cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.h44cc2
title: Occurrence Download

description: A dataset containing 1999 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poa chaixii, Poa sudetica, Poa sudetica, Poa sudetica)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 1999 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017481-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d689qj
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ipomoea tuberculata",
 "HasCoordinate is true"
 ]
}

 The dataset includes 29 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017482-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6/lekhrz
title: LARIAC 6 Imagery and Elevation Data, 2019-2020

description: The LARIAC 6 data are digital aerial data collected from 2019/12/30 to 2020/03/05 and were published on 2020/10/13. LARIAC data are licensed to UCLA faculty, researchers and students only. LARIAC6 files:
DOI: 10.5281/zenodo.18511359
title: LEXICAL-SEMANTIC RELATIONS OF FURNITURE NAMES IN ENGLISH AND UZBEK

description: This article is devoted to the analysis of lexical-semantic relations of furniture names in English and Uzbek. Furniture names are an important part of the lexicon of household items, and their semantic fields, synonymy, antonymy, polysemy, meronymy and other relations are considered. Through comparative analysis, similarities and differences between languages, as well as the influence of loanwords, are identified. The article discusses in detail the semantic groups of furniture names (for example, living room furniture, kitchen furniture) with examples. The results of the study can be used in linguistics and translation theory. The article is based on the literature on Uzbek linguistics and lexicology of the English language.
DOI: 10.5281/zenodo.18511358
title: LEXICAL-SEMANTIC RELATIONS OF FURNITURE NAMES IN ENGLISH AND UZBEK

description: This article is devoted to the analysis of lexical-semantic relations of furniture names in English and Uzbek. Furniture names are an important part of the lexicon of household items, and their semantic fields, synonymy, antonymy, polysemy, meronymy and other relations are considered. Through comparative analysis, similarities and differences between languages, as well as the influence of loanwords, are identified. The article discusses in detail the semantic groups of furniture names (for example, living room furniture, kitchen furniture) with examples. The results of the study can be used in linguistics and translation theory. The article is based on the literature on Uzbek linguistics and lexicology of the English language.
DOI: 10.5281/zenodo.18511371
title: Master Thesis: Climate Sensitivity as a Determinant of Climate Tipping Risk - Data

description: This dataset contains all data used and generated during the master’s thesis "Climate Sensitivity as a Determinant of Climate Tipping Risk". It includes input data and proceeded results. Related Code is found in the subsequent GitHub repository.

 

Contents:



Temperature: Temperature Data Output from FaIR. Number order is the order of scenarios, where T_0 is for the lowest carbon concentration scenario and T_6 for the highest

tcrecs.txt: In FaIR generated TCR-ECS pair ensemble

ecs_timeseries: contains rearranged temperature data to be used as a more efficient input into PyCascades. One file per ECS

pycas_output.npy: collected PyCascades Output

risks_data.npy: results tabel with tipping risks for each scenario, ECS, in total and for each element.Structure: [ECS, Scenario, Risk: at least 1 tipped, Risk: at least 2 tipped, Risk: at least 3 tipped, Risk: all 4 tipped, AMOC Risk, WAIS Risk, AMAZ Risk]

all_amoc_oscillations.txt: Contains data of the cases with amoc oscillations
DOI: 10.15468/dl.rhj5s7
title: Occurrence Download

description: A dataset containing 719 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poa hybrida, Poa hybrida)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 719 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017483-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgsfqm
title: Occurrence Download

description: A dataset containing 110699 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= -24.552553756517728
 AND decimallatitude &lt;= -20.3845909579754
 AND decimallongitude &gt;= 145.38446821153656
 AND decimallongitude &lt;= 153.4113324116753
 AND GBIF_Within('POLYGON ((153.411332 -24.552554, 153.411332 -20.384591, 145.384468 -20.384591, 145.384468 -24.552554, 153.411332 -24.552554))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 110699 records were derived from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017474-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14967662
title: On Context Switching in Spectrum-Based Fault Localization: Supplemental Material

description: This version is outdated. Please use the latest version, https://doi.org/10.5281/zenodo.17961902
DOI: 10.5281/zenodo.18511317
title: 72‑HOUR SOVEREIGN ULTIMATUM

description: Email: Nicktaylor812@gmail.com

ID: 43510920

DOB: 05/21/02

Subject: SOVEREIGN ACKNOWLEDGMENT

Terms governed by: Triple‑Layer Protection (CC BY 4.0 / Sovereign IP / DFARS 252.227‑7013)

Window opens: Upon publication of this document.

