cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24764226.v1
title: R_Workspace_HKI_healthy_food_3D_accessibility

description: This directory provides the source code, raw data and raw results from the paper titling "3D Walking Accessibility in Practice: Exploring the Imperfections from Data, Method, and Assumptions of Human-Space Interaction" from the <i>International Journal of Geographical Information Science</i>.This workspace includes the R scripts for preprocessing the data, conducting the analysis, and producing the results.The "data" folder includes all of the raw data. The "Readme.txt" in each folder inside provides the data sources. The "Preprocessed_data" folder within the "data" folder contains all preprocessed data generated by the R script "DataPreprocess.qmd". The "DataPreprocess.qmd" records the workflow of preprocessing the data for analysis.The "rFunction.qmd" file recorded all customised R functions for this study. The "Analysis01_cal_access.qmd" and "Analysis02_formalAnalysis.qmd" files record the R code for conducting the analysis and producing the results. Please first run the code in "rFunction.qmd" to reproduce the data preprocessing and data analysis. The "workspace.Rproj" is the R workspace for conducting the computation. You can open this workspace and import the R scripts from "rFunction.qmd", "DataPreprocess.qmd", "Analysis01_cal_access.qmd", and "Analysis02_formalAnalysis_update.qmd".The "result" folder comprises all raw figures, tables, and GIS data. Because R cannot produce the 3D map. Therefore, the "Qgis" folder comprises the QGIS files for visualising and mapping the produced GIS data. We used the Qgis2threejs plugin to visualise the 3D scene.
DOI: 10.57760/sciencedb.agriculture.00135
title: Landsat8 Image Training Data Set of Grassland Types in Tarbagatay Prefecture in 2023
title: 2023年新疆塔城地区草地类型Landsat8影像训练数据集

description: Grassland resources are the material basis of animal husbandry production and the gene pool of biodiversity, which have the ecological functions of preventing wind, fixing sand and conserving water. Grassland classification based on satellite remote sensing can not only provide data support for the investigation of grassland resources, but also provide a basis for the study of grassland species diversity. Based on the field survey data, the grassland classification information of real sample plots was obtained. By using the preprocessed Landsat8 remote sensing images such as radiometric calibration, atmospheric correction and image fusion, and by means of visual interpretation,3360 multi-spectral remote sensing image classification training data sets of 8 types of grassland in Tarbagatay Prefecture area were constructed by using ArcGIS software. This data set can not only provide data basis for remote sensing image classification of grassland in Tarbagatay Prefecture, but also provide data reference for researchers in related fields in other areas.
description: Grassland resources are the material basis of animal husbandry production and the gene pool of biodiversity, which have the ecological functions of preventing wind, fixing sand and conserving water. Grassland classification based on satellite remote sensing can not only provide data support for the investigation of grassland resources, but also provide a basis for the study of grassland species diversity. Based on the field survey data, the grassland classification information of real sample plots was obtained. By using the preprocessed Landsat8 remote sensing images such as radiometric calibration, atmospheric correction and image fusion, and by means of visual interpretation,3360 multi-spectral remote sensing image classification training data sets of 8 types of grassland in Tarbagatay Prefecture area were constructed by using ArcGIS software. This data set can not only provide data basis for remote sensing image classification of grassland in Tarbagatay Prefecture, but also provide data reference for researchers in related fields in other areas.
DOI: 10.15468/dl.g6qayr
title: Occurrence Download

description: A dataset containing 2833 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "TaxonKey is Genipa americana L."
 ]
}

 The dataset includes 2833 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068045-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pp2k2c
title: Occurrence Download

description: A dataset containing 89 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-75.58574 4.89667,-75.49641 4.89667,-75.49641 4.96398,-75.58574 4.96398,-75.58574 4.89667))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 89 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068047-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57783/8qhs-vb86
title: LibreChat-DEV
DOI: 10.57783/5adj-1354
title: LibreChat-TEST
DOI: 10.15468/dl.fwz3d2
title: Occurrence Download

description: A dataset containing 9029241 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1910-2025"
 ]
}

