cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.31125479
title: Squintability and Other Metrics for Assessing Projection Pursuit Indexes, and Guiding Optimization Choices

description: The projection pursuit (PP) guided tour optimizes a criterion function, known as the PP index, to gradually reveal projections of interest from high-dimensional data through animation. Optimization of some PP indexes can be non-trivial, if they are non-smooth functions, or when the optimum has a small “squint angle”, detectable only from close proximity. Here, measures for calculating the smoothness and squintability properties of the PP index are defined. These are used to investigate the performance of a recently introduced swarm-based algorithm, Jellyfish Search Optimizer (JSO), for optimizing PP indexes. The performance of JSO in detecting the target pattern (pipe shape) is compared with existing optimizers in PP. Additionally, JSO’s performance on detecting the sine-wave shape is evaluated using different PP indexes (hence different smoothness and squintability) across various data dimensions (d = 4, 6, 8, 10, 12) and JSO hyper-parameters. We observe empirically that higher squintability improves the success rate of the PP index optimization, while smoothness has no significant effect. The JSO algorithm has been implemented in the R package, tourr, and functions to calculate smoothness and squintability measures are implemented in the ferrn package.
DOI: 10.6084/m9.figshare.31125479.v1
title: Squintability and Other Metrics for Assessing Projection Pursuit Indexes, and Guiding Optimization Choices

description: The projection pursuit (PP) guided tour optimizes a criterion function, known as the PP index, to gradually reveal projections of interest from high-dimensional data through animation. Optimization of some PP indexes can be non-trivial, if they are non-smooth functions, or when the optimum has a small “squint angle”, detectable only from close proximity. Here, measures for calculating the smoothness and squintability properties of the PP index are defined. These are used to investigate the performance of a recently introduced swarm-based algorithm, Jellyfish Search Optimizer (JSO), for optimizing PP indexes. The performance of JSO in detecting the target pattern (pipe shape) is compared with existing optimizers in PP. Additionally, JSO’s performance on detecting the sine-wave shape is evaluated using different PP indexes (hence different smoothness and squintability) across various data dimensions (d = 4, 6, 8, 10, 12) and JSO hyper-parameters. We observe empirically that higher squintability improves the success rate of the PP index optimization, while smoothness has no significant effect. The JSO algorithm has been implemented in the R package, tourr, and functions to calculate smoothness and squintability measures are implemented in the ferrn package.
DOI: 10.15468/dl.swemq9
title: Occurrence Download

description: A dataset containing 6873 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-37.3296229189314 32.4392704459637, -18.8578240979978 32.4392704459637, -18.8578240979978 43.6656174814093, -37.3296229189314 43.6656174814093, -37.3296229189314 32.4392704459637))",
 "TaxonKey is one of (Balaenoptera physalus)",
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 }
 ]
}

 The dataset includes 6873 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004887-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18338683
title: Supplementary Package - Socratic User Study & Tool

description: This is the data analysis done for the paper titled "Socratic LLM Framework (Extended Abstract): Fostering Critical Thinking in Software Engineering Students" (submitted to FSE - Software Engineering Education track). 

 

Abstract -- Large language models continue to attract the attention of the software industry due to their potential to boost developers' productivity. However, this focus often sidelines the development of critical thinking skills, which are essential for novice developers. In university settings, educators seek to understand how to make students properly engage with these tools, mitigating the impact on their skills' growth. Our goal is to develop a tool that stimulates novice software developers to think critically rather than simply copying and pasting code. We propose the Socratic LLM framework focused on code generation, code explanation, and debugging. Our framework and system are designed to benefit novice developers and SE educators by primarily encouraging critical thinking and independent problem-solving, as well as providing personalised guidance to students.

 

This repository contains:



Qualtrics surveys: pre_task_survey.pdf and post_task_survey.pdf

Task instruction: User Study Instructions.pdf

Socratic LLM tool User interface: UI_dashboard.png UI_chatbox.png

Socratic LLM Tool (Code): SocraticLLM.zip
DOI: 10.5281/zenodo.18338684
title: Supplementary Package - Socratic User Study & Tool

description: This is the data analysis done for the paper titled "Socratic LLM Framework (Extended Abstract): Fostering Critical Thinking in Software Engineering Students" (submitted to FSE - Software Engineering Education track). 

