cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/kxcza5
title: Morphological and mitogenomic characteristics of Chinese endemic species Blaps (Blaps) chinensis (Faldermann, 1835) (Coleoptera, Tenebrionidae, Blaptini)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Liu, Lan-Fang, Zhao, Wei, Liu, Shan-Shan, Ren, Guo-Dong (2025): Morphological and mitogenomic characteristics of Chinese endemic species Blaps (Blaps) chinensis (Faldermann, 1835) (Coleoptera, Tenebrionidae, Blaptini). Zootaxa 5729 (4): 501-518, DOI: 10.11646/zootaxa.5729.4.1, URL: https://doi.org/10.11646/zootaxa.5729.4.1AbstractBlaps (Blaps) chinensis (Faldermann, 1835) is an endemic species to north-central China. We provide the first description and illustration of the egg and pupal stages of this species, supplemented by additional larval and adult morphology. Updated keys to 24 larval and 11 pupal stages of Chinese Blaps species are presented. Additionally, we report the first complete mitochondrial genome sequence and analysis for B. (B) chinensis.
DOI: 10.3535/mrm-5y4-xrg
title: Latirus barclayi (Reeve, 1847)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/rqt-k9c-7ps
title: Reticunassa paupera (A. Gould, 1850)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/60a-84y-j97
title: Morula uva (Röding, 1798)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/a52-psp-gsm
title: Hysteroconcha lupanaria (Lesson, 1831)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ega-68q-712
title: Albinaria sphakiota (Maltzan, 1887)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/7e0-fns-00e
title: Leptochiton cancellatus (G. B. Sowerby II, 1840)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qte-a5p-cq1
title: Acanthochitona fascicularis (Linnaeus, 1767)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/r47qkz
title: A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Yin, Hai-Xiang, Zhang, Yu-Long, Li, Xin-Jiang (2025): A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae). Zootaxa 5729 (3): 498-500, DOI: 10.11646/zootaxa.5729.3.9, URL: https://doi.org/10.11646/zootaxa.5729.3.9
DOI: 10.6084/m9.figshare.31135108
title: Cool Cities Heat Risk Index (HRI) Rotterdam 100 x 100m shapefile

description: Dataset: Cool Cities Heat Risk Index (HRI) – Rotterdam, The NetherlandsDescriptionThis dataset contains the Cool Cities Heat Risk Index (HRI) for the municipality of Rotterdam, The Netherlands. The HRI is a spatial composite index that identifies where extreme heat is most likely to cause harm by combining hazard, exposure, and vulnerability into a single indicator. The index follows the IPCC risk framework and is designed as a screening tool to support urban climate adaptation planning and prioritisation.The Rotterdam HRI is calculated at 100 by 100 meter grid resolution using open, harmonised datasets. Values range from 0 to 1 and represent relative heat risk within the city, not absolute or predictive health impacts.InputsHazard: Percentage of each grid cell area exposed to high heat stress, based on PET derived from the KlimaatEffectAtlas.Exposure: Number of residents, elderly residents (65 plus), children (0 to 15), women, and dwellings per grid cell.Sensitivity: Single-person households, residents receiving unemployment, social or disability benefits, social housing dwellings, and residents with a migration background.Adaptive capacity: Percentage of owner-occupied dwellings and average property value.All indicators are capped at the city specific mean plus two standard deviations and normalized to a 0 to 1 range.MethodsHazard, exposure, and vulnerability are combined multiplicatively. Vulnerability is calculated as a weighted combination of sensitivity and adaptive capacity, with sensitivity receiving double weight. Missing values are handled using neutral fallback rules to avoid artificial extremes. The final HRI is normalised and transformed using a fourth root to improve interpretability.Intended useThis dataset supports identification of priority areas for heat adaptation in Rotterdam, comparison of relative risk patterns within the city, and communication with planners, policymakers, and stakeholders.LimitationsThe HRI represents relative spatial patterns under modelled extreme heat conditions. It does not include health outcome data, indoor temperatures, or temporal variation such as repeated heatwaves or nighttime heat stress.
DOI: 10.6084/m9.figshare.31135108.v1
title: Rotterdam 100 x 100m Heat Risk Index shapefile

