Results for “community clustering” — Page 13

NASA NTRS2019

Fusion of Surface Ceilometer Data and Satellite Cloud Retrievals in 2D Mesh Interpolating Model with Clustering

For accurate cloud ceiling information, a data fusion approach is proposed that utilizes satellite data to extend surface station information to much wider areas. Cloud base height (CBH) retrieved from satellite observations provides for much larger spatial coverage and higher resolution. The direct comparison of GOES-16 CBH with surface station ceiling yields a local bias that has to be corrected for in the initial GOES-16 cloud base information. This sparsely sampled bias correction presents an irregular 2D mesh of control points, which is then interpolated by constructing a continuous smooth field using polyharmonic splines. The influence of remote stations is restricted by grouping the control points into clusters depending on an effective distance. This cluster-based approach allows for constructing separate spline surfaces corresponding to physically different clouds. The obtained continuous bias correction function is then applied to the entire GOES-16 pixel level CBH except for areas far away from surface stations in data sparse regions such as offshore. The described method is currently being tested using daytime-only observations over the central and eastern United States. Overall, this approach has potential to provide more accurate, high spatial resolution cloud ceiling information for the aviation community.

Khlopenkov, Konstantin↗

NASA NTRS2015

ESIP Earth Sciences Data Analytics (ESDA) Cluster - Work in Progress

The purpose of this poster is to promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations to better understand the cross usage of heterogeneous datasets and to provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities. Objectives Provide a forum for Academic discussions that provides ESIP members a better understanding of the various aspects of Earth Science Data Analytics Bring in guest speakers to describe external efforts, and further teach us about the broader use of Data Analytics. Perform activities that:- Compile use cases generated from specific community needs to cross analyze heterogeneous data- Compile sources of analytics tools, in particular, to satisfy the needs of the above data users- Examine gaps between needs and sources- Examine gaps between needs and community expertise- Document specific data analytics expertise needed to perform Earth science data analytics Seek graduate data analytics Data Science student internship opportunities.

science data analysis↗

NASA NTRS1983

Phased array-fed antenna configuration study

The scope of this contract entails a configuration study for a phased array fed transmit antenna operating in the frequency band of 17.7 to 20.2 GHz. This initial contract provides a basis for understanding the design limitations and advantages of advanced phased array and cluster feeds (both utilizing intergral MMIC modules) illuminating folded reflector optics (both near field and focused types). Design parametric analyses are performed utilizing as constraints the objective secondary performance requirements of the Advanced Communications Technology Satellite (Table 1.0). The output of the study provides design information which serves as a data base for future active phased array fed antenna studies such as detailed designs required to support the development of a ground tested breadboard. In general, this study is significant because it provides the antenna community with an understanding of the basic principles which govern near field phased scanned feed effects on secondary reflector system performance. Although several articles have been written on analysis procedures and results for these systems, the authors of this report have observed phenomenon of near field antenna systems not previously documented. Because the physical justification for the exhibited performance is provided herein, the findings of this study add a new dimension to the available knowledge of the subject matter.

Crosswell, W. F.↗

DOE OSTI2025

New approaches to secondary metabolite discovery from anaerobic gut microbes

The animal gut microbiome is a complex system of diverse, predominantly anaerobic microbiota with secondary metabolite potential. These metabolites likely play roles in shaping microbial community membership and influencing animal host health. As such, novel secondary metabolites from gut microbes hold significant biotechnological and therapeutic interest. Despite their potential, gut microbes are largely untapped for secondary metabolites, with gut fungi and obligate anaerobes being particularly under-explored. To advance understanding of these metabolites, culture-based and (meta)genome-based approaches are essential. Culture-based approaches enable isolation, cultivation, and direct study of gut microbes, and (meta)genome-based approaches utilize in silico tools to mine biosynthetic gene clusters (BGCs) from microbes that have not yet been successfully cultured. In this mini-review, we highlight recent innovations in this area, including anaerobic biofoundries like ExFAB, the NSF BioFoundry for Extreme & Exceptional Fungi, Archaea, and Bacteria. These facilities enable high-throughput workflows to study oxygen-sensitive microbes and biosynthetic machinery. Such recent advances promise to improve our understanding of the gut microbiome and its secondary metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Atomic-scale investigations of Ti 3 C 2 T x MXene surfaces