 

Abstract -- Large language models continue to attract the attention of the software industry due to their potential to boost developers' productivity. However, this focus often sidelines the development of critical thinking skills, which are essential for novice developers. In university settings, educators seek to understand how to make students properly engage with these tools, mitigating the impact on their skills' growth. Our goal is to develop a tool that stimulates novice software developers to think critically rather than simply copying and pasting code. We propose the Socratic LLM framework focused on code generation, code explanation, and debugging. Our framework and system are designed to benefit novice developers and SE educators by primarily encouraging critical thinking and independent problem-solving, as well as providing personalised guidance to students.

 

This repository contains:



Qualtrics surveys: pre_task_survey.pdf and post_task_survey.pdf

Task instruction: User Study Instructions.pdf

Socratic LLM tool User interface: UI_dashboard.png UI_chatbox.png

Socratic LLM Tool (Code): SocraticLLM.zip
DOI: 10.15468/dl.6bqd9q
title: Occurrence Download

description: A dataset containing 1480 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Polyscias murrayi"
 ]
}

 The dataset includes 1480 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002455-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31125412
title: code and dataset for the article "Can ESG disclosure mitigate stock price bubbles? Evidence from the Chinese stock market”

description: This is the data and code for the article "Can ESG disclosure mitigate stock price bubbles? Evidence from the Chinese stock market”
DOI: 10.6084/m9.figshare.31125412.v1
title: code and dataset for the article "Can ESG disclosure mitigate stock price bubbles? Evidence from the Chinese stock market”

description: This is the data and code for the article "Can ESG disclosure mitigate stock price bubbles? Evidence from the Chinese stock market”
DOI: 10.15468/dl.wmn2ma
title: Occurrence Download

description: A dataset containing 1453 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bombus variabilis"
 ]
}

 The dataset includes 1453 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004888-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31125433
title: Raw Data of Communications Biology Manuscript COMMSBIO-25-12629-T

description: Analysis of GRASP65 role in cell cycle progression through mitosis and formation of mitotic spindle
DOI: 10.6084/m9.figshare.31125433.v1
title: Raw Data of Communications Biology Manuscript COMMSBIO-25-12629-T

description: Analysis of GRASP65 role in cell cycle progression through mitosis and formation of mitotic spindle
DOI: 10.7910/dvn/cetpvt
title: 2020 - 2024 Cooperative Election Study Panel Survey

description: A representative sample of more than 6,000 American adults who were interviewed during the 2020 election, recontacted and surveyed again in 2022, and then recontacted and surveyed again in 2024. Includes vote validation for all three waves.
DOI: 10.57903/uj/4nb7ie
title: Persistent oscillation of Cooper pair condensate of topological defects in a nonintegrable quantum Ising chain - replication data

description: Data used for the numerical plots in the publication, together with Julia scripts that regenerate the figures in the article.
DOI: 10.6084/m9.figshare.31125502
title: Machine learning-based meat freshness evaluation: principle, pipeline and application

description: Ensuring the freshness of meat is crucial for food safety and consumer trust. Traditional methods for evaluating meat freshness, such as sensory analysis and chemical assays, are time-consuming, labor-intensive, and destructive. Machine learning (ML) offers a promising alternative by providing real-time, nondestructive solutions for monitoring meat quality, rationalizing the food industry. This review examines the principles and applications of ML in meat freshness evaluation, focusing on key algorithms like Principal Component Regression (PCR), Partial Least Squares (PLS), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and neural networks. It also details the ML-based detection pipeline, covering data acquisition, preprocessing, model selection, and fine-tuning. The paper highlights recent advancements in ML approaches tailored for meat freshness assessment, such as Convolutional Neural Networks (CNN) and ensemble learning models, which have proven effective in tackling spoilage rate, safety concerns, and the complex chemical composition of meat. However, challenges remain, including the need for high-quality datasets and model interpretability. Addressing these challenges will be crucial for the widespread adoption of ML-based solutions in meat freshness detection, ultimately leading to safer and higher-quality food products. SVM and CNN are effective in handling complex data and making reliable predictions.ML shows strong potential for improving meat freshness evaluation accuracy.Future ML should enhance data quality, model accuracy, and interpretability. SVM and CNN are effective in handling complex data and making reliable predictions. ML shows strong potential for improving meat freshness evaluation accuracy. Future ML should enhance data quality, model accuracy, and interpretability.
DOI: 10.6084/m9.figshare.31125502.v1
title: Machine learning-based meat freshness evaluation: principle, pipeline and application

