cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18302478
title: A Quantitative Biophysical Framework for Constraint-Driven Design of Microbial Tumor Microenvironment Reprogramming and Immunological Optimization

description: This dataset contains the complete computational resources supporting the manuscript “A Quantitative Biophysical Framework for Constraint-Driven Design of Microbial Tumor Microenvironment Reprogramming and Immunological Optimization.” The deposit includes all source code, parameter sets, and simulation workflows used to generate the numerical results, figures, and phase-space analyses presented in the study.

The materials are organized into three main components:





microbiotic_model_core.zipCore dynamical system implementing the coupled tumor–immune–acidity model.Includes:





Ordinary differential equation (ODE) and reaction–diffusion formulations




Enzyme-kinetic representations of microbial alkalinization mechanisms




Stability analysis tools (Jacobian evaluation, eigenvalue spectra)




Baseline parameter sets defining physiological and pathological regimes






microbiotic_prediction_framework.zipPredictive modeling and parameter inference framework.Includes:





Sensitivity analysis and parameter sweep utilities




Bayesian posterior inference and uncertainty quantification




Phase-boundary detection and regime classification tools




Scripts for generating probabilistic forecasts of tumor–immune outcomes






microbiotic_predictive_control.zipControl-theoretic and optimization modules.Includes:





Model Predictive Control (MPC) implementations for microbial dosing strategies




Constraint-driven optimization of alkalinization and immunomodulation




Early-response classifiers for therapeutic success/failure prediction




Simulation pipelines linking control inputs to qualitative system transitions





Together, these datasets provide a complete, reproducible implementation of the biophysical framework developed in the manuscript. They enable independent verification of all numerical results and allow extension of the modeling framework to alternative microbial strains, tumor microenvironment parameters, or therapeutic objectives.

All simulations were performed using Python and standard scientific computing libraries (NumPy, SciPy, Matplotlib). Detailed documentation and example scripts are included within each archive to facilitate reuse and reproducibility.

This deposit establishes a permanent, citable computational record of the theoretical and numerical foundations of the study.





License: MIT License. The software is freely available for use, modification, and redistribution with attribution.
DOI: 10.5281/zenodo.18302477
title: A Quantitative Biophysical Framework for Constraint-Driven Design of Microbial Tumor Microenvironment Reprogramming and Immunological Optimization

description: This dataset contains the complete computational resources supporting the manuscript “A Quantitative Biophysical Framework for Constraint-Driven Design of Microbial Tumor Microenvironment Reprogramming and Immunological Optimization.” The deposit includes all source code, parameter sets, and simulation workflows used to generate the numerical results, figures, and phase-space analyses presented in the study.

The materials are organized into three main components:





microbiotic_model_core.zipCore dynamical system implementing the coupled tumor–immune–acidity model.Includes:





Ordinary differential equation (ODE) and reaction–diffusion formulations




Enzyme-kinetic representations of microbial alkalinization mechanisms




Stability analysis tools (Jacobian evaluation, eigenvalue spectra)




Baseline parameter sets defining physiological and pathological regimes






microbiotic_prediction_framework.zipPredictive modeling and parameter inference framework.Includes:





Sensitivity analysis and parameter sweep utilities




Bayesian posterior inference and uncertainty quantification




Phase-boundary detection and regime classification tools




Scripts for generating probabilistic forecasts of tumor–immune outcomes






microbiotic_predictive_control.zipControl-theoretic and optimization modules.Includes:





Model Predictive Control (MPC) implementations for microbial dosing strategies




Constraint-driven optimization of alkalinization and immunomodulation




Early-response classifiers for therapeutic success/failure prediction




Simulation pipelines linking control inputs to qualitative system transitions





Together, these datasets provide a complete, reproducible implementation of the biophysical framework developed in the manuscript. They enable independent verification of all numerical results and allow extension of the modeling framework to alternative microbial strains, tumor microenvironment parameters, or therapeutic objectives.

All simulations were performed using Python and standard scientific computing libraries (NumPy, SciPy, Matplotlib). Detailed documentation and example scripts are included within each archive to facilitate reuse and reproducibility.

This deposit establishes a permanent, citable computational record of the theoretical and numerical foundations of the study.





