Results for “ROI” — Page 2

NASA NTRS2004

Event-Driven Random-Access-Windowing CCD Imaging System

A charge-coupled-device (CCD) based high-speed imaging system, called a realtime, event-driven (RARE) camera, is undergoing development. This camera is capable of readout from multiple subwindows [also known as regions of interest (ROIs)] within the CCD field of view. Both the sizes and the locations of the ROIs can be controlled in real time and can be changed at the camera frame rate. The predecessor of this camera was described in High-Frame-Rate CCD Camera Having Subwindow Capability (NPO- 30564) NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 26. The architecture of the prior camera requires tight coupling between camera control logic and an external host computer that provides commands for camera operation and processes pixels from the camera. This tight coupling limits the attainable frame rate and functionality of the camera. The design of the present camera loosens this coupling to increase the achievable frame rate and functionality. From a host computer perspective, the readout operation in the prior camera was defined on a per-line basis; in this camera, it is defined on a per-ROI basis. In addition, the camera includes internal timing circuitry. This combination of features enables real-time, event-driven operation for adaptive control of the camera. Hence, this camera is well suited for applications requiring autonomous control of multiple ROIs to track multiple targets moving throughout the CCD field of view. Additionally, by eliminating the need for control intervention by the host computer during the pixel readout, the present design reduces ROI-readout times to attain higher frame rates. This camera (see figure) includes an imager card consisting of a commercial CCD imager and two signal-processor chips. The imager card converts transistor/ transistor-logic (TTL)-level signals from a field programmable gate array (FPGA) controller card. These signals are transmitted to the imager card via a low-voltage differential signaling (LVDS) cable assembly. The FPGA controller card is connected to the host computer via a standard peripheral component interface (PCI).

Monacos, Steve↗

NASA NTRS2016

Mars Surface Systems Common Capabilities and Challenges for Human Missions

This paper describes the current status of common systems and operations as they are applied to actual locations on Mars that are representative of Exploration Zones (EZ) - NASA's term for candidate locations where humans could land, live and work on the Martian surface. Given NASA's current concepts for human missions to Mars, an EZ is a collection of Regions of Interest (ROIs) located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. An EZ also contains a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. The Evolvable Mars Campaign (EMC), a description of NASA's current approach to these human Mars missions, assumes that a single EZ will be identified within which NASA will establish a substantial and durable surface infrastructure that will be used by multiple human crews. The process of identifying and eventually selecting this single EZ will likely take many years to finalized. Because of this extended EZ selection process it becomes important to evaluate the current suite of surface systems and operations being evaluated for the EMC as they are likely to perform at a variety of proposed EZ locations and for the types of operations - both scientific and development - that are proposed for these candidate EZs. It is also important to evaluate proposed EZs for their suitability to be explored or developed given the range of capabilities and constraints for the types of surface systems and operations being considered within the EMC. Four locations identified in the Mars Exploration Program Analysis Group (MEPAG)'s Human Exploration of Mars Science Analysis Group (HEM-SAG) report are used in this paper as representative of candidate EZs that will emerge from the selection process that NASA has initiated. A field station site plan is developed for each of these four HEM-SAG sites. Because of the difficulty in getting equipment and supplies to the surface of Mars, specific assessments have been conducted to identify those systems and processes that can perform in multiple, sometimes completely unrelated, situations. Examples of common systems that are assessed at all of these sites include: (a) habitation and associated logistics storage systems, (b) a centralized power plant capable of supplying power to a geographically distributed (but within the central habitation zone) set of systems, (c) mobility systems that can be used to off-load and move payloads to specific locations at the central field station location that could also be used to traverse long distances to reach some of the more remote ROIs and (d) robotic systems that can support various activities (such as system set up and maintenance) at the field station that could also be used to explore scientific ROIs and used to support site-specific ISRU (In Situ Resource Utilization) production activities.

