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

description: A dataset containing 1973 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Pseudoroegneria spicata (Pursh) Á.Löve",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 1973 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005166-250227182430271/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.28532548
title: Full ESM of this study from Integrative Phylogenomics Sheds Light on the Diversity and Evolution of Fluorescence in Coral-Dwelling Gall Crabs

description: Zip file containing all ESM of this study, including Readme file. It is also available on Fig share, link is provided in the manuscript.
DOI: 10.15468/dl.c5x2tr
title: Occurrence Download

description: A dataset containing 287 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Psoralidium tenuiflorum (Pursh) Rydb.",
 "Year is less than or equal to 2000",
 "Year is greater than or equal to 1970",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 287 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005160-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25318/3310092801-eng
title: Business' or organization's plans to invest in advanced technologies over the next 12 months, first quarter of 2025

description: Business' or organization's plans to invest in advanced technologies over the next 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, first quarter of 2025.
DOI: 10.25318/3310092801-fra
title: Plans de l’entreprise ou de l’organisme en matière d’investissement dans les technologies de pointe au cours des 12 prochains mois, premier trimestre de 2025

description: Plans de l’entreprise ou de l’organisme en matière d’investissement dans les technologies de pointe au cours des 12 prochains mois, selon le Système de classification des industries de l’Amérique du Nord (SCIAN), l’effectif de l’entreprise, le type d’entreprise, l’activité de l'entreprise et le propriétaire majoritaire, premier trimestre de 2025.
DOI: 10.15468/dl.y9gyjj
title: Occurrence Download

description: A dataset listing the 21325 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Indonesia",
 "Geometry POLYGON((113.67177 -12.36017,129.55868 -11.87192,130.23471 -6.78285,114.72338 -7.04576,113.67177 -12.36017))"
 ]
}

 The dataset's 21325 records were derived from 472 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005157-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9rzfcp
title: Occurrence Download

description: A dataset containing 313470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Indonesia",
 "GbifRegion is Asia",
 "Geometry POLYGON((114.52575 -10.00407,128.09266 -11.81188,128.93532 -7.02561,114.53974 -7.6394,114.52575 -10.00407))",
 "Year 2016-2025"
 ]
}

 The dataset includes 313470 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005163-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7274/28525448
title: Engineering Active Materials by Dissipative and Programmable Host-Guest Supramolecular Motifs

description: Dynamic and dissipative supramolecular systems inspired by natural processes offer exciting opportunities to develop active materials with precise temporal and spatial control. This dissertation investigates transient hydrogels and programmable nanostructures based on cucurbit[7]uril (CB[7]) host–guest interactions, utilizing both chemically fueled and enzyme-driven mechanisms.
Chemically fueled dissipative hydrogels were first developed using dimethyl sulfate (DMS) as a reactive chemical fuel. These systems demonstrated tunable properties, including stiffness and lifetime, regulated by fuel concentration and environmental pH. Although these systems highlight the potential for time-controlled material dynamics, challenges such as fuel toxicity remain significant.
To address these limitations, enzyme-driven systems were then explored, leveraging urease-catalyzed pH-feedback reactions to achieve biocompatible transient hydrogels. These systems exhibited faster transitions and programmability, offering a sustainable and safer alternative for biomedical applications like drug delivery and tissue scaffolding.
Additionally, programmable morphological transitions were achieved in peptide amphiphile-based nanostructures, enabling reversible transformations between fibers, micelles, and aggregates. These transitions were driven by pH changes and the tunable host–guest binding affinity, demonstrating potential in nanomedicine and responsive materials.
By integrating insights from hydrogels and nanostructures, the research in this dissertation provides a unified platform for designing active materials. This research lays the foundation for advancing supramolecular systems, offering innovative solutions for biomimicry materials, drug delivery systems, and beyond. The findings underscore the transformative potential of transient and programmable materials in bridging nature-inspired adaptability with synthetic innovation.
DOI: 10.7274/28525448.v1
title: Engineering Active Materials by Dissipative and Programmable Host-Guest Supramolecular Motifs

