cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18276477
title: Database

description: In 2024, the forecasted physical availability of heavy equipment at PT. BMC was 89%, using a simple average method, while the actual values ranged from 85.33% to 89.92%. The average difference between the forecast and actual values was -2.02%, with the largest gap occurring in the month with the lowest actual value, at -3.67%. This inaccuracy indicates an over-estimation bias that could impact operational planning. If the issue of misforecasting continues, the company will face challenges in predicting or planning unit replacements. Consequently, declines in availability will become unpredictable, leading to consistently low equipment availability and disruptions in operations. This study aims to train a regression-based machine learning model to identify the model with the best evaluation performance based on field parameters such as equipment condition, equipment age, equipment hours meter, maintenance frequency, equipment activity, and historical maintenance records. This approach will provide more accurate predictions aligned with actual field conditions. PT BMC will also be able to identify the parameters closely related to availability using multivariate analysis. Based on this information, recommendations for improvements will be provided to enhance the availability of heavy equipment. The study's findings indicate that the best-performing model for forecasting availability is the decision tree algorithm, with an R² train score of 1.000 and R² test score of 0.8624, RMSE train of 0.000, RMSE test of 0.0627, and MAPE train of 0.0000 and MAPE test of 10460471212418. A critical parameter significantly affecting availability is risk ranking, which shows a negative correlation with availability, with an R² value of -0.8973. Based on these findings, the recommendations for PT BMC include increasing equipment cleaning, focusing attention on units operating in high-risk areas, and implementing predictive and preventive maintenance procedures.
DOI: 10.5281/zenodo.18276478
title: Database

description: In 2024, the forecasted physical availability of heavy equipment at PT. BMC was 89%, using a simple average method, while the actual values ranged from 85.33% to 89.92%. The average difference between the forecast and actual values was -2.02%, with the largest gap occurring in the month with the lowest actual value, at -3.67%. This inaccuracy indicates an over-estimation bias that could impact operational planning. If the issue of misforecasting continues, the company will face challenges in predicting or planning unit replacements. Consequently, declines in availability will become unpredictable, leading to consistently low equipment availability and disruptions in operations. This study aims to train a regression-based machine learning model to identify the model with the best evaluation performance based on field parameters such as equipment condition, equipment age, equipment hours meter, maintenance frequency, equipment activity, and historical maintenance records. This approach will provide more accurate predictions aligned with actual field conditions. PT BMC will also be able to identify the parameters closely related to availability using multivariate analysis. Based on this information, recommendations for improvements will be provided to enhance the availability of heavy equipment. The study's findings indicate that the best-performing model for forecasting availability is the decision tree algorithm, with an R² train score of 1.000 and R² test score of 0.8624, RMSE train of 0.000, RMSE test of 0.0627, and MAPE train of 0.0000 and MAPE test of 10460471212418. A critical parameter significantly affecting availability is risk ranking, which shows a negative correlation with availability, with an R² value of -0.8973. Based on these findings, the recommendations for PT BMC include increasing equipment cleaning, focusing attention on units operating in high-risk areas, and implementing predictive and preventive maintenance procedures.
DOI: 10.15468/dl.muc83y
title: Occurrence Download

description: A dataset containing 33 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Wollastonia biflora",
 "Country is China",
 "HasCoordinate is true"
 ]
}

 The dataset includes 33 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015987-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tdgqcy
title: Occurrence Download

description: A dataset containing 108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carijoa riisei",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 108 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015988-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hvd4sd
title: Occurrence Download

description: A dataset containing 264 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carijoa riisei",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 264 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015989-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m4bj3q
title: Occurrence Download

description: A dataset containing 28930 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Centaurea diffusa, Chamaecrista mimosoides, Clarkia pulchella)"
 ]
}

 The dataset includes 28930 records from 624 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015990-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18276660
title: Euphorbiaceae Juss. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276659
title: Euphorbiaceae Juss. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276664
title: Euploca Nutt. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276665
title: Euploca Nutt. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276662
title: Supplemental Table 2: Evaluation of different risk cutoffs within the "1 elevated value" group to characterize how well each cutoff identifies patients who require pharmacotherapy
DOI: 10.5281/zenodo.18276663
title: Supplemental Table 2: Evaluation of different risk cutoffs within the "1 elevated value" group to characterize how well each cutoff identifies patients who require pharmacotherapy
DOI: 10.15468/dl.7hq2dk
title: Occurrence Download

description: A dataset containing 155 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hippopotamus amphibius",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 155 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015991-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18276668
title: Euploca krapovickasii J.I.M.Melo & Semir. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276669
title: Euploca krapovickasii J.I.M.Melo & Semir. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276682
title: Euploca ocellata (Cham.) J.I.M.Melo & Semir. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276683
title: Euploca ocellata (Cham.) J.I.M.Melo & Semir. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276585
title: SuperDARN data in netCDF format (1996-Oct)

description: 1996-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6809254
title: SuperDARN data in netCDF format (1996-Oct)

description: 1996-Oct SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.18276686
title: Euploca procumbens (Mill.) Diane & Hilger. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276687
title: Euploca procumbens (Mill.) Diane & Hilger. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.15468/dl.gp9y8e
title: Occurrence Download

description: A dataset containing 570 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Metarhizium anisopliae",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 570 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015993-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sga4b8
title: Occurrence Download

description: A dataset containing 336 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Metarhizium anisopliae",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 336 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015994-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fujrge
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mytilopsis trautwineana",
 "Country is Colombia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015995-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18276699
title: Eustachys Desv. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.5281/zenodo.18276700
title: Eustachys Desv. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:46
DOI: 10.15468/dl.g4pnde
title: Occurrence Download

description: A dataset containing 367654 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Centaurea diffusa, Chamaecrista mimosoides, Cichorium intybus)"
 ]
}