Toups, Larry↗

NASA NTRS2015

Noctis Landing: A Proposed Landing Site/Exploration Zone for Human Missions to the Surface of Mars

The proposed Noctis Landing Site/Exploration Zone (LS/EZ) is shown in Figure 1. Our preliminary study suggests that the proposed site meets all key Science and Resources (incl. Civil Engineering) requirements. The site is of significant interest, as the EZ not only offers a large number and wide range of regions of interest (ROIs) for short-term exploration, it is also located strategically at the crossroads between Tharsis and Valles Marineris, which are key for long-term exploration. The proposed site contains Regions of Interest (ROIs) that meet the following Science requirements: -‐ Access to (1) deposits with a high preservation potential for evidence of past habitability and fossil biosignatures and (2) sites that are promising for present habitability. The site presents a wide variety of ROIs qith likely aqueous features and deposits, including sinous channels and valleys, slope gullies, lobate debris aprons, impact craters with lobate ejecta flows, and "bathtub ring" deposits. Neutron spectrometry also suggests hydrogen is present within the topmost 0.3 m or so of 4 to 10 wt% WEH (Water Equivalent Hydrogen). -‐ Noachian and/or Hesperian rocks in a stratigraphic context that have a high likelihood of containing trapped atmospheric gases. Collapsed canyon rim material with preserved stratigraphy is abundantly present and accessible. -‐ Exposures of at least two crustal units that have regional or global extents, that are suitable for radiometric dating, and that have relative ages that sample a significant range of martian geological time. Canyons floors in Ius Chasma, Tithonium Chasma, and plateau tops on Tharsis and in Sinai Planum offer access to distinct crustal units of regional extent. -‐ Access to outcrops with linked morphological and/or geochemical signatures indicative of aqueous or groundwater/ mineral interactions. Iron and sulfur-bearing deposits on canyon floors in Noctis Labyrinthus, and in Ius Chasma (IC) and Tithonium Chasma (TC) offer many such outcrop options. -‐ Identifiable stratigraphic contacts and cross-cutting relationships from which relative ages can be determined. In place and collapsed canyon walls in NL, TC, and IC offer such opportunities. -‐ Other types of ROIs include access points to surrounding plateau top areas for longer term regional exploration. A key attribute of the proposed Noctic Landing site is its strategic location to allow the shortest possible surface excusions to Tharsis and Valles Marineris (VM). VM is the feature and region on Mars that exposes the longest record of Mars' geology and evolution through time. Tharsis is the region of Mars that has experienced the longest and most extensive volcanic history, and might still be volcanically active. Some of the youngest lava flows on Mars have been identified on the western flanks of the Tharsis Bulge, i.e., within driving range of future longrange (500 - 1000 km) pressurized rover traverses. The proposed site also contains ROIs that offer the following Resources (incl. Civil Engineering) characteristics: -‐ Access to raw material that exhibits the potential to (1) be used as feedstock for water-generating in situ resource utilization (ISRU) processes and (2) yield significant quantities (greater than 100 MT) of water. The raw material is likely in the form of hydrated minerals, and possibly ice/regolith mix. The top of the raw material deposit is at the surface. -‐ Access to a region where infrastructure can be emplaced or constructed. This region is less than 5 km from the LS and contains flat, stable terrain. The region exhibits evidence for an abundant source of loose regolith. Several deep pits in the area combined with the availability of sand suggests that some natural terrain features can be adapted for construction purposes. -‐ Access to raw material that exhibits the potential to be used as metal feedstock for ISRU and construction purposes. Iron and sulfur-rich mineral surface deposits have been identified in CRISM data in many locations in this area. Noctis Landing is the lowest-altitude location on Mars that straddles both the Tharsis region (above average geothermal gradients) and Valles Marineris (minimal crustal thickness from surface (valley floor) to a subsurface liquid water table. Noctis Landing has the potential for being an ideal site for eventual deep drilling on Mars to access deep subsurface liquid water and potentially encountering extant life. Available data remains insufficient to fully qualify the Noctis Landing site. Additional remote sensing data (visible, Near and Mid-IR, and radar) and surface reconnaissance via a high-mobility robotic rover are recommended. In particular, it will be important to assess the trafficability of the site, and its potential for yielding water and metals as a resource. Access to plateau tops from the Noctis Landing site on the canyon floor should be demonstrated. Future exploration of the site would also be enhanced significantly by the availability of robotic (tele-operatable) surveying and sample-collecting drones. Testing of the use of such collaborative science and exploration technologies should be conducted at terrestrial sites such as the Haughton-Mars Project site on Devon Island, High Arctic, among others. Note: Noctis Landing is not an official Mars nomenclature name for this location. Because the area of the proposed LS/EZ had no name, and because it is close to Noctis Labyrinthus to the West while being distinct from it, the provisional name Noctis Landing is proposed. Noctis means night in Latin.

