cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48597/qbss-3rf5
title: Measurement of 2-methylbutane at Chilbolton Observatory

description: Measurement of 2-methylbutane at Chilbolton Observatory
DOI: 10.48597/qc8y-g5et
title: Measurement of Alpha_endosulfan at Pallas (Matorova)

description: Measurement of Alpha_endosulfan at Pallas (Matorova)
DOI: 10.48597/r3pg-wdvm
title: Measurement of Ethyne at Chilbolton Observatory

description: Measurement of Ethyne at Chilbolton Observatory
DOI: 10.48597/rpdb-bj9y
title: Measurement of OC/EC at Víznar

description: Measurement of OC/EC at Víznar
DOI: 10.48597/sb6m-vaeh
title: Measurement of Aerosol_light_scattering_coefficient at James River Face Wilderness

description: Measurement of Aerosol_light_scattering_coefficient at James River Face Wilderness
DOI: 10.48597/se8j-kg8s
title: Measurement of 2-methylpropene at San Pablo de los Montes

description: Measurement of 2-methylpropene at San Pablo de los Montes
DOI: 10.48597/tb48-eea5
title: Measurement of 2-methylbutane at San Pablo de los Montes

description: Measurement of 2-methylbutane at San Pablo de los Montes
DOI: 10.48597/tdpc-pdjq
title: Measurement of 1-pentene at San Pablo de los Montes

description: Measurement of 1-pentene at San Pablo de los Montes
DOI: 10.25592/uhhfdm.14147
title: Cognitive mechanisms of aversive prediction error-induced memory enhancements

description: While prediction errors (PEs) have long been recognized as critical in associative learning, emerging evidence indicates their significant role in episodic memory formation. This series of four experiments sought to elucidate the cognitive mechanisms underlying the enhancing effects of PEs related to aversive events on memory for surrounding neutral events. Specifically, we aimed to determine whether these PE effects are specific to predictive stimuli preceding the PE or if PEs create a transient window of enhanced, unselective memory formation. In a combined incidental encoding-fear learning task, participants (n=xxx) estimated aversive shock probabilities after unique stimuli. Physiological arousal and explicit PEs were measured during encoding to predict recognition memory tested either immediately after encoding (Experiment 3) or 24 hours later (Experiments 1-4). Our results show that PE-driven memory enhancement extends beyond predictive stimuli preceding the PE event to those encountered afterward. Furthermore, the retroactive memory enhancement induced by PEs may extend back longer than previously assumed, impacting stimuli presented 10 seconds before the PE. Importantly, our findings reveal that PE-related memory enhancement is specific to predictive stimuli, with uninformative stimuli not benefiting from PEs and even interfering with the PE-driven memory enhancement. This pattern demonstrates that PE effects are not unspecific but that PEs enhance memory for predictive stimuli encountered around a PE event. Notably, memory-enhancing effects of PEs persist even when controlling for changes in arousal. These findings provide insights into the cognitive mechanisms of PE-induced enhancements of memory, with potential implications for understanding aberrant emotional memory in fear-related disorders.
DOI: 10.5281/zenodo.7500538
title: Stimuli Responsive and Antimicrobial Cellulose-Chitosan Hydrogels Containing Polydiacetylene Nanosheets

description: Hydrogels were prepared by esterification of chitosan (Cs) with monochloroacetic acid to produce CMCs which was then crosslinked to HEC using citric acid as the crosslinking agent. To impart a stimuli responsiveness property to the hydrogels, polydiacetylene-zinc oxide (PDA-ZnO) nanosheets were synthesized in-situ during the crosslinking reaction followed by photopolymerization of the resultant composite. First, 10,12-pentacosadiynoic acid (PCDA) head groups were stabilized with ZnO nanoparticles in the presence of CMCs-HEC hydrogels in petroleum ether. This was followed by irradiating the composite with Uv radiation to photopolymerize the PCDA to PDA within the hydrogel matrix so as to impart thermal and pH responsiveness to the hydrogel
DOI: 10.5281/zenodo.7500539
title: Stimuli Responsive and Antimicrobial Cellulose-Chitosan Hydrogels Containing Polydiacetylene Nanosheets

