cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/qcbpr5
title: A new species of the New Zealand endemic weevil genus Clypeolus Broun (Coleoptera: Curculionidae: Cryptorhynchinae), found attacking an invasive weed, white horehound (Marrubium vulgare L. Lamiales: Lamiaceae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Brown, Samuel D. J., Leschen, Richard A. B., Groenteman, Ronny (2025): A new species of the New Zealand endemic weevil genus Clypeolus Broun (Coleoptera: Curculionidae: Cryptorhynchinae), found attacking an invasive weed, white horehound (Marrubium vulgare L. Lamiales: Lamiaceae). Zootaxa 5717 (4): 544-570, DOI: 10.11646/zootaxa.5717.4.4, URL: https://doi.org/10.11646/zootaxa.5717.4.4AbstractClypeolus hallae Brown, Leschen and Groenteman new species is described from specimens reared from the roots of the invasive weed white horehound (Marrubium vulgare L., Lamiales: Lamiaceae) at a site in the Lowry Peaks Range, North Canterbury, in the South Island of New Zealand. Additional specimens from Kaitorete Spit, Kaikoura and Nelson in the South Island, Stephens Island and Wairarapa, Hawkes Bay and East Cape in the North Island have also been examined. We provide a synopsis of the genus Clypeolus Broun, and propose the following actions: Tychanus complexus Broun, 1921, Tychanus simulans Broun, 1921, Tychanus squamosus Broun, 1914, Tychanus terricola Broun, 1921, Acalles fuscidorsis Broun, 1909, and Acalles notoporhinus Broun, 1914 are new synonyms of Clypeolus cineraceus Broun, 1909; and Tychanus dux Broun, 1893 is a new synonym of Clypeolus lachrymosus (Broun, 1881). We include a key to the known species of Clypeolus, and images of the type specimens for available names, as well as diagnoses and the distribution for each species. Clypeolus hallae is an interesting example of an indigenous herbivore in a novel host association with an adventive invasive plant species, and we recommend further study into the biology and evolution of this weevil and its potential impacts upon horehound populations.
DOI: 10.15468/dl.tamryc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.384 1.674182, 100.313707 1.668614, 100.245147 1.652046, 100.180007 1.624888, 100.119893 1.587809, 100.066285 1.54172, 100.020503 1.487759, 99.98367500000001 1.427255, 99.956706 1.361697, 99.94025999999999 1.292699, 99.934741 1.221962, 99.94028299999999 1.151227, 99.95675 1.082235, 99.98373599999999 1.016685, 100.020575 0.95619, 100.06636 0.902241, 100.119964 0.856164, 100.180068 0.819095, 100.245191 0.791945, 100.313731 0.775383, 100.384 0.769817, 100.454269 0.775383, 100.522809 0.791945, 100.587932 0.819095, 100.648036 0.856164, 100.70164 0.902241, 100.747425 0.95619, 100.784264 1.016685, 100.81125 1.082235, 100.827717 1.151227, 100.833259 1.221962, 100.82774 1.292699, 100.811294 1.361697, 100.784325 1.427255, 100.747497 1.487759, 100.701715 1.54172, 100.648107 1.587809, 100.587993 1.624888, 100.522853 1.652046, 100.454293 1.668614, 100.384 1.674182))"},{"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/0002733-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31113881
title: Lanostane triterpenoids from the fruiting bodies of <i>Ganoderma multipileum</i> and their anti-inflammatory activities

description: A previously unreported lanostane-type triterpenoid designated as (25<i>S</i>)-3<i>β</i>,15<i>β</i>-dihydroxy-7,11,23-trioxo-lanost-8,17(20)-dien-26-oic acid (<b>1</b>) and fifteen known compounds (<b>2</b>–<b>16</b>), was obtained from <i>Ganoderma multipileum</i> fruiting bodies. Combined analysis of NMR and HRESIMS data, together with theoretical computations involving NMR chemical shift prediction and DP4+ analysis, the structural elucidation of the new compound was accomplished. Bioactivity screen was performed on all compounds to assess their anti-inflammatory activity. Notably, in LPS-stimulated RAW264.7 cells, compounds <b>4</b> and <b>5</b> inhibited the NO generation, yielding IC<sub>50</sub> values of 12.89 ± 0.50 and 27.55 ± 2.95 μM, respectively, with potency close to that of quercetin (IC<sub>50</sub>: 11.80 ± 1.75 μM).
DOI: 10.6084/m9.figshare.31113881.v1
title: Lanostane triterpenoids from the fruiting bodies of <i>Ganoderma multipileum</i> and their anti-inflammatory activities