Lee, Pascal↗

NASA NTRS2003

Design of an event-driven random-access-windowing CCD-based camera

Commercially available cameras are not designed for the combination of single frame and high-speed streaming digital video with real-time control of size and location of multiple regions-of-interest (ROI). A new control paradigm is defined to eliminate the tight coupling between the camera logic and the host controller. This functionality is achieved by defining the indivisible pixel read out operation on a per ROI basis with in-camera time keeping capability. This methodology provides a Random Access, Real-time, Event-driven (RARE) camera for adaptive camera control and is well suited for target tracking applications requiring autonomous control of multiple ROIs. This methodology additionally provides for reduced ROI read out time and higher frame rates compared to the original architecture by avoiding external control intervention during the ROI read out process.

Ortiz, Gerardo G.↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

NASA NTRSDate not supplied

The Completion of a Geosynchronous Earth Orbit Survey with the Eugene Stansbery-Meter Class Autonomous Telescope

The Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT) is the primary optical sensor used by the NASA Orbital Debris Program Office (ODPO) to statistically characterize the geosynchronous Earth orbit (GEO) debris environment and support future Orbital Debris Engineering Model (ORDEM) releases. The ES-MCAT completed its first optical survey of the GEO region from 2020 to 2022. The primary goal of this survey was to autonomously collect and process GEO data with calculated photometric and astrometric uncertainties. A pointing plan was developed to provide uniform sampling within the region of interest (ROI) while accounting for predicted downtime due to insufficient observing conditions. Detections are autonomously correlated to the Space Surveillance Network (SSN) catalog to determine if objects are correlated targets (CTs) or uncorrelated targets (UCTs), the latter of which are of interest for modeling the GEO orbital debris environment. To assess the size detection sensitivity over time and monitor the general performance of the telescope’s optics and software, the optical throughput of the system and limiting magnitudes are evaluated on a routine basis. While the telescope’s ability to operate autonomously and remotely allowed for the GEO survey to continue throughout the COVID-19 pandemic, travel restrictions hampered routine cleaning of the optics during this time, and the primary mirror degraded enough to require recoating. The mirror was removed in 2022, concluding the first GEO survey. The primary mirror received a new coating designed to be more robust against the harsh environment surrounding the ES-MCAT’s location on Ascension Island, accounting for experience gained during operations over the first GEO survey. In early 2023, the recoated primary mirror was reinstalled, and the second GEO survey was initiated. The primary goal of the second GEO survey is to characterize the evolving GEO debris environment with updated optics, software, and pointing strategies while allowing for the inclusion of non-GEO regimes or those that are outside of the ROI. While the pointing method implemented in the first survey allowed for adequate coverage of the ROI over two years, it has been improved to include pointings that avoid the Moon’s position and the galactic plane to reduce software processing time and maximize the detection capabilities of fainter objects. This method also accounts for the changing weather patterns throughout the year and reduces coverage gaps in the ROI. Provided the success of the first two-year GEO survey using autonomous operations, the ODPO is actively collaborating with the United States Space Force (USSF) to make the ES-MCAT a contributing sensor to the SSN. This paper presents results from the first GEO survey including magnitude distributions and orbital parameters for CTs and UCTs. Details are provided for the automated processing pipeline and the optical system throughput for the previous and current primary mirror coatings. In addition, an updated strategy for the second GEO survey to optimize coverage over the ROI is discussed, as are preliminary results from the ongoing second survey.

Corbin Cruz↗

DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Evaluating Economic Impact: An Investment Tool for Large Language Model Integration in Workweek Management

This paper explores the development and application of an investment tool designed to quantify the costs and potential savings associated with integrating large language models (LLMs) into work week management optimization (WMO) within the nuclear industry. LLMs, with their advanced natural language processing capabilities, can significantly enhance various aspects of work management, such as problem identification, prioritization, planning, scheduling, information retrieval, and information summary. Our investment tool focuses on evaluating the return on investment (ROI) for LLM applications in WMO by considering four pivotal decision factors: model selection, application, user training, and hosting options. This paper details the development and implementation of the ROI model and illustrates its application through multiple case studies, analyzing the impact of different variables, such as work time saved, number of requests, and model performance, on the computed ROI over two years. The computed ROI is also compared over different hosting solutions. Our findings indicate that ROI increases with enhanced work time savings and optimal request load but can decline with high request volumes or increased model costs. This model aids decision-makers in the nuclear industry by providing a structured approach to assessing the economic viability and potential savings from integrating LLMs into WMO processes.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

