cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/b5sf98
title: Spider occurrences extracted from the 'The remarks to the fauna and biotopical distribution of spiders in the Talovkaya steppe = Замечания к фауне и биотопическому распределению пауков Таловской степи'

description: The dataset contains spider occurrences extracted from the following article/book: [Esyunin S.L., Vlasov S.V. 2021. The remarks to the fauna and biotopical distribution of spiders in the Talovkaya steppe = Замечания к фауне и биотопическому распределению пауков Таловской степи // А.А. Чибилёв (предс. ред. колл.). Степи Северной Евразии: мат-лы IX межд. симпоз. Оренбург: ОГУ. С.300–304 (рус., рез. англ.).] <b>Attention! As far as these were published in print, we strongly recommend to cite the original work along with this GBIF dataset!</b>Data were digitized within the Faunistics International project for the occurrence data extraction from the scientific literature: faunistic, taxonomical, ecological and other kinds. Full text is available here. Data are available here as well.
DOI: 10.6084/m9.figshare.31210204
title: LUXURY'S DNA: A SYSTEMATIC REVIEW OF BRAND ATTRIBUTES AND TRANSFER STRATEGIES

description: Purpose-This systematic review addresses the translation gap between luxury brand management and mainstream categories, examining the transferability of luxury elements and the conditions under which it occurs. Despite extensive luxury scholarship and emerging premiumisation, theoretical fragmentation persists: luxury research remains confined within its sector, while mainstream brand studies lack grounding in luxury theory. Design/methodology/approach-Following PRISMA 2020 guidelines, we systematically reviewed 23 peer-reviewed articles from 2015-2025 in Scopus, Web of Science, and Business Source Complete. Through narrative synthesis across seven themes, we analyzed luxury attributes, exclusivity mechanisms, and transferability conditions. Findings-The results reveal transferability through three layers. Layer 1 (universal brand equity principles) shows full transferability across categories. Layer 2 (strategic codes: artificial scarcity, experiential orchestration, digital stratification, sustainability integration) requires authentic symbolic translation, not superficial imitation. Layer 3 (cultural legitimacy: historical heritage, institutional consecration, extreme craftsmanship) resists replication due to temporal requirements. Cross-cultural findings show that transferability varies: Western consumers prioritize subtle refinement, while emerging markets favor conspicuous signalling, moderating successful adoption strategies. Originality/value-This review provides a systematic integration of luxury-to-mainstream transferability, proposing a three-layer framework that resolves the theoretical ambiguity regarding which elements can be adapted versus resisting replication. This study advances 2 luxury brand management theory by showing that luxury's strategic essence is layered rather than monolithic, while offering evidence-based premiumization guidance for aspirational brands.
DOI: 10.6084/m9.figshare.31210204.v1
title: LUXURY'S DNA: A SYSTEMATIC REVIEW OF BRAND ATTRIBUTES AND TRANSFER STRATEGIES

description: Purpose-This systematic review addresses the translation gap between luxury brand management and mainstream categories, examining the transferability of luxury elements and the conditions under which it occurs. Despite extensive luxury scholarship and emerging premiumisation, theoretical fragmentation persists: luxury research remains confined within its sector, while mainstream brand studies lack grounding in luxury theory. Design/methodology/approach-Following PRISMA 2020 guidelines, we systematically reviewed 23 peer-reviewed articles from 2015-2025 in Scopus, Web of Science, and Business Source Complete. Through narrative synthesis across seven themes, we analyzed luxury attributes, exclusivity mechanisms, and transferability conditions. Findings-The results reveal transferability through three layers. Layer 1 (universal brand equity principles) shows full transferability across categories. Layer 2 (strategic codes: artificial scarcity, experiential orchestration, digital stratification, sustainability integration) requires authentic symbolic translation, not superficial imitation. Layer 3 (cultural legitimacy: historical heritage, institutional consecration, extreme craftsmanship) resists replication due to temporal requirements. Cross-cultural findings show that transferability varies: Western consumers prioritize subtle refinement, while emerging markets favor conspicuous signalling, moderating successful adoption strategies. Originality/value-This review provides a systematic integration of luxury-to-mainstream transferability, proposing a three-layer framework that resolves the theoretical ambiguity regarding which elements can be adapted versus resisting replication. This study advances 2 luxury brand management theory by showing that luxury's strategic essence is layered rather than monolithic, while offering evidence-based premiumization guidance for aspirational brands.
DOI: 10.15468/dl.8m5cje
title: Occurrence Download

description: A dataset containing 773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Excoecaria agallocha",
 "HasCoordinate is true",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2010",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "not" : {
 "HasGeospatialIssue" : [
 "is true"
 ]
 }
 }
 ]
}