description: Dataset: Cool Cities Heat Risk Index (HRI) – Rotterdam, The NetherlandsDescriptionThis dataset contains the Cool Cities Heat Risk Index (HRI) for the municipality of Rotterdam, The Netherlands. The HRI is a spatial composite index that identifies where extreme heat is most likely to cause harm by combining hazard, exposure, and vulnerability into a single indicator. The index follows the IPCC risk framework and is designed as a screening tool to support urban climate adaptation planning and prioritisation.The Rotterdam HRI is calculated at 100 by 100 meter grid resolution using open, harmonised datasets. Values range from 0 to 1 and represent relative heat risk within the city, not absolute or predictive health impacts.InputsHazard: Percentage of each grid cell area exposed to high heat stress, based on PET derived from the KlimaatEffectAtlas.Exposure: Number of residents, elderly residents (65 plus), children (0 to 15), women, and dwellings per grid cell.Sensitivity: Single-person households, residents receiving unemployment, social or disability benefits, social housing dwellings, and residents with a migration background.Adaptive capacity: Percentage of owner-occupied dwellings and average property value.All indicators are capped at the city specific mean plus two standard deviations and normalized to a 0 to 1 range.MethodsHazard, exposure, and vulnerability are combined multiplicatively. Vulnerability is calculated as a weighted combination of sensitivity and adaptive capacity, with sensitivity receiving double weight. Missing values are handled using neutral fallback rules to avoid artificial extremes. The final HRI is normalised and transformed using a fourth root to improve interpretability.Intended useThis dataset supports identification of priority areas for heat adaptation in Rotterdam, comparison of relative risk patterns within the city, and communication with planners, policymakers, and stakeholders.LimitationsThe HRI represents relative spatial patterns under modelled extreme heat conditions. It does not include health outcome data, indoor temperatures, or temporal variation such as repeated heatwaves or nighttime heat stress.
DOI: 10.6084/m9.figshare.31135108.v2
title: Cool Cities Heat Risk Index (HRI) Rotterdam 100 x 100m shapefile

description: Dataset: Cool Cities Heat Risk Index (HRI) – Rotterdam, The NetherlandsDescriptionThis dataset contains the Cool Cities Heat Risk Index (HRI) for the municipality of Rotterdam, The Netherlands. The HRI is a spatial composite index that identifies where extreme heat is most likely to cause harm by combining hazard, exposure, and vulnerability into a single indicator. The index follows the IPCC risk framework and is designed as a screening tool to support urban climate adaptation planning and prioritisation.The Rotterdam HRI is calculated at 100 by 100 meter grid resolution using open, harmonised datasets. Values range from 0 to 1 and represent relative heat risk within the city, not absolute or predictive health impacts.InputsHazard: Percentage of each grid cell area exposed to high heat stress, based on PET derived from the KlimaatEffectAtlas.Exposure: Number of residents, elderly residents (65 plus), children (0 to 15), women, and dwellings per grid cell.Sensitivity: Single-person households, residents receiving unemployment, social or disability benefits, social housing dwellings, and residents with a migration background.Adaptive capacity: Percentage of owner-occupied dwellings and average property value.All indicators are capped at the city specific mean plus two standard deviations and normalized to a 0 to 1 range.MethodsHazard, exposure, and vulnerability are combined multiplicatively. Vulnerability is calculated as a weighted combination of sensitivity and adaptive capacity, with sensitivity receiving double weight. Missing values are handled using neutral fallback rules to avoid artificial extremes. The final HRI is normalised and transformed using a fourth root to improve interpretability.Intended useThis dataset supports identification of priority areas for heat adaptation in Rotterdam, comparison of relative risk patterns within the city, and communication with planners, policymakers, and stakeholders.LimitationsThe HRI represents relative spatial patterns under modelled extreme heat conditions. It does not include health outcome data, indoor temperatures, or temporal variation such as repeated heatwaves or nighttime heat stress.
DOI: 10.6084/m9.figshare.28525091
title: Dataset for 'Influence of glaciological structures on the spatial distribution of cryoconite holes, northern Victoria Land, East Antarctica'

