cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4g4rds55jn
title: Cleaner Air from Massive Long-Distance Power Transmission Upgrade: Evidences from the UHV Grid’s PM2.5 Reduction Effects

description: 1. Program files 
do file.do generates all tables and regression results in the paper. 
2.Data files 
data and code.zip contains 4 data files and 1 do file.
full smaple data.dta is the source dataset used in this paper; this round of revisions excludes provinces that do not have UHV lines in 2020.
extended data.dta is supplemented with data from the 2020 UHV expansion line.
delete data.dta is the data after deleting the explanatory variables, missing values of the control variables, and preserving part of the empirical process in order to reproduce the results fluently.
enterp data.dta is the enterprise data used in this paper.
modelSAR.zip is all the data and code used for spatial metrology, and the .nb file is the mathematica scripts.
3.Data sources 
The UHV project meta data was from the Annual Social Responsibility Report published by the China State Grid Corporation. 
The pollution data was sourced from NASA satellite inversion data. Meteorological data for other variables were sourced from the daily data set of meteorological stations available on the National Meteorological Science Data Sharing Service Platform.
economic variables data was found in the China Urban Statistical Yearbook. 
The firm-level data for mechanism study come from the China Industrial Enterprise Database.
DOI: 10.17632/4g4rds55jn.1
title: Cleaner Air from Massive Long-Distance Power Transmission Upgrade: Evidences from the UHV Grid’s PM2.5 Reduction Effects

description: 1. Program files 
do file.do generates all tables and regression results in the paper. 
2.Data files 
data and code.zip contains 4 data files and 1 do file.
full smaple data.dta is the source dataset used in this paper; this round of revisions excludes provinces that do not have UHV lines in 2020.
extended data.dta is supplemented with data from the 2020 UHV expansion line.
delete data.dta is the data after deleting the explanatory variables, missing values of the control variables, and preserving part of the empirical process in order to reproduce the results fluently.
enterp data.dta is the enterprise data used in this paper.
modelSAR.zip is all the data and code used for spatial metrology, and the .nb file is the mathematica scripts.
3.Data sources 
The UHV project meta data was from the Annual Social Responsibility Report published by the China State Grid Corporation. 
The pollution data was sourced from NASA satellite inversion data. Meteorological data for other variables were sourced from the daily data set of meteorological stations available on the National Meteorological Science Data Sharing Service Platform.
economic variables data was found in the China Urban Statistical Yearbook. 
The firm-level data for mechanism study come from the China Industrial Enterprise Database.
DOI: 10.17632/mrm9wvdvm9
title: Supplementary Material_Ingredients for oral photoprotection: An evidence-based classification_JAAD

description: Supplementary Methods, Figures and Tables.
DOI: 10.17632/mrm9wvdvm9.1
title: Supplementary Material_Ingredients for oral photoprotection: An evidence-based classification_JAAD

description: Supplementary Methods, Figures and Tables.
DOI: 10.17632/s3m4vtzmb6
title: Trace element and isotopic data of calcite from the Nadan deposit

description: Trace elements, C–O isotopes, and U–Pb dating data of calcite from the Nadan deposit
DOI: 10.17632/s3m4vtzmb6.1
title: Trace element and isotopic data of calcite from the Nadan deposit

description: Trace elements, C–O isotopes, and U–Pb dating data of calcite from the Nadan deposit
DOI: 10.17632/w3mcj6xj3n
title: Sacituzumab Tirumotecan versus Docetaxel Trial Data

description: Sacituzumab Tirumotecan
DOI: 10.17632/w3mcj6xj3n.1
title: Sacituzumab Tirumotecan versus Docetaxel Trial Data

description: Sacituzumab Tirumotecan
DOI: 10.5281/zenodo.17340471
title: URP v6.0 – Das Universal-Resonanz-Prinzip und seine Validierung Ein konsistentes physikalisches Modell ohne Gravitation, Dunkle Materie und Dunkle Energie

description: Das Universal-Resonanz-Prinzip (URP v6.0) beschreibt physikalische Systeme als kohärente Schwingungszustände, die aus der Wechselwirkung von Ordnung, Struktur und Umgebung entstehen.