description: A previously unreported lanostane-type triterpenoid designated as (25<i>S</i>)-3<i>β</i>,15<i>β</i>-dihydroxy-7,11,23-trioxo-lanost-8,17(20)-dien-26-oic acid (<b>1</b>) and fifteen known compounds (<b>2</b>–<b>16</b>), was obtained from <i>Ganoderma multipileum</i> fruiting bodies. Combined analysis of NMR and HRESIMS data, together with theoretical computations involving NMR chemical shift prediction and DP4+ analysis, the structural elucidation of the new compound was accomplished. Bioactivity screen was performed on all compounds to assess their anti-inflammatory activity. Notably, in LPS-stimulated RAW264.7 cells, compounds <b>4</b> and <b>5</b> inhibited the NO generation, yielding IC<sub>50</sub> values of 12.89 ± 0.50 and 27.55 ± 2.95 μM, respectively, with potency close to that of quercetin (IC<sub>50</sub>: 11.80 ± 1.75 μM).
DOI: 10.15468/dl.ek2ztt
title: Occurrence Download

description: A dataset containing 1572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tubulidentata"
 ]
}

 The dataset includes 1572 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002734-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7cd5sq
title: Occurrence Download

description: A dataset containing 317 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Geometry POLYGON((0.37241 52.77066,0.37962 52.77066,0.37962 52.77482,0.37241 52.77482,0.37241 52.77066))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year 2020-2026"
 ]
}

 The dataset includes 317 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002735-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17902398
title: Wildfire simulation results

description: Wildfire propagation simulation for the wildfire disaster scenario. Technical Attribution: Simulations performed by the research group Numerical Simulation and Scientific Computation of the University of Salamanca using the Sinumcc tool set (PhyFire, HDWind and PhyNX models). The methodology implemented in this dataset is based on and validated by the works listed in the References section.
DOI: 10.5281/zenodo.17902399
title: Wildfire simulation results

description: Wildfire propagation simulation for the wildfire disaster scenario. Technical Attribution: Simulations performed by the research group Numerical Simulation and Scientific Computation of the University of Salamanca using the Sinumcc tool set (PhyFire, HDWind and PhyNX models). The methodology implemented in this dataset is based on and validated by the works listed in the References section.
DOI: 10.7910/dvn/i913xl
title: Happy primes generated by the polynomial P(n) = 3n^2 + 3n + 23 (sequence)

description: This dataset is a sequence of happy primes generated by the polynomial 
P(n) = 3n^2 + 3n + 23. I raise the question of whether there are infinitely many such primes.
DOI: 10.15468/dl.8xq6y7
title: Occurrence Download

description: A dataset containing 118 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cyperus difformis",
 "Year 1970-2000"
 ]
}

 The dataset includes 118 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002737-260120142942310/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.31113826
title: Vector Database for Mental Health RAG Chatbot

description: Vector Database for Mental Health RAG Chatbot
DOI: 10.6084/m9.figshare.31113826.v1
title: Vector Database for Mental Health RAG Chatbot

description: Vector Database for Mental Health RAG Chatbot
DOI: 10.5281/zenodo.18327695
title: Receiver function data set used in the paper "Geometry of the Main Himalayan Thrust and its role in Seismogenesis in the Northwest Himalaya using Receiver Function analyses", submitted to the Journal of Geophysical Research.

description: The digital waveform files of the computed receiver functions used in this study are organized station-wise, with each station’s data stored in a separate folder named after the corresponding station code. All waveform files are in SAC format and can be visualized using the Seismic Analysis Code (SAC) software (https://ds.iris.edu/ds/nodes/dmc/software/downloads/sac/). An example of plotting the waveforms in SAC is given below:

               r  <file name>               (“r” is used to read the waveform files )

                        ppk                               (“ppk “plots the waveforms)
DOI: 10.5281/zenodo.18327694
title: Receiver function data set used in the paper "Geometry of the Main Himalayan Thrust and its role in Seismogenesis in the Northwest Himalaya using Receiver Function analyses", submitted to the Journal of Geophysical Research.

description: The digital waveform files of the computed receiver functions used in this study are organized station-wise, with each station’s data stored in a separate folder named after the corresponding station code. All waveform files are in SAC format and can be visualized using the Seismic Analysis Code (SAC) software (https://ds.iris.edu/ds/nodes/dmc/software/downloads/sac/). An example of plotting the waveforms in SAC is given below:

               r  <file name>               (“r” is used to read the waveform files )

