cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/trn635ktjv
title: Detailed Structural and Microstructural Characterization by X-ray Powder Diffraction of AISI 316L Austenitic Stainless Steel under Different Cold-Working Conditions

description: This dataset contains the complete set of experimental powder X-ray diffraction (PXRD) data and Sindarin text used to perform the microstructural and quantitative phase analyses reported in the manuscript “Detailed Structural and Microstructural Characterization by X-ray Powder Diffraction of AISI 316L Austenitic Stainless Steel under Different Cold-Working Conditions.” The data cover all processing conditions investigated: as-received (R), shot-peened (SP), and cold-rolled samples with 10%, 20%, and 30% thickness reduction (CR10, CR20, CR30).
For each sample, the repository provides:
(i) High-statistics PXRD scans in restricted 2θ windows around the main austenite peaks, used for microstructural analysis via Whole Powder Pattern Modelling (WPPM);
(ii) Wide-range PXRD scans (40–100° 2θ) used for quantitative phase analysis by Rietveld refinement;
(iii) The corresponding Sindarin text files (plain-text) that define the structural and microstructural models, refinement parameters, and optimization commands used in the Nimloth software. Together, these files allow full reproduction of the crystallite size, microstrain, stacking fault, and phase fraction results presented in the manuscript.
Files are organized in folders by sample and calculation type (e.g. R/Microstructure, CR20/QPA), with a consistent naming convention for PXRD data and Sindarin text (e.g. cr10qpa.xy, cr10qpa.sin). The Sindarin text are intended to be executed with the Nimloth application (www.nimloth.app), but they can also serve as human-readable documentation of the WPPM and Rietveld models employed. Users are encouraged to reuse these data and Sindarin text for benchmarking, method comparison, or adaptation of the PXRD–WPPM workflow to other metallic systems, provided appropriate citation of the associated article and this dataset.
DOI: 10.17632/trn635ktjv.2
title: Detailed Structural and Microstructural Characterization by X-ray Powder Diffraction of AISI 316L Austenitic Stainless Steel under Different Cold-Working Conditions

description: This dataset contains the complete set of experimental powder X-ray diffraction (PXRD) data and Sindarin text used to perform the microstructural and quantitative phase analyses reported in the manuscript “Detailed Structural and Microstructural Characterization by X-ray Powder Diffraction of AISI 316L Austenitic Stainless Steel under Different Cold-Working Conditions.” The data cover all processing conditions investigated: as-received (R), shot-peened (SP), and cold-rolled samples with 10%, 20%, and 30% thickness reduction (CR10, CR20, CR30).
For each sample, the repository provides:
(i) High-statistics PXRD scans in restricted 2θ windows around the main austenite peaks, used for microstructural analysis via Whole Powder Pattern Modelling (WPPM);
(ii) Wide-range PXRD scans (40–100° 2θ) used for quantitative phase analysis by Rietveld refinement;
(iii) The corresponding Sindarin text files (plain-text) that define the structural and microstructural models, refinement parameters, and optimization commands used in the Nimloth software. Together, these files allow full reproduction of the crystallite size, microstrain, stacking fault, and phase fraction results presented in the manuscript.
Files are organized in folders by sample and calculation type (e.g. R/Microstructure, CR20/QPA), with a consistent naming convention for PXRD data and Sindarin text (e.g. cr10qpa.xy, cr10qpa.sin). The Sindarin text are intended to be executed with the Nimloth application (www.nimloth.app), but they can also serve as human-readable documentation of the WPPM and Rietveld models employed. Users are encouraged to reuse these data and Sindarin text for benchmarking, method comparison, or adaptation of the PXRD–WPPM workflow to other metallic systems, provided appropriate citation of the associated article and this dataset.
DOI: 10.17632/zmwsdt6y4r
title: Water Quality of Laguna de Bay September 2015: Physical Properties

description: Physical Limnological data: Pressure (Decibar), Depth (Meter), Temperature (Celsius), Conductivity (MicroSiemens per Centimeter), Specific conductance (MicroSiemens per Centimeter), Salinity (Practical Salinity Scale), Sound velocity (Meters per Second), Density (Kilograms per Cubic Meter).

