cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3217/jknbg-tzq09
title: 3D Model of the Nesar Gompa of Bijer

description: As part of ongoing FWF research projects on Buddhist architecture in the Western Himalayas at Graz University of Technology, it was possible to secure significant documentation and materials relating to sacred buildings in Dolpo in Western Nepal in recent years, led by the Institute of Architectural Theory, History of Art and Cultural Studies (akk). Provoked by the outstanding performance of modern surveying technologies, a cooperation was started with our institute (Institute of Engineering Geodesy and Measurement Systems, IGMS) in order enhance existing methodologies of conventional building research by the integration of modern surveying methods, within the frame of an FWF project “Buddhist Architecture in Western Himalayas” (https://archresearch.tugraz.at/).

The aim of this interdisciplinary work was to explore significant Buddhist temple sites in Upper Dolpo, a remote area in Nepal, and to document several sites using modern 3D laser scanning technology. The derived models show a high level of detail and confidence, both from the outside and inside of the temple. Thus, they provide a solid data foundation for studying architectural connections in topologies of different sites and for further building research within the scientific community.

In order to reach a high accuracy level (within a few millimeters), the documentation strategy in the project was based on a combination of highly accurate laser scan data (Leica RTC360) and photogrammetric images. The individual laser scans were pre-registered in the field, and afterwards post-processed in the Leica Register 360 software. The registration was based on cloud-to-cloud registrations (in order to have a high mobility in the measurement setups), and – where possible - on stable reference points. The coordinates of these ground control points were determined using a geodetic total station (available only 2022) with redundant measurements in local geodetic network configuration.

This DOI represents the whole dataset gathered at the site in the fieldwork in 2022/2023. An overview of the site (JPG) and a down-sampled 3D model are provided herein for general distribution in order to avoid hidden inventory and provide these data to the commited scientific community. Please contact the authors if the complete data set and/or raw data (point cloud) is required for scientific research.
DOI: 10.5281/zenodo.13908976
title: Rschmedding/Machine-Learning-Surface-Tension: Pure Component Surface Tensions of Atmospherically Relevant Organic Compounds

description: Machine Learning techniques for predicting temperature dependent surface tensions of organic compounds from their SMILES codes.
DOI: 10.5281/zenodo.13936980
title: Rschmedding/Machine-Learning-Surface-Tension: Pure Component Surface Tensions of Atmospherically Relevant Organic Compounds

description: Machine Learning techniques for predicting temperature dependent surface tensions of organic compounds from their SMILES codes.
DOI: 10.6084/m9.figshare.26681944
title: Materials related to the manuscript titled: Hummingbirds use compensatory eye movements to stabilize both rotational and translational visual motion

description: ABSTRACT: To maintain stable vision, behaving animals make compensatory eye movements in response to image slip, a reflex known as the optokinetic response (OKR). Although OKR has been studied in several avian species, eye movements during flight are expected to be minimal. This is because vertebrates with laterally placed eyes typically show weak OKR to nasal-to-temporal motion (NT), which simulates typical forward locomotion, compared to temporal-to-nasal motion (TN), which simulates atypical backward locomotion. This OKR asymmetry is also reflected in the pretectum, wherein neurons sensitive to global visual motion also exhibit a TN bias. Hummingbirds, however, stabilize visual motion in all directions through whole-body movements and are unique among vertebrates in that they lack a pretectal bias. We therefore predicted that OKR in hummingbirds would be symmetrical. We measured OKR in restrained hummingbirds by presenting gratings drifting across a range of speeds. OKR in hummingbirds was asymmetrical, though the direction of asymmetry varied with stimulus speed. Hummingbirds moved their eyes largely independent of one another. Consistent with weak eye-to-eye coupling, hummingbirds also exhibited disjunctive OKR to visual motion simulating forward and backward translation. This unexpected oculomotor behavior, previously unexplored in birds, suggests a potential role for compensatory eye movements during flight.
DOI: 10.6084/m9.figshare.26681944.v1
title: Materials related to the manuscript titled: Hummingbirds use compensatory eye movements to stabilize both rotational and translational visual motion