 The dataset includes 773 records from 56 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001873-260129131611470/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.30784407
title: Predictors of Acute Kidney Injury in Patients Prescribed Immune Checkpoint Inhibitor Therapy and Their Association with Death: A Systematic Review and Meta-Analysis

description: Immune checkpoint inhibitors (ICIs) are a novel and promising anti-cancer therapy. We conducted this systematic review to precisely quantify the occurrence and development for actue kidney injury(AKI) following ICIs treatment for cancer. We conducted a search of the PubMed, Embase, Web of Science, and Cochrane Library databases. Twenty-nine studies, comprising 24,953 cancer patients who received ICIs were finally eligible. The incidence of AKI was 16.2% (95%CI:12.8%–19.8%); the incidence of immune checkpoint inhibitor-associated acute kidney injury (ICPi-AKI) was 3.1%(95%CI:2.4%–4%); the incidence of non-ICPi-AKI was 11.2%(95%CI:8.4%–14.3%), and the incidence of sustained AKI was 14.9%(95%CI:7.5%–24.3%). Patients who developed AKI (HR = 1.521(95%CI:1.208–1.916)) and ICPi-AKI (HR = 1.407(95%CI:1.059–1.869)) exhibited an elevated risk of all-cause mortality. An increased risk for AKI was observed with preexisting chronic kidney disease (CKD) and combined with other extrarenal immune-related adverse events (irAEs). The use of nonsteroidal anti-inflammatory drugs (NSAIDs), proton pump inhibitor (PPI), diuretic, renin-angiotensin-aldosterone system (RAASi), antibiotics and fluidone was also significantly associated with incident AKI. Combined therapy had a greater impact on renal injury compared to monotherapy. Patients using ipilimumab were more prone to developing AKI, compared to those using nivoluma. CTLA4 (ref’PD-1) was associated with a higher likelihood of sustained AKI. The use of PDL-1(ref=’PD-1) was linked to an increased susceptibility to ICPi-AKI. The occurrence of AKI was intricately linked to specific complications, the concomitant use of certain medications, and the specific regimen of ICIs. This deserves our attention.
DOI: 10.6084/m9.figshare.30784407.v1
title: Predictors of Acute Kidney Injury in Patients Prescribed Immune Checkpoint Inhibitor Therapy and Their Association with Death: A Systematic Review and Meta-Analysis

description: Immune checkpoint inhibitors (ICIs) are a novel and promising anti-cancer therapy. We conducted this systematic review to precisely quantify the occurrence and development for actue kidney injury(AKI) following ICIs treatment for cancer. We conducted a search of the PubMed, Embase, Web of Science, and Cochrane Library databases. Twenty-nine studies, comprising 24,953 cancer patients who received ICIs were finally eligible. The incidence of AKI was 16.2% (95%CI:12.8%–19.8%); the incidence of immune checkpoint inhibitor-associated acute kidney injury (ICPi-AKI) was 3.1%(95%CI:2.4%–4%); the incidence of non-ICPi-AKI was 11.2%(95%CI:8.4%–14.3%), and the incidence of sustained AKI was 14.9%(95%CI:7.5%–24.3%). Patients who developed AKI (HR = 1.521(95%CI:1.208–1.916)) and ICPi-AKI (HR = 1.407(95%CI:1.059–1.869)) exhibited an elevated risk of all-cause mortality. An increased risk for AKI was observed with preexisting chronic kidney disease (CKD) and combined with other extrarenal immune-related adverse events (irAEs). The use of nonsteroidal anti-inflammatory drugs (NSAIDs), proton pump inhibitor (PPI), diuretic, renin-angiotensin-aldosterone system (RAASi), antibiotics and fluidone was also significantly associated with incident AKI. Combined therapy had a greater impact on renal injury compared to monotherapy. Patients using ipilimumab were more prone to developing AKI, compared to those using nivoluma. CTLA4 (ref’PD-1) was associated with a higher likelihood of sustained AKI. The use of PDL-1(ref=’PD-1) was linked to an increased susceptibility to ICPi-AKI. The occurrence of AKI was intricately linked to specific complications, the concomitant use of certain medications, and the specific regimen of ICIs. This deserves our attention.
DOI: 10.15468/dl.6yrat2
title: Occurrence Download