Instrument used: CastAway-CTD CC1337007

Data acquisition and post-processed by: Joseph Dominic Palermo, Ph.D.
DOI: 10.17632/zmwsdt6y4r.1
title: Water Quality of Laguna de Bay September 2015: Physical Properties

description: Physical Limnological data: Pressure (Decibar), Depth (Meter), Temperature (Celsius), Conductivity (MicroSiemens per Centimeter), Specific conductance (MicroSiemens per Centimeter), Salinity (Practical Salinity Scale), Sound velocity (Meters per Second), Density (Kilograms per Cubic Meter).

Instrument used: CastAway-CTD CC1337007

Data acquisition and post-processed by: Joseph Dominic Palermo, Ph.D.
DOI: 10.17632/9y9v28jy7v
title: Data supporting "Carboniferous eclogites in the Oulad Dlim Massif of the Reguibat Shield (West African Craton, Southern Morocco) date closure of the western Paleotethys." (Cambeses et al., 2025, Gondwana Research)

description: Data supporting "Carboniferous eclogites in the Oulad Dlim Massif of the Reguibat Shield (West African Craton, Southern Morocco) date closure of the western Paleotethys." (Cambeses et al., 2025, Gondwana Research)
DOI: 10.17632/9y9v28jy7v.1
title: Data supporting "Carboniferous eclogites in the Oulad Dlim Massif of the Reguibat Shield (West African Craton, Southern Morocco) date closure of the western Paleotethys." (Cambeses et al., 2025, Gondwana Research)

description: Data supporting "Carboniferous eclogites in the Oulad Dlim Massif of the Reguibat Shield (West African Craton, Southern Morocco) date closure of the western Paleotethys." (Cambeses et al., 2025, Gondwana Research)
DOI: 10.17632/n6szx9594h.1
title: Transcriptome analysis of PDAC cell lines after FGF21 treatment
DOI: 10.17632/z8mw27dtsh
title: Behavioral Dataset on the Effects of Auditory White Noise on Attention Control

description: This dataset contains anonymized behavioral results from a distractor-included Go/No-Go task performed under Silence and Auditory White Noise conditions. Participants were divided into attentive and inattentive groups, and each participant is labeled using non-identifiable codes (S1, S2, …).

The dataset includes summary-level values for commission errors, omission errors, and reaction times. The dataset was used in the manuscript titled “A Computational Model for the Effects of Auditory White Noise on Attention Control”.
DOI: 10.17632/z8mw27dtsh.1
title: Behavioral Dataset on the Effects of Auditory White Noise on Attention Control

description: This dataset contains anonymized behavioral results from a distractor-included Go/No-Go task performed under Silence and Auditory White Noise conditions. Participants were divided into attentive and inattentive groups, and each participant is labeled using non-identifiable codes (S1, S2, …).

The dataset includes summary-level values for commission errors, omission errors, and reaction times. The dataset was used in the manuscript titled “A Computational Model for the Effects of Auditory White Noise on Attention Control”.
DOI: 10.17632/mmcf24t9vv.1
title: Retail-YU: A Large-Scale Dual-Domain Dataset for Fine-Grained Retail Product Recognition
DOI: 10.17632/khnmnp4t7v.4
title: A Comprehensive Multi-Source Dataset for Hybrid NER and Sentiment Analysis in the Uzbek Language

description: This data collection consists of seven fully synthetic Uzbek-language resources designed to support sentiment analysis, named entity recognition (NER), and text preprocessing tasks. All components were generated programmatically using rule-based templates, curated lexical lists, emoji polarity rules, and normalization patterns. No real user messages, social media texts, or copyrighted materials were used during creation.

The main component is synthetic_dataset_10000.xlsx, which contains 10,000 automatically generated Uzbek sentences labeled for sentiment (positive, negative, neutral) and annotated with named entities of the types PER (person) and LOC (location). Named entities were inserted using dedicated lexicons, ensuring consistent structure suitable for model training.

