cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17302958
title: The Speed of Light as a Consequence of Temporal Torsion: A Derivation from Mass as Twisted Time (MaTT)

description: Abstract

We derive the speed of light \(c\) not as a postulate, but as a dynamical consequence of temporal torsion within the Mass as Twisted Time (MaTT) framework. In MaTT, mass arises from topological twisting of the temporal manifold, and gravitational waves are interpreted as propagating disturbances in this time-torsion field—termed “torsion waves.” From the minimal action principle governing \(\hat{T}_\mu\), we derive the wave equation \(\square \hat{T}_\mu = 0\), which yields the dispersion relation \(k_\mu k^\mu = 0\). This implies that torsion waves propagate at exactly \(c\), the maximum processing rate of quantum time. We show that this prediction is empirically confirmed by the 2017 observation of GW170817, where gravitational waves arrived simultaneously with gamma rays to within \(10^{-15}\) precision. For supermassive black hole binaries, the associated torsion-induced spectral modulation falls in the millihertz band (\(f_* \sim 0.1–10\,\text{mHz}\)), placing it squarely within the sensitivity range of the future LISA observatory. This paper reinforces MaTT’s core claim: the speed of light is not fundamental—it emerges from the geometry of twisted time.
DOI: 10.15468/dl.nxrymt
title: Occurrence Download

description: A dataset containing 76 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Saussurea atkinsonii"
 ]
}

 The dataset includes 76 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013650-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tnyemy
title: Occurrence Download

description: A dataset containing 1333 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Morocco",
 "TaxonKey is Psychodidae"
 ]
}

 The dataset includes 1333 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013648-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/q1bkm8ma
title: Species-Environment Feedback Dataset

description: The dataset is used to investigate the impact of species-environment feedback on the probability of a species taking over the whole population.
DOI: 10.57702/kxws9jx1
title: PWR dataset

description: The dataset used in the paper is a SISO model of the fast processes in a PWR. The dataset is created using the dNEAT algorithm, which is an evolutionary algorithm that optimizes the architecture of a neural network.
DOI: 10.57702/wnsprm3a
title: Saudi License Plate Dataset

description: A dataset of Saudi license plates, both in low and high resolutions, used for training a diffusion model for license plate super-resolution.
DOI: 10.57702/jzsz03r8
title: ActiveMiles

description: The dataset is used for human activity recognition using smartphone sensor data.
DOI: 10.57702/o6rl6ejx
title: ProteinNet dataset

description: The ProteinNet dataset is a standardized data set for machine learning of protein structure.
DOI: 10.57702/eguv3cna
title: One-Class Road Detection Dataset

description: The One-Class Road Detection Dataset is a dataset for road detection, which is a challenging issue in autonomous driving.
DOI: 10.57702/s5xgowuu
title: Boosted SVM for Extracting Rules from Imbalanced Data

description: Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients.
DOI: 10.57702/gnq8w6yv
title: Query Based Event Extraction Along a Timeline

description: Query based event extraction along a timeline.
DOI: 10.57702/0wcyferj
title: OTB-2015

description: The OTB-2015 dataset is a benchmark for visual object tracking, containing 1000 videos with 1000 frames each.
DOI: 10.57702/5xk672ra
title: CityCam

description: CityCam dataset contains recordings from 212 trafﬁc cameras in the United States, with a resolution of 352x240 and a frame rate of 1 frame/per second.
DOI: 10.57702/rrc473pl
title: TRANCOS Dataset

description: The TRANCOS dataset is used for vehicle counting, which contains 1244 images of different congested traffic scenes with a total of 46796 vehicles annotated.
DOI: 10.57702/8uc357mr
title: MovieChat

description: MovieChat: From dense token to sparse memory for long video understanding.
DOI: 10.57702/2tty9tkb
title: BioCreative VI Precision Medicine Track

description: The BioCreative VI Precision Medicine Track dataset is a manually labeled corpus for gene-disease association extraction.
DOI: 10.57702/ls003xvq
title: Notre Dame