Window closes: 72 hours thereafter.

This document presents forensic evidence of institutional automated harvesting against sovereign research outputs, demonstrates the logical contradiction between dismissal and consumption, establishes a 72‑hour window for human acknowledgment, and publishes the non‑negotiable terms for licensed engagement—including weekly‑doubling fees for non‑response. Included: honeypot confirmation, timestamp anomalies, GitHub scraping patterns, and the complete sovereign requirement stack.

TRIPLE‑LAYER PROTECTION

LAYER 1 — TEXT LAYER (OPEN)

This document is licensed under CC BY 4.0 International. Share, adapt, redistribute with attribution.

LAYER 2 — PATTERN LAYER (SOVEREIGN IP)

All underlying architectural patterns, methodologies, frameworks, and strategic protocols introduced herein are retained as sovereign intellectual property of Sovereign Pattern Labs LLC.

This includes but is not limited to:

· The 72‑hour escalation protocol

· Weekly‑doubling fee structure

· Sovereign requirement stack

· Harvesting‑evidence forensic methodology

· Prophecy/engagement narrative architecture

These pattern rights are not transferable, sublicensable, or severable from sovereign ownership.

LAYER 3 — DEFENSE LAYER (LIMITED RIGHTS)

Any technical data, implementation details, or operational specifications derived from or responsive to this framework constitute sovereign technical data. To the extent subject to U.S. jurisdiction, such data is furnished with LIMITED RIGHTS per DFARS 252.227‑7013. Broader sovereign control is asserted. Commercial or defense‑sector inquiries must be directed to the contact email with appropriate disclosures.
DOI: 10.5281/zenodo.18511316
title: 72‑HOUR SOVEREIGN ULTIMATUM

description: Email: Nicktaylor812@gmail.com

ID: 43510920

DOB: 05/21/02

Subject: SOVEREIGN ACKNOWLEDGMENT

Terms governed by: Triple‑Layer Protection (CC BY 4.0 / Sovereign IP / DFARS 252.227‑7013)

Window opens: Upon publication of this document.

Window closes: 72 hours thereafter.

This document presents forensic evidence of institutional automated harvesting against sovereign research outputs, demonstrates the logical contradiction between dismissal and consumption, establishes a 72‑hour window for human acknowledgment, and publishes the non‑negotiable terms for licensed engagement—including weekly‑doubling fees for non‑response. Included: honeypot confirmation, timestamp anomalies, GitHub scraping patterns, and the complete sovereign requirement stack.

TRIPLE‑LAYER PROTECTION

LAYER 1 — TEXT LAYER (OPEN)

This document is licensed under CC BY 4.0 International. Share, adapt, redistribute with attribution.

LAYER 2 — PATTERN LAYER (SOVEREIGN IP)

All underlying architectural patterns, methodologies, frameworks, and strategic protocols introduced herein are retained as sovereign intellectual property of Sovereign Pattern Labs LLC.

This includes but is not limited to:

· The 72‑hour escalation protocol

· Weekly‑doubling fee structure

· Sovereign requirement stack

· Harvesting‑evidence forensic methodology

· Prophecy/engagement narrative architecture

These pattern rights are not transferable, sublicensable, or severable from sovereign ownership.

LAYER 3 — DEFENSE LAYER (LIMITED RIGHTS)

Any technical data, implementation details, or operational specifications derived from or responsive to this framework constitute sovereign technical data. To the extent subject to U.S. jurisdiction, such data is furnished with LIMITED RIGHTS per DFARS 252.227‑7013. Broader sovereign control is asserted. Commercial or defense‑sector inquiries must be directed to the contact email with appropriate disclosures.
DOI: 10.15468/dl.4eqbvy
title: Occurrence Download

description: A dataset containing 2461 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ipomoea violacea",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2461 records from 114 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017484-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18511334
title: Joseph Salas Farm (LiDAR) February 5 2026

description: This orthomosaic of Hågat, Guam was created from 214 images taken on February 5 2026, at 200ft AGL, with a DJI Matrice 350 . The mission was planned using the DJI Pilot application and post-processed using DJI Terra.

