cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15473/2481243
title: In-Situ Blade Strain Measurements of a Crossflow Turbine Operating in a Tidal Flow

description: This data was collected between October 25 and December 12 of 2022 at the University of New Hampshire (UNH) and Atlantic Marine Energy Center (AMEC) turbine deployment platform (TDP). The goal was to collect blade strain data from a crossflow turbine operating in a tidal flow. A table in ('Deployment Schedule.PNG') outlines the various dates when each instrument was operational, and more details can be found via literature listed in 'Related Publications'.txt. This dataset includes zipped folders for each instrument containing data in .csv files for the relevant duration specific to each instrument, along with separate README file for each measurement. Some instrument files are quite large and can pose a challenge for a visual spreadsheet editor to open. A processing software like MATLAB or Python is recommended. All data contained in this submission is unfiltered/unprocessed data unless otherwise noted in the README file. Blade strain was measured using 8 foil-based strain gauges along the span of a single turbine blade. Water currents were measured using Acoustic Doppler Current Profilers (ADCP's) and Acoustic Doppler Velocimeters (ADV's) both upstream and downstream of the turbine for inflow, wake and turbulence measurements. Electrical power output was measured using the Voltsys rectifier. Shaft speed was calculated based on the Voltsys measurements of the permanent magnet three phase generator AC generation frequency, coupled directly to the cross flow turbine under test (i.e., no gear box). Platform motions were captured using a Yost IMU (inertial measurement unit). Turbine thrust loading was measured using a reaction arm about the turbine deployment platform spanning beam, where two bi-directional load cells were connected to the system via a pinned connection. The TDP is a floating structure moored on the Portsmouth facing side of Memorial Bridge pier #2, which spans the Piscataqua River between Portsmouth, NH and Kittery, ME. The Piscataqua River connects the Great Bay Estuary to the Gulf of Maine and the river currents are dominated by tidal flow with water velocities exceeding 2.5 m/s during spring ebb tides at this site which were previously characterized by Chancey 2019. The turbine under test was a modified New Energy Corporation (Calgary, CA) model EVG-025 4-blade H-Darrius type vertical axis cross flow turbine that rotates in the clockwise direction with a rotor diameter of 3.2m and blade length of 1.7m. The hydro-foil profile was a NACA 0021 with a 10 inch chord length and a blade preset pitch angle of +4deg with a positive angle corresponding with the toe in direction. The standard EVG-025 has a rotor diameter of 3.4m and its rated power output is 25kW at 3 m/s. The rotor diameter was reduced to accommodate the size of the existing TDP moon-pool. A single blade of this turbine was further modified to accommodate 8 full-bridge strain gauges (Bharath et al 2023, Bichanich et al 2024). For power performance and other relevant details on the turbine and its characteristics, see O'Byrne 2022.
DOI: 10.15473/2481244
title: TEAMER: Triton Systems Oscillating Water Column Modeling Data and Report

description: This dataset provides the output of six Wave Energy Converter Simulator (WEC-Sim) simulations and accompanying documentation for the modeling of Triton Systems' oscillating water column (OWC) system at tank scale (validated using available data for tuning the model, Tests 1-2) and deployment scale (for which no validation data is available, Tests 4-6). Included are the output data in a MATLAB file structure, a comprehensive report on the modeling and design of the Triton OWC system, and a link to the WEC-Sim GitHub page. This work was supported by funding from TEAMER RFTS 5 (Request for Technical Support).
DOI: 10.11578/rais_rad_eco_12_12_2024/2481255
title: Ecological Benchmark for Radionuclides

description: The Ecological Benchmark Tool for radionuclides dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual radionuclides, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against radiological thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.
DOI: 10.15468/dl.48sqy2
title: Occurrence Download

description: A dataset containing 121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Menyanthes trifoliata L."
 ]
}