description: Three blue-ice areas in the upper reaches of Rennick Glacier, East Antarctica, are investigated using satellite remote sensing to assess the influence of meso- to large-scale glaciological structures on cryoconite hole distribution. In total, 15 299 cryoconite holes and 1 600 structures are geospatially analysed, which indicate cryoconite holes are commonly concentrated in areas with prominent meso-scale ice structures. The emergence of debris entrained in primary stratification promotes the development of cryoconite holes along the surface expression of debris-bearing layers. Differential ablation of penetrative structures and their constituent ice facies can form a ridge-and-furrow ice-surface topography that captures supraglacial hydrology and sediments. As a result, trains of cryoconite holes develop in furrows that trace the surface expression of planar layers. Large-scale topographic barriers that form at flow-unit boundaries constrain cryoconite holes within discrete flow units by inhibiting the transport of supraglacial sediments. The majority of cryoconite holes are located in low-slope areas (&lt; 5°) where sediments are less susceptible to stripping events. Cryoconite holes on steeper slopes are preferentially located near to flow-unit boundaries where the topographic expression of meso-scale structures can offset the influence of larger-scale topography by preventing sediments being washed down-slope. Although a range of variables can influence the distribution of cryoconite holes, meso- to large-scale structures play an important role in the development of ice-surface topography and the delivery of sediments from different sources, which can strongly influence the distribution and composition of cryoconite holes.
DOI: 10.6084/m9.figshare.28525091.v2
title: Dataset for 'Influence of glaciological structures on the spatial distribution of cryoconite holes, northern Victoria Land, East Antarctica'

description: Three blue-ice areas in the upper reaches of Rennick Glacier, East Antarctica, are investigated using satellite remote sensing to assess the influence of meso- to large-scale glaciological structures on cryoconite hole distribution. In total, 15 299 cryoconite holes and 1 600 structures are geospatially analysed, which indicate cryoconite holes are commonly concentrated in areas with prominent meso-scale ice structures. The emergence of debris entrained in primary stratification promotes the development of cryoconite holes along the surface expression of debris-bearing layers. Differential ablation of penetrative structures and their constituent ice facies can form a ridge-and-furrow ice-surface topography that captures supraglacial hydrology and sediments. As a result, trains of cryoconite holes develop in furrows that trace the surface expression of planar layers. Large-scale topographic barriers that form at flow-unit boundaries constrain cryoconite holes within discrete flow units by inhibiting the transport of supraglacial sediments. The majority of cryoconite holes are located in low-slope areas (&lt; 5°) where sediments are less susceptible to stripping events. Cryoconite holes on steeper slopes are preferentially located near to flow-unit boundaries where the topographic expression of meso-scale structures can offset the influence of larger-scale topography by preventing sediments being washed down-slope. Although a range of variables can influence the distribution of cryoconite holes, meso- to large-scale structures play an important role in the development of ice-surface topography and the delivery of sediments from different sources, which can strongly influence the distribution and composition of cryoconite holes.
DOI: 10.6084/m9.figshare.28525091.v1
title: Influence of glaciological structures on the spatial distribution of cryoconite holes, northern Victoria Land, East Antarctica