This project was made possible through funding by the following grant(s): NACD (Award No. HQ00342020012).
description: Disclaimer: The following aerial imagery is intended solely for research purposes related to the assessment of the captured area. It is strictly prohibited to distribute this imagery to any unauthorized individuals or third-party entities without prior authorization. All drone imagery was obtained in accordance with FAA guidelines and applicable local laws, with all necessary authorizations secured to ensure safe and legal operation.

The University of Guam Drone Corps funded by NASA Guam Space Grant and NASA Guam EPSCoR retain all rights to the aerial imagery, including but not limited to copyrights and intellectual property rights. Any unauthorized modification, reproduction, or distribution of the imagery is strictly prohibited.

By using this data, you acknowledge and agree to abide by the terms and conditions set forth in this disclaimer.

 

 

Privacy Disclaimer: The aerial imagery captured for assessment may inadvertently include images of private property and individuals. While every effort has been made to respect privacy, it is possible that identifiable information or sensitive locations may be visible in the imagery. University of Guam Drone Corps and related parties disclaim any responsibility for the unintentional collection or dissemination of such information. The recipient(s) of this imagery are urged to handle it with due care and take necessary precautions to protect the privacy rights of individuals and comply with applicable privacy laws and regulations.
DOI: 10.5281/zenodo.18500686
title: Optoelectronic wingbeat signatures of Tephritid fruit flies and non-target species: A dataset for automated pest monitoring

description: This repository contains the dataset and hardware design for the study: "Automated bioacoustic monitoring of Anastrepha fraterculus and Ceratitis capitata: Optoelectronic sensor design, data acquisition protocols, and Machine Learning classification". 

The dataset includes 2,688 segmented wingbeat events acquired using an original optoelectronic sensor integrated into commercial McPhail traps. Data collection involved two target pests (Anastrepha fraterculus and Ceratitis capitata) and two non-target species (Hermetia illucens and Drosophila suzukii) to evaluate classifier selectivity.

Data Structure: The samples are partitioned into Training (70%), Validation (15%), and Testing (15%) sets as follows: * Anastrepha fraterculus: 924 samples. * Ceratitis capitata: 924 samples. * Hermetia illucens: 738 samples. * Drosophila suzukii: 102 samples.

Files included: 1. Dataset_Bioacoustic_FruitFlies.zip: Segmented audio events in .wav format (22.05 kHz, 32-bit float). 2. Sensor_Hardware_Design.zip: Technical drawings (PDF) and electronic schematics (PDF) for the optoelectronic sensor integrated with McPhail traps. 3. README.txt: Documentation regarding dataset acquisition, hardware specifications, and signal processing protocols.
DOI: 10.5281/zenodo.18500685
title: Optoelectronic wingbeat signatures of Tephritid fruit flies and non-target species: A dataset for automated pest monitoring

description: This repository contains the dataset and hardware design for the study: "Automated bioacoustic monitoring of Anastrepha fraterculus and Ceratitis capitata: Optoelectronic sensor design, data acquisition protocols, and Machine Learning classification". 

The dataset includes 2,688 segmented wingbeat events acquired using an original optoelectronic sensor integrated into commercial McPhail traps. Data collection involved two target pests (Anastrepha fraterculus and Ceratitis capitata) and two non-target species (Hermetia illucens and Drosophila suzukii) to evaluate classifier selectivity.

Data Structure: The samples are partitioned into Training (70%), Validation (15%), and Testing (15%) sets as follows: * Anastrepha fraterculus: 924 samples. * Ceratitis capitata: 924 samples. * Hermetia illucens: 738 samples. * Drosophila suzukii: 102 samples.