Anstatt Gravitation, Dunkle Materie oder Dunkle Energie anzunehmen, erklärt das URP die Stabilität und Dynamik von Galaxien, kosmischen Strukturen und Laborprozessen durch Resonanzkopplung.

 

Im Zentrum steht die Idee, dass alle Systeme – von Galaxien bis zu mikroskopischen Resonatoren – durch dieselbe fundamentale Schwingung verbunden sind. Diese Resonanz erzeugt beobachtbare Muster: Rotationskurven, Lensing-Profile und Frequenzstrukturen lassen sich als unterschiedliche Erscheinungsformen einer universellen Kohärenz verstehen.

 

URP v6.0 wurde in mehreren Schritten validiert:

 



Galaktische Ebene (SPARC-Datensatz) – Die baryonische Tully-Fisher-Relation wird mit einer Streuung von etwa 0,10 dex reproduziert.

Dwarf-Spheroidal-Systeme (Gaia DR3) – Die beobachteten Geschwindigkeitsdispersionen stimmen bis auf 1–2 km/s mit den URP-Vorhersagen überein.

Schwach-Lensing-Analysen (HSC / KiDS) – Die modellierte Flächenmassendichte weicht im Median weniger als 10 % von Beobachtungsdaten ab.

Labor-Taktung (≈ 7,8 Hz) – In Resonator-Messungen erscheint reproduzierbar ein signifikanter Signal-Peak, der als mikroskopisches Analogon der makroskopischen Resonanz interpretiert wird.


 

 

Damit bietet URP v6.0 einen einheitlichen Rahmen, der kosmologische und physikalische Skalen überbrückt und aufzeigt, dass Ordnung und Energie nicht durch Gravitation, sondern durch Resonanz entstehen und erhalten werden.

 

Das Projekt umfasst:

 



Das theoretische Hauptdokument „URP v6.0 – Grundmodell und Datenbasis“

Die Validierung „URP v6.0 – dSph, Lensing, Labor-Taktung“

Die Arbeits- und Archivdokumente mit Code-Verweisen, Tabellen und Referenzen


 

 

Alle Inhalte stehen unter der Lizenz Creative Commons BY-NC 4.0 (Namensnennung – nicht kommerziell).
DOI: 10.5281/zenodo.17340472
title: URP v6.0 – Das Universal-Resonanz-Prinzip und seine Validierung Ein konsistentes physikalisches Modell ohne Gravitation, Dunkle Materie und Dunkle Energie

description: Das Universal-Resonanz-Prinzip (URP v6.0) beschreibt physikalische Systeme als kohärente Schwingungszustände, die aus der Wechselwirkung von Ordnung, Struktur und Umgebung entstehen.

Anstatt Gravitation, Dunkle Materie oder Dunkle Energie anzunehmen, erklärt das URP die Stabilität und Dynamik von Galaxien, kosmischen Strukturen und Laborprozessen durch Resonanzkopplung.

 

Im Zentrum steht die Idee, dass alle Systeme – von Galaxien bis zu mikroskopischen Resonatoren – durch dieselbe fundamentale Schwingung verbunden sind. Diese Resonanz erzeugt beobachtbare Muster: Rotationskurven, Lensing-Profile und Frequenzstrukturen lassen sich als unterschiedliche Erscheinungsformen einer universellen Kohärenz verstehen.

 

URP v6.0 wurde in mehreren Schritten validiert:

 



Galaktische Ebene (SPARC-Datensatz) – Die baryonische Tully-Fisher-Relation wird mit einer Streuung von etwa 0,10 dex reproduziert.

Dwarf-Spheroidal-Systeme (Gaia DR3) – Die beobachteten Geschwindigkeitsdispersionen stimmen bis auf 1–2 km/s mit den URP-Vorhersagen überein.

Schwach-Lensing-Analysen (HSC / KiDS) – Die modellierte Flächenmassendichte weicht im Median weniger als 10 % von Beobachtungsdaten ab.