description: Hydrogels were prepared by esterification of chitosan (Cs) with monochloroacetic acid to produce CMCs which was then crosslinked to HEC using citric acid as the crosslinking agent. To impart a stimuli responsiveness property to the hydrogels, polydiacetylene-zinc oxide (PDA-ZnO) nanosheets were synthesized in-situ during the crosslinking reaction followed by photopolymerization of the resultant composite. First, 10,12-pentacosadiynoic acid (PCDA) head groups were stabilized with ZnO nanoparticles in the presence of CMCs-HEC hydrogels in petroleum ether. This was followed by irradiating the composite with Uv radiation to photopolymerize the PCDA to PDA within the hydrogel matrix so as to impart thermal and pH responsiveness to the hydrogel
DOI: 10.48597/te6j-kepz
title: Measurement of Ethyne at San Pablo de los Montes

description: Measurement of Ethyne at San Pablo de los Montes
DOI: 10.48597/tkzr-yt8z
title: Measurement of PCB_101 at Pallas (Matorova)

description: Measurement of PCB_101 at Pallas (Matorova)
DOI: 10.48597/tm2x-qhdr
title: Measurement of Fluoranthene at Pallas (Matorova)

description: Measurement of Fluoranthene at Pallas (Matorova)
DOI: 10.48597/u5at-wf2u
title: Measurement of Toluene at San Pablo de los Montes

description: Measurement of Toluene at San Pablo de los Montes
DOI: 10.15468/dl.g889vs
title: Occurrence Download

description: A dataset containing 949 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Japan",
 "TaxonKey is Calopteryx atrata"
 ]
}

 The dataset includes 949 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013058-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z7zsb3
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Benin",
 "OccurrenceStatus is Present",
 "TaxonKey is Laccosperma opacum"
 ]
}

 The dataset includes 6 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013059-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.atvqfw
title: Occurrence Download

description: A dataset containing 507 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lucioperca lucioperca"
 ]
}

 The dataset includes 507 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013060-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.23405.65768
title: GY STEPS Analysis of PERS050-5S4 263 1 20 Real World Data by the Persian Curve (PC) GY STEP 07 PERSIAN QUANTILE COMPLETE
DOI: 10.15468/dl.unbexm
title: Occurrence Download

description: A dataset containing 6676 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to 9.085278",
 "DecimalLatitude is less than or equal to 14.085278",
 "DecimalLongitude is greater than or equal to -95.0",
 "DecimalLongitude is less than or equal to -90.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 6676 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013061-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17743761
title: Computational dataset for polymer–pharmaceutical interactions
DOI: 10.34740/kaggle/dsv/13902213
title: SOLANA Price Data Binance API (2020–Now)
DOI: 10.15468/dl.tscckc
title: Occurrence Download

description: A dataset containing 597 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Pomacea canaliculata"
 ]
}

 The dataset includes 597 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013062-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cut7y5
title: Occurrence Download

description: A dataset containing 192 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhadinaea laureata"
 ]
}

 The dataset includes 192 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013063-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17514455
title: Computational dataset for polymer–pharmaceutical interactions
DOI: 10.21420/p9gc-xf39
title: Nation-wide 1% AEP flood hazard for actual and future climates in Aotearoa New Zealand
DOI: 10.15468/dl.fk9jac
title: Occurrence Download

description: A dataset containing 37382 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acanthopagrus australis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 37382 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013064-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jyt4wq
title: Occurrence Download

description: A dataset containing 7286 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters 0.0-5000.0",
 "Country is Germany",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinus sylvestris",
 "Year 1980-2020"
 ]
}

 The dataset includes 7286 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013067-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jrvfgd
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fritillaria thunbergii",
 "Year 1900-2025"
 ]
}

 The dataset includes 7 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013066-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8j3tn3
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Cotinis pauperula"
 ]
}

 The dataset includes 106 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013068-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tqsnzw
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhadinaea macdougalli"
 ]
}

 The dataset includes 28 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013069-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17744058
title: CNT Cross-Domain Hazard Pure v1 — Baseline Hazard Fields Across Finance, Crypto, and Volatility

description: OverviewThis dataset provides the first Cross-Domain Hazard Pure (CDHR_PURE v1) release for Cognitive Nexus Theory (CNT). It collects a “pure” baseline set of hazard fields for multiple market domains using CNT’s hazard-band logic, before they are combined into a global drift index or cross-domain echo models.

CDHR_PURE v1 is meant to act as a backbone dataset: the raw hazard structure that underlies later CNT work such as the CNT Global Drift Field (D_global) and the CNT Cross-Domain Echo Window (CDEW).

Files in this release (CDHR_PURE_CDNN_release.zip)





CDHR_PURE_CDNN_SUMMARY.md





Human-readable summary of the CDHR_PURE pipeline and main findings.






CDHR_PURE_ZENODO_README.md





Detailed file layout and usage notes for this release.






CDHR_PURE_ZENODO_ABSTRACT.txt





Short abstract text for reuse.