The family of two-dimensional (2D) carbides and/or nitrides, also known as MXenes, has generated great excitement within the scientific community and has been proposed for a wide variety of applications since its discovery. Despite this attention, there have been only limited studies of the atomically resolved local electronic and physical structure of MXene surfaces strongly affecting the physicochemical properties of these materials. Here, in this study, we report local structural, spectroscopic, and chemical investigations of the surfaces of Ti 3 C 2 T x flakes using scanning tunneling microscopy and spectroscopy, closely coupled to theoretical studies. Terminal groups are visualized and characterized, along with surface TiO 2 clusters formed upon exposure to air. Fundamental insight into the local electronic and chemical properties associated with different terminal groups on MXenes and their oxidation products is presented.

36 MATERIALS SCIENCE↗

DOE OSTI2023

White Paper On Nuclear Structure Reactions and Astrophysics

In preparation for the 2023 NSAC Long Range Plan (LRP), the DNP Town Meeting on Nuclear Structure, Reactions, and Astrophysics was held at Argonne National Laboratory (ANL) on Nov 14-16, 2022. The town meeting brought together 578 members of the low-energy nuclear science community, including 216 in-person attendees and 362 remote participants coming from US national laboratories, a wide range of US universities and other research institutions and universities abroad. Participants met in five topic-oriented and seven cross-cutting and intersecting working groups to discuss progress since the 2015 LRP and identify compelling science opportunities and the resources needed to realize them. These considerations were used during the Town Meeting to determine a set of resolutions outlining the highest priorities for our subfield. The full text of the resolutions endorsed by unanimous consent by the low-energy nuclear science community at the Town Meeting is presented at the end of this executive summary. The reports from all working groups that met during the Town Meeting are included as Secs. 1 to 11 of this Whitepaper. The intellectual challenges for nuclear structure, reactions and astrophysics can be captured in the following questions: What is the nature of the nuclear force that binds protons and neutrons into stable nuclei and rare isotopes, and how do the rich phenomena of nuclear structure and reactions emerge? How do single-nucleon, cluster, and collective degrees of freedom coexist and evolve with increasing proton-neutron imbalance and excitation energies? What are the limits of nuclear existence, and what features arise near and beyond these limits? What are the astrophysical origins of the elements and how did the associated chemical evolution proceed? How do stars evolve, and what nuclear signatures do they leave behind? What is the nature of neutron stars and dense matter? How can the knowledge and technological progress provided by nuclear science best be used to benefit society?

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1999

Development of a 12-Thrust Chamber Kerosene /Oxygen Primary Rocket Sub-System for an Early (1964) Air-Augmented Rocket Ground-Test System

Airbreathing/Rocket combined-cycle, and specifically rocket-based combined- cycle (RBCC), propulsion systems, typically employ an internal engine flow-path installed primary rocket subsystem. To achieve acceptably short mixing lengths in effecting the "air augmentation" process, a large rocket-exhaust/air interfacial mixing surface is needed. This leads, in some engine design concepts, to a "cluster" of small rocket units, suitably arrayed in the flowpath. To support an early (1964) subscale ground-test of a specific RBCC concept, such a 12-rocket cluster was developed by NASA's Marshall Space Flight Center (MSFC). The small primary rockets used in the cluster assembly were modified versions of an existing small kerosene/oxygen water-cooled rocket engine unit routinely tested at MSFC. Following individual thrust-chamber tests and overall subsystem qualification testing, the cluster assembly was installed at the U. S. Air Force's Arnold Engineering Development Center (AEDC) for RBCC systems testing. (The results of the special air-augmented rocket testing are not covered here.) While this project was eventually successfully completed, a number of hardware integration problems were met, leading to catastrophic thrust chamber failures. The principal "lessons learned" in conducting this early primary rocket subsystem experimental effort are documented here as a basic knowledge-base contribution for the benefit of today's RBCC research and development community.

