cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48577/jpl.nc9yzj
title: A multiarc approach to detecting Uranus normal modes via Doppler tracking of a 5 planetary orbiter

description: Uranus is the proposed target of NASA’s next large-scale mission, offering a unique opportunity to advance our understanding of ice giant systems. The planet hasn’t been visited by a spacecraft since Voyager 2, and fundamental questions about its interior structure, atmospheric composition, and magnetosphere remain unanswered. As part of the strategy to address these knowledge gaps, a gravity science experiment is strongly recommended for the future Uranus Orbiter and Probe (UOP) mission. The primary objective is to accurately determine the planet’s gravity field and tidal parameters, providing crucial insights into its internal structure. However, these parameters alone may not be sufficient to fully constrain Uranus’s density gradients and core structure. Complementary approaches are being considered, such as the study of normal modes. These global-scale planetary oscillations have been observed in Saturn and possibly Jupiter, are directly linked to interior properties and may be observable using a gravity science instrument. Yet, Uranus’s normal mode frequencies and amplitudes remain unknown, posing a challenge for their detection via gravitational seismology. Here, we draw comparisons with Saturn’s observed oscillations and conduct numerical simulations of the orbit determination process at Uranus. The goal is to assess whether an orbiter on a realistic trajectory can detect planetary oscillations and determine how many orbits would be required. This work is useful for designing UOP trajectories and contributes to a more comprehensive understanding of ice giants, both within our solar system and beyond.
DOI: 10.48577/jpl.on3uyw
title: Investigating the Role of Protostellar Variability with PRIMA Using Monte Carlo Simulations

description: Evidence suggests that protostellar outbursts likely play a critical role in the stellar mass assembly process, but the extent of this contribution is not well understood. Using the proposed observing program of PRIMA, a concept far-IR observatory (PRIMA GO Case #43 in Moullet et al. 2023), we examine the probe’s ability to unambiguously determine whether or not variable accretion events dominate the stellar mass assembly process (Mburst ≥ 0.5M∗). To do this, we construct multiple protostellar ensembles using Herschel 70µm flux data and evolve them using a toy Monte Carlo simulation through steady-state and high magnitude accretion events. Ensembles are observed at various epochs in the evolution process to conclude how many large amplitude outbursts are observationally recoverable during the proposed program. Based on our synthetic observations and our simulation specifications, we determine that observing a protostellar ensemble of at least 2000 protostars using PRIMA’s proposed program is sufficient for determining the importance of protostellar outbursts in the stellar mass assembly process.
DOI: 10.13140/rg.2.2.12016.32001
title: Served as a Reviewer for the International Conference on Optical Communication, Photonics, Telecommunications and Intelligent Machine Applications (OPTIMA-2025) held on 4–5 December 2025, organized by Tashkent University of Information Technologies (TUIT), contributing rigorous manuscript reviews, providing constructive and insightful feedback, and upholding the academic quality and integrity of the conference.
DOI: 10.6084/m9.figshare.30972055
title: Supplementary Material for: Influence of the molecular subtype-dependent immune microenvironment of metastatic axillary lymph nodes on breast cancer patient outcomes

description: Metastasis in the axillary lymph nodes (ALNs) occurs in 30-50% of breast cancers (BCs), where residing immune cells play a crucial role in disease progression. Specifically at diagnosis, the immune elements infiltrating the primary tumour are among the best-established prognostic factors. However, their prognostic value in the metastatic ALNs (ALNs+) is poorly understood.
We aim to retrospectively assess the immune populations of ALNs+ in luminal A (LA) and triple-negative BC (TNBC) patients using immunohistochemistry, to compare it with non-metastatic ALNs (ALNs-), and to determine their relationship with patient outcomes. 
We found differences in the immune concentrations of matched ALNs (ALNs- vs. ALNs+) from patients with positive nodal status in either LA or TNBC subtypes. In contrast, compared with LA, the levels of immune cells in ALNs- of the TNBC profile differ much more from ALNs+ than in the LA subtype, regardless of the nodal status. In addition, TNBC patients with higher levels of CD4 and CD8 lymphocytes in ALNs+ have worse cancer-specific survival (CSS) and higher levels of CD83 dendritic cells (DCs) are related to worse CSS and time to progression (TTP). Conversely, LA patients with higher levels of CD21 DC showed better TTP. 
Our results showed that ALN immune profiles and their influence on disease evolution vary by molecular BC subtype and nodal status, suggesting that accurate ALN immune profiling at diagnosis could provide new insights into the immune BC landscape. These observations require validation in larger, prospective cohorts before they can be reliably used to inform clinical decision-making.
DOI: 10.6084/m9.figshare.30972055.v1
title: Supplementary Material for: Influence of the molecular subtype-dependent immune microenvironment of metastatic axillary lymph nodes on breast cancer patient outcomes