License: MIT License. The software is freely available for use, modification, and redistribution with attribution.
DOI: 10.5281/zenodo.18302793
title: Local vibrational mode analysis of phonon dispersion relations in crystals

description: Data for manuscript Local vibrational mode analysis of phonon dispersion relations in crystals
DOI: 10.5281/zenodo.18302794
title: Local vibrational mode analysis of phonon dispersion relations in crystals

description: Data for manuscript Local vibrational mode analysis of phonon dispersion relations in crystals
DOI: 10.15468/dl.qpeh98
title: Occurrence Download

description: A dataset containing 4017 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((104.045 2.01918, 103.974694 2.013612, 103.90612 1.997044, 103.840969 1.969885, 103.780844 1.932804, 103.727228 1.886714, 103.68144 1.832752, 103.644608 1.772246, 103.617638 1.706686, 103.601192 1.637689, 103.595675 1.566952, 103.601222 1.496217, 103.617694 1.427226, 103.644686 1.361677, 103.681532 1.301184, 103.727324 1.247236, 103.780936 1.201162, 103.841047 1.164094, 103.906177 1.136945, 103.974724 1.120384, 104.045 1.114818, 104.115276 1.120384, 104.183823 1.136945, 104.248953 1.164094, 104.309064 1.201162, 104.362676 1.247236, 104.408468 1.301184, 104.445314 1.361677, 104.472306 1.427226, 104.488778 1.496217, 104.494325 1.566952, 104.488808 1.637689, 104.472362 1.706686, 104.445392 1.772246, 104.40856 1.832752, 104.362772 1.886714, 104.309156 1.932804, 104.249031 1.969885, 104.18388 1.997044, 104.115306 2.013612, 104.045 2.01918))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 4017 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000041-260119153935675/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.28255886.v3
title: READ ME

description: Instructions for use of the files found in this project, including additional scripts and an updated plugin for troubleshooting.
DOI: 10.5281/zenodo.18231265
title: Valley-bottom wetland agricultural conversion and recovery shape greenhouse gas dynamics and soil carbon sequestration in an African tropical highland system.

description: This data set contains soil flux measurements for CO2, CH4, and N2O from 28 wetlands in Taita Hills Kenya from converted, recovering, and one intact wetland measured bi-weekly from November 2022 - March 2024. Manual static chamber method was used.  The data set also include soil carbon, nitrogen, and phosphorus concentrations, moisture content, bulk density, and soil temperature.
DOI: 10.5281/zenodo.18231266
title: Valley-bottom wetland agricultural conversion and recovery shape greenhouse gas dynamics and soil carbon sequestration in an African tropical highland system.

description: This data set contains soil flux measurements for CO2, CH4, and N2O from 28 wetlands in Taita Hills Kenya from converted, recovering, and one intact wetland measured bi-weekly from November 2022 - March 2024. Manual static chamber method was used.  The data set also include soil carbon, nitrogen, and phosphorus concentrations, moisture content, bulk density, and soil temperature.
DOI: 10.5281/zenodo.18302911
title: Radlkoferotoma Kuntze. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18302910
title: Radlkoferotoma Kuntze. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.15468/dl.2dmscw
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Esox lucius",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1885",
 "Year is less than or equal to 1889"
 ]
}

 The dataset includes 19 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000043-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3kfvah
title: Occurrence Download

description: A dataset containing 8358 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than 2016",
 "DistanceFromCentroidInMeters is null",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "OccurrenceStatus is Present",
 "PublishingOrg is 1928bdf0-f5d2-11dc-8c12-b8a03c50a862",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Specimen, Fossil, Material citation, Literature Occurrence, Unknown evidence)"
 ]
 }
 },
 "Geometry POLYGON ((2.9606809447746496 42.637074153325266, 2.960591565913497 42.637055749453616, 2.960761633032068 42.636605488837716, 2.9608432250807906 42.63648474547652, 2.9611167404525394 42.63549130114095, 2.9635458968042467 42.63248490776787, 2.9648856352908544 42.63050192947281, 2.9717906502066285 42.62597138284842, 2.9726002317982876 42.62561653250211, 2.972791522596244 42.62553272409463, 2.97301700911462 42.6254338217894, 2.9800647362716397 42.62335774182579, 2.9876354134398717 42.622984130936835, 2.9949944335870473 42.62434923983422, 3.0014276739820716 42.62732061129796, 3.006310633258834 42.631609898735036, 3.006417262999654 42.63174047677207, 3.009327888872505 42.63710003940127, 3.0093989503592615 42.63799068388748, 3.009432092417448 42.638052439163445, 3.0099075694929835 42.64368185925356, 3.0079972057512694 42.649143088706666, 3.0038883949177113 42.653898629985825, 2.9979851538447173 42.65748031411896, 2.9969985816227975 42.65790743413014, 2.9907083141016466 42.65981785875469, 2.9839474166902016 42.6603698411378, 2.9772433897966315 42.659520311767686, 2.971119284877506 42.657335556323474, 2.970483080677479 42.657020917928435, 2.970272550943276 42.65691678975006, 2.9643383426383223 42.65276105721751, 2.9606031258921153 42.64738951762691, 2.9594875911442404 42.64140809291268, 2.9606809447746496 42.637074153325266))"
 ]
}