Pryor, D.↗

DOE OSTI2021

Using Pilot Jobs and CernVM File System for Simplified Use of Containers and Software Distribution

High Energy Physics (HEP) experiments entail an abundance of computing resources, i.e. sites, to run simulations and analyses by processing data. This requirement is fulfilled by local batch farms, grid sites, private/commercial clouds, and supercomputing centers via High Throughput Computing (HTC). The growing needs of such experiments and resources being prone to trends of heterogeneity make it difficult for physicists to handle these resources directly. Additionally, HEP collaborations heavily rely on data and software releases, typically in the order of tens of gigabytes, while conducting simulations and analyses. Hence, aspects of scalability, reliability, and maintenance become crucial with regards to the distribution of the necessary data and software stack. The GlideinWMS [4] framework helps with the resource management problem by using pilot jobs, aka Glideins, to provision reliable elastic virtual clusters. Glideins are submitted to unreliable heterogeneous resources which are validated and customized by the Glideins to make the worker nodes available for end-user job execution. On the other hand, the CernVM File System (CernVM-FS or CVMFS) [1] helps with data distribution. It is a write-once, read-everywhere filesystem used to deploy scientific software to thousands of nodes on a worldwide distributed computing infrastructure. CVMFS is based on the Hyper Text Transfer Protocol and has been widely used within the particle physics community for (1) distributing experiment software and data such as calibrations, and (2) facilitating containerization by efficiently hosting container images along with providing containerization software, especially Singularity [3] GlideinWMS relies on CVMFS installed locally on the computing resources to satisfy the experiments' software needs. This requires system administrators' effort to install and maintain CVMFS at the sites and limits the use of sites, especially HPC resources, that do not have CVMFS installed. This poster presents a solution, taking advantage of Glideins to provide CVMFS at most sites without the need for a local installation. Doing so expands the pool of resources available for HEP experiments and reduces the effort of system administrators for current resources. Additionally, the proposed solution allows GlideinWMS to also start Singularity [3], a containerization software that can run unprivileged, on sites where neither CVMFS nor Singularity are available, including HPC sites. The benefits provided by this solution are: (1) lower overhead for site administrators in that they have less software to install, (2) an expanded pool of resources that run user jobs with easy access to software and data provided by CVMFS, thus making life easier for the scientists, and (3) improved flexibility to use HPC resources by enabling GlideinWMS pilot jobs to support HPC sites.

Urs, Namratha↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

NASA NTRSDate not supplied

An Approach to Identifying Aspects of Positive Pilot Behavior within the Aviation Safety Reporting System