Labor-Taktung (≈ 7,8 Hz) – In Resonator-Messungen erscheint reproduzierbar ein signifikanter Signal-Peak, der als mikroskopisches Analogon der makroskopischen Resonanz interpretiert wird.


 

 

Damit bietet URP v6.0 einen einheitlichen Rahmen, der kosmologische und physikalische Skalen überbrückt und aufzeigt, dass Ordnung und Energie nicht durch Gravitation, sondern durch Resonanz entstehen und erhalten werden.

 

Das Projekt umfasst:

 



Das theoretische Hauptdokument „URP v6.0 – Grundmodell und Datenbasis“

Die Validierung „URP v6.0 – dSph, Lensing, Labor-Taktung“

Die Arbeits- und Archivdokumente mit Code-Verweisen, Tabellen und Referenzen


 

 

Alle Inhalte stehen unter der Lizenz Creative Commons BY-NC 4.0 (Namensnennung – nicht kommerziell).
DOI: 10.6084/m9.figshare.30343573.v1
title: CGHD

description: CGHD：用于双类型地质灾害变化检测的全球分布式多源数据集
DOI: 10.23728/b2share.515d0a8145a64db8b3069466d642a40c
title: Forest regrowth after wildfire in northeastern Germany -- data from the PYROPHOB project - Part 2 (acces after 31.Mar.2026)

description: We present the data recorded by eight institutions within the PYROPHOB project, running from 2020 to 2024 at two forest research sites in the south-west of Brandenburg, Germany. The aim of the project was to monitor abiotic and biotic parameters of forest regrowth under different management regimes on former wildfire sites in northeastern Germany. The observations comprised intermittent and continuous measurements or surveys on meteorological parameters (rainfall, temperature, vapour pressure deficit), soil (soil type and texture, soil chemistry and leaching, water content, soil temperature), deadwood, stand structure, vegetation regrowth, abundance of selected fauna (moths, beetles, mammals), UAV-based remote sensing, and photo monitoring. Thus, the multitude of collected data allows not only for detailed analyses of these observables separately, but also considering their interaction for a more multidisciplinary view on forest recovery after a wildfire.
description: This data set contains part 2 - acces after 31.Mar.2026
DOI: 10.6084/m9.figshare.30344719
title: <b>A Hybrid Hierarchical Clustering Model Based on Whale Optimization Algorithm and Its Application in Segmentation of Sports Consumption Behavior</b>

description: <b>A Hybrid Hierarchical Clustering Model Based on Whale Optimization Algorithm and Its Application in Segmentation of Sports Consumption Behavior</b>
DOI: 10.6084/m9.figshare.30344719.v1
title: <b>A Hybrid Hierarchical Clustering Model Based on Whale Optimization Algorithm and Its Application in Segmentation of Sports Consumption Behavior</b>

description: <b>A Hybrid Hierarchical Clustering Model Based on Whale Optimization Algorithm and Its Application in Segmentation of Sports Consumption Behavior</b>
DOI: 10.17632/6n9t58g2v3.1
title: Design of a miniature sensing module for pressure mapping in functionality hydrogel using Programmable System-on-Chip

description: Flexible tactile sensors hold great promise in mimicking human skin to achieve tactile perception. However, their practical implementation still faces key technical challenges, including device miniaturization, high-sensitivity detection, and suppression of signal crosstalk. In this work, we propose a micro multi-channel pressure monitoring system, which integrates a sensor electrode array with a downsized multi-channel acquisition module for efficient pressure sensing. The hydrogel material was combined with the electrode array to form the sensing units. To address the influence of different array structures on the integrity of the hydrogel, an independent array design is adopted to reduce interference from redundant conductive pathways. The array is downscaled to a 4 × 4 structure with a size of 1.8 cm × 1.8 cm. The system employs a conversion circuit to provide alternating current excitation, which helps mitigate electrochemical corrosion caused by redox reactions between the hydrogel and metal electrodes. The system consists of a programmable system-on-chip (PSoC) and a multiplexer, enabling multi-pixel tactile array measurement while minimizing the use of additional components. The acquisition circuit is compact, with dimensions of only 2.3 cm × 3.0 cm. The array characteristics were validated by testing individual pixel elements, and experiments such as pressing concave and convex letter patterns as well as touching blood vessels were conducted, with vascular structures successfully displayed on the interface. This system enables real-time tactile measurement through touch, demonstrating significant potential in applications such as human–machine interaction and electronic skin.