Files included: 1. Dataset_Bioacoustic_FruitFlies.zip: Segmented audio events in .wav format (22.05 kHz, 32-bit float). 2. Sensor_Hardware_Design.zip: Technical drawings (PDF) and electronic schematics (PDF) for the optoelectronic sensor integrated with McPhail traps. 3. README.txt: Documentation regarding dataset acquisition, hardware specifications, and signal processing protocols.
DOI: 10.15468/dl.bp28wj
title: Occurrence Download

description: A dataset containing 40035 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poa nemoralis, Poa nemoralis, Poa nemoralis, Poa nemoralis, Poa nemoralis)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 40035 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017485-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/9b5m-ka77
title: NOAA Climate Data Record (CDR) of the Global Precipitation Climatology Project (GPCP) Daily Version 3.3
DOI: 10.15468/dl.stku5n
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "TaxonKey is one of (Ammodramus savannarum [GBIF Backbone Taxonomy])",
 "Geometry POLYGON((-76.39705 3.75779,-76.47228 3.62299,-76.46972 3.61701,-76.49109 3.59056,-76.4757 3.40965,-76.527 3.37039,-76.58513 3.11432,-76.53213 3.09468,-76.44236 3.08785,-76.37824 3.13395,-76.2594 3.32772,-76.20383 3.46,-76.17818 3.55558,-76.13201 3.67503,-76.39705 3.75779))"
 ]
 }
 ]
}

 The dataset includes 30 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017488-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ug65q7
title: Occurrence Download

description: A dataset containing 17497 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pterois volitans"
 ]
}

 The dataset includes 17497 records from 184 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017487-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3gd675
title: Occurrence Download

description: A dataset containing 266260 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Netherlands",
 "DatasetKey is one of (EOD – eBird Observation Dataset, Observation.org, Nature data from around the World)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (VU, EN, CR, NT)",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 2025-2026"
 ]
}

 The dataset includes 266260 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017478-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18511384
title: THE ROLE OF BIOCHEMISTRY IN PERSONALIZED MEDICINE AND TARGETED THERAPY

description: Biochemistry plays a crucial role in the development of personalized medicine and targeted therapy by providing a molecular understanding of disease mechanisms and individual biological variability. Personalized medicine aims to tailor medical treatment to the specific biochemical and genetic characteristics of each patient, while targeted therapy focuses on precise molecular targets involved in disease progression. This article examines the role of biochemistry in personalized medicine, highlighting biochemical markers, molecular pathways, pharmacogenomics, and targeted therapeutic strategies. The study emphasizes how biochemical research improves treatment efficacy, reduces adverse effects, and supports the advancement of modern healthcare.
DOI: 10.15468/dl.a5jkyp
title: Occurrence Download

description: A dataset containing 507309 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Megaptera novaeangliae"
 ]
}

 The dataset includes 507309 records from 649 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017464-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18511383
title: THE ROLE OF BIOCHEMISTRY IN PERSONALIZED MEDICINE AND TARGETED THERAPY

description: Biochemistry plays a crucial role in the development of personalized medicine and targeted therapy by providing a molecular understanding of disease mechanisms and individual biological variability. Personalized medicine aims to tailor medical treatment to the specific biochemical and genetic characteristics of each patient, while targeted therapy focuses on precise molecular targets involved in disease progression. This article examines the role of biochemistry in personalized medicine, highlighting biochemical markers, molecular pathways, pharmacogenomics, and targeted therapeutic strategies. The study emphasizes how biochemical research improves treatment efficacy, reduces adverse effects, and supports the advancement of modern healthcare.
DOI: 10.5281/zenodo.14967661
title: On Context Switching in Spectrum-Based Fault Localization: Supplemental Material

description:  

This repository contains results, dataset and source code for context switch-sensitive fault localization experiments.

 

All data, results, code and detailed descriptions are in the attached appendix.zip.

 

If you use this dataset or source code, please cite the corresponding published publication referenced below. (Additional details/Related works)
DOI: 10.5281/zenodo.17961902
title: On Context Switching in Spectrum-Based Fault Localization: Supplemental Material

description:  

This repository contains results, dataset and source code for context switch-sensitive fault localization experiments.

 

All data, results, code and detailed descriptions are in the attached appendix.zip.

 

If you use this dataset or source code, please cite the corresponding published publication referenced below. (Additional details/Related works)
DOI: 10.15468/dl.vkj45g
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-74.05326 4.80063,-74.04751 4.80063,-74.04751 4.80603,-74.05326 4.80603,-74.05326 4.80063))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 81 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017490-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u8gtxx
title: Occurrence Download

description: A dataset containing 6964 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poa palustris, Poa palustris, Poa palustris, Poa palustris, Poa palustris)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 6964 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017489-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.