The National Airspace System (NAS) is constantly evolving as air traffic continues to ramp up to pre-pandemic numbers and projected to grow to unprecedented levels in the coming years. As well as increasing demand to the current system, emerging operations such as Unmanned Autonomous Systems are also expected to add to complexity in the airspace. To address these issues, the industry and government agencies supporting the NAS will need to rely upon additional automation and new technologies to address future operational requirements, while continuing to be a world-leading safe transportation system. As these new technologies are implemented, the system continues to rely on human pilots and controllers in the loop to monitor the system and intervene in situations the automation cannot handle. The goal of proactively addressing safety is of foremost concern to ensure passenger confidence. The industry has implemented various Safety Monitoring Systems to identify safety risks and proactively address them before they result in a serious incident or accident. One such program is the Aviation Safety Reporting System (ASRS). ASRS is a long-established system where pilots and controllers voluntarily and anonymously report safety incidents they experienced and observed during line operations by providing rich text narratives describing the events, the environment, and conditions leading to the safety event of concern. These narratives provide insight and context around events of interest and can be used to identify emerging problems. They can trigger investigations within Flight Operational Quality Assurance or Flight Data Monitoring programs. However, this process typically focuses on the adverse events and the unsafe aspects of the operations surrounding the reported or detected events. This perspective of investigating factors that went wrong around an adverse event is commonly referred to as Safety I. Alternatively, characterizing successful actions that operators perform every day under varying conditions that keep the system within safe operating bounds is a concept referred to as Safety II. The benefit of the Safety II view is that the scope is much larger than that of Safety I since a vast majority of the operations result in successful flights. Many of the successful techniques used to manage operational threats are not documented in standard operating procedures or taught during training. They are typically acquired over time by working with experienced pilots during line operations or in many cases after experiencing a problem for the first time and reacting to it in situ, drawing from years of experience to manage the threat. In an attempt to quantify these positive actions, we are proposing an approach to extracting key behaviors within ASRS reports that can support the Safety II concept. Our analysis assumes that ASRS reports contain some descriptions of corrective actions that operators performed to prevent a situation from leading to an accident. Leveraging recent advances in Natural Language Process modeling, we have developed an approach to extract positive sentiment from reports, embed these positive statements in a vector space where they can be numerically analyzed, and clustering these statements into similar contextual categories. From these contextualized categories we can attempt to summarized and distilled aspects of the positive behavior. The goal is to identify categories of behavior that describe consistent operator techniques that supports the Safety II concept. With this information, airlines may enable learning from these positive actions, or address procedures that need to be changed to avoid having pilots implement a workaround. These insights can provide a lens into what is “going right” in the operations that may otherwise not be known widely within the community. It is envisioned that this approach can be extended to other narrative programs such as Line Operation Safety Audit or Learning Improvement Team reports where similar observed behavior can be analyzed to extract positive actions and inform the overall operations.

NLP↗

DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

NASA NTRS2004

An Overview of Electric Propulsion Activities at NASA

This paper provides an overview of NASA s activities in the area of electric propulsion with an emphasis on project directions, recent progress, and a view of future project directions. The goals of the electric propulsion programs are to develop key technologies to enable new and ambitious science missions and to transfer these technologies to industry. Activities include the development of gridded ion thruster technology, Hall thruster technology, pulsed plasma thruster technology, and very high power electric propulsion technology, as well as systems technology that supports practical implementation of these advanced concepts. The performance of clusters of ion and Hall thrusters is being revisited. Mission analyses, based on science requirements and preliminary mission specifications, guide the technology projects and introduce mission planners to new capabilities. Significant in-house activity, with strong industrial/academia participation via contracts and grants, is maintained to address these development efforts. NASA has initiated a program covering nuclear powered spacecraft that includes both reactor and radioisotope power sources. This has provided an impetus to investigate higher power and higher specific impulse thruster systems. NASA continues to work closely with both supplier and user communities to maximize the understanding and acceptance of new technology in a timely and cost-effective manner. NASA s electric propulsion efforts are closely coordinated with Department of Defense and other national programs to assure the most effective use of available resources. Several NASA Centers are actively involved in these electric propulsion activities, including, the Glenn Research Center, Jet Propulsion Laboratory, Johnson Space Center, and Marshall Space Flight Center.

Dunning, John W., Jr.↗

NASA NTRS2008

Multiscale Computer Simulation of Failure in Aerogels

Aerogels have been of interest to the aerospace community primarily for their thermal properties, notably their low thermal conductivities. While such gels are typically fragile, recent advances in the application of conformal polymer layers to these gels has made them potentially useful as lightweight structural materials as well. We have previously performed computer simulations of aerogel thermal conductivity and tensile and compressive failure, with results that are in qualitative, and sometimes quantitative, agreement with experiment. However, recent experiments in our laboratory suggest that gels having similar densities may exhibit substantially different properties. In this work, we extend our original diffusion limited cluster aggregation (DLCA) model for gel structure to incorporate additional variation in DLCA simulation parameters, with the aim of producing DLCA clusters of similar densities that nevertheless have different fractal dimension and secondary particle coordination. We perform particle statics simulations of gel strain on these clusters, and consider the effects of differing DLCA simulation conditions, and the resultant differences in fractal dimension and coordination, on gel strain properties.