CDHR_PURE_ZENODO_TWEET.txt





Tweet-length description of the dataset.






tables/cdhr_pure_cross_domain_aligned_raw.csv





Cross-domain aligned “raw” hazard features used in the CDHR_PURE analysis.






tables/cdhr_pure_h1_model_summary.csv





Summary of hazard-based models at horizon H=1, including performance metrics per domain/model.






tables/cdhr_pure_h1_segment_auc.csv





AUC values by segment for H=1 hazard models, useful for inspecting where hazard-based predictions work best or fail.






plots/cdhr_pure_h1_auc_by_model_finance_SPY.png





Visualization of H=1 AUC by model for the finance (SPY) hazard field.






plots/cdhr_pure_h1_auc_by_model_vol_VIX.png





Visualization of H=1 AUC by model for the volatility (VIX) hazard field.





Role in Cognitive Nexus Theory (CNT)





CDHR_PURE v1 exposes the baseline hazard planes for key market domains, before any compression into:





a global drift index D_globalD\_globalD_global, or




cross-domain echo / decoder models.






It is intended to sit alongside:





CNT Global Drift Field v1 — the scalar D_globalD\_globalD_global index built from cross-market hazard/drift features.




CNT Cross-Domain Echo Window v1 — the lead–lag map of how hazard in one system predicts hazard in another.





Together, these datasets form a small empirical backbone for CNT’s claims about shared drift structure and early-warning signals across domains.

Intended useThis dataset is suitable for:





independent analysis of hazard-band structure in SPY and VIX,




testing and reproducing H=1 hazard-based prediction results, and




serving as input to external systemic-risk or early-warning experiments that want a clean “pure hazard” baseline.



License and reuseThis dataset is intended for open reuse, replication, and criticism. Please cite this Zenodo record and relevant CNT materials when using it.
DOI: 10.5286/isis.e.rb2320286-3
title: Mixtures of 124-Triazole and TBA Bromide with H2O as examples of ternary deep eutectic solvents. Their structure by theoretical and experimental investigation.

description: The effect of water on the nanostructure of deep eutectic solvents (DES) is an evidence that emerges from a large number of experimental reports: several groups have studied the nanostructure of DES/water mixtures to develop our understanding of how water interacts with the hydrogen bond networks within DESs. In this work we propose to measure in NIMROD instrument the solvation structure and the nature of the intermolecular interactions of 124Triazole-TBABr/water in amount (0.33 TBA-Br: 0.67 Triazole) /1H2O). The joint use of Neutron scattering experiments and DFT/Molecular Dynamics (MD) simulations represents a key opportunity to access spatial correlations in aqueous solutions at atomistic resolutions, thus enabling a profound understanding of the connection between the chemical properties, the resulting structural features and the bulk behavior.
DOI: 10.15468/dl.k54s4p
title: Occurrence Download

description: A dataset containing 21780 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Boops boops",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 21780 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013070-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uqs8as
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhadinaea marcellae"
 ]
}

 The dataset includes 45 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013071-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17744057
title: CNT Cross-Domain Hazard Pure v1 — Baseline Hazard Fields Across Finance, Crypto, and Volatility

description: OverviewThis dataset provides the first Cross-Domain Hazard Pure (CDHR_PURE v1) release for Cognitive Nexus Theory (CNT). It collects a “pure” baseline set of hazard fields for multiple market domains using CNT’s hazard-band logic, before they are combined into a global drift index or cross-domain echo models.

CDHR_PURE v1 is meant to act as a backbone dataset: the raw hazard structure that underlies later CNT work such as the CNT Global Drift Field (D_global) and the CNT Cross-Domain Echo Window (CDEW).

Files in this release (CDHR_PURE_CDNN_release.zip)





CDHR_PURE_CDNN_SUMMARY.md





Human-readable summary of the CDHR_PURE pipeline and main findings.






CDHR_PURE_ZENODO_README.md





Detailed file layout and usage notes for this release.






CDHR_PURE_ZENODO_ABSTRACT.txt





Short abstract text for reuse.






CDHR_PURE_ZENODO_TWEET.txt





Tweet-length description of the dataset.






tables/cdhr_pure_cross_domain_aligned_raw.csv





Cross-domain aligned “raw” hazard features used in the CDHR_PURE analysis.






tables/cdhr_pure_h1_model_summary.csv





Summary of hazard-based models at horizon H=1, including performance metrics per domain/model.






tables/cdhr_pure_h1_segment_auc.csv





AUC values by segment for H=1 hazard models, useful for inspecting where hazard-based predictions work best or fail.






plots/cdhr_pure_h1_auc_by_model_finance_SPY.png





Visualization of H=1 AUC by model for the finance (SPY) hazard field.






plots/cdhr_pure_h1_auc_by_model_vol_VIX.png





Visualization of H=1 AUC by model for the volatility (VIX) hazard field.





