGS, EMIA, FLAME, EMA).
Table II: Unified list of variability scenarios used for the semantic matching validation in Case Study 2.
DOI: 10.5281/zenodo.18762368
title: PERSONAL INCOME LAND TAX: DIGITIZATION AND CADASTRE INTEGRATION MECHANISMS

description: This article provides a systematic analysis of the existing challenges in the calculation and payment of land tax by individuals in Uzbekistan. The relevance of the study is determined by the growing importance of land tax in the formation of local budget revenues and the need to ensure efficient and rational use of land resources.
DOI: 10.17632/9sd8mk6mfn.1
title: Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing

description: Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing
This repository contains the reference implementation of the framework proposed in the research article: "Towards a Common Framework for Computational Models of Emotion: Unifying Cognitive and Emotional Processing".
Overview
Current Computational Models of Emotion (CMEs) often operate as isolated systems characterized by architectural rigidity and fixed execution cycles. This framework serves as a mediating core designed to integrate heterogeneous affective components into unified, theoretically coherent processes. By decoupling domain-specific implementations, the system employs an ontology-based semantic controller to align disparate terminologies and a dependency coordinator to enable configurable execution sequences.
Key Features
Ontology-Based Semantic Alignment: Resolves terminological inconsistencies using a formal affective ontology comprising 139 elements.
Dynamic Execution Orchestration: Employs a dependency-aware execution planner that identifies independent component groups for parallel execution while managing sequential data flow.
Machine-Readable Traceability: Enriches every affective output with formal metadata and ontological provenance, yielding a semantic trace suitable for explainability analysis.
Architectural Extensibility: Supports the modular integration of diverse third-party components (e.g., appraisal evaluation, mood dynamics, behavioral generators) without requiring structural redesigns.
Repository Contents
FRAMEWORKV7_(English).py: The main Python implementation containing the core modules (Central Executive, Semantic Controller, and Execution Coordinator).
CMEs_ontology.owl: The formal OWL ontology file containing the 139 affective elements used for semantic alignment.
Supplementary_Material_Tables.pdf: This document includes:
Table I: Comprehensive listings of affective labels and theories extracted per model (ALMA, EEGS, EMIA, FLAME, EMA).
Table II: Unified list of variability scenarios used for the semantic matching validation in Case Study 2.
DOI: 10.25549/examiner-c44-42909
title: Baseball -- Los Angeles Dodgers staff and workers, 1957

description: 4 images. Baseball -- Los Angeles Dodgers staff and workers, 24 October 1957. Al Campanis; Captain Emil Praeyer; Fresco Thompson; Buzzi Bavasi; Phyllis Masone; Jean Canova; Harold Parrott, Business Manager; Ann Sparanzo; Jeanne Grammatico. "Sports". (Sleeve reads: SP-12256).; Caption slip reads: "Photographer: Monteverde. Date: 10-24. Assignment: Los Angeles Dodgers staff at work at Wrigley".
DOI: 10.25549/examiner-c44-42727
title: Dodgers sign contract with Los Angeles, 1957

description: 5 images. Dodgers sign contract with Los Angeles, 8 October 1957. Mayor Norris Poulson; Kenneth Hahn; Rosalind Wyman; Ransom Callicott; Charles Navarro; John S. Gibson; L.E. Timberlake; James Corman; Everett Burkhalter. (Sign contract with Dodgers) all with little "Bums" hats on.
DOI: 10.17632/v2zm4k2zv9
title: TWN kinase pathway_Cell_Rep
DOI: 10.25549/examiner-c44-48555
title: Air views of Los Angeles Memorial Coliseum, 1957

description: 2 images. Air views of Los Angeles Memorial Coliseum, 7 December 1957. (UCLA -- USC 1955. Examiner photo by Samuel Sansone).
DOI: 10.17632/v2zm4k2zv9.1
title: TWN kinase pathway_Cell_Rep
DOI: 10.25549/examiner-c44-42925
title: Dodgers meeting in Pasadena, 1957

description: 4 images. Dodgers meeting in Pasadena, 17 December 1957. Seth Miller; A.R. Benedict (Resolution for Dodgers).; Caption slip reads: "Photographer: Jensen. Assignment: Dodgers meeting, Pasadena. 92-93: Seth Miller & resolution for Dodgers. 98-99: Seth Miller (Mayor); A.R. Benedict made motion of resolution".
DOI: 10.25549/examiner-c44-42929
title: Dodgers in Rose Bowl controversy (Pasadena), 1957

description: 3 images. Dodgers in Rose Bowl controversy (Pasadena), 17 December 1957. Oliver Prickett; Richard Spalding; Crowd and signs; james B. Wilcott.; Caption slip reads: "Photographer: Jensen. Assignment: Baseball. Rose Bowl hearing. J-13: Oliver Prickett represents Linda Vista Association (opposing group). J-14: Richard Spalding representing sporting groups in favor of proposition. 11-12: James B. Wilcott speaking of Pasadena Quarterbacks".
DOI: 10.25549/examiner-c44-42706
title: Baseball -- Dodgers, 1957

description: 14 images. Baseball -- Dodgers, 30 September 1952. Norbert B. Moffatt; John Holland; Jacob Cohen; Phill C. Silvers; Barney Silverstein; J.J. Rodriguez; Margaret Wheeler Hess; Tobert Mitchell; Don Allen; Burton Rawlins; Nathan G. Freeberg.; Caption slip reads: "Photographer: Lou Mack. Date: 1957-09-30. Assignment: Dodgers (City council). 27: Harold McClellan, for Dodgers. 25: Burton Rawlins, President, Downtown Business Men's Association. 26: Nathan G. Freeberg, President, Zoological Society of Los Angeles. 71: C.A. Owen, apartment house owner, against Dodgers. 72: Phill (c) Silvers, Attorney, against Dodgers here. 15: Barney Silverstein, Citizen Against Dodgers. 16: J.J. Rodriguez, Citizen Against. 19: Margaret Wheeler Hess, President, Small Property Owners, against, with lineup of other people against Dodgers who want to make speech. 8: Norbert B. Moffatt, businessman from San Fernando, For Dodgers. 7: Councilman John Holland, who wanted meeting adjourned. 3-4: Jacob Cohen shows petition to John Holland which he signed. 5: Robert Mitchell, past president, Merchants & Manufacturers Association. 6: Don Allen, former Councilman. 50/51: General view of signed Dodgers petition".