description: Dynamic and dissipative supramolecular systems inspired by natural processes offer exciting opportunities to develop active materials with precise temporal and spatial control. This dissertation investigates transient hydrogels and programmable nanostructures based on cucurbit[7]uril (CB[7]) host–guest interactions, utilizing both chemically fueled and enzyme-driven mechanisms.
Chemically fueled dissipative hydrogels were first developed using dimethyl sulfate (DMS) as a reactive chemical fuel. These systems demonstrated tunable properties, including stiffness and lifetime, regulated by fuel concentration and environmental pH. Although these systems highlight the potential for time-controlled material dynamics, challenges such as fuel toxicity remain significant.
To address these limitations, enzyme-driven systems were then explored, leveraging urease-catalyzed pH-feedback reactions to achieve biocompatible transient hydrogels. These systems exhibited faster transitions and programmability, offering a sustainable and safer alternative for biomedical applications like drug delivery and tissue scaffolding.
Additionally, programmable morphological transitions were achieved in peptide amphiphile-based nanostructures, enabling reversible transformations between fibers, micelles, and aggregates. These transitions were driven by pH changes and the tunable host–guest binding affinity, demonstrating potential in nanomedicine and responsive materials.
By integrating insights from hydrogels and nanostructures, the research in this dissertation provides a unified platform for designing active materials. This research lays the foundation for advancing supramolecular systems, offering innovative solutions for biomimicry materials, drug delivery systems, and beyond. The findings underscore the transformative potential of transient and programmable materials in bridging nature-inspired adaptability with synthetic innovation.
DOI: 10.23708/oxvdfb
title: Investigation of Aedes mosquitoes and their ecological determinants in Phnom Penh, Cambodia, 2019-2020

description: This dataset is related to a study of the ecology of the two mosquito species, Aedes aegypti and Aedes albopictus, vector of Dengue virus, in Phnom Penh in 2019-2020. This study was conducted by the Medical and Veterinary Entomology Unit of Institut Pasteur du Cambodge, and IRD Espace-Dev for the ecological analysis. The sampling of larvae was organized in 40 pagodas, randomly sampled among all pagodas in Phnom Penh. The collected mosquito larvae were transferred to the insectarium room to be bred at the adult stage and to identify Aedes aegypti and Aedes albopictus. A SPOT7 (@ Airbus DS 2019) satellite image acquired on the 11th of December 2019 (DINAMIS Id 2020-111-Sci) was classified using object-based image analysis with complementary OpenStreetMap data (@ OpenStreetMap contributors), in nine classes (1. Roads, 2. Built-up areas, 3. Water bodies and rivers, 4. Wetlands, 5. Dry bare areas, 6. Bare crop fields, 7. Low vegetation areas, 8. High vegetation areas, 9. Forested areas). For each of the 40 pagodas, landscape indices were calculated within a radius of 250, 500 or 1000 meters: the proportion of surface covered by each class, the patch density (the number of patches of each class per buffer zone), and the edge density (the perimeter of all the patches of each class). The entomological study was supported by an internal funding of the Institut Pasteur du Cambodge, and by the Calmette & Yersin post-doctoral grant for Dr. Pierre-Olivier Maquart. The acquisition of the SPOT7 (@ Airbus DS 2019) image was funded by the French DINAMIS and GEOSUD programs (DINAMIS Id 2020-111-Sci).
DOI: 10.15468/dd.p498f9
title: Uncovering the hidden amphipod biodiversity and its drivers in the Persian Gulf

description: Records used in [paper](https://doi.org/10.1016/j.dsr2.2025.105463) (dn)
DOI: 10.15468/dl.3ud3my
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Cyanopsitta spixii (Wagler, 1832)"
 ]
}

 The dataset includes 45 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005171-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mw7ver
title: Occurrence Download

description: A dataset containing 2005 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Crax alberti Fraser, 1852"
 ]
}

 The dataset includes 2005 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005162-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ch4sc
title: Occurrence Download

description: A dataset containing 237 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Muscarella zephyrina (Rchb.f.) Luer"
 ]
}