File description:
PSoC programming: Files for PSoC's programming.
LabVIEW:Upper computer software
PCB:Hardware PCB
DOI: 10.17632/g8rpj7w69h.1
title: Perceived Difficulties in Swimming

description: This data was used to produce the paper Perceived Difficulties in Swimming. It includes two files: the database and the outputs.
DOI: 10.17632/jp4ds5s3b6
title: Sentiments in Oncology: A Cancer treatment sentiment dataset

description: The Cancer Treatment Sentiment Dataset was compiled by collecting 14419 patient comments from various multilingual websites in English, French, and German. Sources include popular platforms like Reddit, Drugs.com, AskPatient, and WebMD (English); Carenity and Espoir de Vie Cancer du Sein (French); and Medzin Forum Medecine (German). The dataset focuses on patient comments and experiences with three specific cancer treatments: Afinitor, Aromasin, and Folfox, and covers a timeframe from 2005 to 2024. This dataset has numerous potential applications. It can be used to develop machine learning models for classifying patient sentiments, identifying trends, and exploring common themes in patient feedback on cancer treatments. Healthcare professionals can leverage this data to gain deeper insights into patient concerns and preferences, enhancing patient care and support. Additionally, pharmaceutical companies can utilize this resource to gather real-world feedback on treatments, helping to inform drug development and improve patient outcomes.
DOI: 10.17632/jp4ds5s3b6.2
title: Sentiments in Oncology: A Cancer treatment sentiment dataset

description: The Cancer Treatment Sentiment Dataset was compiled by collecting 14419 patient comments from various multilingual websites in English, French, and German. Sources include popular platforms like Reddit, Drugs.com, AskPatient, and WebMD (English); Carenity and Espoir de Vie Cancer du Sein (French); and Medzin Forum Medecine (German). The dataset focuses on patient comments and experiences with three specific cancer treatments: Afinitor, Aromasin, and Folfox, and covers a timeframe from 2005 to 2024. This dataset has numerous potential applications. It can be used to develop machine learning models for classifying patient sentiments, identifying trends, and exploring common themes in patient feedback on cancer treatments. Healthcare professionals can leverage this data to gain deeper insights into patient concerns and preferences, enhancing patient care and support. Additionally, pharmaceutical companies can utilize this resource to gather real-world feedback on treatments, helping to inform drug development and improve patient outcomes.
DOI: 10.17632/pysnkp9n23
title: Dataset of Software Self-evolution with SelfEvolve: an Agentic Architecture for Runtime Code Generation

description: A collection of 11 curated datasets for evaluating AI agents capable of runtime self-evolution through autonomous code generation, codebase integration, and cross-session 
 composition. Used in ICSE 2026 paper "Self-evolving Systems: a Runtime Architecture for Autonomous Code Generation".

Dataset Categories:

 Integration Tasks (4 datasets): Multi-file codebases (577-783 LOC, 7-20 classes)
 • Patient Risk Analyzer (Healthcare) - 752 LOC, 12 files, 20 classes
 • Student GPA Calculator (Education) - 783 LOC, 10 files, 10 classes
 • Salary Analyzer (HR Analytics) - 616 LOC, 13 files, 12 classes
 • Inventory Low Stock Alert (E-commerce) - 577 LOC, 8 files, 7 classes

 Compositional Tasks (3 datasets): Cross-session capability building
 • Matrix Eigenvalue, Portfolio Risk, IoT Sensor Pipeline

 Data Processing Tasks (4 datasets): External data manipulation
 • Book Recommender (100 books CSV), Friend Suggester (100 users JSON)
 • Movie API (100 movies CSV), Performance Tracker (50 reviews CSV)

Statistics:65 files, ~80 KB compressed, 49 Python classes, 2,685 LOC, 9 domains (Healthcare, Education, HR Analytics, E-commerce, Finance, Linear Algebra, IoT, Media, 
 Social Networks)

 Contents: Each dataset includes problem.json (task specification), Python source files (PEP 8 compliant with type hints), __init__.py (package exports), and data files 
 (CSV/JSON where applicable).