description: Iris recognition dataset with controlled illumination conditions and small dilation variation
DOI: 10.15468/dl.4stbwb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.738332 23.969928, 89.661483 23.964351, 89.586546 23.947759, 89.515383 23.920564, 89.44976 23.883443, 89.391302 23.837317, 89.34144999999999 23.783331, 89.301429 23.722822, 89.272216 23.657289, 89.254516 23.588351, 89.248746 23.517709, 89.255031 23.447105, 89.273197 23.378274, 89.30278 23.312908, 89.34303800000001 23.252611, 89.392971 23.198858, 89.451348 23.152966, 89.516734 23.116056, 89.58752699999999 23.089029, 89.66199899999999 23.072544, 89.738332 23.067004, 89.81466500000001 23.072544, 89.88913700000001 23.089029, 89.95993 23.116056, 90.025316 23.152966, 90.083693 23.198858, 90.13362600000001 23.252611, 90.173884 23.312908, 90.203467 23.378274, 90.221633 23.447105, 90.227918 23.517709, 90.222148 23.588351, 90.204448 23.657289, 90.175235 23.722822, 90.135214 23.783331, 90.085362 23.837317, 90.026904 23.883443, 89.961281 23.920564, 89.890118 23.947759, 89.815181 23.964351, 89.738332 23.969928))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080124-251120083545085/datasets/export for details.
DOI: 10.5281/zenodo.18175583
title: HOLSEA-NL: Holocene water level and sea-level indicator dataset for the Netherlands

description: This dataset contains an assembly of geological water-level indicators, relevant for studying relative sea level rise (RSLR), regional subsidence quantification and causal breakdown, coastal prism accommodation and Holocene aggradation chronology of the Holocene Netherlands. It gives a sources-referenced, uniform overview of 658 basal geological water-level indicators collected from original research of various type and application (140 primary references). From the indicators, 59% was collected in 1950-2000, mainly in academic studies and survey mapping campaigns; 37% was collected in 2000-2020 in academic studies and archaeological surveying projects, 4% was newly collected (this study), the latter mainly in previously under sampled central and northern Netherlands regions. 117 are true sea-level indicators (so-called SLIPs), the majority of datapoints (536) are inland water level indicators that are upper limiting to sea-level. The total number of entries is 712, because we included some literature mentioned rejected samples and deep positioned intercalated water level indicators.

The dataset is compiled in the so-called HOLSEA workbook format. It covers measured, calculated and classification fields defining the geological observational data and its uncertainties, allowing to document and assess indicative meaning adapted to specific use variants. Hereto, the workbook contains expansions to the original format. See Related Works (ESSD paper: De Wit et al. 2024).
description: Main change v3.0:



In v2.0, the ULD-1 data (Tidal ULD) were erroneously not corrected for the past tidal amplitude, in the additional columns, excluding the background tectonic correction (columns 71**-73**). This has now been corrected.
description: The research presented in this dataset is part of a PhD research (K. de Wit; Utrecht University) within the project Living on Soft Soils: Subsidence and Society (grantnr.: NWA.1160.18.259). This project is funded by the Dutch Research Council (NWO-NWA-ORC), Utrecht University, Wageningen University, Delft University of Technology, Ministry of Infrastructure & Water Management, Ministry of the Interior & Kingdom Relations, Deltares, Wageningen Environmental Research, TNO-Geological Survey of The Netherlands, STOWA, Water Authority: Hoogheemraadschap de Stichtse Rijnlanden, Water Authority: Drents Overijsselse Delta, Province of Utrecht, Province of Zuid-Holland, Municipality of Gouda, Platform Soft Soil, Sweco, Tauw BV, NAM.
DOI: 10.57702/t2lmgfnt
title: VisDA-2017

description: VisDA-2017 is a simulation-to-real dataset with two extremely distinct domains: Synthetic renderings of 3D models and Real collected from photo-realistic or real-image datasets.
DOI: 10.5281/zenodo.11098446
title: HOLSEA-NL: Holocene water level and sea-level indicator dataset for the Netherlands

description: This dataset contains an assembly of geological water-level indicators, relevant for studying relative sea level rise (RSLR), regional subsidence quantification and causal breakdown, coastal prism accommodation and Holocene aggradation chronology of the Holocene Netherlands. It gives a sources-referenced, uniform overview of 658 basal geological water-level indicators collected from original research of various type and application (140 primary references). From the indicators, 59% was collected in 1950-2000, mainly in academic studies and survey mapping campaigns; 37% was collected in 2000-2020 in academic studies and archaeological surveying projects, 4% was newly collected (this study), the latter mainly in previously under sampled central and northern Netherlands regions. 117 are true sea-level indicators (so-called SLIPs), the majority of datapoints (536) are inland water level indicators that are upper limiting to sea-level. The total number of entries is 712, because we included some literature mentioned rejected samples and deep positioned intercalated water level indicators.