description: A dataset containing 8470 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lentipes watsoni, Melanochromis dialeptos, Pseudotropheus cyaneorhabdos, Corydoras sychri, Corydoras undulatus, Corydoras zygatus, Aspidoras albater, Aspidoras brunneus, Aspidoras carvalhoi, Aspidoras eurycephalus, Aspidoras fuscoguttatus, Aspidoras lakoi, Aspidoras maculosus, Aspidoras menezesi, Pseudotropheus perileucos, Melanochromis baliodigma, Pseudotropheus benetos, Melanochromis lepidiadaptes, Aspidoras poecilus, Aspidoras raimundi, Aspidoras rochai, Aspidoras spilotus, Aspidoras virgulatus, Chilodus fritillus, Mastacembelus traversi, Rasbora laticlavia, Silurichthys citatus, Hyphessobrycon epicharis, Hyphessobrycon micropterus, Corydoras vittatus, Hyphessobrycon eques, Corydoras coppenamensis, Hyphessobrycon compressus, Hyphessobrycon milleri, Hyphessobrycon panamensis, Hyphessobrycon ecuadoriensis, Ectrepopterus uruguayensis, Hyphessobrycon haraldschultzi, Hyphessobrycon georgettae, Hyphessobrycon werneri, Hyphessobrycon pyrrhonotus, Hyphessobrycon loweae, Hyphessobrycon hasemani, Crenicichla cincta, Tahuantinsuyoa macantzatza, Parachondrostoma arrigonis, Chondrostoma scodrense, Chondrostoma vardarense, Periophthalmus waltoni, Allodontichthys polylepis, Allodontichthys zonistius, Allotoca regalis, Chapalichthys peraticus, Acentrogobius dayi, Ilyodon lennoni, Ilyodon whitei, Allotoca catarinae, Allotoca diazi, Allotoca meeki, Skiffia lermae, Alfaro cultratus, Alfaro huberi, Brachyrhaphis cascajalensis, Brachyrhaphis episcopi, Brachyrhaphis hartwegi, Brachyrhaphis holdridgei, Brachyrhaphis parismina, Brachyrhaphis punctifer, Brachyrhaphis rhabdophora, Brachyrhaphis roseni, Brachyrhaphis terrabensis, Spectrolebias semiocellatus, Carasobarbus sublimus, Crenicichla rosemariae, Carlhubbsia kidderi, Carlhubbsia stuarti, Cnesterodon carnegiei, Salmo carpio, Salmo dentex, Hoplosternum punctatum, Salmo marmoratus, Megalechis thoracata, Lepthoplosternum pectorale, Lepthoplosternum altamazonicum, Salmo ohridanus, Lepthoplosternum beni, Lepthoplosternum tordilho, Romanogobio benacensis, Tropidophoxinellus spartiaticus, Cobitis hellenica, Cobitis meridionalis, Cobitis punctilineata, Cobitis trichonica, Cobitis vardarensis, Sabanejewia larvata, Oxynoemacheilus argyrogramma, Oxynoemacheilus pindus, Knipowitschia ephesi, Knipowitschia mrakovcici, Brachymystax savinovi)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 8470 records from 135 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001874-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pfy8sa
title: Occurrence Download

description: A dataset containing 2094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is South America",
 "Country is Brazil",
 "GadmGid is one of (BRA, BRA.10_1)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aspidosperma pyrifolium"
 ]
}

 The dataset includes 2094 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001875-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mpc52g
title: Occurrence Download

description: A dataset containing 56097 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Geometry POLYGON((-1.46573 50.98398,0.88192 50.98398,0.88192 52.0532,-1.46573 52.0532,-1.46573 50.98398))",
 "HasGeospatialIssue is false",
 "TaxonKey is Fungi",
 "Year 2005-2015"
 ]
}

 The dataset includes 56097 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001836-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/sfe3qz
title: Spider occurrences extracted from the 'Fauna and biotopical distribution of the gnaphosid spiders (Aranei) in Aschisayskaya steppe = Фауна и биотопическое распределение пауков сем. Gnaphosidae (Aranei) участка «Ащисайская степь»'