 The dataset includes 9029241 records from 2659 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068033-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2p8c7l
title: CCDC 2480689: Experimental Crystal Structure Determination

description: Related Article: K. Tsubokawa, T. Iida, K. Tsuge, H. Ohtsu|2025|IUCrData|10|x250764|doi:10.1107/S2414314625007643
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: 10.5281/zenodo.17188582
title: БОШҚАРУВ ЭТИКАСИ
DOI: 10.5281/zenodo.17188583
title: БОШҚАРУВ ЭТИКАСИ
DOI: 10.5281/zenodo.17188603
title: COGNITIVE FOUNDATIONS AND CONCEPTUAL MANIFESTATION OF NEGATIVE EMOTION LEXIS
DOI: 10.5281/zenodo.17188604
title: COGNITIVE FOUNDATIONS AND CONCEPTUAL MANIFESTATION OF NEGATIVE EMOTION LEXIS
DOI: 10.5281/zenodo.17188609
title: INTEGRATING PUBLIC SPEAKING INTO EFL TEACHER EDUCATION CURRICULA: CHALLENGES AND OPPORTUNITIES
DOI: 10.5281/zenodo.17188610
title: INTEGRATING PUBLIC SPEAKING INTO EFL TEACHER EDUCATION CURRICULA: CHALLENGES AND OPPORTUNITIES
DOI: 10.5281/zenodo.15777201
title: Learning the bulk and interfacial physics of liquid-liquid phase separation with neural density functionals - Data and Models

description: This work is connected to the research detailed in the paper "Learning the bulk and interfacial physics of liquid-liquid phase separation" (to be published, Arxiv: https://arxiv.org/pdf/2507.08395) and the associated SWNeural software available on GitHub (https://github.com/SilasRobitschko/SWNeural)

Abstract: 

We use simulation-based supervised machine learning and classical density functional theory to investigate bulk andinterfacial phenomena associated with phase coexistence in binary mixtures. For a prototypical symmetrical Lennard-Jones mixture our trained neural density functional yields accurate liquid-liquid and liquid-vapour binodals togetherwith predictions for the variation of the associated interfacial tensions across the entire fluid phase diagram. From thelatter we determine the contact angles at fluid-fluid interfaces along the line of triple-phase coexistence and confirmthere can be no wetting transition in this symmetrical mixture.

 

The dataset BinaryLJ_All_Runs.zip comprises 2200 Grand Canonical Monte Carlo (GCMC) simulation runs of a binary Lennard-Jones (LJ) fluid. The simulations were performed under a variety of random external potentials.

The primary purpose of this data is to serve as a training set for machine learning models aimed at deriving the c1-functional, a crucial component for classical density functional theory. 

The simulated system is a binary symmetric Lennard-Jones fluid with the following parameters: same-species interaction (ϵ11=ϵ22) and weakened cross-species interaction (ϵ12=0.7⋅ϵ11). The particle sizes are identical (σ1=σ2), and the potential is truncated at 2.5σ (without an energy shift being applied).

The data was generated using the MBD software package, developed by Florian Sammüller at the University of Bayreuth (https://gitlab.uni-bayreuth.de/bt306964/mbd).

 

Models_and_Results.zip includes two neural models trained on this dataset (as Pytorch-Path-Files) and their respective calculations of the Binodal of the aforementioned symmetric binary LJ fluid.  

Both models are basic fully connected neural models with the softplus activation function. 

The first original trained model has the following parameters: - Size: 1404x1024x512x512x512x2- Learning Rate: 0.001- Epochs: 100 - Decay/Epoch: 0.95

The refined model has the following parameters: - Size: 1404x512x512x512x512x2- Learning Rate: 0.0003- Epochs: 100 - Decay/Epoch: 0.90- L2 Regularization: 1.0*10^-5
DOI: 10.5281/zenodo.17188538
title: Learning the bulk and interfacial physics of liquid-liquid phase separation with neural density functionals - Data and Models

description: This work is connected to the research detailed in the paper "Learning the bulk and interfacial physics of liquid-liquid phase separation" (to be published, Arxiv: https://arxiv.org/pdf/2507.08395) and the associated SWNeural software available on GitHub (https://github.com/SilasRobitschko/SWNeural)

Abstract: 

We use simulation-based supervised machine learning and classical density functional theory to investigate bulk andinterfacial phenomena associated with phase coexistence in binary mixtures. For a prototypical symmetrical Lennard-Jones mixture our trained neural density functional yields accurate liquid-liquid and liquid-vapour binodals togetherwith predictions for the variation of the associated interfacial tensions across the entire fluid phase diagram. From thelatter we determine the contact angles at fluid-fluid interfaces along the line of triple-phase coexistence and confirmthere can be no wetting transition in this symmetrical mixture.

 

The dataset BinaryLJ_All_Runs.zip comprises 2200 Grand Canonical Monte Carlo (GCMC) simulation runs of a binary Lennard-Jones (LJ) fluid. The simulations were performed under a variety of random external potentials.

The primary purpose of this data is to serve as a training set for machine learning models aimed at deriving the c1-functional, a crucial component for classical density functional theory. 

