cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.9juusv
title: Occurrence Download

description: A dataset containing 3337 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((143.27605 21.32831,155.19202 45.39855,105.26417 37.41485,77.61915 37.17654,73.81359 33.388,76.89128 29.25938,72.83774 8.91654,103.3057 -7.03481,136.48728 -23.81933,154.26776 -48.03105,170.91331 -10.20024,143.27605 21.32831))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Ehretia acuminata"
 ]
}

 The dataset includes 3337 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011432-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17505210
title: Useful Tree Species for Africa: files for the 2012 Google Earth version

description: This Zenodo archive provides a backup of files made available via https://www.worldagroforestry.org/output/useful-tree-species-africa

Hint: when using the Excel species selectors, check via the Tropicos hyperlink for taxonomic revisions in World Flora Online.

Updated information for the Useful Tree Species for Africa is available from this shinyapp: https://patspo.shinyapps.io/UsefulTreeSpecies4Africa/

 

Follow this link to read Frank White's 1983 The Vegetation of Africa.

Read this article to learn more about the history and methods used by Frank White: White, F. (1993). The AETFAT chorological classification of Africa: history, methods and applications. Bulletin du jardin botanique national de Belgique/Bulletin van de Nationale Plantentuin van België, 225-281. https://www.jstor.org/stable/3668279?origin=JSTOR-pdf

 

Please check the Global Tree Knowledge Platform for a wider set of databases, interactive maps and other resources developed at CIFOR-ICRAF to select "the right tree for the right place, climate and purpose".
DOI: 10.5281/zenodo.17505211
title: Useful Tree Species for Africa: files for the 2012 Google Earth version

description: This Zenodo archive provides a backup of files made available via https://www.worldagroforestry.org/output/useful-tree-species-africa

Hint: when using the Excel species selectors, check via the Tropicos hyperlink for taxonomic revisions in World Flora Online.

Updated information for the Useful Tree Species for Africa is available from this shinyapp: https://patspo.shinyapps.io/UsefulTreeSpecies4Africa/

 

Follow this link to read Frank White's 1983 The Vegetation of Africa.

Read this article to learn more about the history and methods used by Frank White: White, F. (1993). The AETFAT chorological classification of Africa: history, methods and applications. Bulletin du jardin botanique national de Belgique/Bulletin van de Nationale Plantentuin van België, 225-281. https://www.jstor.org/stable/3668279?origin=JSTOR-pdf

 

Please check the Global Tree Knowledge Platform for a wider set of databases, interactive maps and other resources developed at CIFOR-ICRAF to select "the right tree for the right place, climate and purpose".
DOI: 10.15468/dl.m8a642
title: Occurrence Download

description: A dataset containing 2487 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Fauna y Flora del Complejo Parques Solares de Bolívar, 2020-2022"
 ]
}

 The dataset includes 2487 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011434-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17505246
title: SUDEXP-TE1

description: This is the full set of data for the analysis of 9x9 Sudoku puzzles in the T&E(1) kingdom, via (1+BRT)-expansion of T&E(1) minimals, as explained in the book: BERTHIER Denis, Hierarchical Classifications in Constraint Satisfaction (Third Edition), Lulu Press, October 2025, ISBN 978-1-326-05648-3.
DOI: 10.5281/zenodo.17505247
title: SUDEXP-TE1

description: This is the full set of data for the analysis of 9x9 Sudoku puzzles in the T&E(1) kingdom, via (1+BRT)-expansion of T&E(1) minimals, as explained in the book: BERTHIER Denis, Hierarchical Classifications in Constraint Satisfaction (Third Edition), Lulu Press, October 2025, ISBN 978-1-326-05648-3.
DOI: 10.15468/dl.8sdtn7
title: Occurrence Download

description: A dataset containing 3460 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium candidum"
 ]
}