description: The dataset contains spider occurrences extracted from the following article/book: [Esyunin S.L., Tuneva T.K., Sokolova S.S. 2019. Fauna and biotopical distribution of the gnaphosid spiders (Aranei) in Aschisayskaya steppe = Фауна и биотопическое распределение пауков сем. Gnaphosidae (Aranei) участка «Ащисайская степь» // А.А. Чибилев (гл. ред.). Труды ФГБУ «Заповедники Оренбуржья». Оренбург, Саратов. Вып.2. С.143–149 (рус., рез. англ.).] <b>Attention! As far as these were published in print, we strongly recommend to cite the original work along with this GBIF dataset!</b>Data were digitized within the Faunistics International project for the occurrence data extraction from the scientific literature: faunistic, taxonomical, ecological and other kinds. Full text is available here. Data are available here as well.
DOI: 10.15468/dl.nwavqm
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Weberbauera spathulifolia",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 52 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001877-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34894/lny9vq
title: 2029-01-29 - NAKALA - CoreTrustSeal Requirements 2023-2025

description: CoreTrustSeal certification
DOI: 10.15468/dl.6bt5sj
title: Occurrence Download

description: A dataset containing 12361 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Chondrostoma oxyrhynchum, Chasmocranus bleekeri, Chasmocranus brevior, Chondrostoma variabile, Chasmocranus chimantanus, Nannoglanis fasciatus, Acentronichthys fissipinnis, Imparfinis hollandi, Acentronichthys leptos, Chasmocranus longior, Nemuroglanis mariai, Heptapterus multiradiatus, Heptapterus mustelinus, Heptapterus ornaticeps, Nemuroglanis panamensis, Chasmocranus peruanus, Chasmocranus quadrizonatus, Chasmocranus rosae, Heptapterus stewarti, Chasmocranus surinamensis, Heptapterus sympterygium, Chasmocranus tapanahoniensis, Phenacorhamdia tenuis, Chasmocranus truncatorostris, Squalius aphipsi, Microphysogobio tungtingensis, Oreoleuciscus humilis, Oreoleuciscus potanini, Rhynchocypris czekanowskii, Cetopsorhamdia insidiosa, Cetopsorhamdia molinae, Cetopsorhamdia nasus, Cetopsorhamdia boquillae, Cetopsorhamdia orinoco, Cetopsorhamdia phantasia, Cetopsorhamdia picklei, Cetopsorhamdia iheringi, Pimelodella leptosoma, Leiarius arekaima, Rhamdia foina, Rhodeus lighti, Rhamdia schomburgkii, Pimelodus albofasciatus, Romanogobio ciscaucasicus, Brachyrhamdia heteropleura, Pimelodella cristata, Pimelodella geryi, Chilatherina pricei, Melanotaenia caerulea, Melanotaenia mubiensis, Pseudaspius brandtii, Awaous flavus, Pimelodella macturki, Pimelodella megalops, Pimelodella procera, Goeldiella eques, Oxynoemacheilus merga, Hampala salweenensis, Cobitis sinensis, Sabanejewia caspia, Sabanejewia caucasica, Romanogobio elimeius, Xenotilapia rotundiventralis, Eigenmannia nigra, Sternopygus astrabes, Megadontognathus cuyuniensis, Compsaraia compsa, Sternarchella orthos, Hypopygus neblinae, Anatirostrum profundorum, Benthophiloides turcomanus, Benthophilus baeri, Benthophilus macrocephalus, Benthophilus granulosus, Benthophilus leptocephalus, Benthophilus leptorhynchus, Racenisia fimbriipinna, Gymnotus cataniapo, Gymnotus pedanopterus, Gymnotus stenoleucus, Sternarchorhynchus roseni, Archolaemus blax, Distocyclus conirostris, Eigenmannia goajira, Eigenmannia humboldtii, Eigenmannia macrops, Eigenmannia microstoma, Eigenmannia limbata, Eigenmannia trilineata, Hyrcanogobius bergi, Ponticola rhodioni, Ageneiosus inermis, Batrachocottus baicalensis, Batrachocottus multiradiatus, Batrachocottus nikolskii, Cottus czerskii, Leocottus kesslerii, Cottus sibiricus, Rhabdolichops caviceps, Rhabdolichops electrogrammus)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12361 records from 190 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001878-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10694911
title: ENCODE LR-RNA-seq models and expression values

description: In this object are the following files:

 



filt_ab_tpm_mouse.tsv / filt_ab_tpm_human.tsv: Expression levels in TPM for each transcript in human and mouse

lr_mouse_library_data_summary.tsv / lr_human_library_data_summary.tsv: Metadata for each dataset in human and mouse

cerberus.gtf / mouse_cerberus.gtf: Transcript models in GTF format

human_ucsc_transcripts.gtf / mouse_ucsc_transcripts.gtf: Transcript models for transcripts that passed expression filtering (>= 1 TPM in at least one library; transcripts from known 

human_protein_summary.tsv / mouse_protein_summary.tsv: Summary of protein coding predictions, including ORF locations and NMD status

human_triplets.h5  / mouse_triplets.h5: Cerberus H5 objects (see here for specification) that detail the TSSs, ICs, and TESs used in each transcript, as well as the triplets calculated globally and for individual samples. 