The simulated system is a binary symmetric Lennard-Jones fluid with the following parameters: same-species interaction (ϵ11=ϵ22) and weakened cross-species interaction (ϵ12=0.7⋅ϵ11). The particle sizes are identical (σ1=σ2), and the potential is truncated at 2.5σ (without an energy shift being applied).

The data was generated using the MBD software package, developed by Florian Sammüller at the University of Bayreuth (https://gitlab.uni-bayreuth.de/bt306964/mbd).

 

Models_and_Results.zip includes two neural models trained on this dataset (as Pytorch-Path-Files) and their respective calculations of the Binodal of the aforementioned symmetric binary LJ fluid.  

Both models are basic fully connected neural models with the softplus activation function. 

The first original trained model has the following parameters: - Size: 1404x1024x512x512x512x2- Learning Rate: 0.001- Epochs: 100 - Decay/Epoch: 0.95

The refined model has the following parameters: - Size: 1404x512x512x512x512x2- Learning Rate: 0.0003- Epochs: 100 - Decay/Epoch: 0.90- L2 Regularization: 1.0*10^-5
DOI: 10.6084/m9.figshare.30193333
title: Spatially resolved profiling of human distal cholangiocarcinoma tissues with low/high neural invasion status

description: To dissect the topological architecture of perineural invasion (PNI) in dCCA, primary tumor regions with and without PNI were selected from eight surgically resected cases based on H&E staining, as evaluated by a board-certified pathologist. Formalin-fixed, paraffin-embedded (FFPE) tissues from these patients were used to construct a tissue microarray (TMA) comprising 14 representative cores. Subcellular spatial transcriptomic profiling targeting over 5,000 genes was then performed using the Xenium platform.
DOI: 10.6084/m9.figshare.30193333.v1
title: Spatially resolved profiling of human distal cholangiocarcinoma tissues with low/high neural invasion status

description: To dissect the topological architecture of perineural invasion (PNI) in dCCA, primary tumor regions with and without PNI were selected from eight surgically resected cases based on H&E staining, as evaluated by a board-certified pathologist. Formalin-fixed, paraffin-embedded (FFPE) tissues from these patients were used to construct a tissue microarray (TMA) comprising 14 representative cores. Subcellular spatial transcriptomic profiling targeting over 5,000 genes was then performed using the Xenium platform.
DOI: 10.5281/zenodo.17182275
title: Hot Plasma Wave Dispersion Relations Inside and Outside the Current Sheet
DOI: 10.5281/zenodo.17188626
title: Hot Plasma Wave Dispersion Relations Inside and Outside the Current Sheet
DOI: 10.5281/zenodo.17188629
title: FAVQULODDA VAZIYATLARDA BOLALARGA PSIXOLOGIK YORDAM KO'RSATISH XUSUSIYATLARI BO'YICHA QOIDALAR
DOI: 10.5281/zenodo.17188630
title: FAVQULODDA VAZIYATLARDA BOLALARGA PSIXOLOGIK YORDAM KO'RSATISH XUSUSIYATLARI BO'YICHA QOIDALAR
DOI: 10.25919/9cv0-dr74
title: NBDL-HXDQPBW8MNF8HC
DOI: 10.25919/nqgz-tg92
title: NBDL-HXDQPBW5PNFSYG
DOI: 10.25919/2w3d-nv27
title: NBDL-HXDQPBWMMNEPAW
DOI: 10.25919/vf27-tb24
title: NBDL-HXDQPBWGMNEZWC
DOI: 10.25919/2s6a-qy43
title: NBDL-HXDQPBWXPNE47G
DOI: 10.25919/zzmz-2539
title: NBDL-HXDQPBWPGNEK74
DOI: 10.25919/1kpq-h636
title: NBDL-HXDQPBX0MNDBJC
DOI: 10.25919/rwxm-x615
title: NBDL-HXDQPBWYGNE6J4
DOI: 10.25919/1932-zw18
title: NBDL-HXDQPBX1PNCNW0
DOI: 10.25919/bw1e-ym35
title: NBDL-HXDQPBX7JND97R
DOI: 10.25919/zq3d-r181
title: NBDL-HXDQPBX9PNCSF0
DOI: 10.25919/tsj1-8137
title: NBDL-HXDQPBXBJNCT48
DOI: 10.25919/was1-kc93
title: NBDL-HXDQPBXFJNCWJR
DOI: 10.25919/fmk5-2g95
title: NBDL-HXDQPBXHPNCCT0
DOI: 10.25340/r4/3lljdr
title: Related Data for: Mathematics resilience in preschool and executive functions