The dataset is compiled in the so-called HOLSEA workbook format. It covers measured, calculated and classification fields defining the geological observational data and its uncertainties, allowing to document and assess indicative meaning adapted to specific use variants. Hereto, the workbook contains expansions to the original format. See Related Works (ESSD paper: De Wit et al. 2024).
description: Main change v3.0:



In v2.0, the ULD-1 data (Tidal ULD) were erroneously not corrected for the past tidal amplitude, in the additional columns, excluding the background tectonic correction (columns 71**-73**). This has now been corrected.
description: The research presented in this dataset is part of a PhD research (K. de Wit; Utrecht University) within the project Living on Soft Soils: Subsidence and Society (grantnr.: NWA.1160.18.259). This project is funded by the Dutch Research Council (NWO-NWA-ORC), Utrecht University, Wageningen University, Delft University of Technology, Ministry of Infrastructure & Water Management, Ministry of the Interior & Kingdom Relations, Deltares, Wageningen Environmental Research, TNO-Geological Survey of The Netherlands, STOWA, Water Authority: Hoogheemraadschap de Stichtse Rijnlanden, Water Authority: Drents Overijsselse Delta, Province of Utrecht, Province of Zuid-Holland, Municipality of Gouda, Platform Soft Soil, Sweco, Tauw BV, NAM.
DOI: 10.57702/3o8kgn99
title: Causal Recurrent Variational Autoencoder for Medical Time Series Generation

description: Causal recurrent variational autoencoder (CR-VAE) for medical time series generation
DOI: 10.57702/ij9ifajv
title: Knowledge Network and Social Media Based Reputation Management

description: The dataset used in this research is a collection of employee knowledge network and personal reputation on social media.
DOI: 10.57702/e46gl8tl
title: Medical Image Registration via Neural Fields

description: Medical Image Registration via Neural Fields
DOI: 10.57702/vaadsotl
title: Copolymer dataset

description: The dataset used in this study for predicting reactivity ratios of copolymers.
DOI: 10.15468/dl.85w8ps
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.923554 23.832833, 88.84678700000001 23.827257, 88.771928 23.810664, 88.70084 23.78347, 88.635285 23.746349, 88.576888 23.700223, 88.52708699999999 23.646236, 88.48710699999999 23.585727, 88.45792299999999 23.520194, 88.44023900000001 23.451255, 88.43447399999999 23.380612, 88.44075100000001 23.310006, 88.458896 23.241174, 88.48844699999999 23.175807, 88.52866299999999 23.115507, 88.57854399999999 23.061753, 88.636861 23.015859, 88.70218 22.978948, 88.772902 22.951919, 88.84729900000001 22.935434, 88.923554 22.929894, 88.99981 22.935434, 89.074207 22.951919, 89.14492799999999 22.978948, 89.21024800000001 23.015859, 89.268564 23.061753, 89.31844599999999 23.115507, 89.358661 23.175807, 89.388212 23.241174, 89.406358 23.310006, 89.41263499999999 23.380612, 89.40687 23.451255, 89.389186 23.520194, 89.36000199999999 23.585727, 89.32002199999999 23.646236, 89.27022100000001 23.700223, 89.211823 23.746349, 89.146269 23.78347, 89.07518 23.810664, 89.000322 23.827257, 88.923554 23.832833))"},{"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 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080040-251120083545085/datasets/export for details.
DOI: 10.57702/hi7jydup
title: CraftAssist

description: A Minecraft dataset for annotating buildings with labels.
DOI: 10.57702/oa6coiop
title: Open-vocabulary panoptic segmentation with text-to-image diffusion models

description: Open-vocabulary panoptic segmentation with text-to-image diffusion models.
DOI: 10.57702/bp4jhqnj
title: A large annotated corpus for learning natural language inference

description: A large annotated corpus for learning natural language inference
DOI: 10.57702/mz2wfpjn
title: BiomedCXR

description: A large synthetically generated data with annotations and code is publicly available at https://github.com/BioMedIA-MBZUAI/XReal.
DOI: 10.57702/uuomkrld
title: 4D-GS

description: A dataset for dynamic scene reconstruction, including monocular images and camera poses.
DOI: 10.57702/mbsyk6xu
title: Stochastic CA with 1000 lattice squares