description: ABSTRACT: To maintain stable vision, behaving animals make compensatory eye movements in response to image slip, a reflex known as the optokinetic response (OKR). Although OKR has been studied in several avian species, eye movements during flight are expected to be minimal. This is because vertebrates with laterally placed eyes typically show weak OKR to nasal-to-temporal motion (NT), which simulates typical forward locomotion, compared to temporal-to-nasal motion (TN), which simulates atypical backward locomotion. This OKR asymmetry is also reflected in the pretectum, wherein neurons sensitive to global visual motion also exhibit a TN bias. Hummingbirds, however, stabilize visual motion in all directions through whole-body movements and are unique among vertebrates in that they lack a pretectal bias. We therefore predicted that OKR in hummingbirds would be symmetrical. We measured OKR in restrained hummingbirds by presenting gratings drifting across a range of speeds. OKR in hummingbirds was asymmetrical, though the direction of asymmetry varied with stimulus speed. Hummingbirds moved their eyes largely independent of one another. Consistent with weak eye-to-eye coupling, hummingbirds also exhibited disjunctive OKR to visual motion simulating forward and backward translation. This unexpected oculomotor behavior, previously unexplored in birds, suggests a potential role for compensatory eye movements during flight.
DOI: 10.6084/m9.figshare.27154098
title: atx235DVIO_canuCorTrmTotal.fasta.gz

description: Targeted sequencing of the metalloproteinase gene complex. These are PacBio CCS reads that have been corrected and trimmed with the CANU genome assembly software.
DOI: 10.6084/m9.figshare.27154098.v1
title: atx235DVIO_canuCorTrmTotal.fasta.gz

description: Targeted sequencing of the metalloproteinase gene complex. These are PacBio CCS reads that have been corrected and trimmed with the CANU genome assembly software.
DOI: 10.5281/zenodo.13935080
title: APPLICATION OF MACHINE LEARNING METHODS TO ENHANCE THE PERFORMANCE OF BIG DATA SORTING ALGORITHMS

description: The use of machine learning methods to optimize big data sorting algorithms has become an urgent research topic due to the growing volume of information and the requirements for their rapid processing. Machine learning provides opportunities to automate and improve traditional sorting methods, allowing you to reduce the cost of computing resources and time. This is achieved by analyzing the characteristics of the data and preprocessing them using classification and regression. The main advantages of using machine learning in sorting big data include improving the accuracy and adaptability of algorithms to different types of data, which is especially important for areas with large amounts of information, such as finance, medicine and logistics. Progressive machine learning algorithms such as supporting vectors, decision trees, and gradient boosting demonstrate high efficiency and potential for further development and integration.
DOI: 10.5281/zenodo.13935081
title: APPLICATION OF MACHINE LEARNING METHODS TO ENHANCE THE PERFORMANCE OF BIG DATA SORTING ALGORITHMS

description: The use of machine learning methods to optimize big data sorting algorithms has become an urgent research topic due to the growing volume of information and the requirements for their rapid processing. Machine learning provides opportunities to automate and improve traditional sorting methods, allowing you to reduce the cost of computing resources and time. This is achieved by analyzing the characteristics of the data and preprocessing them using classification and regression. The main advantages of using machine learning in sorting big data include improving the accuracy and adaptability of algorithms to different types of data, which is especially important for areas with large amounts of information, such as finance, medicine and logistics. Progressive machine learning algorithms such as supporting vectors, decision trees, and gradient boosting demonstrate high efficiency and potential for further development and integration.
DOI: 10.6084/m9.figshare.26272765.v2
title: Self Documenting Plasmids

description: Embedding sequencing information physically within plasmid sequences to have a digital signature to help verify samples with sequencing.
DOI: 10.5281/zenodo.13136161
title: Dados do Estudo "Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC"

description: Dados do estudo:

Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC
DOI: 10.5281/zenodo.13136160
title: Dados do Estudo "Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC"

description: Dados do estudo:

Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC
DOI: 10.5281/zenodo.13935091
title: Dados do Estudo "Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC"

description: Dados do estudo:

Análise Acústica de Características Prosódicas em Modelos de Síntese de Fala: Uma Comparação Entre YOURTTS e SYNTACC
DOI: 10.5281/zenodo.11212263
title: Shasta County Arrest Disposition Data 2022

description: This dataset was exported from the California Department of Justice's OpenJustice platform (https://openjustice.doj.ca.gov/data) on May 17, 2024, and contains arrest data for Shasta County for the year 2022. The data was reported by local law enforcement agencies as part of the Monthly Arrest and Citation Register (MACR), which tracks felony, misdemeanor, and status offense arrests.