description: Three blue-ice areas in the upper reaches of Rennick Glacier, East Antarctica, are investigated using satellite remote sensing to assess the influence of meso- to large-scale glaciological structures on cryoconite hole distribution. In total, 15 299 cryoconite holes and 1 600 structures are geospatially analysed, which indicate cryoconite holes are commonly concentrated in areas with prominent meso-scale ice structures. The emergence of debris entrained in primary stratification promotes the development of cryoconite holes along the surface expression of debris-bearing layers. Differential ablation of penetrative structures and their constituent ice facies can form a ridge-and-furrow ice-surface topography that captures supraglacial hydrology and sediments. As a result, trains of cryoconite holes develop in furrows that trace the surface expression of planar layers. Large-scale topographic barriers that form at flow-unit boundaries constrain cryoconite holes within discrete flow units by inhibiting the transport of supraglacial sediments. The majority of cryoconite holes are located in low-slope areas (&lt; 5°) where sediments are less susceptible to stripping events. Cryoconite holes on steeper slopes are preferentially located near to flow-unit boundaries where the topographic expression of meso-scale structures can offset the influence of larger-scale topography by preventing sediments being washed down-slope. Although a range of variables can influence the distribution of cryoconite holes, meso- to large-scale structures play an important role in the development of ice-surface topography and the delivery of sediments from different sources, which can strongly influence the distribution and composition of cryoconite holes.
DOI: 10.3535/69q-bgz-49n
title: Vexillum Röding, 1798

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/j9s-avc-5tc
title: Vexillum Röding, 1798

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.18349071
title: TABLE 1 in A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae)

description: TABLE 1. Comparison of Bryodemella (s. str.) dui sp. nov. and B. (s. str.) holdereri (Krauss, 1901).
MaleBryodemella (s. str.) dui sp. novB. (s. str.) holdereri (Krauss, 1901)Length of body in male26.8 mm30.0–33.7 mmElytraRadial vein of elytra in male with 5 branchesRadial vein of elytra in male with 4 branchesHind tibiaRed on upper sideYellow on upper sideHind wingApical part darkApical part transparent
description: Published as part of Yin, Hai-Xiang, Zhang, Yu-Long & Li, Xin-Jiang, 2025, A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae), pp. 499 in Zootaxa 5729 (3) on page 499, DOI: 10.11646/zootaxa.5729.3.9, http://zenodo.org/record/18018972
DOI: 10.5281/zenodo.18349072
title: TABLE 1 in A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae)

description: TABLE 1. Comparison of Bryodemella (s. str.) dui sp. nov. and B. (s. str.) holdereri (Krauss, 1901).
MaleBryodemella (s. str.) dui sp. novB. (s. str.) holdereri (Krauss, 1901)Length of body in male26.8 mm30.0–33.7 mmElytraRadial vein of elytra in male with 5 branchesRadial vein of elytra in male with 4 branchesHind tibiaRed on upper sideYellow on upper sideHind wingApical part darkApical part transparent
description: Published as part of Yin, Hai-Xiang, Zhang, Yu-Long & Li, Xin-Jiang, 2025, A new species of the subgenus Bryodemella (s. str.) Yin, 1982 from Xizang, China (Orthoptera: Acridoidea: Oedipodidae), pp. 499 in Zootaxa 5729 (3) on page 499, DOI: 10.11646/zootaxa.5729.3.9, http://zenodo.org/record/18018972
DOI: 10.3535/aw5-y8p-j3r
title: Engina lineata (Reeve, 1846)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/b43-yen-szg
title: Nassarius alabasteroides H. H. Kool, 2009

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/4p1-q8j-zeg
title: Albinaria idaea lindneri H. Nordsieck, 1998

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/6es-kyz-75w
title: Albinaria anatolica (J. R. Roth, 1839)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/tt5-e78-es1
title: Albinaria senilis leucadia (Westerlund, 1901)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.18348425
title: Core scripts used for the results in the article "Closing the Late‑Time Sector of the Hubble Tension in the Alternative Cosmological Model (AMC)"

description: Core scripts used for the results in article "AMC_HubbleTension_LateTime_Article":

·        amc_cosmo.py — AMC mapping (τ(z), D_M(z), d_L), closed‑form integral, H_geo diagnostic, SN χ² with analytic M minimization, BAO χ² utilities.