 Evaluation Results: Pass@1: 92.7% (WITH TDD) vs 72.7% (WITHOUT TDD); Avg iterations: 2.2 vs 4.7; Wilcoxon test: W=55, p&lt;0.001, r=0.98

 Dependencies: Python 3.8+, minimal (NumPy for 1 dataset)

 License:CC BY 4.0
DOI: 10.17632/pysnkp9n23.1
title: Dataset of Software Self-evolution with SelfEvolve: an Agentic Architecture for Runtime Code Generation

description: A collection of 11 curated datasets for evaluating AI agents capable of runtime self-evolution through autonomous code generation, codebase integration, and cross-session 
 composition. Used in ICSE 2026 paper "Self-evolving Systems: a Runtime Architecture for Autonomous Code Generation".

Dataset Categories:

 Integration Tasks (4 datasets): Multi-file codebases (577-783 LOC, 7-20 classes)
 • Patient Risk Analyzer (Healthcare) - 752 LOC, 12 files, 20 classes
 • Student GPA Calculator (Education) - 783 LOC, 10 files, 10 classes
 • Salary Analyzer (HR Analytics) - 616 LOC, 13 files, 12 classes
 • Inventory Low Stock Alert (E-commerce) - 577 LOC, 8 files, 7 classes

 Compositional Tasks (3 datasets): Cross-session capability building
 • Matrix Eigenvalue, Portfolio Risk, IoT Sensor Pipeline

 Data Processing Tasks (4 datasets): External data manipulation
 • Book Recommender (100 books CSV), Friend Suggester (100 users JSON)
 • Movie API (100 movies CSV), Performance Tracker (50 reviews CSV)

Statistics:65 files, ~80 KB compressed, 49 Python classes, 2,685 LOC, 9 domains (Healthcare, Education, HR Analytics, E-commerce, Finance, Linear Algebra, IoT, Media, 
 Social Networks)

 Contents: Each dataset includes problem.json (task specification), Python source files (PEP 8 compliant with type hints), __init__.py (package exports), and data files 
 (CSV/JSON where applicable).

 Evaluation Results: Pass@1: 92.7% (WITH TDD) vs 72.7% (WITHOUT TDD); Avg iterations: 2.2 vs 4.7; Wilcoxon test: W=55, p&lt;0.001, r=0.98

 Dependencies: Python 3.8+, minimal (NumPy for 1 dataset)

 License:CC BY 4.0
DOI: 10.17632/5fj2fww2yv
title: Codes_Gilli_Sorrentino - Equilibrium Indeterminacy in Max-Min Two-Group Contests with Binary Actions and a Private Good Prize

description: These codes reproduce the results of the paper available in its preliminary version at SSRN: https://ssrn.com/abstract=486323 .

Gilli, Mario and Sorrentino, Andrea, The Set of Equilibria in Max-Min Two Groups Contests with Binary Actions and a Private Good Prize (June 12, 2024). University of Milan Bicocca Department of Economics, Management and Statistics Working Paper No. 539, Available at SSRN: https://ssrn.com/abstract=4863239 or http://dx.doi.org/10.2139/ssrn.4863239
DOI: 10.17632/5fj2fww2yv.1
title: Codes_Gilli_Sorrentino - Equilibrium Indeterminacy in Max-Min Two-Group Contests with Binary Actions and a Private Good Prize

description: These codes reproduce the results of the paper available in its preliminary version at SSRN: https://ssrn.com/abstract=486323 .