 The dataset includes 121 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037398-241126133413365/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.28039505
title: <b>Methionine-driven methylation modification overcomes</b><b> </b><b>plasmid-mediated high-level tigecycline resistance</b>

description: This work highlights the therapeutic potential of Methionine in overcoming plasmid-mediated high-level tigecycline resistance, and provides a new paradigm to enhance antibiotic efficacy by harnessing cellular metabolic networks as well as epigenetic modifications. The uploaded database is the metabolomics data.
DOI: 10.15468/dl.yqn8nb
title: Occurrence Download

description: A dataset containing 2036 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreos de fauna en el departamento de Cundinamarca del 2016 al 2019 por la CAR"
 ]
}

 The dataset includes 2036 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037400-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.g5fok65f
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.15468/dl.9b3c36
title: Occurrence Download

description: A dataset containing 195845 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Castor fiber Linnaeus, 1758",
 "Year 2009-2024"
 ]
}

 The dataset includes 195845 records from 439 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037399-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z5p2zt
title: Occurrence Download

description: A dataset containing 5946 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tricholoma matsutake (S.Ito & S.Imai) Singer"
 ]
}

 The dataset includes 5946 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037401-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/qq1p-8103
title: part of multiscale defects PCBA dataset

description: To further evaluate the practical performance of HPDM, we apply it to detect defects in actual industrial circuit boards. Various defects, such as board, lifting, and ffipping defects, occur on the circuit board because of external forces imposed during the placement and soldering processes .A real industrial circuit board defect detection dataset is collected and presented. This dataset includes five different categories of components with various real multiscale defects. A real industrial circuit board defect detection dataset is collected and presented. This dataset includes ffve different categories of components with various real multiscale defects, comprises a total of 1,000 images, and is publicly available for use.
DOI: 10.6084/m9.figshare.28039424
title: mixed_reality_stereo_vision_model

description: The multimodal datasets in a mixed reality environment were validated using state-of-the-art deep learning models. Please refer to our GitHub repository for details.
DOI: 10.6084/m9.figshare.28039424.v1
title: mixed_reality_stereo_vision_model

description: The multimodal datasets in a mixed reality environment were validated using state-of-the-art deep learning models. Please refer to our GitHub repository for details.
DOI: 10.15468/dl.d38mdh
title: Occurrence Download

description: A dataset containing 198 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Encyclia parviflora (Regel) Withner"
 ]
}

 The dataset includes 198 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037402-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14504179
title: "Technological Trinity: Faith, Machines, and the Future of Humanity" Exploring the Intersection of Faith, Technology, and Ethics in Christianity, Judaism, and Islam

description: This article explores the intersection of faith, artificial intelligence (AI), and ethical responsibility, drawing on Vincent Froom’s Technological Trinity: Faith, Machines, and the Future of Humanity. Froom introduces the concept of the “Technological Trinity,” which parallels theological constructs by framing humans (body), machines (mind), and ethics (spirit) as an interconnected system that mirrors humanity’s search for purpose, justice, and divine alignment. The work highlights the need for ethics to serve as the guiding principle in the development and application of AI, ensuring it promotes human flourishing, justice, and the common good.

 

This article situates Froom’s arguments within the broader theological frameworks of the Abrahamic traditions—Christianity, Judaism, and Islam. By analyzing scriptural teachings (e.g., imago Dei in Genesis 1:27, tikkun olam in the Torah, and khalifa in Qur’an 35:39), the study underscores how these faiths converge on shared values: the sanctity of human creativity, the rejection of technological hubris, and the moral imperative to ensure AI aligns with divine purpose.

 

Building on Froom’s assertion that “machines can amplify human potential but not replace the divine spark of intentional creativity,” this article incorporates contributions from contemporary AI ethicists such as Nick Bostrom (superintelligence risks), Stuart Russell (human-compatible AI), and Mark Coeckelbergh (AI transparency and justice). The analysis also examines AI’s role in ethical dilemmas, particularly concerning issues of explainability, probabilistic outcomes, and interpretability, which challenge both human agency and moral accountability.

 

Through theological and ethical reflection, the article emphasizes that the future of AI is not deterministic but contingent upon human choices. Froom’s work aligns with eschatological concerns in the Abrahamic traditions—such as Christian teachings on stewardship and redemption, Jewish principles of justice and accountability, and Islamic values of maslaha (the common good). These frameworks collectively call for the development of AI technologies that respect human dignity, promote equity, and reflect divine values of justice, mercy, and stewardship.

