cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17489408
title: Inverse Design of Thermally Active Composite via Policy-Transferred Reinforcement Learning

description: Data and code of "Inverse Design of Temperature-Responsive 4D Active Composites Using Reinforcement Learning"

When you extract the compressed file, you will find the following four files:

DATA/├── DATA 1: final_input_data.npy│└── DATA 2: final_output_data.npy

DATA: Two NumPy arrays containing the complete dataset used for training and evaluation:



final_input_data.npy: (shape: 10000 × 4 × 24): Binary material configurations for the TAC cantilever beam, where each element represents material assignment (0 or 1) in a 4-row × 24-column grid. The dataset comprises 80% randomly generated configurations and 20% patterned designs.

final_output_data.npy: (shape: 10000 × 2 × 24): Corresponding deformation trajectories containing x and y coordinates of 24 centerline points along the beam after thermal actuation.


CODE/├── CODE 1: s1v1_surrogate.py│├── CODE 2: s2v1_GA_train.py│├── CODE 3: s2v1_SSO_train.py│├── CODE 4: s5v1_1case_DDQN_original_train_nstep.py│├── CODE 5: s6v1_multicase_DDQN_original_earlystop_nstep.py│└── CODE 6: s7v1_multi2single_transfer_DDQN_original_earlystop_train_nstep.py

CODE 1: s1v1_surrogate.pyForward prediction surrogate model using neural networks to predict deformation trajectories from material configurations, serving as the environment for RL training.

CODE 2: s2v1_GA_train.pyGenetic Algorithm (GA) implementation for inverse design optimization, used as a baseline comparison method.

CODE 3: s2v1_SSO_train.pySequential Subdomain Optimization (SSO) implementation that divides the design space into column-wise subdomains for local optimization.

CODE 4: s5v1_1case_DDQN_original_train_nstep.pySingle-target Double Deep Q-Network (DDQN) with n-step returns for optimizing material configurations toward individual target shapes.

CODE 5: s6v1_multicase_DDQN_original_earlystop_nstep.pyMulti-target DDQN training with early stopping, enabling generalization across diverse target trajectories without retraining.

CODE 6: s7v1_multi2single_transfer_DDQN_original_earlystop_train_nstep.pyTransfer learning implementation that fine-tunes the multi-target pretrained model for accelerated single-target optimization, reducing sample usage by up to fivefold.
DOI: 10.15468/dl.davqqs
title: Occurrence Download

description: A dataset containing 11726 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stellaria graminea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 11726 records from 353 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010995-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a5jzr6
title: Occurrence Download

description: A dataset containing 32274 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-83.835457 40.486621, -83.885132 40.550066, -83.968819 40.550066, -83.919096 40.486621, -83.835457 40.486621))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 32274 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010997-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bfb4tu
title: Occurrence Download

description: A dataset containing 168905 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 countrycode countrycode,
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, countrycode, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, countrycode, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, countrycode, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, countrycode, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, countrycode, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, countrycode, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'CD'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.classificationdetails['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c']['specieskey'] &lt;&gt; '' AND occurrence."year" IS NOT NULL AND occurrence.hascoordinate = TRUE)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year",
 occurrence.countrycode

 The dataset's 168905 records were derived from 486 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010963-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.psych.00977
title: Dataset for paper "How Visual Experience Shapes Face Processing"
title: Dataset for paper "How Visual Experience Shapes Face Processing"

description: This dataset contains the raw data associated with a paper investigating face representations in artificial neural networks (ANNs). This study examines two ANNs, and for each network, five independently trained copies are provided, each initialized with a different random seed. In addition, untrained versions corresponding to the same five seeds are included. All model files and their training logs are available in the Model folder.The Rawdata folder contains all original test results reported in the paper, provided as CSV files. The Stimuli folder includes lists of file names for all test images used in the study (to respect the licenses of public datasets, we do not redistribute those images; only the filenames used in the paper are provided). The folder also contains a small set of stimuli generated by the authors.The Code folder contains the training and testing code (Python 3.12.11, PyTorch 2.8.0).
description: This dataset contains the raw data associated with a paper investigating face representations in artificial neural networks (ANNs). This study examines two ANNs, and for each network, five independently trained copies are provided, each initialized with a different random seed. In addition, untrained versions corresponding to the same five seeds are included. All model files and their training logs are available in the Model folder.The Rawdata folder contains all original test results reported in the paper, provided as CSV files. The Stimuli folder includes lists of file names for all test images used in the study (to respect the licenses of public datasets, we do not redistribute those images; only the filenames used in the paper are provided). The folder also contains a small set of stimuli generated by the authors.The Code folder contains the training and testing code (Python 3.12.11, PyTorch 2.8.0).
DOI: 10.5281/zenodo.18464135
title: Data from: Bioactive Janus Barrier Membrane

description: This dataset contains the experimental data supporting the findings of our study on the development and evaluation of a bioactive Janus barrier membrane designed for guided bone regeneration (GBR) in aging bone. The dataset includes raw and processed data derived from material characterization, in vitro biological experiments, and in vivo bone regeneration assessments.
DOI: 10.5281/zenodo.18464136
title: Data from: Bioactive Janus Barrier Membrane