                        ppk                               (“ppk “plots the waveforms)
DOI: 10.5517/ccdc.csd.cc2g5291
title: CCDC 2268992: Experimental Crystal Structure Determination

description: Related Article: Chu Wang, Lin Liu, Wei Sun, Juanjuan Wang, Qing-Kai Li, Kai Feng, Bin Liao, Wei-Hai Fang, Xuebo Chen
|2025|Adv. Opt. Mater.|13|2402317|doi:10.1002/adom.202402317
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: 10.5066/p1q68hzt
title: "Luminescence Data from Trench Exposures across the Dead Coyote fault scarp in Kittitas Valley, Washington and the Walllula fault at Finely Quarry, Washington"

description: This data release presents optically stimulated luminescence (OSL) and infrared stimulated luminescence (IRSL) measurements from sediment samples collected at Quaternary fault exposures in central and southeastern Washington. The primary focus of the dataset is luminescence data from three paleoseismic trenches excavated across the Dead Coyote fault scarp in the Kittitas Valley, central Washington. These include samples BB22-OSL1 and BB22-OSL2 from the Bitter Brush trench; RC22-OSL1, RC22-OSL2, RC22-OSL3, and RC22-OSL4 from the Reecer Creek trench; and TL-01, TL-02, and TL-03 from the Dead Coyote trench. These samples support a forthcoming USGS Special Investigations Map publication titled Field and Laboratory Data from Trench Exposures across the Dead Coyote fault scarp in Kittitas Valley, Washington. In addition, this release includes luminescence data for samples 13BS016, 13BS017, and 13BS018 collected from an exposure of the Wallula fault at Finley Quarry in southeastern Washington. These samples were previously used to constrain the timing of faulting and deformation described in Sherrod et al. (2013). Together, the datasets provide luminescence-based age constraints relevant to Quaternary deformation along the Dead Coyote and Wallula faults and support ongoing and prior investigations of earthquake history and fault activity in central and southeastern Washington.
DOI: 10.15468/dl.9z8m4v
title: Occurrence Download

description: A dataset listing the 546 species recorded in GBIF matching the query:
{
 "GadmGid" : [
 "is BRA.13.271_2"
 ]
}

 The dataset's 546 records were derived from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002732-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.npqwrj
title: Occurrence Download

description: A dataset containing 646 species occurrences available in GBIF matching the query:
{
 "and" : [
 "License is one of (CC-BY 4.0, CC0 1.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Cherax quadricarinatus"
 ]
}

 The dataset includes 646 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002738-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e233575
title: Rural-urban disparities in post-acute therapy utilization: identifying hot spots of low utilization among fee-for-service Medicare beneficiaries toward informing policy and public health interventions

description: This project has two aims, each one described below.<b><br><br>Aim 1: To quantify rural-urban
disparities in rehabilitation therapy utilization (IRFs/ SNFs/ HHAs) among FFS
Medicare beneficiaries (2021) and evaluate their change over time (2013-2021). </b>Hypothesis 1: Rural Fee For
Service (FFS) Medicare beneficiaries had lower therapy utilization than urban
counterparts in 2021. Hypothesis 2: Rural disparities have been stagnant
or increased as opposed to significantly reduced over time (2013-2021),
stratified for the pre- (2013-2019) and post-pandemic (2020-2021) times. We will use hierarchical linear multiple regressions. Dependent
variable:<b> </b>counties’<b> therapy utilization rate for </b>IRFs,
SNFs, and HHAs combined. Independent variable<b>:
rural area</b>, per two indicators: a) rural residency of FFS beneficiaries b)
rural county gradient. Covariates: 1) FFS beneficiaries’
characteristics; 2) FFS Medicare expenditures; 3) counties’ disability
statistics, e.g., poverty; 4) community-level health, health access and social
determinants of health; and 6) regions and states. The significance of the
interaction between years and rurality will be tested. <br><b></b>

<b><br>Aim 2: To build interactive,
user-centered maps of rehabilitation therapy utilization (IRFs / SNFs / HHAs), identifying
hot spots of low utilization (in 2021) and their evolving trends
(2013-2021).</b> A GIS (ArcGIS Pro) will be used to
spatiotemporally analyze the data used in the Aim 1. First, we will develop <b>choropleth
maps</b>: gradients of county-level utilization rates, intersected with
rural areas. Second, <b>hot spot analyses</b> (statistical spatial
clustering) will map clusters of counties with low utilization. Third, a <b>spatiotemporal</b>,
<b>emerging hot spot analysis</b> (2013-2021) will map<b> </b>areas
with up to eight types of time-trends such as those showing an<b> intensifying
or persistent low utilization</b>. The spatiotemporal analysis will be
also stratified
for the pre- (2013-2019) and post-pandemic (2020-2021) time periods. All the maps, with customizable options, will be shared online for
public access. An<b> Advisory Group</b> of target end-users (e.g., disability
advocates, public health agents) will provide input throughout to design the maps’
attributes and refine them after beta testing
description: The utilization data was adjusted for the Hierarchical Condition Category (HCC) that CMS uses to predict patient healthcare costs
description: Response Rates: NA
description: Presence of Common Scales: NA
description: NA
description: Public domain Part A postacute therapy minutes for Medicare Fee-For-Service Beneficiaries. Smallest Geographic Unit: County and State
description: other; All the data here used and aggregated at the county and state level are derived from public domain data.
DOI: 10.3886/e233575v2
title: Rural-urban disparities in post-acute therapy utilization: identifying hot spots of low utilization among fee-for-service Medicare beneficiaries toward informing policy and public health interventions