 

The conclusion reiterates Vincent Froom’s central premise: “Faith, ethics, and accountability are not constraints on progress but safeguards for a future where technology reflects—not rivals—the values that connect us to one another, creation, and God.” By bridging ancient wisdom with contemporary technological challenges, this study argues for a hopeful and ethically grounded vision for AI, rooted in theological traditions and moral responsibility.
DOI: 10.5281/zenodo.14504180
title: "Technological Trinity: Faith, Machines, and the Future of Humanity" Exploring the Intersection of Faith, Technology, and Ethics in Christianity, Judaism, and Islam

description: This article explores the intersection of faith, artificial intelligence (AI), and ethical responsibility, drawing on Vincent Froom’s Technological Trinity: Faith, Machines, and the Future of Humanity. Froom introduces the concept of the “Technological Trinity,” which parallels theological constructs by framing humans (body), machines (mind), and ethics (spirit) as an interconnected system that mirrors humanity’s search for purpose, justice, and divine alignment. The work highlights the need for ethics to serve as the guiding principle in the development and application of AI, ensuring it promotes human flourishing, justice, and the common good.

 

This article situates Froom’s arguments within the broader theological frameworks of the Abrahamic traditions—Christianity, Judaism, and Islam. By analyzing scriptural teachings (e.g., imago Dei in Genesis 1:27, tikkun olam in the Torah, and khalifa in Qur’an 35:39), the study underscores how these faiths converge on shared values: the sanctity of human creativity, the rejection of technological hubris, and the moral imperative to ensure AI aligns with divine purpose.

 

Building on Froom’s assertion that “machines can amplify human potential but not replace the divine spark of intentional creativity,” this article incorporates contributions from contemporary AI ethicists such as Nick Bostrom (superintelligence risks), Stuart Russell (human-compatible AI), and Mark Coeckelbergh (AI transparency and justice). The analysis also examines AI’s role in ethical dilemmas, particularly concerning issues of explainability, probabilistic outcomes, and interpretability, which challenge both human agency and moral accountability.

 

Through theological and ethical reflection, the article emphasizes that the future of AI is not deterministic but contingent upon human choices. Froom’s work aligns with eschatological concerns in the Abrahamic traditions—such as Christian teachings on stewardship and redemption, Jewish principles of justice and accountability, and Islamic values of maslaha (the common good). These frameworks collectively call for the development of AI technologies that respect human dignity, promote equity, and reflect divine values of justice, mercy, and stewardship.

 

The conclusion reiterates Vincent Froom’s central premise: “Faith, ethics, and accountability are not constraints on progress but safeguards for a future where technology reflects—not rivals—the values that connect us to one another, creation, and God.” By bridging ancient wisdom with contemporary technological challenges, this study argues for a hopeful and ethically grounded vision for AI, rooted in theological traditions and moral responsibility.
DOI: 10.15468/dl.6hs2mp
title: Occurrence Download

description: A dataset containing 5946 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tricholoma matsutake (S.Ito & S.Imai) Singer"
 ]
}

 The dataset includes 5946 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037403-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18112/openneuro.ds005106.v1.1.0
title: 200 Objects Infants EEG
DOI: 10.15468/dl.v6kpes
title: Occurrence Download

description: A dataset containing 2036 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Monitoreos de fauna en el departamento de Cundinamarca del 2016 al 2019 por la CAR"
 ]
}

 The dataset includes 2036 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037404-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14504181
title: Interaksi Simbolik Tradisi Marosok dalam Transaksi Jual Beli Ternak di Minangkabau

description: Interaksi Simbolik Tradisi Marosok dalam Transaksi Jual BeliTernak di Minangkabau
DOI: 10.5281/zenodo.14504182
title: Interaksi Simbolik Tradisi Marosok dalam Transaksi Jual Beli Ternak di Minangkabau

description: Interaksi Simbolik Tradisi Marosok dalam Transaksi Jual BeliTernak di Minangkabau
DOI: 10.15468/dl.9ta3g8
title: Occurrence Download

description: A dataset containing 4662 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Maryland Department of Natural Resources"
 ]
}