description: Background Children from disadvantaged socioeconomic (SES) backgrounds already show poorer academic skills than their more advantaged peers in preschool and are at higher risk of experiencing learning difficulties in formal school. However, not all children facing adversity experience negative academic outcomes. Some children show academic resilience, performing at the level of their more advantaged peers. Aims This study investigated whether mathematics resilience is observed in preschool children, whether executive functions are associated with mathematics resilience, and whether earlier resilience status relates to later mathematics achievement (six years later). Sample The sample included 1132 children (Mage = 57 months, SD = 3.9; 51 % female) attending preschool in Singapore. Methods Resilient children (at-risk with math development over two preschool years that breaks the average trend of their similar-risk peers) were identified using person-centered methods. Their trajectories were matched against those of children from more advantaged backgrounds using multigroup mixture growth model. Results One resilient profile was identified (6 % of the at-risk sample), which was associated with later mathematics achievement. Intelligence, but not executive function, predicted resilience status. Maternal education emerged as a protective factor rather than a risk factor. Conclusions Findings highlight the heterogeneity in the development of mathematics among at-risk children. Young children's mathematics resilience is built upon a combination of foundational cognitive aptitude that protects against initial failure, and environmental resources that sustain growth over time.
DOI: 10.25919/8gy8-ye73
title: NBDL-HXDQPBXQJNC3XR
DOI: 10.25919/0bqs-j505
title: NBDL-HXDQPBXWMNC81W
DOI: 10.25919/t8wg-5s27
title: NBDL-HXDQPBXXPNCAKG
DOI: 10.25919/p3g8-3038
title: NBDL-HXDQPBXYGNFMY4
DOI: 10.25919/z13a-x680
title: NBDL-HXDQPBY3NNJ7ED
DOI: 10.25919/1p1m-hr56
title: NBDL-HXDQPBY5HNJ0AN
DOI: 10.25919/wzng-y026
title: NBDL-HXDQPBY8KNJHGS
DOI: 10.25919/2qsx-hy58
title: NBDL-HXDQPBYAQNJJD1
DOI: 10.25919/5zka-8r76
title: NBDL-HXDQPBYEQNJR6H
DOI: 10.25919/c7ka-3714
title: NBDL-HXDQPBYBNNJG3D
DOI: 10.25919/d32b-1t20
title: NBDL-HXDQPBYGKNNZSS
DOI: 10.25919/5s5r-5818
title: NBDL-HXDQPBYMKNN5K9
DOI: 10.25919/qft1-re26
title: NBDL-HXDQPBYTQNNNB1
DOI: 10.25919/8fpg-hv57
title: NBDL-HXDQPBYQNNN7XX
DOI: 10.25919/8rkf-k463
title: NBDL-HXDQPBYVNNJASD
DOI: 10.25919/eee9-r222
title: NBDL-HXDQPBYYQNNJWH
DOI: 10.25919/2w3r-t465
title: NBDL-HXDQPBZ3NNMH2D
DOI: 10.25919/anpb-sa54
title: NBDL-HXDQPBZ6QNMS5H
DOI: 10.25919/z0h8-am50
title: NBDL-HXDQPBZBNNNDQD
DOI: 10.25919/6qej-0t04
title: NBDL-HXDQPBZDHNNEKN
DOI: 10.25919/sarr-6x14
title: NBDL-HXDQPC00G6YQNJ
DOI: 10.25919/91w2-9846
title: Parkes observations for project P1345 semester 2025APRS_20

description: This proposal aims to constrain burst rates and spin down properties of a sample of new Rotating Radio Transients (RRATs) discovered with the ASKAP CRAFT Coherent upgrade (CRACO) system. Over the past 12-months of commissioning, CRACO discovered and precisely localised 15 new RRATs, characterised by their sporadic pulses with dispersion measures (DM) consistent with Galactic sources. We request 22.5h of Parkes time split into three 30min observations spanning 6-months for each target. This can help constrain periods and potentially phase-coherent timing solutions given that we already have arcsec-precision interferometric localisations. Our main science goals are: 1) to measure their burst rates, periods, and spin-down properties; 2) to assess their nulling fraction and intermittency; 3) to measure their polarimetric properties and constrain their emission mechanism; 4) to determine if the CRACO RRATs are fundamentally different from the known RRAT population. Some of these goals can be answered even with the detection of a limited number of pulses.
DOI: 10.25919/xgk6-9g96
title: NBDL-HXDQPC03J6Z8EP
DOI: 10.6084/m9.figshare.28646846
title: <b>Dynamic Spatiotemporal Feature Extraction Integrating Temporal Information and Fluctuation Features For Traffic Prediction</b>

