cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.r6qrz8
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron ziyuanense P.C.Tam"
 ]
}

 The dataset includes 17 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097708-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jf2b52
title: Occurrence Download

description: A dataset containing 223 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rottboellia striata Nees ex Steud."
 ]
}

 The dataset includes 223 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097709-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n67u6w
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Roepera botulifolia (Van Zyl) Beier & Thulin"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097711-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hymrwh
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron zoelleri Warb."
 ]
}

 The dataset includes 283 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097712-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ha87mx
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rourea acutipetala Miq."
 ]
}

 The dataset includes 64 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097713-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/8bxr-w370
title: Cost evaluation of medical software

description: Accounting for the cost of software development projects involves multiple aspects, including human resources, hardware equipment, software tools, training, testing, maintenance, etc. Here are some steps and factors to consider, including labor costs: calculating labor costs such as salaries, benefits, bonuses, etc. for development team members. This may include developers, testers, project managers, designers, etc. Hardware and software tool costs: Consider the purchase or rental costs of required hardware and software tools such as computers, servers, development tools, testing tools, etc.Invited by the research team of the National University of Malaysia, Chifeng University of China collaborated with more than 20 Chinese medical research companies to conduct a survey on its research software. Data was collected based on the above factors, and finally, the cost of each software was summarized.
DOI: 10.57780/esa-00b7cpk
title: 2162150

description:   Target RA (J2000):  317.551544  and deg    Target Dec (J2000):  10.73888  and deg    Gaia GMag:  8.242    Programme ID:  CH_PR140061   Programme Manager:  LENDL   PI of observing programme:  Benz   Title of programme:  Axis 2 - A Deep search for hot JupIter VAriability (DIVA)   Abstract:  The temporal stability of hot Jupiter atmospheres remains an open question. While there are several tentative detections of changes in the observed planetary occultation depths phase curve shapes or transmission spectra no indisputable evidence exists to date. This program will perform a deep search for variability in the dayside brightness of several hot Jupiters. A detection of clear variability and the measurement of its timescale would open the door to a suite of follow-up studies involving the dynamical behaviour of exoplanet atmospheres.    [truncated! Please see actual data for full text]
DOI: 10.57780/esa-0a82qku
title: 2313983

description:   Target RA (J2000):  68.593750  and deg    Target Dec (J2000):  43.03742  and deg    Gaia GMag:  12.3    Programme ID:  CH_PR140068   Programme Manager:  EGGER   PI of observing programme:  Benz   Title of programme:  Axis 1 - Constraining the abundance of water in hot planets (HotWatermelon)   Abstract:  Planets located close enough to their star experience evaporation which leads to a dichotomy in the possible gas content of these objects. These planets either contain more than around one percent of gas (in mass) or no gas at all (see Owen and Wu 2017). This dichotomy when expressed in term of mass-radius relation implies the existence of a region in the mass-radius diagram of hot planets where dry planets cannot exist. We propose to observe planets that could lie in this region with CHEOPS. Combining a precise radius and mass will allow us to identify planets in this forbidden region hence showing that they have to contain volatiles most likely water. Our data combined with future JWST observations will also constrain the efficiency of evaporation.    [truncated! Please see actual data for full text]
DOI: 10.5281/zenodo.10148439
title: BeBOD estimates of incidence, prevalence, and years lived with disability for 57 cancer types, 2004-2021

description: Belgian National Burden of Disease Study
Estimates of the morbidity burden of disease for 57 cancer sites
Incidence
Data on new cancer cases in Belgium are collected by the Belgian Cancer Registry (BCR). For the current study, we selected 80 ICD-10 (C00.0-96.9 and chronic myeloid neoplasms) codes resulting in 57 cancer sites. Data were extracted by year (from 2004 to 2021), age group (5-years), sex and region (N=3). We excluded "Respiratory system and intrathoracic organs, NOS (not otherwise specified)" from further analyses because of too few cases.
Prevalence
Prevalence estimates were estimated using the above-described incidence estimates and the survival estimates also provided by BCR, derived from linkage with the Belgian Crossroads Bank for Social Security. We used a 10-year prevalence perspective meaning that from the year 2013 onwards, we were able to define the prevalence in a given year as the sum of person-months spent in the different health states. Specifically, we used a microsimulation approach to simulate future health states for each year-, age-, sex-, region- and cancer-specific cohort of incident cases.
See for more details: https://doi.org/10.1186/s12885-021-09109-4
Years Lived with Disability
Years Lived with Disability (YLDs) were calculated using both an incidence and prevalence perspective as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.
description: Explore the estimates via https://burden.sciensano.be/shiny/cancer
DOI: 10.5281/zenodo.10148438
title: BeBOD estimates of incidence, prevalence, and years lived with disability for 57 cancer types, 2004-2021