 The dataset includes 237 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005163-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15472/gcqnp2
title: Propagación y siembra comunitaria de árboles amenazados del Río Claro

description: I2D-BIO_2024_019. Conjunto de datos de los producto del contrato No. 24-21-452-065PS y el contrato No. 24-21-452-325, entre el Instituto de Recursos Biológicos Alexander von Humboldt y el vivero recuperando un mundo verde, el cual contiene 128 registros, con datos de la propagación y siembra de 4.163 árboles en la cuenca de Río Claro, en el marco del proyecto árboles amenazados del río Claro, financiado por fundación Franklinia. Los datos corresponden a ocho especies de árboles, de los cuales siete especies fueron priorizados por el proyecto por ser endémicas del país, pues tienen distribución en la cuenca media del río claro, en Antioquía, y además se encuentran en categoría de amenaza, según la UICN, estas especies son: Caryodaphnopsis cogolloi, Cybianthus cogolloi, Duguetia colombiana, Matisia serpicostata, Pseudoxandra sclerocarpa, Rhodostemonodaphne antioquensis y Simira hirsuta. Las otras dos especies, fueron escogidas por la comunidad por su importancia en la producción de madera, estas especies son: Cariniana pyriformis y Clathrotropis brunnea.
DOI: 10.15468/dl.qwk9ve
title: Occurrence Download

description: A dataset containing 10204150 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Orchidaceae"
 ]
}

 The dataset includes 10204150 records from 6063 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005164-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dnk8d5
title: Occurrence Download

description: A dataset containing 1668 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia acuruana Moric."
 ]
}

 The dataset includes 1668 records from 113 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001560-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14911741
title: skills2
DOI: 10.5281/zenodo.14911742
title: skills2
DOI: 10.15468/dl.9mefpx
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia funchiana Vaz & G.P.Lewis"
 ]
}

 The dataset includes 39 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001562-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c5jj9n
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia orbiculata A.C.B.Santos & L.P.Queiroz"
 ]
}

 The dataset includes 57 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001561-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.543xbp
title: Occurrence Download

description: A dataset containing 32634366 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 32634366 records from 726 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001559-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vtakhy
title: Occurrence Download

description: A dataset containing 477 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bauhinia subclavata Benth."
 ]
}

 The dataset includes 477 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001563-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sgbbbn
title: Occurrence Download

description: A dataset containing 402 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bionia pedicellata (Benth.) L.P.Queiroz"
 ]
}

 The dataset includes 402 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001565-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.urdx2g
title: Occurrence Download

description: A dataset containing 193 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calliandra aeschynomenoides Benth."
 ]
}

 The dataset includes 193 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001566-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2yu8zs
title: Occurrence Download

description: A dataset containing 789 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calliandra asplenioides (Nees) Renvoize"
 ]
}

 The dataset includes 789 records from 61 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001567-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14373955
title: BioSR for LLS-SIM: Dataset of ER (in adherent cells)

description: This is LLS-SIM dataset of ER (in adherent cells), which is a part of BioSR for LLS-SIM dataset (https://doi.org/10.5281/zenodo.14322457).

BioSR for LLS-SIM is a biological image dataset acquired using our home-built lattice light-sheet structured illumination microscopy (LLS-SIM). It currently includes paired diffraction-limited LLSM and LLS-SIM images of a variety of biology structures, constituting a high-quality volumetric SR dataset. The BioSR for LLS-SIM dataset originates from our paper [Qiao, C., Li, Z., Wang, Z., Lin, Y., ... & Li, D. (2024). Fast adaptive super-resolution lattice light-sheet microscopy for rapid, long-term, near-isotropic subcellular imaging. bioRxiv, 2024-05], serving as the supplementary data to execute meta-training or other proposed deep-learning-based algorithms, which provides sources for the community to try our methods, replicate our results, and develop their own methods for super-resolution lattice light-sheet microscopy.