 The dataset includes 4662 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037405-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bjykrh
title: Occurrence Download

description: A dataset containing 569 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Taphrolesbia griseiventris (Taczanowski, 1883)"
 ]
}

 The dataset includes 569 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037406-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c34cd2
title: Occurrence Download

description: A dataset containing 5946 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Tricholoma matsutake (S.Ito & S.Imai) Singer"
 ]
}

 The dataset includes 5946 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037407-241126133413365/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.28009532
title: <b>LOCAL SCALE CLIMATE VARIABILITY: Case of Mandraka slope, eastern central of Madagascar</b>

description: This dataset supports the research article entitled <i>"LOCAL SCALE CLIMATE VARIABILITY: CASE OF MANDRAKA SLOPE, EASTERN CENTRAL OF MADAGASCAR"</i>. It incorporates:<b>Observed data</b>: Monthly rainfall, maximum, and minimum temperatures from the Directorate General of Meteorology of Madagascar (2010–2020).<b>Estimated data</b>: Climate variables interpolated using Inverse Distance Weighting (IDW) based on gridded data from the University of Delaware (Version 5.01).<br>
DOI: 10.15468/dl.cpb2wp
title: Occurrence Download

description: A dataset containing 6821 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tricholoma matsutake (S.Ito & S.Imai) Singer"
 ]
}

 The dataset includes 6821 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037408-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ht6yua
title: Occurrence Download

description: A dataset containing 103272637 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is iNaturalist Research-grade Observations"
 ]
}

 The dataset includes 103272637 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037396-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rsxzya
title: Occurrence Download

description: A dataset containing 24284 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Weed plants of the European part of Russia"
 ]
}

 The dataset includes 24284 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037409-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b7jbxf
title: Occurrence Download

description: A dataset containing 24284 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Weed plants of the European part of Russia"
 ]
}

 The dataset includes 24284 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037410-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/c02w-y816
title: Australian Natural Products dataset

description: A continuation of the "Phytochemistry of Australian Plants" database compiled by David Collins and Don McGilvery. Contains chemical structures, references, species names, with persistent identifiers to the literature and Atlas of Living Australia (ALA) for geographical distributions.
The current curation effort here adds DOIs/ISBNs/ISSNs for ~80% of references, persistent IDs for all species or genus to the ALA or other datasets, and validated structures (smiles) for ~70% of structures.
No new entries have been added since the last update to the original database in 2022. Change log is in the README file.

Data provided here was obtained by the listed authors on linked publications, and these authors may have no association with CSIRO. 
CSIRO acknowledges that the publications linked here may contain Indigenous Cultural and Intellectual Property (ICIP), including traditional knowledge. CSIRO recognizes that First Nations peoples have the right to control, own and maintain their ICIP in accordance with Article 31 of the United Nations Declaration on the Rights of Indigenous Peoples. Users of this dataset may need to obtain permission from First Nations peoples for use of the information in linked publications. Users intending to collect and use biological specimens containing the compounds described in the dataset may also require permission of First Nations peoples, and may require permits and access permission from landholders. 
Recognizing that any ICIP in the linked publications is already publicly available but that the publications are not readily accessible by First Nations peoples, CSIRO is committed to finding ways to make the ICIP in these publications more findable and accessible to the First Nations communities from which the knowledge was originally obtained.
Users should be aware that because of the historical context of some of the linked publications, they may contain words, descriptions, images or terms which may be culturally sensitive and/or offensive and that reflect authors’ views, or those of the period in which the content was created but may not be considered appropriate today.
If First Nations people identify content within this dataset that they consider breaches cultural protocols they are encouraged to contact CSIRO on csiroenquiries@csiro.au or +61 3 9545 2176 to request its removal from the dataset. Please note that while CSIRO is able to administer the data housed within this dataset, this control does not extend to the associated publications. Requests to remove publications should be directed to the associated publishing company.