Estimating Return on Investment for Energy Technical Assistance Programs

The U.S. Department of Energy's Office of State and Community Energy Programs engaged the National Laboratory of the Rockies to assess the return on investment (ROI) of technical assistance (TA) programs that support state, local, and Tribal energy planning. Although TA delivers value through capacity building, stakeholder engagement, and knowledge transfer, these benefits are often intangible and challenging to monetize. This study reviews existing ROI frameworks and synthesizes the most relevant elements into a hybrid approach tailored to energy TA programs. The proposed framework integrates monetary and non-monetary outcomes through early logic model development, baseline data collection, and the use of proxies for intangible benefits. As a case study, this paper applies this approach to the Communities Local Energy Action Program (Communities LEAP), demonstrating how ROI can inform program design, data strategy, and performance assessment. Findings underscore that ROI should be applied selectively and planned from the outset to ensure data alignment and attribution accuracy. The framework offers TA practitioners a structured approach that can be leveraged for future programs to evaluate and communicate the multifaceted value of TA investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2010

Algorithms for High-Speed Noninvasive Eye-Tracking System

Two image-data-processing algorithms are essential to the successful operation of a system of electronic hardware and software that noninvasively tracks the direction of a person s gaze in real time. The system was described in High-Speed Noninvasive Eye-Tracking System (NPO-30700) NASA Tech Briefs, Vol. 31, No. 8 (August 2007), page 51. To recapitulate from the cited article: Like prior commercial noninvasive eyetracking systems, this system is based on (1) illumination of an eye by a low-power infrared light-emitting diode (LED); (2) acquisition of video images of the pupil, iris, and cornea in the reflected infrared light; (3) digitization of the images; and (4) processing the digital image data to determine the direction of gaze from the centroids of the pupil and cornea in the images. Most of the prior commercial noninvasive eyetracking systems rely on standard video cameras, which operate at frame rates of about 30 Hz. Such systems are limited to slow, full-frame operation. The video camera in the present system includes a charge-coupled-device (CCD) image detector plus electronic circuitry capable of implementing an advanced control scheme that effects readout from a small region of interest (ROI), or subwindow, of the full image. Inasmuch as the image features of interest (the cornea and pupil) typically occupy a small part of the camera frame, this ROI capability can be exploited to determine the direction of gaze at a high frame rate by reading out from the ROI that contains the cornea and pupil (but not from the rest of the image) repeatedly. One of the present algorithms exploits the ROI capability. The algorithm takes horizontal row slices and takes advantage of the symmetry of the pupil and cornea circles and of the gray-scale contrasts of the pupil and cornea with respect to other parts of the eye. The algorithm determines which horizontal image slices contain the pupil and cornea, and, on each valid slice, the end coordinates of the pupil and cornea. Information from multiple slices is then combined to robustly locate the centroids of the pupil and cornea images. The other of the two present algorithms is a modified version of an older algorithm for estimating the direction of gaze from the centroids of the pupil and cornea. The modification lies in the use of the coordinates of the centroids, rather than differences between the coordinates of the centroids, in a gaze-mapping equation. The equation locates a gaze point, defined as the intersection of the gaze axis with a surface of interest, which is typically a computer display screen (see figure). The expected advantage of the modification is to make the gaze computation less dependent on some simplifying assumptions that are sometimes not accurate