description: This dataset contains the experimental data supporting the findings of our study on the development and evaluation of a bioactive Janus barrier membrane designed for guided bone regeneration (GBR) in aging bone. The dataset includes raw and processed data derived from material characterization, in vitro biological experiments, and in vivo bone regeneration assessments.
DOI: 10.15468/dl.8nsstq
title: Occurrence Download

description: A dataset containing 874 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((120.48256102806093 36.06153889927215,120.5824246951442 36.06153889927215,120.5824246951442 36.161402566355406,120.48256102806093 36.161402566355406,120.48256102806093 36.06153889927215))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 874 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010998-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.295djt
title: Occurrence Download

description: A dataset containing 261 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stellaria obtusa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 261 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010999-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18478123
title: ANALYSIS OF INTERNATIONAL EXPERIENCE IN INCREASING THE EMPLOYMENT RATE OF THE POPULATION IN UZBEKISTAN

description: This study examines international experience in employment enhancement and labor market regulation, analyzing five distinct national models: American, Swedish, British, German, and Japanese. The research employs dialectical methods, comparative analysis, and systematic approaches to evaluate the applicability of these models to Uzbekistan's socio-economic context. For Uzbekistan, with its young population, developing economy, and specific labor market challenges, the study recommends a hybrid approach that combines active state involvement with regional autonomy, emphasizes vocational counseling infrastructure development, and prioritizes small and medium enterprise support. The findings contribute to understanding how international employment practices can be adapted to transition economies facing demographic pressures and technological transformation.
DOI: 10.5281/zenodo.18478124
title: ANALYSIS OF INTERNATIONAL EXPERIENCE IN INCREASING THE EMPLOYMENT RATE OF THE POPULATION IN UZBEKISTAN

description: This study examines international experience in employment enhancement and labor market regulation, analyzing five distinct national models: American, Swedish, British, German, and Japanese. The research employs dialectical methods, comparative analysis, and systematic approaches to evaluate the applicability of these models to Uzbekistan's socio-economic context. For Uzbekistan, with its young population, developing economy, and specific labor market challenges, the study recommends a hybrid approach that combines active state involvement with regional autonomy, emphasizes vocational counseling infrastructure development, and prioritizes small and medium enterprise support. The findings contribute to understanding how international employment practices can be adapted to transition economies facing demographic pressures and technological transformation.
DOI: 10.15468/dl.gm7z43
title: Occurrence Download

description: A dataset containing 0 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.datasetkey = '6d504df4-2037-45b0-a61b-1e74dcafa4eb'
 AND GBIF_WITHIN('POLYGON((120.0376795841846 30.255039028508477,120.14119224116034 30.255039028508477,120.14119224116034 30.358551685484215,120.0376795841846 30.358551685484215,120.0376795841846 30.255039028508477))', occurrence.decimallatitude, occurrence.decimallongitude) = TRUE
 AND occurrence.hascoordinate = TRUE
 AND occurrence.hasgeospatialissues = FALSE
 AND occurrence.occurrencestatus = 'PRESENT'
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.classificationdetails['d7dddbf4-2cf0-4f39-9b2a-bb099caae36c']['specieskey'] &lt;&gt; '' AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 0 records were derived from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010989-260129131611470/datasets/export for details.
DOI: 10.5281/zenodo.18477260
title: E-commerce and Urban-Rural Market Vitality: Evidence from a Double Machine Learning Approach
DOI: 10.5281/zenodo.18477261
title: E-commerce and Urban-Rural Market Vitality: Evidence from a Double Machine Learning Approach
DOI: 10.15468/dl.6cja7j
title: Occurrence Download

description: A dataset containing 141321 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plutella xylostella",
 "BasisOfRecord is Human Observation",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 141321 records from 324 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010930-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrnksg
title: Occurrence Download

description: A dataset containing 47866 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-82.274916 39.296322, -82.323583 39.362445, -82.410423 39.362445, -82.361704 39.296322, -82.274916 39.296322))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 47866 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011000-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/7rn-0s4-gat
title: Noctuidae

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/8m8-nez-tz8
title: Agonopterix imbutella Christoph, 1888

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/x13-3x4-em8
title: Agonopterix imbutella Christoph, 1888

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.3535/xbf-e10-f0k
title: Noctua Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.5281/zenodo.18477143
title: A Study on the Marginal Measurement and Driving Factors of China's "External Market Provider" Status
DOI: 10.5281/zenodo.18477144
title: A Study on the Marginal Measurement and Driving Factors of China's "External Market Provider" Status
DOI: 10.5281/zenodo.18477120
title: How Digital Technology Narrows the Urban–Rural Consumption Gap: Mechanisms, Moderators, and Evidence from 286 Chinese Cities (2011–2022)
DOI: 10.5281/zenodo.18477121
title: How Digital Technology Narrows the Urban–Rural Consumption Gap: Mechanisms, Moderators, and Evidence from 286 Chinese Cities (2011–2022)
DOI: 10.15468/dl.496reh
title: Occurrence Download

description: A dataset containing 360 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stipulicida setacea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 360 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011001-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/r3f-8xf-sqy
title: Noctuidae

description: Digital Specimen for the physical specimen hosted at Finnish Museum of Natural History.
DOI: 10.15468/dl.hyjpnk
title: Occurrence Download

description: A dataset containing 3042 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "TaxonKey is Riodinidae",
 "Year 2024-2026"
 ]
}