The dataset includes the following demographic and arrest-related variables: year, county, gender, race, arrest disposition code, age group, and various categories of offenses. It provides aggregate counts for total arrests, violent crimes, property crimes, drug offenses, sex offenses, and other felonies, as well as misdemeanor and status offense totals.

This dataset is presented in CSV format and offers a detailed snapshot of arrests within Shasta County for 2022, broken down by key demographic and offense-related factors.
DOI: 10.5281/zenodo.11212264
title: Shasta County Arrest Disposition Data 2022

description: This dataset was exported from the California Department of Justice's OpenJustice platform (https://openjustice.doj.ca.gov/data) on May 17, 2024, and contains arrest data for Shasta County for the year 2022. The data was reported by local law enforcement agencies as part of the Monthly Arrest and Citation Register (MACR), which tracks felony, misdemeanor, and status offense arrests.

The dataset includes the following demographic and arrest-related variables: year, county, gender, race, arrest disposition code, age group, and various categories of offenses. It provides aggregate counts for total arrests, violent crimes, property crimes, drug offenses, sex offenses, and other felonies, as well as misdemeanor and status offense totals.

This dataset is presented in CSV format and offers a detailed snapshot of arrests within Shasta County for 2022, broken down by key demographic and offense-related factors.
DOI: 10.5281/zenodo.13358787
title: Supplementary material for "The Multi-Segment Complexity of the 2024 Mw 7.5 Noto Peninsula Earthquake Governs Tsunami Generation"

description: This repository contains the supplementary files for the GRL submission "The Multi-Segment Complexity of the 2024 Mw 7.5 Noto Peninsula Earthquake Governs Tsunami Generation" by Fabian Kutschera, Zhe Jia, Bar Oryan, Jeremy Wing Ching Wong, Wenyuan Fan, and Alice-Agnes Gabriel.

The repository is subdivided into 5 folders:



multi-cmt:



contains subevent and subfault information of the preferred multi-CMT model 

contains the multi-CMT solution for the adapted scaling relation model 

all 2000 multi-CMT solutions



displacement:



contains the python script to compute the elastic dislocation based on Okada (1992) using the python implementation okada4py (https://github.com/jolivetr/okada4py)

contains the calculated displacements of models presented in the paper (readily available in *.tt3 format for GeoClaw, see tsunami folder)

contains the synthetic GNSS files for each model

all 2000 displacement models constructed from the 2000 multi-CMT solutions



tsunami:



input files necessary to run GeoClaw 

output of the synthetic tide gauges for the various tsunami simulations



misc:



additional files for aftershocks and observed GNSS data



movies:



supplementary movies S1 and S2 from the submission
DOI: 10.25835/xvdntbqg
title: Genotypic and phenotypic raw data for GWAS study Wamhoff et al. 2024

description: Genotypic SNP raw data and phenotypic raw data for anatomy shoot base measurements at the start of rooting experiments and after 1 week of cultivation, RP formation after 1 week and AR formation characteristcs for 106 tested rose genotypes.
DOI: 10.18434/mds2-3431
title: SRM 3122 Lot 230104 Hafnium (Hf) Standard Solution Data
DOI: 10.15468/dl.6ez6qf
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is COL.2.103_2",
 "IucnRedListCategory is one of (EN, VU, NT)",
 "TaxonKey is Bromeliaceae"
 ]
}

 The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015746-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n64yhr
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Brownea santanderensis Quiñones"
 ]
}

 The dataset includes 33 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015797-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fcdx7
title: Occurrence Download

description: A dataset containing 922 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristimantis actites (Lynch, 1979)"
 ]
}

 The dataset includes 922 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015798-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.twx8r7
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Occurrence evidence, Human Observation, Fossil)",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Carcharodon carcharias (Linnaeus, 1758)"
 ]
}