Talukder, Ashit↗

NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

NASA NTRS2020

Remote Support of ISS Payload Operations During the COVID19 Pandemic

As part of the Human Health and Performance Contract (HHPC) with the NASA Johnson Space Center, the Human Research Program’s (HRP) Research Operations and Integration (ROI) element conducts the planning, implementation, and closing of human research operations on-board the International Space Station (ISS). These operations are supported out of the Telescience Support Center (TSC) located in the Mission Control Center at Houston’s Johnson Space Center (MCC-H). HRP ROI has an Emergency Response Plan in place to allow for remote operations to be completed in the case of inclement weather or other natural disaster; however, nominally, the remote support is only expected to last one to two weeks. In response to the COVID-19 global pandemic, HRP ROI was challenged to complete a quick transition to supporting on-orbit operations remotely and distanced for an indefinite amount of time. This shift in ground support required close collaboration with various external groups as well as the implementation or adaptation of various technologies and tools to ensure no loss of science data. Operational adjustments were put into place for ground commanding, telemetry monitoring, personnel staffing and private and public audio and video with the ISS. Adjustments were also put in place for communication and collaboration with MCC-H, the Payload Operation and Integration Center (POIC) at Marshall Space Flight Center (MSFC), as well as between the various HRP ROI console team members spread across Houston, TX. The ability to successfully support a variety of on-orbit operations from any remote location is more in demand as the commercialization of low Earth orbit is expanding.

Operations↗

DOE OSTI2026

Enhanced Ionization Charge Identification in the Short-Baseline Neutrino Program Neutrino Detectors with Deep Neural Networks

We present a deep neural net-based region of interest detection method (DNN ROI) for signal processing in the liquid argon time projection chambers of the Short-Baseline Neutrino (SBN) Program, SBND and ICARUS. DNN ROI addresses limitations of the traditional wire-by-wire thresholding algorithm by leveraging the full two-dimensional detector readout and cross-plane matching information. To account for detector performance variations, we explore training with augmented samples. We find that DNN ROI outperforms the traditional method in both low-level ROI identification performance and high-level reconstruction metrics for high-energy cosmic and accelerator neutrino interaction products, while also being more robust against detector variations, with or without sample augmentation.

Abratenko, P. [Tufts U.]↗

DOE OSTI2024

Untargeted Spatial Metabolomics and Spatial Proteomics on the Same Tissue Section

An increasing number of spatial multiomic workflows have been recently developed. Some of these approaches have leveraged initial mass spectrometry imaging (MSI)-based spatial metabolomics to inform region of interest (ROI) selection for downstream spatial proteomics. However, these workflows have been limited by varied substrate requirements between modalities or have required analyzing serial sections (i.e., one section per modality). To mitigate these issues, we present a novel multiomic workflow that uses desorption electrospray ionization (DESI)-MSI to identify representative spatial metabolite patterns on-tissue prior to spatial proteomic analyses on the same tissue section. Further, this workflow is demonstrated here with a model mammalian tissue (coronal rat brain section) mounted on a polyethylene naphthalate-membrane slide. Initial DESI-MSI resulted in 160 annotations (SwissLipids) within to the METASPACE platform (≤20% false discovery rate). A segmentation map from the annotated ion images informed downstream ROI selection for spatial proteomics characterization from the same sample. The unspecific substrate requirements and minimal sample disruption inherent to DESI-MSI allowed for an optimized, downstream spatial proteomics assay, resulting in 3888 ± 240 to 4717 ± 48 proteins being confidently directed per ROI (200 µm x 200 µm). Finally, we demonstrate the integration of multiomic information, where we found ceramide localization to be correlated with SMPD3 abundance (ceramide synthesis protein), and we also utilized protein abundance to resolve metabolite isomeric ambiguity. Overall, the integration of DESI-MSI into the multiomic workflow allows for complementary spatial and molecular-level information to be achieved from optimized implementations of each MS assay inherent to the workflow itself.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Estradiol associations with brain functional connectivity in postmenopausal women

Abstract Objective Previous studies have found that estrogens play a role in functional connectivity in the brain; however, little research has been done regarding how estradiol is associated with functional connectivity in postmenopausal women. The purpose of this study was to examine the relationship between estradiol and functional connectivity in postmenopausal women. Methods Structural and blood oxygenation level–dependent resting-state magnetic resonance imaging scans of 88 cognitively healthy postmenopausal individuals were obtained along with blood samples collected the same day as the magnetic resonance imaging to assess hormone levels. We generated connectivity values in CONN toolbox version 20.b, an SPM-based software. Results A regression analysis was run using estradiol level and regions of interest (ROI), including the hippocampus, parahippocampus, dorsolateral prefrontal cortex, and precuneus. Estradiol level was found to enhance parahippocampal gyrus anterior division left functional connectivity during ROI-to-ROI regression analysis. Estradiol enhanced functional connectivity between the parahippocampal gyrus anterior division left and the precuneus as well as the parahippocampal gyrus anterior division left and parahippocampal gyrus posterior division right. An exploratory analysis showed that years since the final menstrual period was related to enhanced connectivity between regions within the frontoparietal network. Conclusions These results illustrated the relationship between estradiol level and functional connectivity in postmenopausal women. They have implications for understanding how the functioning of the brain changes for individuals after menopause that may eventually lead to changes in cognition and behavior in older ages.