description: Short-term traffic flow prediction reflects changes in the traffic system, aiding in signal control, route planning, and congestion reduction. However, existing methods often overlook fluctuation features and lack sufficient integration of temporal position information, limiting spatiotemporal modeling. To address this, we propose the dynamic spatiotemporal feature extraction model (DSTFE-TIFF). The DSTFE-TIFF model encodes temporal location using trigonometric functions and extracts fluctuation features via an exponentially decaying weighted method with a sliding window. A dynamic relational module enhances adaptability by integrating these features into traffic data. Additionally, a spatiotemporal attention fusion module uses temporal additive attention to capture local fluctuations and spatial attention to link geographically distant yet similar nodes. Finally, an adaptive fusion method dynamically adjusts the focus on temporal and spatial features. Experimental results on PeMSD4, PeMSD8, and METR-LA datasets show that DSTFE-TIFF outperforms baseline models in RMSE, MAE, and MAPE, confirming its effectiveness.
DOI: 10.6084/m9.figshare.28646846.v1
title: <b>Dynamic Spatiotemporal Feature Extraction Integrating Temporal Information and Fluctuation Features For Traffic Prediction</b>

description: Short-term traffic flow prediction reflects changes in the traffic system, aiding in signal control, route planning, and congestion reduction. However, existing methods often overlook fluctuation features and lack sufficient integration of temporal position information, limiting spatiotemporal modeling. To address this, we propose the dynamic spatiotemporal feature extraction model (DSTFE-TIFF). The DSTFE-TIFF model encodes temporal location using trigonometric functions and extracts fluctuation features via an exponentially decaying weighted method with a sliding window. A dynamic relational module enhances adaptability by integrating these features into traffic data. Additionally, a spatiotemporal attention fusion module uses temporal additive attention to capture local fluctuations and spatial attention to link geographically distant yet similar nodes. Finally, an adaptive fusion method dynamically adjusts the focus on temporal and spatial features. Experimental results on PeMSD4, PeMSD8, and METR-LA datasets show that DSTFE-TIFF outperforms baseline models in RMSE, MAE, and MAPE, confirming its effectiveness.
DOI: 10.25919/3x2h-ep97
title: NBDL-HXDQPC05P6YJXE
DOI: 10.25919/v3v0-nx46
title: NBDL-HXDQPC06M6YGJT
DOI: 10.25919/70gp-9r93
title: NBDL-HXDQPC08G6Z0AJ
DOI: 10.25919/fnqv-4659
title: NBDL-HXDQPC0AM6Z7EA
DOI: 10.25919/vy3q-z067
title: NBDL-HXDQPC0CG6Z9W2
DOI: 10.25919/j5xc-nv66
title: NBDL-HXDQPC0FJ6Z2N6
DOI: 10.25919/tpah-jt09
title: NBDL-HXDQPC0JM6ZG3A
DOI: 10.25919/n011-dk72
title: NBDL-HXDQPC0MG6ZTH2
DOI: 10.25919/4sgr-sy75
title: NBDL-HXDQPC0RG6W9CJ
DOI: 10.25919/dr6a-9j52
title: NBDL-HXDQPC0SP6WF2Y
DOI: 10.25919/fm9t-5s09
title: NBDL-HXDQPC0VJ6W25P
DOI: 10.25919/m5zx-da94
title: NBDL-HXDQPC0YM6WA9T
DOI: 10.25919/5e61-zz73
title: NBDL-HXDQPC10G6WT1J
DOI: 10.5281/zenodo.16533580
title: OpenLambdaVerse: An Open-Source Dataset of AWS Lambda Functions Published on GitHub

description: Collection of repositories, their Serverless Framework configuration files, JSONL with Github and template derived metadata.



Please cite as follows:


Ángel C. Chávez-Moreno and Cristina L. Abad. OpenLambdaVerse: A Dataset and Analysis of Open-Source Serverless Applications. IEEE International Conference on Cloud Engineering (IC2E), to appear. 2025.

Link to code repository: https://github.com/disel-espol/openlambdaverse

Link to dataset (latest): https://doi.org/10.5281/zenodo.16533580
DOI: 10.5281/zenodo.17188579
title: OpenLambdaVerse: An Open-Source Dataset of AWS Lambda Functions Published on GitHub

description: Collection of repositories, their Serverless Framework configuration files, JSONL with Github and template derived metadata.



Please cite as follows:


Ángel C. Chávez-Moreno and Cristina L. Abad. OpenLambdaVerse: A Dataset and Analysis of Open-Source Serverless Applications. IEEE International Conference on Cloud Engineering (IC2E), to appear. 2025.

Link to code repository: https://github.com/disel-espol/openlambdaverse

Link to dataset (latest): https://doi.org/10.5281/zenodo.16533580