 The dataset includes 3460 records from 116 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011435-251025141854904/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.30061432.v2
title: Supporting information for "Breaching the border during Cenozoic eastward growth of Tibetan Plateau revealed by secular magmatic pulses"

description: Supporting information for "Breaching the border during Cenozoic eastward growth of Tibetan Plateau revealed by secular magmatic pulses", including Table S1 to S8.<br>
DOI: 10.15468/dl.xan52n
title: Occurrence Download

description: A dataset containing 1399 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium fasciculatum"
 ]
}

 The dataset includes 1399 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011437-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17461781
title: Datasets for: "Synapar: A Large Decision Model Utilizing a Hierarchical Temporal-Spatial Architecture for Financial Time-Series Trading Decisions"

description: Abstract

Financial time-series trading decisions are persistently challenged by the highly non-stationary nature and low signal-to-noise ratio. This manuscript introduces Synapar, a Large Decision Model (LDM) utilizing an innovative hierarchical temporal-spatial (HTS) architecture, designed to address these challenges. We propose a novel training paradigm that transforms imitation learning into a supervised learning problem. This methodology first utilizes an "oracle-view" optimal strategy solver, based on dynamic programming, to generate theoretically optimal expert trajectories from complete historical K-line data. Subsequently, the Synapar model is trained to imitate these expert behaviors. The core of the model is its HTS architecture, which is engineered to perform deep feature extraction and model the dynamic evolution of market states across both spatial and temporal dimensions. This manuscript elaborates on the complete methodology, from expert trajectory generation and feature engineering to the model architecture and training paradigm. In preliminary inference validation, the v0.1.0-mini-alpha version of the model achieved average end-point returns of 34.68% and 49.67% (using maximum context lengths of 256 and 512, respectively) on 1-day frequency data from the main test set. On an independent CSI 300 test set, it achieved average end-point returns of 14.00% and 43.92% under the same lengths. While the model is currently closed-source, a public inference demonstration page https://synapar-0-1-0-mini-alpha-frontend.vercel.app and a public API endpoint are provided for further research and evaluation.

Dataset for Synapar v0.1.0-mini-alpha

This repository contains the complete dataset for the training, validation, and inference-testing of the Synapar v0.1.0-mini-alpha model.

This dataset is released in support of the research paper: "Synapar: A Large Decision Model Utilizing a Hierarchical Temporal-Spatial Architecture for Financial Time-Series Trading Decisions".

The data is organized into a primary training set, a primary test set, and several independent test sets to evaluate model generalization, including CSI 300, S&P 500, and China futures continuous contracts.
DOI: 10.5281/zenodo.17461782
title: Datasets for: "Synapar: A Large Decision Model Utilizing a Hierarchical Temporal-Spatial Architecture for Financial Time-Series Trading Decisions"

description: Abstract

Financial time-series trading decisions are persistently challenged by the highly non-stationary nature and low signal-to-noise ratio. This manuscript introduces Synapar, a Large Decision Model (LDM) utilizing an innovative hierarchical temporal-spatial (HTS) architecture, designed to address these challenges. We propose a novel training paradigm that transforms imitation learning into a supervised learning problem. This methodology first utilizes an "oracle-view" optimal strategy solver, based on dynamic programming, to generate theoretically optimal expert trajectories from complete historical K-line data. Subsequently, the Synapar model is trained to imitate these expert behaviors. The core of the model is its HTS architecture, which is engineered to perform deep feature extraction and model the dynamic evolution of market states across both spatial and temporal dimensions. This manuscript elaborates on the complete methodology, from expert trajectory generation and feature engineering to the model architecture and training paradigm. In preliminary inference validation, the v0.1.0-mini-alpha version of the model achieved average end-point returns of 34.68% and 49.67% (using maximum context lengths of 256 and 512, respectively) on 1-day frequency data from the main test set. On an independent CSI 300 test set, it achieved average end-point returns of 14.00% and 43.92% under the same lengths. While the model is currently closed-source, a public inference demonstration page https://synapar-0-1-0-mini-alpha-frontend.vercel.app and a public API endpoint are provided for further research and evaluation.