Obstetrics & Gynecology↗

DOE OSTI2025

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗

DOE OSTI2024

Region of Interest Filter in DUNE DAQ

The Deep Underground Neutrino Experiment (DUNE) is the next generation neutrino experiment currently under construction. It consists of a broadband neutrino beam at Fermilab, a high precision near detector, and the largest liquid argon time projection chamber far detector ever designed at the Sanford Underground Research Facility (SURF). The Region of Interest (ROI) filter is designed for DUNE’s online Data Acquisition (DAQ) system to address data rate constraints and enable low energy physics in the <10 MeV range. The filter employs zero suppression on the detector signal, and by tuning the readout window and threshold the data rates can be reduced by >90%. Performance of the ROI is analyzed in LArsoft on MARLEY generated low energy MC events propagated through the detector simulation. Notably, the optimized ROI filter enables a lower trigger threshold for readout at ~5-10 MeV, allowing DUNE to explore low-energy physics, specifically focusing on solar boron 8 neutrinos which are relevant in this energy range. This advancement enhances DUNE's scientific capabilities, opening avenues for detailed analyses of previously inaccessible low-energy neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

SPRUCE Vegetation Phenology in Experimental Plots from PhenoCam Imagery, 2015-2024

This data set consists of PhenoCam data from the SPRUCE experiment from the beginning of whole ecosystem warming (Hanson et al. 2017) in August 2015 through March 31 of 2025 (2015-08-24 to 2025-03-31), with start- and end-of-season phenological transition dates derived through the end of autumn 2024. Digital cameras, or phenocams, installed in each SPRUCE enclosure track seasonal variation in vegetation “greenness”, a proxy for vegetation phenology and associated physiological activity. Three separate regions of interest (ROIs) were defined for each camera field of view, corresponding to different vegetation types and demarcating (1) Picea trees (vegetation type EN, for evergreen needleleaf); (2) Larix trees (vegetation type DN, for deciduous needleleaf); and (3) the mixed shrub layer (vegetation type SH). This data set consists of three sets of data files: (1) 3-day summary product files: One file for each camera and each ROI (i.e. vegetation type), characterizing vegetation color at a 3-day time step. • Contains 36 files in *.csv format inside a compressed (*.zip) file. (2) Transition date file: Estimates “greenness rising” (spring) and “greenness falling” (autumn) transition dates derived from the smoothed daily green chromatic coordinate (GCC) values, for each camera and each ROI (i.e., vegetation type). • Contains one file in *.csv format. (3) Snow flag files: Indicate days with snow on trees or snow on ground for each experimental enclosure. • Contains two files in *.csv format, one for snow on trees and one for snow on ground. This data set consists of two sets of companion files: (1) Accompanying HTML files show the 90th quantiles of the mean GCC plotted together with transition dates for each vegetation type and plot. • Contains three files in HTML format, one for each vegetation type. • One additional file in HTML format with the transition dates plotted for each vegetation type, by year. (2) R files for processing PhenoCam files and flags. • Contains five files in R file(*.R) format and the components of the phenocamr package (Version 1.1.4) used for calculating transition dates for 2015-2024. These are contained in a compressed (*.zip) file. User Note: All imagery is posted in near-real time to the PhenoCam Project web page (https://phenocam.nau.edu), where it is publicly available. Scroll to “spruce” in the Gallery or link directly to the 29 SPRUCE cameras at https://tinyurl.com/sprucecams. This data set is based on the complete camera record from SPRUCE and supersedes all previously released PhenoCam datasets (see Related Data Sets). The estimated transition dates for previously released datasets may differ slightly (in most cases, by ±3 days or less), because following standard PhenoCam processing protocols (Richardson et al. 2018, Scientific Data), smoothing and interpolation, outlier removal, and transition date estimation are always conducted using the full data record.

54 ENVIRONMENTAL SCIENCES↗