human_swan_graph.p  / mouse_swan_graph.p: SwanGraph pickled python objects.

viewer_data.tar.gz: Compressed files used for the data viewer comprised of human_triplets.h5, mouse_triplets.h5, human_swan_graph.p, and mouse_swan_graph.p
DOI: 10.5281/zenodo.18415427
title: ENCODE LR-RNA-seq models and expression values

description: In this object are the following files:

 



filt_ab_tpm_mouse.tsv / filt_ab_tpm_human.tsv: Expression levels in TPM for each transcript in human and mouse

lr_mouse_library_data_summary.tsv / lr_human_library_data_summary.tsv: Metadata for each dataset in human and mouse

cerberus.gtf / mouse_cerberus.gtf: Transcript models in GTF format

human_ucsc_transcripts.gtf / mouse_ucsc_transcripts.gtf: Transcript models for transcripts that passed expression filtering (>= 1 TPM in at least one library; transcripts from known 

human_protein_summary.tsv / mouse_protein_summary.tsv: Summary of protein coding predictions, including ORF locations and NMD status

human_triplets.h5  / mouse_triplets.h5: Cerberus H5 objects (see here for specification) that detail the TSSs, ICs, and TESs used in each transcript, as well as the triplets calculated globally and for individual samples. 

human_swan_graph.p  / mouse_swan_graph.p: SwanGraph pickled python objects.

viewer_data.tar.gz: Compressed files used for the data viewer comprised of human_triplets.h5, mouse_triplets.h5, human_swan_graph.p, and mouse_swan_graph.p
DOI: 10.15468/tnfdvc
title: Spider occurrences extracted from the 'The first data on spiders from the “Burtinskaya steppe” Kordon in the Orenburg Reserve'

description: The dataset contains spider occurrences extracted from the following article/book: [Vlasov S.V. 2021. The first data on spiders from the “Burtinskaya steppe” Kordon in the Orenburg Reserve // Ю.М. Марусик и др. (ред.). Мат-лы IV Межд. арахнол. совещ. “Arachnomeeting”, посвящ. 50-летию «Определителя пауков Европейской части СССР» В.П. Тыщенко (Екатеринбург, 13, 19 и 25 февр. 2021 г.). М.: Т-во науч. изданий КМК. С.49. ] <b>Attention! As far as these were published in print, we strongly recommend to cite the original work along with this GBIF dataset!</b>Data were digitized within the Faunistics International project for the occurrence data extraction from the scientific literature: faunistic, taxonomical, ecological and other kinds. Full text is available here. Data are available here as well.
DOI: 10.5281/zenodo.18430475
title: Pretrained GNN model weights for SCADA data imputation (Kelmarsh and Penmanshiel wind farms)

description: Model weights for GNN Wind Farm models based on Kelmarsh and Penmanshiel wind farm data. This is part of the project Data imputation for SCADA data using Graph Neural Networks and Transfer Learning.

The model files (.pt) are PyTorch state dicts. 

To load the models, the FarmGATv2 class from the code repository (DOI pending) needs to be used.
DOI: 10.5281/zenodo.18430474
title: Pretrained GNN model weights for SCADA data imputation (Kelmarsh and Penmanshiel wind farms)

description: Model weights for GNN Wind Farm models based on Kelmarsh and Penmanshiel wind farm data. This is part of the project Data imputation for SCADA data using Graph Neural Networks and Transfer Learning.

The model files (.pt) are PyTorch state dicts. 

To load the models, the FarmGATv2 class from the code repository (DOI pending) needs to be used.
DOI: 10.15468/dl.wtzmch
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Kandelia candel",
 "HasCoordinate is true",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2010",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "not" : {
 "HasGeospatialIssue" : [
 "is true"
 ]
 }
 }
 ]
}

 The dataset includes 67 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001879-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17340266
title: Reusability Report: Evaluating reproducibility and reusability of a biologically-informed deep neural network for biomedical research

description: Contains the pre-processed datasets for each experiment performed in the titular publication.
DOI: 10.5281/zenodo.17340265
title: Reusability Report: Evaluating reproducibility and reusability of a biologically-informed deep neural network for biomedical research

description: Contains the pre-processed datasets for each experiment performed in the titular publication.