 The dataset includes 8358 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000044-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q8ywgx
title: Occurrence Download

description: A dataset containing 116917 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((4.365257861165057 50.81139477610762, 4.363893926574558 50.82016364345536, 4.359854615542845 50.828595334407865, 4.353293903916128 50.83636556191421, 4.344463078773204 50.843175328595045, 4.333701209778635 50.848762476694155, 4.321422164295194 50.85291183308549, 4.308098658143635 50.855463548725915, 4.294243961601539 50.85631930130749, 4.280391983148416 50.855446113607414, 4.2670765256407295 50.8528776346941, 4.254810546725068 50.84871283262402, 4.2440662551070085 50.84311215104032, 4.235256836799537 50.83629128351347, 4.228720532962615 50.828512814033374, 4.224707687747429 50.82007605567895, 4.223371256638894 50.81130548869261, 4.224761120194833 50.80253825133067, 4.228822392332879 50.79411117020439, 4.235397753831359 50.786347830561674, 4.244233687297328 50.779546181168385, 4.254990345360855 50.77396714399779, 4.267254653966707 50.769824657360076, 4.280556140846267 50.76727752443939, 4.294384887960467 50.76642336986485, 4.30821093740447 50.767294927576636, 4.321504433787872 50.76985879665786, 4.3337557628500685 50.77401671085846, 4.344494946188906 50.77960927515218, 4.353309575471104 50.78642203175298, 4.359860616203564 50.79419363148534, 4.363895480672456 50.80262580712588, 4.365257861165057 50.81139477610762))",
 "KingdomKey is one of (Animalia, Fungi, Plantae)",
 "Year is one of (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026)"
 ]
}

 The dataset includes 116917 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000012-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fad49b
title: Occurrence Download

description: A dataset containing 2214 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is White shark tagging off New Zealand"
 ]
}

 The dataset includes 2214 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000045-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8mjfwz
title: Occurrence Download

description: A dataset containing 81234 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-50.0",
 "DatasetKey is iNaturalist Research-grade Observations",
 "GadmGid is one of (CAN.11_1, CAN.9_1)",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 81234 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000030-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18302920
title: Radlkoferotoma berroi (Hutch.) R.M.King & H.Rob. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18302921
title: Radlkoferotoma berroi (Hutch.) R.M.King & H.Rob. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.15468/whv4ya
title: A new species of black fly in the Simulium (Simulium) melanopus species-group (Diptera: Simuliidae) from Sarawak, Malaysia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Takaoka, Hiroyuki (2025): A new species of black fly in the Simulium (Simulium) melanopus species-group (Diptera: Simuliidae) from Sarawak, Malaysia. Zootaxa 5729 (3): 477-484, DOI: 10.11646/zootaxa.5729.3.6, URL: https://doi.org/10.11646/zootaxa.5729.3.6AbstractSimulium (Simulium) puehense sp. nov. is described based on a female and its pupal exuviae and cocoon collected from Sarawak, Malaysia. This new species is assigned to the S. melanopus species-group and is characterized in the female by the haired basal portion of the radial vein, and in the pupa by the frons densely covered with tubercles, relatively stout facial and thoracic trichomes, and cocoon shoe-shaped with a few small open spaces anteriorly. Taxonomic notes are given to separate this new species from related species. This is the tenth member of the S. melanopus species-group in Borneo. Keys to identify all 10 species in the S. melanopus species-group in Borneo are provided.
DOI: 10.15468/dl.59nrr2
title: Occurrence Download