description: Belgian National Burden of Disease Study
Estimates of the morbidity burden of disease for 57 cancer sites
Incidence
Data on new cancer cases in Belgium are collected by the Belgian Cancer Registry (BCR). For the current study, we selected 80 ICD-10 (C00.0-96.9 and chronic myeloid neoplasms) codes resulting in 57 cancer sites. Data were extracted by year (from 2004 to 2021), age group (5-years), sex and region (N=3). We excluded "Respiratory system and intrathoracic organs, NOS (not otherwise specified)" from further analyses because of too few cases.
Prevalence
Prevalence estimates were estimated using the above-described incidence estimates and the survival estimates also provided by BCR, derived from linkage with the Belgian Crossroads Bank for Social Security. We used a 10-year prevalence perspective meaning that from the year 2013 onwards, we were able to define the prevalence in a given year as the sum of person-months spent in the different health states. Specifically, we used a microsimulation approach to simulate future health states for each year-, age-, sex-, region- and cancer-specific cohort of incident cases.
See for more details: https://doi.org/10.1186/s12885-021-09109-4
Years Lived with Disability
Years Lived with Disability (YLDs) were calculated using both an incidence and prevalence perspective as a measure of morbidity. YLDs are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.
description: Explore the estimates via https://burden.sciensano.be/shiny/cancer
DOI: 10.15468/dl.3h3ann
title: Occurrence Download

description: A dataset listing the 312 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-8.88684 37.32601,-8.88706 37.2762,-8.83059 37.27577,-8.83169 37.32634,-8.88684 37.32601))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset's 312 records were derived from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097691-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.63a3wc
title: Occurrence Download

description: A dataset containing 283 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Roepera cordifolia (L.fil.) Beier & Thulin"
 ]
}

 The dataset includes 283 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097714-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zfpuvr
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rourea aspleniifolia (G.Schellenb.) Jongkind"
 ]
}

 The dataset includes 28 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097715-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/8027838
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.15468/dl.6ckadj
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhododendron zollingeri J.J.Sm."
 ]
}

 The dataset includes 78 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097716-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.63skrz
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Roepera cuneifolia (Eckl. & Zeyh.) Beier & Thulin"
 ]
}

 The dataset includes 29 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097717-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10926005
title: Julia constitutive model integration replication files

description: These files allow the user to check that their local version of Julia and the codes provided in the repository at https://github.com/nickcollins-craft/julia_constitutive_model_integration have successfully performed the integration and bifurcation analysis of a Cosserat Breakage Mechanics model. Each file is labelled with the integrator (h² or hyperplastic), the load condition (constant volume or constant confining stress) and whether it is an integration result (containing the mechanical information such as stresses and strains) or a localisation result (the wavelength corresponding to the largest value of the Lyapunov exponent, and a Boolean vector stating whether localisation has occurred or not). The files are in the jld2 format, which is read by Julia using the JLD2 and FileIO packages.
DOI: 10.5281/zenodo.10926006
title: Julia constitutive model integration replication files

description: These files allow the user to check that their local version of Julia and the codes provided in the repository at https://github.com/nickcollins-craft/julia_constitutive_model_integration have successfully performed the integration and bifurcation analysis of a Cosserat Breakage Mechanics model. Each file is labelled with the integrator (h² or hyperplastic), the load condition (constant volume or constant confining stress) and whether it is an integration result (containing the mechanical information such as stresses and strains) or a localisation result (the wavelength corresponding to the largest value of the Lyapunov exponent, and a Boolean vector stating whether localisation has occurred or not). The files are in the jld2 format, which is read by Julia using the JLD2 and FileIO packages.
DOI: 10.15468/dl.tkaejz
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rourea balansana Baill."
 ]
}

 The dataset includes 13 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097720-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10730748
title: Physical deep symbolic regression to learn crack tip correction formulas

description: This repository publishes the data generated in the article "A universal crack tip correction algorithm discovered by physical deep symbolic regression" (see preprint: arXiv.2403.10320).