Role in Cognitive Nexus Theory (CNT)





CDHR_PURE v1 exposes the baseline hazard planes for key market domains, before any compression into:





a global drift index D_globalD\_globalD_global, or




cross-domain echo / decoder models.






It is intended to sit alongside:





CNT Global Drift Field v1 — the scalar D_globalD\_globalD_global index built from cross-market hazard/drift features.




CNT Cross-Domain Echo Window v1 — the lead–lag map of how hazard in one system predicts hazard in another.





Together, these datasets form a small empirical backbone for CNT’s claims about shared drift structure and early-warning signals across domains.

Intended useThis dataset is suitable for:





independent analysis of hazard-band structure in SPY and VIX,




testing and reproducing H=1 hazard-based prediction results, and




serving as input to external systemic-risk or early-warning experiments that want a clean “pure hazard” baseline.



License and reuseThis dataset is intended for open reuse, replication, and criticism. Please cite this Zenodo record and relevant CNT materials when using it.
DOI: 10.5281/zenodo.17744072
title: CNT Cross-Domain Hazard Pure v1 — Baseline Hazard Fields Across Finance, Crypto, and Volatility

description: OverviewThis dataset provides the first Cross-Domain Hazard Pure (CDHR_PURE v1) release for Cognitive Nexus Theory (CNT). It collects a “pure” baseline set of hazard fields for multiple market domains using CNT’s hazard-band logic, before they are combined into a global drift index or cross-domain echo models.

CDHR_PURE v1 is meant to act as a backbone dataset: the raw hazard structure that underlies later CNT work such as the CNT Global Drift Field (D_global) and the CNT Cross-Domain Echo Window (CDEW).

Files in this release (CDHR_PURE_CDNN_release.zip)





CDHR_PURE_CDNN_SUMMARY.md





Human-readable summary of the CDHR_PURE pipeline and main findings.






CDHR_PURE_ZENODO_README.md





Detailed file layout and usage notes for this release.






CDHR_PURE_ZENODO_ABSTRACT.txt





Short abstract text for reuse.






CDHR_PURE_ZENODO_TWEET.txt





Tweet-length description of the dataset.






tables/cdhr_pure_cross_domain_aligned_raw.csv





Cross-domain aligned “raw” hazard features used in the CDHR_PURE analysis.






tables/cdhr_pure_h1_model_summary.csv





Summary of hazard-based models at horizon H=1, including performance metrics per domain/model.






tables/cdhr_pure_h1_segment_auc.csv





AUC values by segment for H=1 hazard models, useful for inspecting where hazard-based predictions work best or fail.






plots/cdhr_pure_h1_auc_by_model_finance_SPY.png





Visualization of H=1 AUC by model for the finance (SPY) hazard field.






plots/cdhr_pure_h1_auc_by_model_vol_VIX.png





Visualization of H=1 AUC by model for the volatility (VIX) hazard field.





Role in Cognitive Nexus Theory (CNT)





CDHR_PURE v1 exposes the baseline hazard planes for key market domains, before any compression into:





a global drift index D_globalD\_globalD_global, or




cross-domain echo / decoder models.






It is intended to sit alongside:





CNT Global Drift Field v1 — the scalar D_globalD\_globalD_global index built from cross-market hazard/drift features.




CNT Cross-Domain Echo Window v1 — the lead–lag map of how hazard in one system predicts hazard in another.





Together, these datasets form a small empirical backbone for CNT’s claims about shared drift structure and early-warning signals across domains.

Intended useThis dataset is suitable for:





independent analysis of hazard-band structure in SPY and VIX,




testing and reproducing H=1 hazard-based prediction results, and




serving as input to external systemic-risk or early-warning experiments that want a clean “pure hazard” baseline.



License and reuseThis dataset is intended for open reuse, replication, and criticism. Please cite this Zenodo record and relevant CNT materials when using it.
DOI: 10.15468/dl.egxxt9
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhodiola primuloides"
 ]
}

 The dataset includes 81 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013073-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w8asnq
title: Occurrence Download

description: A dataset containing 36074 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Calamus calamus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 36074 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013072-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ay4p49
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhadinaea myersi"
 ]
}

 The dataset includes 26 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013074-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.