description: Ensuring the freshness of meat is crucial for food safety and consumer trust. Traditional methods for evaluating meat freshness, such as sensory analysis and chemical assays, are time-consuming, labor-intensive, and destructive. Machine learning (ML) offers a promising alternative by providing real-time, nondestructive solutions for monitoring meat quality, rationalizing the food industry. This review examines the principles and applications of ML in meat freshness evaluation, focusing on key algorithms like Principal Component Regression (PCR), Partial Least Squares (PLS), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), and neural networks. It also details the ML-based detection pipeline, covering data acquisition, preprocessing, model selection, and fine-tuning. The paper highlights recent advancements in ML approaches tailored for meat freshness assessment, such as Convolutional Neural Networks (CNN) and ensemble learning models, which have proven effective in tackling spoilage rate, safety concerns, and the complex chemical composition of meat. However, challenges remain, including the need for high-quality datasets and model interpretability. Addressing these challenges will be crucial for the widespread adoption of ML-based solutions in meat freshness detection, ultimately leading to safer and higher-quality food products. SVM and CNN are effective in handling complex data and making reliable predictions.ML shows strong potential for improving meat freshness evaluation accuracy.Future ML should enhance data quality, model accuracy, and interpretability. SVM and CNN are effective in handling complex data and making reliable predictions. ML shows strong potential for improving meat freshness evaluation accuracy. Future ML should enhance data quality, model accuracy, and interpretability.
DOI: 10.5281/zenodo.18339492
title: Environmental filtering shapes divergent bacterial strategies and genomic traits across soil niches
DOI: 10.5281/zenodo.18339491
title: Environmental filtering shapes divergent bacterial strategies and genomic traits across soil niches
DOI: 10.5281/zenodo.18339716
title: ОТРАЖЕНИЕ ИДЕЙ НАЦИОНАЛЬНОГО САМОСОЗНАНИЯ И СВОБОДЫ В РУССКОЙ И УЗБЕКСКОЙ ЛИТЕРАТУРЕ НАЧАЛА XX ВЕКА

description: Статья посвящена сравнительному анализу идей национального самосознания и свободы в русской и узбекской литературах 1900–1920-х годов. Рассматриваются ключевые произведения русской литературы (А. Блок, А. Белый, М. Горький, В. Маяковский) и джадидской литературы Узбекистана (Махмудходжа Бехбуди, Абдулла Кодирий, Хамза Чулпон, Абдурауф Фитрат). Выявляются общие черты (пробуждение национального чувства на фоне революционных потрясений, критика колониализма и отсталости, мечта о свободе личности и народа) и национально-специфические различия (религиозно-реформаторский характер узбекского джадидизма, мессианские мотивы в русском символизме).
DOI: 10.5281/zenodo.18339717
title: ОТРАЖЕНИЕ ИДЕЙ НАЦИОНАЛЬНОГО САМОСОЗНАНИЯ И СВОБОДЫ В РУССКОЙ И УЗБЕКСКОЙ ЛИТЕРАТУРЕ НАЧАЛА XX ВЕКА

description: Статья посвящена сравнительному анализу идей национального самосознания и свободы в русской и узбекской литературах 1900–1920-х годов. Рассматриваются ключевые произведения русской литературы (А. Блок, А. Белый, М. Горький, В. Маяковский) и джадидской литературы Узбекистана (Махмудходжа Бехбуди, Абдулла Кодирий, Хамза Чулпон, Абдурауф Фитрат). Выявляются общие черты (пробуждение национального чувства на фоне революционных потрясений, критика колониализма и отсталости, мечта о свободе личности и народа) и национально-специфические различия (религиозно-реформаторский характер узбекского джадидизма, мессианские мотивы в русском символизме).
DOI: 10.5281/zenodo.18339658
title: Micro to Nano Mineralized Biomaterials Characterization