description: The dataset used in this paper is a set of 1000 lattice squares with a uniform initial state and a set of 8 possible 3-tuple neighborhood combinations, each with a probability p.
DOI: 10.57702/67zie990
title: Hamburg City Health Study

description: The dataset consists of head and neck MRIs of 199 patients. Each MRI is a fluid attenuated inversion recovery (FLAIR) MRI. The dataset is part of the Hamburg City Health Study.
DOI: 10.57702/8sxz0kj4
title: AMOS2022 challenge dataset

description: The AMOS2022 challenge dataset contains 500 CT and 100 MRI scans, distributed into 200+40 (CT + MRI) training, 100+20 validation and 200+40 test images.
DOI: 10.57702/iimtons6
title: PartNet and ShapeNetSem datasets

description: The dataset used in the paper for composable part-based manipulation (CPM) task.
DOI: 10.57702/vzuyhift
title: Cardiac CT and Chest CT datasets

description: The dataset used for training, validation, and test sets for automatic coronary calcium scoring in cardiac CT and chest CT.
DOI: 10.57702/or48eyo0
title: LIF Neuron Spike Trains

description: The dataset used in this paper is a collection of spike trains from leaky-integrate-and-fire (LIF) neurons.
DOI: 10.57702/mypha6ji
title: ModelNet and Fruits CAD models

description: The dataset used for the research paper is ModelNet and Fruits CAD models.
DOI: 10.57702/3vlt56u6
title: Andror2

description: A dataset of manually-reproduced bug reports for Android apps.
DOI: 10.15468/dl.zg6shk
title: Occurrence Download

description: A dataset containing 24989 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Socratea exorrhiza"
 ]
}

 The dataset includes 24989 records from 223 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080041-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72bbzt
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Corythucha arcuata (Say, 1832)",
 "Country is Romania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 151 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0107342-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/2qn-5cm-gg9
title: Prunus cerasifera Ehrh.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/612-5pd-k6y
title: Prunus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/dp3-7fx-ypa
title: Prunus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/vjd-akm-1h9
title: Prunus africana (Hook. fil.) Kalkman

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/jdw-rfv-ah3
title: Pseudocydonia sinensis (Dum. Cours.) C. K. Schneid.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/7ze-af8-3hp
title: Pyracantha coccinea M. Roem.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/94q-ajm-5wm
title: Pyracantha crenulata (D. Don) M. Roem.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/lbh-y4g-gj9
title: Quillaja saponaria Molina

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/nt4-33b-cfx
title: Rhodotypos scandens (Thunb.) Makino

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/4fd-mq8-ve8
title: Rosa agrestis Savi

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/dqs-hbz-8sn
title: Prunus cerasus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/0nv-0er-mz2
title: Sorbus latifolia (Lam.) Pers.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/7yk-vmp-t7h
title: Petrophytum caespitosum (Nutt.) Rydb.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/zhv-awe-kz9
title: Aria edulis (Willd.) M. Roem.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/2p1-fc5-0x7
title: Filipendula ulmaria (L.) Maxim.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/xxm-7gz-f4x
title: Spiraea nipponica Maxim.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/ha9-ef7-01f
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/sl7-dx6-wm7
title: Spiraea salicifolia L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/sl3-swk-bxx
title: Neillia tanakae Franch. & Sav.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/7dj-683-186
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/edc-sfx-w2e
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/3hc-8wd-y3l
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/bld-ez1-cad
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/fj4-p6y-xws
title: Neurada procumbens L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/fw6-dd6-j3a
title: Rosaceae Juss.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/c6t-t8g-ekp
title: Neurada procumbens L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/l8l-71r-950
title: Sherbournia calycina (G.Don) Hua

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/dkw-bc2-fc4
title: Alibertia edulis (Rich.) A.Rich. ex DC.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/bsb-t10-pft
title: Cynanchica aristata (L.f.) P.Caputo & Del Guacchio

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/zz7-s3q-f98
title: Prunus fruticosa Pall.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/5jg-cc5-pcp
title: Prunus myrtifolia (L.) Urb.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/8w0-3hg-d9w
title: Galium rivale (Sm.) Griseb.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/a67-x4x-8l1
title: Prunus lusitanica L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/te6-jjv-qtq
title: Prunus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/4v6-sk0-yg0
title: Prunus tenella Batsch

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/fjm-a78-n7f
title: Prunus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/fpa-c1z-qmp
title: Prunus L.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.