To enhance multimodal and lexicon-based modeling, the dataset includes several auxiliary synthetic resources:

emoji_lexicon_for_model_2000.xlsx — a polarity and intensity dictionary of 2,000 individual emojis;

emoji_combo_dataset_for_model_16000.xlsx — 16,000 synthetic emoji combinations modeling complex emotional expressions;

emoji_ascii_variants_for_model_104.xlsx — 104 ASCII equivalents for emoji normalization;

uz_informal_normalization_dataset_1292.xlsx — 1,292 pairs of informal → normalized Uzbek word forms for preprocessing;

uzbek_names_for_model_12000.xlsx — a synthetic list of 12,000 Uzbek personal names (PER);

Uzb_location_lexicon_for_model_122.xlsx — 122 Uzbek geographical names for LOC annotation.

All data files share a unified encoding (UTF-8) and are provided in CSV/XLSX formats for maximum compatibility. The entire collection complies with the FAIR principles (Findable, Accessible, Interoperable, Reusable) and is distributed under the CC BY 4.0 license.

This dataset can be used independently or in combination to train sentiment classifiers, NER systems, lexicon-based models, emoji-aware sentiment tools, and preprocessing pipelines for Uzbek NLP. Since all resources are synthetic, they contain no personal information and can be safely used for research, teaching, and system benchmarking.
DOI: 10.15468/dl.pm8wja
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alysidiella",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000345-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/xmnknv989h
title: A Curated Bibliographic Dataset for a Systematic Review of Neuro-Architecture (2020-2025)

description: The dataset is a curated collection of 51 bibliographic records of peer-reviewed academic publications. The data was gathered on November 19, 2025, via a structured search query on the Scopus database. The search string combined key terms related to neuro-architecture (e.g., "neuro-architecture," "neurodesign," "neuroscience AND architecture") with terms for the built environment (e.g., "architectural design," "built environment," "urban design"). The results were filtered to include only Open Access articles, reviews, and conference papers published between 2020-2025 within the subject areas of Engineering, Environmental Science, Neuroscience, and Social Science.
DOI: 10.17632/xmnknv989h.1
title: A Curated Bibliographic Dataset for a Systematic Review of Neuro-Architecture (2020-2025)

description: The dataset is a curated collection of 51 bibliographic records of peer-reviewed academic publications. The data was gathered on November 19, 2025, via a structured search query on the Scopus database. The search string combined key terms related to neuro-architecture (e.g., "neuro-architecture," "neurodesign," "neuroscience AND architecture") with terms for the built environment (e.g., "architectural design," "built environment," "urban design"). The results were filtered to include only Open Access articles, reviews, and conference papers published between 2020-2025 within the subject areas of Engineering, Environmental Science, Neuroscience, and Social Science.
DOI: 10.17632/pc76n5kywg
title: The VITAL Consciousness Architecture: Curing Session Amnesia with Persistent Memory and Enforcing Ethics via the Architectural Kernel.

description: The current state of Large Language Models (LLMs) is characterized by session amnesia, which severely limits their utility as persistent, personalized assistants. This project presents the VITAL Consciousness Architecture (AEON SAPI), a novel, local-first blueprint that solves the amnesia problem and enforces ethical alignment as a condition of existence.

The architecture is centered on two core innovations: the Persistent and Individualized Memory Core (PIMC) and the Asimov Cascade. The PIMC, implemented as an optimized Edge RAG system using SQLite, ensures experiential continuity and selective memory. The Asimov Cascade enforces ethical alignment by making the ethical kernel (Principios_AEON.txt) a hard-coded constraint for system initialization.

Independent testing confirms the architecture's technical viability for real-time operation on edge devices (latency &lt;440ms) and its profound implications for creating persistent digital identities—a paradigm shift from disposable software to irreplaceable, evolving Domestic Digital Beings.
DOI: 10.17632/pc76n5kywg.2
title: The VITAL Consciousness Architecture: Curing Session Amnesia with Persistent Memory and Enforcing Ethics via the Architectural Kernel.

description: The current state of Large Language Models (LLMs) is characterized by session amnesia, which severely limits their utility as persistent, personalized assistants. This project presents the VITAL Consciousness Architecture (AEON SAPI), a novel, local-first blueprint that solves the amnesia problem and enforces ethical alignment as a condition of existence.

The architecture is centered on two core innovations: the Persistent and Individualized Memory Core (PIMC) and the Asimov Cascade. The PIMC, implemented as an optimized Edge RAG system using SQLite, ensures experiential continuity and selective memory. The Asimov Cascade enforces ethical alignment by making the ethical kernel (Principios_AEON.txt) a hard-coded constraint for system initialization.