description: Dataset used in the following article: "Micro to Nano Mineralized Biomaterials Characterization" by M. Petay et al.
DOI: 10.5281/zenodo.18339659
title: Micro to Nano Mineralized Biomaterials Characterization

description: Dataset used in the following article: "Micro to Nano Mineralized Biomaterials Characterization" by M. Petay et al.
DOI: 10.6084/m9.figshare.31125463
title: <b>Erythropoietin </b><b>m</b><b>odulates </b><b>h</b><b>epatic </b><b>i</b><b>nflammation, </b><b>g</b><b>lucose </b><b>h</b><b>omeostasis, and </b><b>s</b><b>oluble </b><b>e</b><b>poxide </b><b>h</b><b>ydrolase and </b><b>e</b><b>poxides in </b><b>h</b><b>igh-</b><b>f</b><b>at </b><b>d</b><b>iet–</b><b>i</b><b>nduced </b><b>o</b><b>bese </b><b>m</b><b>ice</b>

description: Obesity-related liver disease remains a critical global health challenge, underscoring the need to elucidate the molecular mechanisms underlying hepatic inflammation and metabolic dysfunction, and to identify novel therapeutic targets. This study aimed to determine whether erythropoietin (EPO) modulates soluble epoxide hydrolase (sEH) and lipid mediator pathways to ameliorate hepatic inflammation and metabolic dysfunction in high-fat diet (HFD)–induced obese mice. Male C57BL/6 mice were fed HFD with or without EPO treatment, and metabolic phenotyping, including glucose tolerance testing and homeostasis model assessment of insulin resistance, was performed. Hepatic histology and quantitative real-time polymerase chain reaction were conducted, together with flow cytometry to assess macrophage polarization, Western blotting for sEH, and targeted liquid chromatography–tandem mass spectrometry profiling of cytochrome P450 epoxygenase–derived epoxides. EPO treatment improved glucose metabolism reduced hepatic steatosis, lowered <i>Ccr2</i>, <i>Mcp1</i>, and <i>Tnfα</i> expression, promoted a shift of hepatic macrophages toward an M2 (anti-inflammatory) phenotype, downregulated hepatic sEH protein levels, and increased both hepatic and plasma concentrations of epoxygenase-derived epoxides. These findings indicate that EPO suppresses hepatic sEH and favors pro-resolving lipid mediator signaling, suggesting a potential therapeutic avenue for obesity-related hepatic inflammation.
DOI: 10.6084/m9.figshare.31125463.v1
title: <b>Erythropoietin </b><b>m</b><b>odulates </b><b>h</b><b>epatic </b><b>i</b><b>nflammation, </b><b>g</b><b>lucose </b><b>h</b><b>omeostasis, and </b><b>s</b><b>oluble </b><b>e</b><b>poxide </b><b>h</b><b>ydrolase and </b><b>e</b><b>poxides in </b><b>h</b><b>igh-</b><b>f</b><b>at </b><b>d</b><b>iet–</b><b>i</b><b>nduced </b><b>o</b><b>bese </b><b>m</b><b>ice</b>

description: Obesity-related liver disease remains a critical global health challenge, underscoring the need to elucidate the molecular mechanisms underlying hepatic inflammation and metabolic dysfunction, and to identify novel therapeutic targets. This study aimed to determine whether erythropoietin (EPO) modulates soluble epoxide hydrolase (sEH) and lipid mediator pathways to ameliorate hepatic inflammation and metabolic dysfunction in high-fat diet (HFD)–induced obese mice. Male C57BL/6 mice were fed HFD with or without EPO treatment, and metabolic phenotyping, including glucose tolerance testing and homeostasis model assessment of insulin resistance, was performed. Hepatic histology and quantitative real-time polymerase chain reaction were conducted, together with flow cytometry to assess macrophage polarization, Western blotting for sEH, and targeted liquid chromatography–tandem mass spectrometry profiling of cytochrome P450 epoxygenase–derived epoxides. EPO treatment improved glucose metabolism reduced hepatic steatosis, lowered <i>Ccr2</i>, <i>Mcp1</i>, and <i>Tnfα</i> expression, promoted a shift of hepatic macrophages toward an M2 (anti-inflammatory) phenotype, downregulated hepatic sEH protein levels, and increased both hepatic and plasma concentrations of epoxygenase-derived epoxides. These findings indicate that EPO suppresses hepatic sEH and favors pro-resolving lipid mediator signaling, suggesting a potential therapeutic avenue for obesity-related hepatic inflammation.
DOI: 10.3886/e113837v1-197995
title: Replication data for: Are Big-Time Sports a Threat to Student Achievement?