description: Metastasis in the axillary lymph nodes (ALNs) occurs in 30-50% of breast cancers (BCs), where residing immune cells play a crucial role in disease progression. Specifically at diagnosis, the immune elements infiltrating the primary tumour are among the best-established prognostic factors. However, their prognostic value in the metastatic ALNs (ALNs+) is poorly understood.
We aim to retrospectively assess the immune populations of ALNs+ in luminal A (LA) and triple-negative BC (TNBC) patients using immunohistochemistry, to compare it with non-metastatic ALNs (ALNs-), and to determine their relationship with patient outcomes. 
We found differences in the immune concentrations of matched ALNs (ALNs- vs. ALNs+) from patients with positive nodal status in either LA or TNBC subtypes. In contrast, compared with LA, the levels of immune cells in ALNs- of the TNBC profile differ much more from ALNs+ than in the LA subtype, regardless of the nodal status. In addition, TNBC patients with higher levels of CD4 and CD8 lymphocytes in ALNs+ have worse cancer-specific survival (CSS) and higher levels of CD83 dendritic cells (DCs) are related to worse CSS and time to progression (TTP). Conversely, LA patients with higher levels of CD21 DC showed better TTP. 
Our results showed that ALN immune profiles and their influence on disease evolution vary by molecular BC subtype and nodal status, suggesting that accurate ALN immune profiling at diagnosis could provide new insights into the immune BC landscape. These observations require validation in larger, prospective cohorts before they can be reliably used to inform clinical decision-making.
DOI: 10.6084/m9.figshare.30971977
title: Bathymetry Prediction with SWOT Gravity Anomaly using Machine Learning Methods

description: The ocean surface has broad bumps and dips caused by variations in gravity, which reflect the mass of seafloor features such as ridges, seamounts, and trenches. Because of this link, mapping gravity allows us to infer seafloor depth, though physics limits the resolution to about 3–5 km in the deep ocean. Satellite altimeters have steadily improved these maps for decades, and the new SWOT mission now provides the most precise gravity data to date. In this study, five research groups used machine learning to combine SWOT gravity data with ship soundings, producing consistent global seafloor maps that are 23–46\% more accurate than older methods. The largest improvements are in mapping shallow seamounts and deep trenches, advancing our ability to study ocean circulation, tectonics, hazards, and marine ecosystems, while contributing to the international Seabed 2030 effort.
DOI: 10.6084/m9.figshare.30971977.v1
title: Bathymetry Prediction with SWOT Gravity Anomaly using Machine Learning Methods

description: The ocean surface has broad bumps and dips caused by variations in gravity, which reflect the mass of seafloor features such as ridges, seamounts, and trenches. Because of this link, mapping gravity allows us to infer seafloor depth, though physics limits the resolution to about 3–5 km in the deep ocean. Satellite altimeters have steadily improved these maps for decades, and the new SWOT mission now provides the most precise gravity data to date. In this study, five research groups used machine learning to combine SWOT gravity data with ship soundings, producing consistent global seafloor maps that are 23–46\% more accurate than older methods. The largest improvements are in mapping shallow seamounts and deep trenches, advancing our ability to study ocean circulation, tectonics, hazards, and marine ecosystems, while contributing to the international Seabed 2030 effort.
DOI: 10.5281/zenodo.18086742
title: Reconstructing the Holy Loch Ecosystem: Metadata Anchors for Environmental Gradients and Molecular Taxonomic Standards, using Chironomoidea collected in 2024 as a model.

description: Foundational dataset used for reconstructing the Holy Loch Ecosystem

This foundational dataset archives environmental, spatial, and molecular baselines for the Holy Loch Food Web Project, specifically focusing on the two Malaise trap sites for the UK BIOSCAN project. By utilizing Chironomoidea (Diptera) as a model taxon, these data and associated papers establish permanent Metadata Anchors to help overcome the "taxonomic impediment" and provide a high-resolution audit of the Holy Loch Nature Reserve (HLNR) and its surroundings2.