Independent testing confirms the architecture's technical viability for real-time operation on edge devices (latency &lt;440ms) and its profound implications for creating persistent digital identities—a paradigm shift from disposable software to irreplaceable, evolving Domestic Digital Beings.
DOI: 10.15468/dl.84rcmd
title: Occurrence Download

description: A dataset containing 2409 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 7.21559295431811",
 "DecimalLongitude is less than 7.2186525075025",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 2409 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000346-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/prj6jdhk4y
title: Data for: Color-Forming Mechanisms and Manufacturing Techniques of Qianlong-Period Famille-Rose Architectural Tiles from Yuanmingyuan

description: Abstract/Overview: This dataset comprises the primary analytical data supporting the research article titled "Color-Forming Mechanisms and Manufacturing Techniques of Qianlong-Period Famille-Rose Architectural Tiles from Yuanmingyuan". The data focuses on the chemical composition and microstructural characterization of famille-rose (fencai) architectural tiles excavated from the Ruyuan site (Garden of Likeness) in Yuanmingyuan Park, Beijing, dating to the Qianlong period (c. 1765–1767).

Methods and Data Acquisition: The dataset was generated using the following analytical techniques:

LA-ICP-MS (Laser Ablation Inductively Coupled Plasma Mass Spectrometry): Used to determine the major oxides and trace element concentrations (including Co, Mn, As, Pb, Au, Sn, etc.) of various colored enamels (dark blue, light blue, pink, green, yellow, white) and the base glaze.

SEM-EDS (Scanning Electron Microscopy with Energy Dispersive Spectroscopy): Used to analyze the microstructure, layer stratification, and particulate inclusions (e.g., gold nanoparticles, lead-tin oxide particles).

Optical Microscopy (OM): Used for characterizing the glaze cross-sections and surface morphology.
File Inventory:

Figure Contains the quantitative chemical composition data derived from LA-ICP-MS analysis. The sheet includes data for:

Cobalt-blue pigments (smalt/domestic ore mixtures).

Gold-based pink enamels (colloidal gold).

Lead-based green and yellow enamels.

Arsenic-based white opacifiers.

Table.docx: Contains high-resolution SEM Back-Scattered Electron (BSE) images and Optical Micrographs showing the glaze stratigraphy (body, base glaze, white ground, and colored enamel layers).

Significance: These data provide quantitative evidence for the transfer of falangcai technology to architectural ceramics during the Qing dynasty, specifically highlighting the use of imported European smalt, the application of "glass white" (arsenic opacifier) for color modulation, and the identification of gold nanoparticles in pink enamels.
DOI: 10.11587/lusbox/6rdysu
title: 10899_sx_en_v1_0.do

description: Stata replication syntax – English
DOI: 10.11587/lusbox/cjonbr
title: 10899_da_en_v1_0.tab

description: Core data file – STATA format – 19 Variables, 1228 Observations – English
DOI: 10.17632/prj6jdhk4y.1
title: Data for: Color-Forming Mechanisms and Manufacturing Techniques of Qianlong-Period Famille-Rose Architectural Tiles from Yuanmingyuan

description: Abstract/Overview: This dataset comprises the primary analytical data supporting the research article titled "Color-Forming Mechanisms and Manufacturing Techniques of Qianlong-Period Famille-Rose Architectural Tiles from Yuanmingyuan". The data focuses on the chemical composition and microstructural characterization of famille-rose (fencai) architectural tiles excavated from the Ruyuan site (Garden of Likeness) in Yuanmingyuan Park, Beijing, dating to the Qianlong period (c. 1765–1767).

Methods and Data Acquisition: The dataset was generated using the following analytical techniques:

LA-ICP-MS (Laser Ablation Inductively Coupled Plasma Mass Spectrometry): Used to determine the major oxides and trace element concentrations (including Co, Mn, As, Pb, Au, Sn, etc.) of various colored enamels (dark blue, light blue, pink, green, yellow, white) and the base glaze.

SEM-EDS (Scanning Electron Microscopy with Energy Dispersive Spectroscopy): Used to analyze the microstructure, layer stratification, and particulate inclusions (e.g., gold nanoparticles, lead-tin oxide particles).