description: A dataset containing 139 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((101.387 13.525944, 101.314747 13.52037, 101.244284 13.503785, 101.177353 13.4766, 101.115609 13.439488, 101.060578 13.393367, 101.013616 13.339377, 100.975877 13.278852, 100.948286 13.213287, 100.931515 13.144299, 100.925969 13.073589, 100.931775 13.002898, 100.948779 12.933968, 100.976556 12.868492, 101.014414 12.808079, 101.061418 12.754214, 101.116408 12.708217, 101.178032 12.671217, 101.244777 12.644122, 101.315007 12.627594, 101.387 12.62204, 101.458993 12.627594, 101.529223 12.644122, 101.595968 12.671217, 101.657592 12.708217, 101.712582 12.754214, 101.759586 12.808079, 101.797444 12.868492, 101.825221 12.933968, 101.842225 13.002898, 101.848031 13.073589, 101.842485 13.144299, 101.825714 13.213287, 101.798123 13.278852, 101.760384 13.339377, 101.713422 13.393367, 101.658391 13.439488, 101.596647 13.4766, 101.529716 13.503785, 101.459253 13.52037, 101.387 13.525944))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 139 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000046-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/s6tx-d739
title: Diffusion of Facebook Posts with 100 or More Reshares

description: This dataset contains information about all content reshared 100 times or more from July 1, 2020 through February 1, 2021. Each row of the dataset corresponds to properties of an individual reshare tree. Each column contains a value, or set of values, that aggregates data for that specific reshare tree over the study period.
description: The U.S. 2020 Facebook and Instagram Election Study (US 2020 FIES) is a partnership between Meta and academic researchers to understand the impact of Facebook and Instagram on key political attitudes and behaviors during the US 2020 election.
DOI: 10.6084/m9.figshare.28255886
title: READ ME

description: Instructions for use of the files found in this project, including additional scripts and an updated plugin for troubleshooting.
DOI: 10.6084/m9.figshare.28255886.v5
title: READ ME

description: Instructions for use of the files found in this project, including additional scripts and an updated plugin for troubleshooting.
DOI: 10.34740/kaggle/dsv/14550176
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.6084/m9.figshare.28255886.v4
title: READ ME

description: Instructions for use of the files found in this project, including additional scripts and an updated plugin for troubleshooting.
DOI: 10.25505/fiz.icsd.cc2bzr7b
title: CSD 2174502: Experimental Crystal Structure Determination

description: Related Article: Trent M Kyrk, Ellis R Kennedy, Jorge Galeano-Cabral, Kaya Wei, Gregory T McCandless, Mary C Scott, Ryan E Baumbach, Julia Y Chan|2022|JPhys Mater.|50/4|044007|doi:10.1088/2515-7639/ac9ad9
description: Related Article: Trent M. Kyrk, Ellis R. Kennedy, Jorge Galeano-Cabral, Gregory T. McCandless, Mary C. Scott, Ryan E. Baumbach, Julia Y. Chan|2024|Sci. Adv.|10|eadl2818|doi:10.1126/sciadv.adl2818
description: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18256330
title: The direct democracy paradox: Microtargeting and issue ownership in Swiss online political ads

description: This dataset contains the raw and annotated data supporting the findings of the research paper: "Talking Past Each Other": Issue Ownership and Microtargeting in Swiss Online Political Ads.

Switzerland's system of direct democracy, with its frequent popular referenda, offers a unique context for studying online political advertising. This study presents a large-scale analysis of approximately 40,000 political ads published on Facebook and Instagram in Switzerland between 2021 and 2025. The research examines demographic microtargeting, partisan strategies in referenda and. federal elections.

Data Files

The repository includes the following four files:





ads.zip: A compressed archive containing the raw text and metadata of the collected advertisements. The data is organized into three sub-folders by language: German (DE), French (FR), and Italian (IT).




federal_elections_authors_annotation.csv: A manually curated list of authors who published at least one ad in the 30 days preceding the 2023 Swiss federal elections. Each author is labeled with:





Political affiliation.




Relevance to the federal election.




Entity type (Party, NGO, Newspaper, Committee, Union, or Association).




Specific linkage to a political party or individual politician.






federal_election_gpt_topic.json: Results of an automated annotation process using GPT-4o for ads published within the 30-day window of the federal election. It identifies whether an ad is election-relevant and provides up to three thematic keywords describing the ad's topic.




referendum_gpt_stance.json: Annotated data for ads published within 30 days of the 42 referenda held during the study period. This file identifies the ad's relevance to a specific referendum and its stance ("Yes", "No", or "Neutral") as determined by GPT-4o.



 

The data collection was initiated via the Meta Ad Library API using election-related keywords in three national languages. For full transparency, manual label verification on a random sample of 100 ads confirmed a 100% accuracy rate for referendum stance and 96% for federal election topic related keywords.