description: This project has two aims, each one described below.<b><br><br>Aim 1: To quantify rural-urban
disparities in rehabilitation therapy utilization (IRFs/ SNFs/ HHAs) among FFS
Medicare beneficiaries (2021) and evaluate their change over time (2013-2021). </b>Hypothesis 1: Rural Fee For
Service (FFS) Medicare beneficiaries had lower therapy utilization than urban
counterparts in 2021. Hypothesis 2: Rural disparities have been stagnant
or increased as opposed to significantly reduced over time (2013-2021),
stratified for the pre- (2013-2019) and post-pandemic (2020-2021) times. We will use hierarchical linear multiple regressions. Dependent
variable:<b> </b>counties’<b> therapy utilization rate for </b>IRFs,
SNFs, and HHAs combined. Independent variable<b>:
rural area</b>, per two indicators: a) rural residency of FFS beneficiaries b)
rural county gradient. Covariates: 1) FFS beneficiaries’
characteristics; 2) FFS Medicare expenditures; 3) counties’ disability
statistics, e.g., poverty; 4) community-level health, health access and social
determinants of health; and 6) regions and states. The significance of the
interaction between years and rurality will be tested. <br><b></b>

<b><br>Aim 2: To build interactive,
user-centered maps of rehabilitation therapy utilization (IRFs / SNFs / HHAs), identifying
hot spots of low utilization (in 2021) and their evolving trends
(2013-2021).</b> A GIS (ArcGIS Pro) will be used to
spatiotemporally analyze the data used in the Aim 1. First, we will develop <b>choropleth
maps</b>: gradients of county-level utilization rates, intersected with
rural areas. Second, <b>hot spot analyses</b> (statistical spatial
clustering) will map clusters of counties with low utilization. Third, a <b>spatiotemporal</b>,
<b>emerging hot spot analysis</b> (2013-2021) will map<b> </b>areas
with up to eight types of time-trends such as those showing an<b> intensifying
or persistent low utilization</b>. The spatiotemporal analysis will be
also stratified
for the pre- (2013-2019) and post-pandemic (2020-2021) time periods. All the maps, with customizable options, will be shared online for
public access. An<b> Advisory Group</b> of target end-users (e.g., disability
advocates, public health agents) will provide input throughout to design the maps’
attributes and refine them after beta testing
description: The utilization data was adjusted for the Hierarchical Condition Category (HCC) that CMS uses to predict patient healthcare costs
description: Response Rates: NA
description: Presence of Common Scales: NA
description: NA
description: Public domain Part A postacute therapy minutes for Medicare Fee-For-Service Beneficiaries. Smallest Geographic Unit: County and State
description: other; All the data here used and aggregated at the county and state level are derived from public domain data.
DOI: 10.15468/dl.xryycg
title: Occurrence Download

description: A dataset containing 940 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-72.84 4.944154, -72.910523 4.938584, -72.97930599999999 4.92201, -73.044653 4.894843, -73.104952 4.857751, -73.158717 4.81165, -73.204623 4.757677, -73.241541 4.697162, -73.268564 4.631597, -73.28502899999999 4.562596, -73.290532 4.491861, -73.284943 4.421132, -73.268401 4.352151, -73.241317 4.286616, -73.204359 4.226139, -73.158439 4.172207, -73.104688 4.126149, -73.04442899999999 4.089095, -72.97914299999999 4.061958, -72.910437 4.045404, -72.84 4.03984, -72.76956300000001 4.045404, -72.700857 4.061958, -72.635571 4.089095, -72.575312 4.126149, -72.52156100000001 4.172207, -72.475641 4.226139, -72.438683 4.286616, -72.411599 4.352151, -72.39505699999999 4.421132, -72.38946799999999 4.491861, -72.394971 4.562596, -72.41143599999999 4.631597, -72.43845899999999 4.697162, -72.47537699999999 4.757677, -72.521283 4.81165, -72.575048 4.857751, -72.635347 4.894843, -72.700694 4.92201, -72.76947699999999 4.938584, -72.84 4.944154))"},{"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 940 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002739-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.newwp8
title: Occurrence Download

description: A dataset containing 14390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Alnus incana)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 14390 records from 229 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002741-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.