This repository is structured with the following subfolders:



01_Simulation_Output: The results of the finite element (FE) simulations described in the paper

02_CrackPy_single_evaluation: For each FE simulation, the fracture analysis results of CrackPy performed with the crack tip as origin

04_CrackPy_random_evaluation_pipeline: For each FE simulation, the fracture analysis is performed at 1000 random perturbations of the crack tip position as origin and the results are stored in the subfolder samples

05_1_PhySO_log_mode_I, 05_2_PhySO_log_mode_II, 05_3_PhySO_log_mixed_mode: These folders contain the logs of three distinct training runs of PhySO - mode I, mode II, and mixed mode. For each of these three load cases, we train symbolic regression models for the x-correction and y-correction separately. The symbolic regression results are stored in the files curves_pareto.csv 

06_Pareto_Plots: The visualization of the Pareto front for each training run of PhySO

07_Plots_vector_fields: The correction vector fields for each discovered Pareto formula

08_Convergence_study_FEA: The iterative convergence behavior for the FE simulations data

13_Application: We applied the most promising formulas to experimental DIC data from uniaxial and biaxial fatigue crack growth experiments. The results are contained in this folder.


The code to reproduce these results can be fould on our GitHub page at the following link: https://github.com/dlr-wf/crack_tip_correction_symbolic_regression
DOI: 10.5281/zenodo.10730749
title: Physical deep symbolic regression to learn crack tip correction formulas

description: This repository publishes the data generated in the article "A universal crack tip correction algorithm discovered by physical deep symbolic regression" (see preprint: arXiv.2403.10320).

This repository is structured with the following subfolders:



01_Simulation_Output: The results of the finite element (FE) simulations described in the paper

02_CrackPy_single_evaluation: For each FE simulation, the fracture analysis results of CrackPy performed with the crack tip as origin

04_CrackPy_random_evaluation_pipeline: For each FE simulation, the fracture analysis is performed at 1000 random perturbations of the crack tip position as origin and the results are stored in the subfolder samples

05_1_PhySO_log_mode_I, 05_2_PhySO_log_mode_II, 05_3_PhySO_log_mixed_mode: These folders contain the logs of three distinct training runs of PhySO - mode I, mode II, and mixed mode. For each of these three load cases, we train symbolic regression models for the x-correction and y-correction separately. The symbolic regression results are stored in the files curves_pareto.csv 

06_Pareto_Plots: The visualization of the Pareto front for each training run of PhySO

07_Plots_vector_fields: The correction vector fields for each discovered Pareto formula

08_Convergence_study_FEA: The iterative convergence behavior for the FE simulations data

13_Application: We applied the most promising formulas to experimental DIC data from uniaxial and biaxial fatigue crack growth experiments. The results are contained in this folder.


The code to reproduce these results can be fould on our GitHub page at the following link: https://github.com/dlr-wf/crack_tip_correction_symbolic_regression
DOI: 10.15468/dl.mmk87k
title: Occurrence Download

description: A dataset containing 234388122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Animalia, Fungi, Plantae)",
 "BasisOfRecord is one of (Specimen, Material sample, Living Specimen)",
 {
 "not" : {
 "DatasetKey" : [
 "is one of (INSDC Sequences, Southern Ocean Continuous Zooplankton Recorder (SO-CPR) Survey, Finnish Insect Database, SHARK - Regional marine environmental monitoring, recipient control and monitoring projects of Zoobenthos in Sweden since 1972, Digitalización y Sistematización de las Colecciones Biológicas Nacionales del Instituto de Biología, UNAM (CNIN), SysTax - Zoological Collections, Mosquito Occurrence Dataset, Lajitietokeskus/FinBIF - Notebook, general observations, Wild bees of Belgium)"
 ]
 }
 },
 "CatalogNumber is not null"
 ]
}

 The dataset includes 234388122 records from 6598 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0097680-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sgeebd
title: Occurrence Download

description: A dataset containing 8309415 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Peru"
 ]
}

 The dataset includes 8309415 records from 2451 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000748-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh2803732.08fu
title: SH2803732.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh535438.07fu
title: SH535438.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh535439.07fu
title: SH535439.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh535440.07fu
title: SH535440.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.