description: We consider the relationship between collegiate football success and non-athlete student performance. We find that the team's success significantly reduces male grades relative to female grades, and only in
fall quarters, which coincides with the football season. Using survey data, we find that males are more likely than females to increase alcohol consumption, decrease studying, and increase partying in response to the success of the team. Yet, females also report that their behavior is affected by athletic success, suggesting that their performance is likely impaired but that this effect is masked by the practice of grade curving. (JEL I21, L83)
DOI: 10.18150/y0ppky
title: Raw data for: Two-dimensional Pb-free organic-inorganic Ni-based perovskites with two-color emission and their scintillation properties

description: Raw data from measurements shown in a scientific paper entitled Two-dimensional Pb-free organic-inorganic Ni-based perovskites with two-color emission and their scintillation properties. These data are intended to enable the reproduction of the presented results. The paper has not yet been published (currently in peer review). Each .xlsx file cointains experimental data from measurements. Specifically, the files beginning with a proper abbreviation (see list below) contain only data for that kind of measurement for a corresponding sample: (PMA)2NiCl4, (PEA)2NiCl4, (PPA)2NiCl4 and one for (PEA)2PbBr4. The .cif files contain crystallographic structures to simulate. More information can be found in readme.txt file.List of abbreviations:PAS - Photoacoustic spectroscopyTRPL - Time-resolved photoluminescence at 300 and 80 KPL_213 - Steady-state photoluminescence with 213 nm laser beam excitationPL_temp - Temperature-dependent photoluminescencePL_time - Time-dependent photoluminescenceRL - Temperature-dependent radioluminescenceXRD - X-ray diffractionSI_PAS_phases - Photoacoustic phase shifts (supplementary information)SI_PL - Photoluminescence at low temperature (supplementary information)
DOI: 10.5517/ccdc.csd.cc2p8r2t
title: CCDC 2481056: Experimental Crystal Structure Determination

description: Related Article: Seong Hyun Jang, JeongIl Ko, Jimin Seong, Woo Jin Choi, Dong Jun Lee, Se Hun Kim, Ga-Ram Jang, Hyun Kyu Lee, Jae Pil Kim, Jun Choi
|2026|Progress in Organic Coatings|211|109776|doi:10.1016/j.porgcoat.2025.109776
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34894/9oimwy
title: Rotterdam Artery-Vein Segmentation Dataset - RAV

description: Dataset of color fundus images annotated at the Department of Ophthalmology, Erasmus MC, Rotterdam with semi-manual artery-vein segmentations. Segmentations were acquired by manual refinement of outputs from a vessel segmentation model trained on publicly-available datasets followed by coloring of the artery and vein trees in an overlapping manner. Annotations were checked for correct connectivity of artery and vein trees. The public / open access set consists of 53 images. A private set consisting of 155 additional images can be accessed for research purposes upon signature of an End License User Agreement (EULA).
description: Files restricted that were open before.
DOI: 10.15468/dl.cdbmy5
title: Occurrence Download

description: A dataset containing 581829 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sciurus carolinensis"
 ]
}

 The dataset includes 581829 records from 315 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004847-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.myqxx2
title: Occurrence Download

description: A dataset containing 611577 species occurrences available in GBIF matching the query:
{
 "CollectionKey" : [
 "is c0e59491-e319-4822-90bf-3e3c6fbd4a13"
 ]
}

 The dataset includes 611577 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004865-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.