Dataset for Synapar v0.1.0-mini-alpha

This repository contains the complete dataset for the training, validation, and inference-testing of the Synapar v0.1.0-mini-alpha model.

This dataset is released in support of the research paper: "Synapar: A Large Decision Model Utilizing a Hierarchical Temporal-Spatial Architecture for Financial Time-Series Trading Decisions".

The data is organized into a primary training set, a primary test set, and several independent test sets to evaluate model generalization, including CSI 300, S&P 500, and China futures continuous contracts.
DOI: 10.15151/esrf-es-2232067975
title: Italian CryoEM Bag II (ICB-II)

description: This BAG application builds on the development of single particle cryoEM in the Italian Structural Biology community, as in Italy there is no top-end instrument isopen to rhe structural biology community.
The groups in this application have acquired know-how in cryoEM through international collaborations or by acquiring medium-level in-house equipment. Access tothe CM01 beamline at the ESRF since August 2020 has allowed the development of projects from groups that do not have in-house equipment that resulted inpaper in publication on Nucleic Acid Research NAR.
We now have six screening microscopes in Italy and two more are being funded, making the access to CM01 more demanded and relevant for high-resolution
data and, consequently high profile publications
DOI: 10.15468/dl.53hj63
title: Occurrence Download

description: A dataset containing 103 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Nigeria",
 "TaxonKey is Cercopithecus mona"
 ]
}

 The dataset includes 103 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011438-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.te9cmm
title: Occurrence Download

description: A dataset containing 585 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium kentuckiense"
 ]
}

 The dataset includes 585 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011440-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kkas85
title: Occurrence Download

description: A dataset containing 112348 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 04ce62dd-30ec-4d98-8b30-b09cafc3ac38",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 112348 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011436-251025141854904/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.28891607
title: <b>A Railway Network Dataset Incorporating Multi-Type Train Operation Records and Train Scheduling</b>

description: Train operation data contains valuable insights, yet the datasets released by railway companies are often unstandardized or incomplete, limiting their directapplicability in research. Publicly available railway network datasets thatcomprehensively integrate train operation records with scheduling information remain rare. To support research in large-scale complex networks, dynamic systems, and intelligent transportation, we present the Italian Railway Network Dataset. This dataset includes operational records for various traintypes, station locations, inter-station mileage, weather conditions, and scheduling data. By providing detailed and structured railway data, our dataset facilitates research in diverse areassuch as spatio-temporal pattern mining, network topology analysis, and the study of train delay propagation and distribution. Moreover,it offers valuable support for addressing operational challenges in the railwaydomain, including timetable optimization, intelligent transportationsystems, and advanced scheduling strategies.
DOI: 10.6084/m9.figshare.28891607.v1
title: <b>A Railway Network Dataset Incorporating Multi-Type Train Operation Records and Train Scheduling</b>

description: Train operation data contains valuable insights, yet the datasets released by railway companies are often unstandardized or incomplete, limiting their directapplicability in research. Publicly available railway network datasets thatcomprehensively integrate train operation records with scheduling information remain rare. To support research in large-scale complex networks, dynamic systems, and intelligent transportation, we present the Italian Railway Network Dataset. This dataset includes operational records for various traintypes, station locations, inter-station mileage, weather conditions, and scheduling data. By providing detailed and structured railway data, our dataset facilitates research in diverse areassuch as spatio-temporal pattern mining, network topology analysis, and the study of train delay propagation and distribution. Moreover,it offers valuable support for addressing operational challenges in the railwaydomain, including timetable optimization, intelligent transportationsystems, and advanced scheduling strategies.
DOI: 10.6084/m9.figshare.28891607.v2
title: <b>A Railway Network Dataset Incorporating Multi-Type Train Operation Records and Train Scheduling</b>