 The dataset includes 367654 records from 2278 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015982-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/usctheses-ouc11399khte
title: Physics-Guided Deep Learning for Prediction and Optimization in Subsurface Flow Systems
DOI: 10.25549/usctheses-ouc11399khtc
title: "Care in the Wake of Violence: Gender, Prisons, and the Movement Against Mass Incarceration in California"
DOI: 10.7910/dvn/w1sm7y
title: Visualizing Emptiness and Beyond: A Stylometric and Adversarial Analysis of Mahayana Buddhist Concept Illustrations as Intersemiotic Translation

description: This study investigates how core Mahayana Buddhist concepts—including but not limited to emptiness (空), enlightenment (菩提), nirvana (涅槃), prajñā (般若), middle path (中道), dharma realm (法界), Buddha-nature (如來藏), bodhisattva stages (十地), true vs. deluded mind (真/妄心), and great compassion (大悲)—are visually rendered across seven fully illustrated Buddhist volumes. Treating these illustrations as intersemiotic translations of doctrinal teachings, we construct a multimodal visual-textual corpus comprising over 600 images. Stylometric profiling (via CLIP embeddings), adversarial modeling, and entropy-based metrics are used to test whether doctrinal styles possess computationally detectable “visual fingerprints.” We also explore the role of adversarial classifiers in flagging doctrinal inauthenticity in modern adaptations. This project advances Translation Studies by introducing a novel paradigm to evaluate sacred image translation through both machine learning and doctrinally informed visual hermeneutics.
DOI: 10.15468/dl.hhyk95
title: Occurrence Download

description: A dataset containing 27384 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Capitella capitata"
 ]
}

 The dataset includes 27384 records from 239 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045082-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22002/dz51j-axe10
title: Ecoli_Cojugation

description: These are donor E coli cells (ANB35) and recipient Ecoli cells (ANB24). These are the same  .  cells described in the Science paper (Direct visualization of horizontal gene transfer). The .  cells were mixed on the grid and then plunge frozen and imaged with cryo-ET without CLEM. .  Targets were imaged with cryo-ET randomly.
description: <strong>Tilt Series Date:</strong> 2019-02-28</p>
<strong>Data Taken By:</strong> Mohammed Kaplan</p>
<strong>Species / Specimen:</strong> Escherichia coli</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-50.0°, 50.0°), step: 1°, constant angular increment, dosage: 130.0 eV/Å²,  defocus: -10.0 μm,  magnification: 26000x. </p>
<strong>Microscope:</strong> Caltech Titan Krios</p>
<strong>Acquisition Software:</strong> Serial EM</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> The cells were sent to the Jensen lab from the lab of Ariel Lindner in Paris. These are the same . cells used in their Science paper (direct visualization of horizontal gene transfer).</p>
<strong>Purification / Growth Conditions / Treatment:</strong> ANB 35 were grown in LB while ANB24 (Recipient) in M9. I followed the same protocol . described in the Science paper described above.</p>
<strong>Sample Preparation:</strong> The donor and recipient cells were mixed on the EM grid, incubated in the vitrobot chamber with . 100% humidity and then blotted and plunge frozen.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/mka2019-02-28-5/rawdata/</p>Ecoli_conjugation10.mrc,  Tilt Series (Pixel Size 0.541 nm), 2.9 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/mka2019-02-28-5/rawdata/Ecoli_conjugation10.mrc"
        > <i class="download icon"></i> Download </a></p>

        Ecoli_conjugation10_full.rec,  Reconstruction (Pixel Size 2.164 nm), 445.4 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/mka2019-02-28-5/3dimage_107025/Ecoli_conjugation10_full.rec"
        > <i class="download icon"></i> Download </a></p>

        Ecoli_conjugation10.mrc.mdoc,  50.6 kB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/mka2019-02-28-5/rawdata/Ecoli_conjugation10.mrc.mdoc"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/qvsft-34z57
title: Exp phase S. acidocaldarius

description: Collected sm2017-12-21-x dataset on Caltech Krios
description: <strong>Tilt Series Date:</strong> 2017-12-21</p>
<strong>Data Taken By:</strong> Shrawan kumar Mageswaran</p>
<strong>Species / Specimen:</strong> Sulfolobus acidocaldarius</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 2°, constant angular increment, dosage: 100.0 eV/Å²,  defocus: -10.0 μm,  magnification: 26000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> SerialEM</p>
<strong>Upload Method:</strong> reupload_downloaded</p>
<strong>Processing Software Used:</strong> IMOD for backprojection, tomo3d for SIRT</p>
<strong>Collaborators and Roles:</strong> Megan Dobro's stock of cells</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Grew cells to stationary phase overnight at 77 C in ATCC medium 1723 by shaking at ~180 rpm. Topped up H2O every 12-16 hr. Diluted cells in new medium to ~0.02 OD and grew till 0.05 OD.</p>
<strong>Sample Preparation:</strong> Kept cells on ice until freezing. Concentrated cells to ~5 OD. Added 3.5 µL of cells on glow discharged Cu finder grids and blotted for 2-3 sec from behind, manually.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/smk2017-12-21-6/rawdata/</p>TS8_4bin_orig.mrc,  Tilt Series (Pixel Size 0.541 nm), 90.9 MB  
        
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        > <i class="download icon"></i> Download </a></p>

        TS8_4bin_SIRT90rot_DB.rec,  Reconstruction (Pixel Size 0.0 nm), 1.8 GB  
        
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        TS8_4bin_WBP_DB.rec,  Reconstruction (Pixel Size 0.0 nm), 372.4 MB  
        
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