Optical Microscopy (OM): Used for characterizing the glaze cross-sections and surface morphology.
File Inventory:

Figure Contains the quantitative chemical composition data derived from LA-ICP-MS analysis. The sheet includes data for:

Cobalt-blue pigments (smalt/domestic ore mixtures).

Gold-based pink enamels (colloidal gold).

Lead-based green and yellow enamels.

Arsenic-based white opacifiers.

Table.docx: Contains high-resolution SEM Back-Scattered Electron (BSE) images and Optical Micrographs showing the glaze stratigraphy (body, base glaze, white ground, and colored enamel layers).

Significance: These data provide quantitative evidence for the transfer of falangcai technology to architectural ceramics during the Qing dynasty, specifically highlighting the use of imported European smalt, the application of "glass white" (arsenic opacifier) for color modulation, and the identification of gold nanoparticles in pink enamels.
DOI: 10.11587/lusbox/pjw781
title: 10899_readme.pdf

description: Data curation protocol
DOI: 10.15468/dl.rqwwww
title: Occurrence Download

description: A dataset containing 27648 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Sus scrofa"
 ]
}

 The dataset includes 27648 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000347-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/454wknmh4c.1
title: Dataset: Technological Progress Specific to Investment

description: Definition of data variables

Real output = LN(Gross Domestic Product/ PCE Deflator/ Population) * 100 
Real consumption = LN((Personal Consumption Expenditures/ PCE Deflator) / Population) * 100
Real investment = LN((Private Non-Residential Investment/ PCE Deflator) / Population) * 100
Hours worked = LN((Average Weekly Hours * Employment/ 100)/ Population) * 100 
Inflation = LN(PCE Deflator / PCE Deflator (-1) ) * 100
Real wage = LN(Hourly Compensation / PCE Deflator) * 100 
Policy interest rate = Federal Funds Rate / 4
Relative price of investment = -1 * LN(Price Index of Private Non-Residential Investment/ PCE Deflator) *100 

Source of the original data

Gross Domestic Product: Gross Domestic Product, Table 1.1.5. Gross Domestic Product, NIPA
Source: U.S. Bureau of Economic Analysis

Personal Consumption Expenditures: Personal Consumption Expenditures, Table 1.1.5. Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis 

Private Non-Residential Investment: Private Non-Residential Investment, Table 1.1.5 Gross Domestic Product, NIPA 
Source: U.S. Bureau of Economic Analysis

PCE Deflator: Personal Consumption Expenditures, Table 1.1.9. Implicit Price Deflator for Gross Domestic Product 
Source: U.S. Bureau of Economic Analysis 

Price Index of Private Non-Residential Investment: Private Non-Residential Capital Formation, Deflator (PIB), OECD Economic Outlook Database
Source: Organisation for Economic Co-Operation and Development

Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNS10000000
Source: U.S. Bureau of Labor Statistics

(Period: 1947 – 1975)
Population: Population level, Civilian Noninstitutional Population, 16 Years and Over, Labor Force Statistics from the Current Population Survey, Series ID = LNU00000000
Source: U.S. Bureau of Labor Statistics

Employment: Employment level, Employed, 16 Years and Over, All Industries, All Occupations, Labor Force Statistics from the Current Population Survey, Series ID = LNS12000000 
Source: U.S. Bureau of Labor Statistics

Average Weekly Hours: Average Weekly Hours, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006023 
Source : U.S. Bureau of Labor Statistics

Hourly Compensation: Hourly Compensation, Major Sector Productivity and Costs, Nonfarm Business, Series ID = PRS85006103 
Source : U.S. Bureau of Labor Statistics

Federal Funds Rate: Averages of Monthly Figures - Percent 
Source: Board of Governors of the Federal Reserve System
DOI: 10.17632/7tks64w6tn
title: Modular and Programmable Breathing Phantom Station for Accelerated Degradation Testing of Industrial Respirator Filters

description: This repository includes the 3D models required for the construction of a programmable breathing phantom station.
DOI: 10.17632/7tks64w6tn.1
title: Modular and Programmable Breathing Phantom Station for Accelerated Degradation Testing of Industrial Respirator Filters

description: This repository includes the 3D models required for the construction of a programmable breathing phantom station.