 The dataset includes 106 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015796-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zn4j4s
title: Occurrence Download

description: A dataset containing 9748 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Bulnesia arborea (Jacq.) Engl."
 ]
}

 The dataset includes 9748 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015799-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwvk8a
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "TaxonKey is Iguana Laurenti, 1768"
 ]
}

 The dataset includes 283 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015795-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/gtbqe6/nquhpd
title: Daily weather data for Ambohibary (Madagascar) from 2015 to 2018.xls
DOI: 10.7910/dvn/gtbqe6/rgmztn
title: Dictionary.xls
DOI: 10.15468/dl.y83uz5
title: Occurrence Download

description: A dataset containing 141408 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is one of (Europe, Asia)",
 "TaxonKey is Quercus petraea (Matt.) Liebl.",
 "Year 1999-2015"
 ]
}

 The dataset includes 141408 records from 740 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015721-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2s7tk5
title: Occurrence Download

description: A dataset containing 653 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Beaucarnea gracilis Lem."
 ]
}

 The dataset includes 653 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015801-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w3ayx7
title: Occurrence Download

description: A dataset containing 2100 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Psidium sartorianum (O.Berg) Nied."
 ]
}

 The dataset includes 2100 records from 197 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015800-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qy8c9a
title: Occurrence Download

description: A dataset listing the 775 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((9.018335768649106 40.3035614749543,9.38921488952823 40.3035614749543,9.38921488952823 40.674440595833424,9.018335768649106 40.674440595833424,9.018335768649106 40.3035614749543))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset's 775 records were derived from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015747-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ws63k3
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Canada",
 "TaxonKey is Stenotrema barbatum (G.H.Clapp, 1904)"
 ]
}

 The dataset includes 20 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015802-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2k72fb
title: CCDC 2360291: Experimental Crystal Structure Determination

description: Related Article: Paul G. Waddell, Michael R. Probert, Natalie T. Johnson|2024|J.Chem.Educ.|101|4276|doi:10.1021/acs.jchemed.4c00797
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: 10.18434/mds2-3324
title: Standard Reference Material (SRM) 3290 Dry Cat Food Data
DOI: 10.18120/qbvy-zb29
title: SREP_CorTec_BIC_Benchmarking_2024
DOI: 10.15468/dl.shunxr
title: Occurrence Download

description: A dataset containing 204861 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The Scottish Squirrel Database"
 ]
}

 The dataset includes 204861 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015744-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zp9h56
title: Occurrence Download

description: A dataset listing the 66 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((177.18044 -38.18743,177.19149 -38.18617,177.20535 -38.1819,177.21605 -38.17585,177.2243 -38.17293,177.23058 -38.16976,177.23996 -38.16286,177.24992 -38.16005,177.25644 -38.15721,177.26781 -38.14964,177.27631 -38.14,177.28136 -38.12895,177.28262 -38.11725,177.28135 -38.10482,177.28004 -38.09903,177.27708 -38.09187,177.2714 -38.0832,177.2697 -38.07785,177.265 -38.06802,177.25783 -38.05774,177.24753 -38.04927,177.23482 -38.0432,177.22056 -38.03993,177.20241 -38.03948,177.18963 -38.03668,177.18222 -38.03617,177.17077 -38.03689,177.16355 -38.03829,177.15525 -38.04087,177.14843 -38.04385,177.13706 -38.05141,177.13241 -38.056,177.12805 -38.06187,177.11939 -38.06956,177.11254 -38.07998,177.1084 -38.09185,177.1078 -38.10029,177.10342 -38.11018,177.10229 -38.116,177.10236 -38.12439,177.09978 -38.14168,177.10064 -38.15047,177.10242 -38.15619,177.10871 -38.16683,177.11828 -38.17582,177.13048 -38.18255,177.14447 -38.18655,177.15717 -38.18761,177.18044 -38.18743))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Athoracophoridae, Insecta, Rhytididae, Onychophora, Arachnida)"
 ]
}

 The dataset's 66 records were derived from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015768-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vt5x7w
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Fossil, Occurrence evidence)",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Carcharodon carcharias (Linnaeus, 1758)"
 ]
}

 The dataset includes 106 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015814-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.afhdx5
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Leonites Spath, 1932"
 ]
}

 The dataset includes 59 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015812-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.