·        run_step12_caseA.py — Step 1+2 Case A run: Pantheon full (stat+sys cov) + BOSS DR12 BAO consensus (6×6 cov). Produces Table 1.

·        run_amc_drag_option1_timescale.py — toy microphysics (Saha+floor, SI‑fixed) diagnostic; produces Table 2.

·        run_amc_optionB_drag_option1.py — Option B scaling diagnostic; produces Table 3.

·        run_amc_optionB_option1_xe_tanh.py — tanh x_e(T) diagnostic; produces Table 4.

·        run_amc_optionB_option1_prefactor_sweep.py — Γ_drag prefactor sensitivity; produces Table 5.

·        run_amc_optionB_option1_Tbg_eps_scan_v2.py — ε deformation scan of T_bg(τ); produces Table 6.

Data inputs: Pantheon ‘full’ light‑curve parameter file and systematic covariance matrix; BOSS DR12 BAO consensus measurements and covariance. These are standard public products.
DOI: 10.3535/y58-4hb-dyw
title: Kaliella W. T. Blanford, 1863

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.18348424
title: Core scripts used for the results in the article "Closing the Late‑Time Sector of the Hubble Tension in the Alternative Cosmological Model (AMC)"

description: Core scripts used for the results in article "AMC_HubbleTension_LateTime_Article":

·        amc_cosmo.py — AMC mapping (τ(z), D_M(z), d_L), closed‑form integral, H_geo diagnostic, SN χ² with analytic M minimization, BAO χ² utilities.

·        run_step12_caseA.py — Step 1+2 Case A run: Pantheon full (stat+sys cov) + BOSS DR12 BAO consensus (6×6 cov). Produces Table 1.

·        run_amc_drag_option1_timescale.py — toy microphysics (Saha+floor, SI‑fixed) diagnostic; produces Table 2.

·        run_amc_optionB_drag_option1.py — Option B scaling diagnostic; produces Table 3.

·        run_amc_optionB_option1_xe_tanh.py — tanh x_e(T) diagnostic; produces Table 4.

·        run_amc_optionB_option1_prefactor_sweep.py — Γ_drag prefactor sensitivity; produces Table 5.

·        run_amc_optionB_option1_Tbg_eps_scan_v2.py — ε deformation scan of T_bg(τ); produces Table 6.

Data inputs: Pantheon ‘full’ light‑curve parameter file and systematic covariance matrix; BOSS DR12 BAO consensus measurements and covariance. These are standard public products.
DOI: 10.3535/fm3-9bq-qgw
title: Trochozonites Pfeffer, 1883

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qpz-qql-nk1
title: Trochozonites Pfeffer, 1883

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9pd-31c-mkv
title: Afropunctum F. Haas, 1934

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fdm-z79-me2
title: Trochoidea T. Brown, 1827

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.4yw8xw
title: Occurrence Download

description: A dataset containing 954 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((27.88120 17.36132,131.11880 17.36132,131.11880 58.63868,27.88120 58.63868,27.88120 17.36132))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Haloxylon ammodendron"
 ]
}

 The dataset includes 954 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007023-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2ztv4w
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Denmark",
 "DatasetKey is Danish benthic marine monitoring data from ODAM",
 "Geometry POLYGON((11.954823410190357 55.98427132084233,12.08730124536359 55.98427132084233,12.08730124536359 56.116749156015565,11.954823410190357 56.116749156015565,11.954823410190357 55.98427132084233))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Macoma balthica",
 "Year 1996-2026"
 ]
}

 The dataset includes 28 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007021-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.92rryw
title: Occurrence Download

description: A dataset containing 1471 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A Darwin Core Dataset of Scorpions (Arachnida: Scorpiones) from the Royal Belgian Institute of Natural Sciences (RBINS) Collections"
 ]
}

 The dataset includes 1471 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007022-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.