Gilli, Mario and Sorrentino, Andrea, The Set of Equilibria in Max-Min Two Groups Contests with Binary Actions and a Private Good Prize (June 12, 2024). University of Milan Bicocca Department of Economics, Management and Statistics Working Paper No. 539, Available at SSRN: https://ssrn.com/abstract=4863239 or http://dx.doi.org/10.2139/ssrn.4863239
DOI: 10.17632/t2fv9sbwm8
title: Data of Suberin barrier architecture and composition reveal the secrets of low cadmium accumulation in Salvia miltiorrhiza Bunge

description: This database contains the raw data for the article ‘Suberin barrier architecture and composition reveal the secrets of low cadmium accumulation in Salvia miltiorrhiza Bunge’.
DOI: 10.17632/t2fv9sbwm8.1
title: Data of Suberin barrier architecture and composition reveal the secrets of low cadmium accumulation in Salvia miltiorrhiza Bunge

description: This database contains the raw data for the article ‘Suberin barrier architecture and composition reveal the secrets of low cadmium accumulation in Salvia miltiorrhiza Bunge’.
DOI: 10.17632/zttgbk4s7f
title: flame retardant

description: Data Availability
DOI: 10.17632/zttgbk4s7f.1
title: flame retardant

description: Data Availability
DOI: 10.17632/8yvmft2sdp.1
title: The Impact of External Equity Dispersion on Corporate Innovation

description: The Impact of External Equity Dispersion on Corporate Innovation
DOI: 10.17632/5chyc49gtj
title: Morphological adaptation of the root system of silver fir responding to changes of local environmental conditions

description: The aim of the study was to verify possible allometric changes in the spatial structure of the root system of nearly 100-year-old silver fir (Abies alba Mill.) growing outside its natural range (Białowieża Forest). The traditional view of it as a taproot with 4–5 strong diagonal roots should be supplemented by the finding that, under certain conditions, it undergoes significant modification. This involves development of an extensive lateral root network reaching 41.8–44.0 m in diameter in the upper soil profile (0.2–1.0 m), markedly exceeding previously reported maxima (21.2 m). This adaptive change is a result of the lack of competition from the shallow roots of Norway spruce (Picea abies (L.) H. Karst.), which died due to drought, a drop in the groundwater level below 3 m and infestation by the European spruce bark beetle (Ips typographus L.). With increased availability of nutrients and water (including from horizontal precipitation) in upper soil layers enriched by decomposing organic matter, silver fir develops long roots in the niche previously occupied by spruce. The allometric shift favoring lateral roots corresponds to increased growth rates after spruce retreat, demonstrating considerable morphological plasticity despite the trees’ advanced age, confirming the climax nature of the species. Noteworthy spatial parameters include root depth of 1.95–2.40 m and lateral extension of 6.40–10.38 m, likely representing flattened root bundles growing parallel to the soil surface from the taproot tip. These findings offer insights for managing species composition and productivity in mixed stands containing silver fir, emphasizing long-term species management.
DOI: 10.17632/5chyc49gtj.1
title: Morphological adaptation of the root system of silver fir responding to changes of local environmental conditions

description: The aim of the study was to verify possible allometric changes in the spatial structure of the root system of nearly 100-year-old silver fir (Abies alba Mill.) growing outside its natural range (Białowieża Forest). The traditional view of it as a taproot with 4–5 strong diagonal roots should be supplemented by the finding that, under certain conditions, it undergoes significant modification. This involves development of an extensive lateral root network reaching 41.8–44.0 m in diameter in the upper soil profile (0.2–1.0 m), markedly exceeding previously reported maxima (21.2 m). This adaptive change is a result of the lack of competition from the shallow roots of Norway spruce (Picea abies (L.) H. Karst.), which died due to drought, a drop in the groundwater level below 3 m and infestation by the European spruce bark beetle (Ips typographus L.). With increased availability of nutrients and water (including from horizontal precipitation) in upper soil layers enriched by decomposing organic matter, silver fir develops long roots in the niche previously occupied by spruce. The allometric shift favoring lateral roots corresponds to increased growth rates after spruce retreat, demonstrating considerable morphological plasticity despite the trees’ advanced age, confirming the climax nature of the species. Noteworthy spatial parameters include root depth of 1.95–2.40 m and lateral extension of 6.40–10.38 m, likely representing flattened root bundles growing parallel to the soil surface from the taproot tip. These findings offer insights for managing species composition and productivity in mixed stands containing silver fir, emphasizing long-term species management.