The BioSR for LLS-SIM dataset includes 10 diverse task datasets from 10 distinct biological specimens (granular component, chromosomes, fibrillar center, fibrillarin, Lyso, MTs, F-actin in pollen tubes, inner mitochondrial membrane, ER in adherent Cos-7 cells and ER in mitotic Hela cells during metaphase). For each type of samples, we acquired raw LLS-SIM images from about 30-50 ROIs. For each ROI, five different levels of light intensity ranging from low to high fluorescence levels were acquired, and the images of the highest fluorescence level (i.e. the GT raw images) were reconstructed into high-quality GT LLS-SIM images via the conventional LLS-SIM reconstruction algorithm, which could be used as the groud truth in the training phase of deep-learning models.
DOI: 10.5281/zenodo.14373956
title: BioSR for LLS-SIM: Dataset of ER (in adherent cells)

description: This is LLS-SIM dataset of ER (in adherent cells), which is a part of BioSR for LLS-SIM dataset (https://doi.org/10.5281/zenodo.14322457).

BioSR for LLS-SIM is a biological image dataset acquired using our home-built lattice light-sheet structured illumination microscopy (LLS-SIM). It currently includes paired diffraction-limited LLSM and LLS-SIM images of a variety of biology structures, constituting a high-quality volumetric SR dataset. The BioSR for LLS-SIM dataset originates from our paper [Qiao, C., Li, Z., Wang, Z., Lin, Y., ... & Li, D. (2024). Fast adaptive super-resolution lattice light-sheet microscopy for rapid, long-term, near-isotropic subcellular imaging. bioRxiv, 2024-05], serving as the supplementary data to execute meta-training or other proposed deep-learning-based algorithms, which provides sources for the community to try our methods, replicate our results, and develop their own methods for super-resolution lattice light-sheet microscopy.

The BioSR for LLS-SIM dataset includes 10 diverse task datasets from 10 distinct biological specimens (granular component, chromosomes, fibrillar center, fibrillarin, Lyso, MTs, F-actin in pollen tubes, inner mitochondrial membrane, ER in adherent Cos-7 cells and ER in mitotic Hela cells during metaphase). For each type of samples, we acquired raw LLS-SIM images from about 30-50 ROIs. For each ROI, five different levels of light intensity ranging from low to high fluorescence levels were acquired, and the images of the highest fluorescence level (i.e. the GT raw images) were reconstructed into high-quality GT LLS-SIM images via the conventional LLS-SIM reconstruction algorithm, which could be used as the groud truth in the training phase of deep-learning models.
DOI: 10.5281/zenodo.14911564
title: BioSR for LLS-SIM: Dataset of ER (in adherent cells)

description: This is LLS-SIM dataset of ER (in adherent cells), which is a part of BioSR for LLS-SIM dataset (https://doi.org/10.5281/zenodo.14322457).

BioSR for LLS-SIM is a biological image dataset acquired using our home-built lattice light-sheet structured illumination microscopy (LLS-SIM). It currently includes paired diffraction-limited LLSM and LLS-SIM images of a variety of biology structures, constituting a high-quality volumetric SR dataset. The BioSR for LLS-SIM dataset originates from our paper [Qiao, C., Li, Z., Wang, Z., Lin, Y., ... & Li, D. (2024). Fast adaptive super-resolution lattice light-sheet microscopy for rapid, long-term, near-isotropic subcellular imaging. bioRxiv, 2024-05], serving as the supplementary data to execute meta-training or other proposed deep-learning-based algorithms, which provides sources for the community to try our methods, replicate our results, and develop their own methods for super-resolution lattice light-sheet microscopy.

The BioSR for LLS-SIM dataset includes 10 diverse task datasets from 10 distinct biological specimens (granular component, chromosomes, fibrillar center, fibrillarin, Lyso, MTs, F-actin in pollen tubes, inner mitochondrial membrane, ER in adherent Cos-7 cells and ER in mitotic Hela cells during metaphase). For each type of samples, we acquired raw LLS-SIM images from about 30-50 ROIs. For each ROI, five different levels of light intensity ranging from low to high fluorescence levels were acquired, and the images of the highest fluorescence level (i.e. the GT raw images) were reconstructed into high-quality GT LLS-SIM images via the conventional LLS-SIM reconstruction algorithm, which could be used as the groud truth in the training phase of deep-learning models.
DOI: 10.15468/dl.3zxpde
title: Occurrence Download

description: A dataset containing 138280 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Casuariiformes"
 ]
}

 The dataset includes 138280 records from 178 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001564-250221090833381/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.