Key Anchors:

Spatial & Visual: Includes three aerial and ground-level photographs of the complex saltmarsh-based habitat complex, featuring a 40m test transect used for physicochemical measurements.

Physicochemical: Records a pH gradient ranging from 4.4 (acidic woodland/shingle ridge) to 6.8 (upper saltmarsh) and electrical conductivity from 0.39 to 4 ms m-1.

Taxonomic Framework: Establishes a four-tier categorization system—Confirmed Identity, Rare Biosphere, Emerging Identity, and Barcode Silence—for interpreting BIOSCAN Biodiversity Index Numbers (BINs).

Ecological Data: Six tables include abundance data collected for Chironomoidea BINs at the two trap sites over twelve monthly trapping dates in 2024.

Molecular Discoveries: Documents site-specific BINs, such as BOLD:AGX5543 (unique to HLNR with 97.1% similarity to Limnophyes natalensis), and at least ten species new to the web discoverable Scottish known list.

Scientific Significance:

This archive serves as the definitive reference for all subsequent biodiversity checklists and longitudinal ecological modeling at the Holy Loch Nature Reserve, which currently lists approximately 3100 species/BINs/MOTUs.

By anchoring records of cryptic or rare taxa—such as salt-resistant Simuliidae larvae (BOLD:AAB8624 and BOLD:ACX9864) found in tidal drains—to permanent, open-access BOLD BINs, this dataset ensures that 2024 discoveries remain accessible for future comparative research.

The dataset also contains our methods for DNA barcoding and a reference list for two associated papers.
DOI: 10.5281/zenodo.18086741
title: Reconstructing the Holy Loch Ecosystem: Metadata Anchors for Environmental Gradients and Molecular Taxonomic Standards, using Chironomoidea collected in 2024 as a model.

description: Foundational dataset used for reconstructing the Holy Loch Ecosystem

This foundational dataset archives environmental, spatial, and molecular baselines for the Holy Loch Food Web Project, specifically focusing on the two Malaise trap sites for the UK BIOSCAN project. By utilizing Chironomoidea (Diptera) as a model taxon, these data and associated papers establish permanent Metadata Anchors to help overcome the "taxonomic impediment" and provide a high-resolution audit of the Holy Loch Nature Reserve (HLNR) and its surroundings2.

Key Anchors:

Spatial & Visual: Includes three aerial and ground-level photographs of the complex saltmarsh-based habitat complex, featuring a 40m test transect used for physicochemical measurements.

Physicochemical: Records a pH gradient ranging from 4.4 (acidic woodland/shingle ridge) to 6.8 (upper saltmarsh) and electrical conductivity from 0.39 to 4 ms m-1.

Taxonomic Framework: Establishes a four-tier categorization system—Confirmed Identity, Rare Biosphere, Emerging Identity, and Barcode Silence—for interpreting BIOSCAN Biodiversity Index Numbers (BINs).

Ecological Data: Six tables include abundance data collected for Chironomoidea BINs at the two trap sites over twelve monthly trapping dates in 2024.

Molecular Discoveries: Documents site-specific BINs, such as BOLD:AGX5543 (unique to HLNR with 97.1% similarity to Limnophyes natalensis), and at least ten species new to the web discoverable Scottish known list.

Scientific Significance:

This archive serves as the definitive reference for all subsequent biodiversity checklists and longitudinal ecological modeling at the Holy Loch Nature Reserve, which currently lists approximately 3100 species/BINs/MOTUs.

By anchoring records of cryptic or rare taxa—such as salt-resistant Simuliidae larvae (BOLD:AAB8624 and BOLD:ACX9864) found in tidal drains—to permanent, open-access BOLD BINs, this dataset ensures that 2024 discoveries remain accessible for future comparative research.