 The dataset includes 3042 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011002-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18478150
title: KORXONALARDA ISHLAB CHIQARISH XARAJATLARINING HISOBI VA ULARNI TAKOMILLASHTIRISH MASALALARI

description: Mazkur tezisda korxonalarda ishlab chiqarish xarajatlarining tarkibi, ularni buxgalteriya hisobida aks ettirishning amaldagi holati hamda mavjud muammolar tahlil qilingan. Tadqiqot davomida xarajatlar hisobini yuritishda uchrayotgan kamchiliklar aniqlanib, moliyaviy hisobni takomillashtirishga qaratilgan ilmiy-amaliy takliflar ishlab chiqilgan. Tezis natijalari korxonalarda xarajatlar hisobini samarali tashkil etish va mahsulot tannarxini optimallashtirishga xizmat qiladi.
DOI: 10.5281/zenodo.18478151
title: KORXONALARDA ISHLAB CHIQARISH XARAJATLARINING HISOBI VA ULARNI TAKOMILLASHTIRISH MASALALARI

description: Mazkur tezisda korxonalarda ishlab chiqarish xarajatlarining tarkibi, ularni buxgalteriya hisobida aks ettirishning amaldagi holati hamda mavjud muammolar tahlil qilingan. Tadqiqot davomida xarajatlar hisobini yuritishda uchrayotgan kamchiliklar aniqlanib, moliyaviy hisobni takomillashtirishga qaratilgan ilmiy-amaliy takliflar ishlab chiqilgan. Tezis natijalari korxonalarda xarajatlar hisobini samarali tashkil etish va mahsulot tannarxini optimallashtirishga xizmat qiladi.
DOI: 10.15468/dl.earf4j
title: Occurrence Download

description: A dataset containing 3421 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-83.692394 40.302274, -83.743886 40.368590, -83.831301 40.368590, -83.779755 40.302274, -83.692394 40.302274))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 3421 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011003-260129131611470/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.30875492
title: IceCT Result

description: Prediction results of the deep learning model IceCT for Arctic sea ice on the test dataset
DOI: 10.6084/m9.figshare.30875492.v1
title: IceCT Result

description: Prediction results of the deep learning model IceCT for Arctic sea ice on the test dataset
DOI: 10.57760/sciencedb.psych.00966
title: Experimental dataset on the influence of the level of information explanation on monthly donation intentions on charity webpages
title: 慈善网页信息解释水平对月捐意愿的影响实验数据集

description: This research dataset is derived from a behavioral study of an offline eye movement experiment and three online situational experiments, with online data collected through the Credamo online experimental platform. All four studies focused on the impact of the level of information interpretation in online donations on individual donation intentions, using standardized experimental procedures and consistent core measurement indicators. All participants participated with informed consent and the experiment has passed ethical review. Study 1 was conducted using a Tobii TX300 eye tracker with a sampling frequency of 300Hz, a display resolution of 1920 × 1080, and a refresh rate of 60Hz. The experimental software version used was Tobii Studio 3.2.0.135. During the experiment, 7 AOIs were divided, and eye movement data indicators for each AOI were collected as follows: First Fixation Duration, which represents the length of time the subject spends fixating in the area of interest after the first fixation behavior occurs. This can be used to test whether the subject's fixation behavior is influenced by the order in which the area of interest is presented. The main variables of Study 2-4 are donation intention and project urgency, both scored using an 8-point Likert scale. The above data is stored in SPSS (. sav) format. 
description: This research dataset is derived from a behavioral study of an offline eye movement experiment and three online situational experiments, with online data collected through the Credamo online experimental platform. All four studies focused on the impact of the level of information interpretation in online donations on individual donation intentions, using standardized experimental procedures and consistent core measurement indicators. All participants participated with informed consent and the experiment has passed ethical review. Study 1 was conducted using a Tobii TX300 eye tracker with a sampling frequency of 300Hz, a display resolution of 1920 × 1080, and a refresh rate of 60Hz. The experimental software version used was Tobii Studio 3.2.0.135. During the experiment, 7 AOIs were divided, and eye movement data indicators for each AOI were collected as follows: First Fixation Duration, which represents the length of time the subject spends fixating in the area of interest after the first fixation behavior occurs. This can be used to test whether the subject's fixation behavior is influenced by the order in which the area of interest is presented. The main variables of Study 2-4 are donation intention and project urgency, both scored using an 8-point Likert scale. The above data is stored in SPSS (. sav) format.