Good, Brian S.↗

DOE OSTI2023

Spatiotemporal Studies of Soluble Inorganic Nanostructures with X‐rays and Neutrons

Abstract This Review addresses the use of X‐ray and neutron scattering as well as X‐ray absorption to describe how inorganic nanostructured materials assemble, evolve, and function in solution. We first provide an overview of techniques and instrumentation (both large user facilities and benchtop). We review recent studies of soluble inorganic nanostructure assembly, covering the disciplines of materials synthesis, processes in nature, nuclear materials, and the widely applicable fundamental processes of hydrophobic interactions and ion pairing. Reviewed studies cover size regimes and length scales ranging from sub‐Ångström (coordination chemistry and ion pairing) to several nanometers (molecular clusters, i.e. polyoxometalates, polyoxocations, and metal‐organic polyhedra), to the mesoscale (supramolecular assembly processes). Reviewed studies predominantly exploit 1) SAXS/WAXS/SANS (small‐ and wide‐angle X‐ray or neutron scattering), 2) PDF (pair‐distribution function analysis of X‐ray total scattering), and 3) XANES and EXAFS (X‐ray absorption near‐edge structure and extended X‐ray absorption fine structure, respectively). While the scattering techniques provide structural information, X‐ray absorption yields the oxidation state in addition to the local coordination. Our goal for this Review is to provide information and inspiration for the inorganic/materials science communities that may benefit from elucidating the role of solution speciation in natural and synthetic processes.

Yin, Jia‐Fu↗

DOE OSTI2023

A proteomic meta-analysis refinement of plasma extracellular vesicles

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks

In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Vegetation heterogeneity reflects soil thermal state and surface soil displacement in a thawing permafrost landscape

Thawing permafrost has the potential to dramatically alter the physical and ecological structure of northern landscapes. Warming of the Arctic and subsequent degradation of permafrost have created a need to assess the stability and movement of soils on hillslopes and the potential impacts on ecosystem structure. In this work, we explore the relationships among vegetation heterogeneity, soil temperature, and soil surface displacements observed from 2019 to 2022 in a watershed in the discontinuous permafrost region on the Seward Peninsula of Alaska. Vegetation heterogeneity was measured as the standard deviation (SD) of the normalized difference vegetation index (NDVI) from 3 m PlanetScope satellite imagery around each soil temperature and active layer thickness observation. Locations of observations were clustered into three soil thermal groups, warm, intermediate, and cold, based on soil temperature and active layer thickness. Average annual horizontal surface displacements were significantly lower for soils within the warm thermal group (median = 0.033 m yr −1 ) compared to soils within the cold thermal group (median = 0.090 m yr −1 ; p < 0.001). Conversely, vegetation heterogeneity was significantly higher in the warm (median = 0.014 SD NDVI; p = 0.002) and intermediate (median = 0.015 SD NDVI; p = 0.002) groups compared with the cold thermal group (median = 0.012 SD NDVI), suggesting a warming-induced shift in vegetation community complexity. Because of the observed associations of ground surface displacement rates and vegetation heterogeneity with soil thermal state, we hypothesize that warming soil conditions induce changes in the rates and patterns of hillslope erosion due to an increase in surface movement as near-surface permafrost thaws, followed by a decrease as the permafrost table deepens and excess ice content diminishes. The transition to warm soils promotes surface ecosystem transformation, shifting the dominant vegetation at the site, given the warming climatic conditions of the region. We integrated our observations of soil temperature, vegetation heterogeneity, and soil surface displacements into a conceptual model that describes the co-evolution of hillslopes and vegetation in warming permafrost environments, which is currently unrepresented in earth system models.

54 ENVIRONMENTAL SCIENCES↗