The dataset also contains our methods for DNA barcoding and a reference list for two associated papers.
DOI: 10.5281/zenodo.17572114
title: Passive volcanic sulfur degassing emissions from Jongebloed et al. (2023, 2026)

description: Passive volcanic sulfur degassing emissions from volcanoes around the world. Latitude, longitude, emission elevation, emission rate (kg S sec-1). Sulfur speciation is not specified (assumed to be a mixture of SO2 and H2S). For detailed description of these emissions, please see Jongebloed et al. (2023) GRL and Jongebloed et al. (2026) GRL.
DOI: 10.5281/zenodo.17572115
title: Passive volcanic sulfur degassing emissions from Jongebloed et al. (2023, 2026)

description: Passive volcanic sulfur degassing emissions from volcanoes around the world. Latitude, longitude, emission elevation, emission rate (kg S sec-1). Sulfur speciation is not specified (assumed to be a mixture of SO2 and H2S). For detailed description of these emissions, please see Jongebloed et al. (2023) GRL and Jongebloed et al. (2026) GRL.
DOI: 10.5281/zenodo.17428582
title: Pole-to-pole Phyllotaxis MRI Dataset: Phantom and Cardiac Data

description: This dataset accompanies the paper "Pole-to-Pole 3D Radial Trajectory Designs Improve Image Quality and Quantitative Parametric Mapping in the Brain and Heart", accepted for publication in Magnetic Resonance in Medicine (MRM) in 2025. It includes data from various MRI experiments using different radial trajectory designs to evaluate their impact on image quality and parametric mapping.

The dataset is organized into three parts:





Phantom bSSFP Data: Data acquired from a spherical phantom using multiple trajectory designs, bandwidths, and orientations.





File: data_spherical_phantom.zip






Phase-Cycled bSSFP NIST Phantom Data: Data from a NIST phantom scanned with three different radial trajectories—original, pole-to-pole, and continuous Phyllotaxis.





File: data_NIST_phantom.zip






In Vivo GRE Data (Heart): Data acquired from the human heart using two different radial trajectories—original and pole-to-pole Phyllotaxis.





File: data_heart_phantom.zip





Each dataset provides valuable insights into the effects of radial trajectory designs on imaging performance and quantitative mapping in both phantom and in vivo conditions.
DOI: 10.5281/zenodo.17428583
title: Pole-to-pole Phyllotaxis MRI Dataset: Phantom and Cardiac Data

description: This dataset accompanies the paper "Pole-to-Pole 3D Radial Trajectory Designs Improve Image Quality and Quantitative Parametric Mapping in the Brain and Heart", accepted for publication in Magnetic Resonance in Medicine (MRM) in 2025. It includes data from various MRI experiments using different radial trajectory designs to evaluate their impact on image quality and parametric mapping.

The dataset is organized into three parts:





Phantom bSSFP Data: Data acquired from a spherical phantom using multiple trajectory designs, bandwidths, and orientations.





File: data_spherical_phantom.zip






Phase-Cycled bSSFP NIST Phantom Data: Data from a NIST phantom scanned with three different radial trajectories—original, pole-to-pole, and continuous Phyllotaxis.





File: data_NIST_phantom.zip






In Vivo GRE Data (Heart): Data acquired from the human heart using two different radial trajectories—original and pole-to-pole Phyllotaxis.





File: data_heart_phantom.zip





Each dataset provides valuable insights into the effects of radial trajectory designs on imaging performance and quantitative mapping in both phantom and in vivo conditions.
DOI: 10.6084/m9.figshare.30924677
title: <b>Use of Web-GIS for Management in Industrial Parks: A Proactive and Effective Response to Hazardous Materials Emergencies</b>

description: Industrial parks located near urban areas lack real-time GIS systems for hazardous materials emergencies, severely limiting the effectiveness of first-response agencies. This study developed an operational Web-GIS platform for the Coquimbo Industrial District in Chile, integrating a geospatial database of 436 georeferenced companies with automated geoprocessing workflows aligned with the 2024 Emergency Response Guide. Through field campaigns (2023-2024), information on hazardous Hazmat incident responsesubstances and infrastructure was collected, implementing automated tools in ArcGIS Online and Survey123 to generate safety perimeters, evacuation routes, and real-time risk assessments accessible from mobile devices. The platform successfully operationalized regulatory guidelines into executable geoprocesses, enabling instant queries of business information, visualization of danger zones based on stored materials, and access to chemical safety data sheets during emergencies. This research bridges the critical gap between desktop planning and field operations, demonstrating that geomatics-based emergency management systems transform reactive protocols into proactive responses that reduce decision-making times, enhance situational awareness, and strengthen resilience in industrial areas adjacent to vulnerable populations, establishing a replicable framework for similar global contexts.
DOI: 10.6084/m9.figshare.30924677.v1
title: <b>Use of Web-GIS for Management in Industrial Parks: A Proactive and Effective Response to Hazardous Materials Emergencies</b>