description: Train operation data contains valuable insights, yet the datasets released by railway companies are often unstandardized or incomplete, limiting their directapplicability in research. Publicly available railway network datasets thatcomprehensively integrate train operation records with scheduling information remain rare. To support research in large-scale complex networks, dynamic systems, and intelligent transportation, we present the Italian Railway Network Dataset. This dataset includes operational records for various traintypes, station locations, inter-station mileage, weather conditions, and scheduling data. By providing detailed and structured railway data, our dataset facilitates research in diverse areassuch as spatio-temporal pattern mining, network topology analysis, and the study of train delay propagation and distribution. Moreover,it offers valuable support for addressing operational challenges in the railwaydomain, including timetable optimization, intelligent transportationsystems, and advanced scheduling strategies.
DOI: 10.15468/dl.c7t4zh
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cistanche deserticola"
 ]
}

 The dataset includes 120 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011442-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ypstn
title: Occurrence Download

description: A dataset containing 3464 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium montanum"
 ]
}

 The dataset includes 3464 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011443-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.knf3es
title: Occurrence Download

description: A dataset containing 7084 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreo de seguimiento de fauna pozo Lisama 158, décimo informe"
 ]
}

 The dataset includes 7084 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011444-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pqp8z7
title: Occurrence Download

description: A dataset containing 22453 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium parviflorum"
 ]
}

 The dataset includes 22453 records from 238 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011445-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yx5adn
title: Occurrence Download

description: A dataset containing 977 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Africa, Asia)",
 "Geometry POLYGON((-37.90845 32.59675,8.8126 14.05966,96.58008 22.76072,133.40713 18.64981,153.18764 48.79717,120.87965 81.91042,-37.90845 32.59675))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Buglossoides arvensis"
 ]
}

 The dataset includes 977 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011446-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.66tm7h
title: Occurrence Download

description: A dataset containing 53436 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cypripedium acaule"
 ]
}

 The dataset includes 53436 records from 232 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011429-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/cc5kqjy
title: CCDC 165990: Experimental Crystal Structure Determination

description: Related Article: D.Bellamy, N.G.Connelly, G.R.Lewis, A.G.Orpen|2002|CrystEngComm|4|68|doi:10.1039/b111164g
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: 10.5517/cc5kqkz
title: CCDC 165991: Experimental Crystal Structure Determination

description: Related Article: D.Bellamy, N.G.Connelly, G.R.Lewis, A.G.Orpen|2002|CrystEngComm|4|68|doi:10.1039/b111164g
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: 10.5517/cc5kql0
title: CCDC 165992: Experimental Crystal Structure Determination

description: Related Article: D.Bellamy, N.G.Connelly, G.R.Lewis, A.G.Orpen|2002|CrystEngComm|4|68|doi:10.1039/b111164g
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: 10.5517/cc5kqm1
title: CCDC 165993: Experimental Crystal Structure Determination

description: Related Article: D.Bellamy, N.G.Connelly, G.R.Lewis, A.G.Orpen|2002|CrystEngComm|4|68|doi:10.1039/b111164g
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: 10.5517/cc5jp9n
title: CCDC 164991: Experimental Crystal Structure Determination

description: Related Article: E.S.Lang, R.A.Zan, C.C.Gatto, R.A.Burrow, E.M.Vazquez-Lopez|2002|Eur.J.Inorg.Chem.|2002|331|doi:10.1002/1099-0682(20022)2002:2<331::AID-EJIC331>3.0.CO;2-O
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: 10.5517/cc5kqn2
title: CCDC 165994: Experimental Crystal Structure Determination

description: Related Article: D.Bellamy, N.G.Connelly, G.R.Lewis, A.G.Orpen|2002|CrystEngComm|4|68|doi:10.1039/b111164g
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: 10.5517/cc5jpbp
title: CCDC 164992: Experimental Crystal Structure Determination

description: Related Article: E.S.Lang, R.A.Zan, C.C.Gatto, R.A.Burrow, E.M.Vazquez-Lopez|2002|Eur.J.Inorg.Chem.|2002|331|doi:10.1002/1099-0682(20022)2002:2<331::AID-EJIC331>3.0.CO;2-O
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.