description: Industrial parks located near urban areas lack real-time GIS systems for hazardous materials emergencies, severely limiting the effectiveness of first-response agencies. This study developed an operational Web-GIS platform for the Coquimbo Industrial District in Chile, integrating a geospatial database of 436 georeferenced companies with automated geoprocessing workflows aligned with the 2024 Emergency Response Guide. Through field campaigns (2023-2024), information on hazardous Hazmat incident responsesubstances and infrastructure was collected, implementing automated tools in ArcGIS Online and Survey123 to generate safety perimeters, evacuation routes, and real-time risk assessments accessible from mobile devices. The platform successfully operationalized regulatory guidelines into executable geoprocesses, enabling instant queries of business information, visualization of danger zones based on stored materials, and access to chemical safety data sheets during emergencies. This research bridges the critical gap between desktop planning and field operations, demonstrating that geomatics-based emergency management systems transform reactive protocols into proactive responses that reduce decision-making times, enhance situational awareness, and strengthen resilience in industrial areas adjacent to vulnerable populations, establishing a replicable framework for similar global contexts.
DOI: 10.25573/serc.26871091.v2
title: 2016-2023 Water Quality Data, Richardson Bay

description: Yearly water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO and San Francisco Bay National Estuarine Research Reserve (SF Bay NERRs) Richardson Bay water quality monitoring station. Location: 37.876692, 122.487564. The local time at this site is Pacific Standard Time (UTC-7). Note that timestamps in this dataset are reported as Coordinated Universal Time (UTC).<br>The authors thank the National Estuarine Research Reserve System (NERRS) System-Wide Monitoring Program (SWMP) data group for their collaboration and support. The quality assurance and quality control steps taken on this data set were carried out by the NERRS SWMP. Character codes are applied to denote data that should be removed or to provide comments <br>
DOI: 10.25573/serc.26871091.v1
title: 2016-2023 Water Quality Data, Richardson Bay

description: Yearly water quality data collected on a YSI EXO2 multiparameter sonde at the MarineGEO and San Francisco Bay National Estuarine Research Reserve (SF Bay NERRs) Richardson Bay water quality monitoring station. Location: 37.876692, 122.487564. The local time at this site is Pacific Standard Time (UTC-7). Note that timestamps in this dataset are reported as Coordinated Universal Time (UTC).<br>The authors thank the National Estuarine Research Reserve System (NERRS) System-Wide Monitoring Program (SWMP) data group for their collaboration and support. The quality assurance and quality control steps taken on this data set were carried out by the NERRS SWMP. Character codes are applied to denote data that should be removed or to provide comments <br>
DOI: 10.48577/jpl.21c5kf
title: Dust back-reaction on gas around planets modifies the cold thermal torque

description: Context. A nascent planet in a gas disk experiences radial migration due to the different torques which act on it (e.g., Lindblad and corotation torques). It has recently been shown that the torques produced by the gas and dust density variations around a non-accreting low-mass planet, the so-called cold thermal and dust streaming torques, can surpass each of the other torque components. Aims. We investigate how the total torque acting on the planet is affected by the presence of dust grains and their aerodynamic back-reaction on gas, while taking into account the cold thermal torque produced by thermal diffusion in the gas component. Methods. We perform high-resolution local and global three-dimensional two-fluid simulations within the pressureless-fluid dust approximation using the Fargo3D code. We explore the influence of different dust species parameterized by the Stokes number, focusing on non-accreting protoplanets with masses from one-third the mass of Mars to one Earth mass. Results. The dust feedback has substantial impact on the asymmetry of the cold thermal lobes (which produce the cold thermal torque). However, the total torque is dominated by the dust torque when St &gt; 10−2 . The dust torque becomes more negative over time due to the formation of dust lobes that resemble the cold thermal lobes that form in the gas component. Therefore, the dust streaming torque prevails over the cold thermal torque. On the other hand, when St ≤ 10−2 , the dust streaming torque is negligible and thus, the total torque on the planet comes from the gaseous component of the disk. Conclusions. Our results suggest that a planet embedded in a gas-dust disk may experience stagnant migration or inward runaway migration in regions of the protoplanetary disk where the dust is not fully coupled to the gas. However, this behaviour could change in regions with strong dust–gas coupling or in the inner transition region of the disk, where the cold thermal torque may become relevant.