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Analysis of driver performance under reduced visibility

Mathematical models describing vehicle dynamics as well as human behavior may be useful in evaluating driver performance and in establishing design criteria for vehicles more compatible with man. In 1977, a two level model of driver steering behavior was developed, but its parameters were identified for clear visibility conditions only. Since driver performance degrades under conditions of reduced visibility, e.g., fog, the two level model should be investigated to determine its applicability to such conditions. The data analysis of a recently performed driving simulation experiment showed that the model still performed reasonably well under fog conditions, although there was a degradation in its predictive capacity during fog. Some additional parameters affecting anticipation and lag time may improve the model's performance for reduced visibility conditions.

Kaeppler, W. D.↗

Human factors model concerning the man-machine interface of mining crewstations

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

Rider, James P.↗

Application of statistical distribution theory to launch-on-time for space construction logistic support

The ability to launch-on-time and to send payloads into space has progressed dramatically since the days of the earliest missile and space programs. Causes for delay during launch, i.e., unplanned 'holds', are attributable to several sources: weather, range activities, vehicle conditions, human performance, etc. Recent developments in space program, particularly the need for highly reliable logistic support of space construction and the subsequent planned operation of space stations, large unmanned space structures, lunar and Mars bases, and the necessity of providing 'guaranteed' commercial launches have placed increased emphasis on understanding and mastering every aspect of launch vehicle operations. The Center of Space Construction has acquired historical launch vehicle data and is applying these data to the analysis of space launch vehicle logistic support of space construction. This analysis will include development of a better understanding of launch-on-time capability and simulation of required support systems for vehicle assembly and launch which are necessary to support national space program construction schedules. In this paper, the author presents actual launch data on unscheduled 'hold' distributions of various launch vehicles. The data have been supplied by industrial associate companies of the Center for Space Construction. The paper seeks to determine suitable probability models which describe these historical data and that can be used for several purposes such as: inputs to broader simulations of launch vehicle logistic space construction support processes and the determination of which launch operations sources cause the majority of the unscheduled 'holds', and hence to suggest changes which might improve launch-on-time. In particular, the paper investigates the ability of a compound distribution probability model to fit actual data, versus alternative models, and recommends the most productive avenues for future statistical work.

Morgenthaler, George W.↗

An Initial Strategy for Commercial Industry Awareness of the International Space Station

While plans are being developed to utilize the ISS for scientific research, and human and microgravity experiments, it is time to consider the future of the ISS as a world-wide commercial marketplace developed from a government owned, operated and controlled facility. Commercial industry will be able to seize this opportunity to utilize the ISS as a unique manufacturing platform and engineering testbed for advanced technology. NASA has begun the strategic planning of the evolution and commercialization of the ISS. The Pre-Planned Program Improvement (P3I) Working Group at NASA is assessing the future ISS needs and technology plans to enhance ISS performance. Some of these enhancements will allow the accommodation of commercial applications and the Human Exploration and Development of Space mission support. As this information develops, it is essential to disseminate this information to commercial industry, targeting not only the private and public space sector but also the non-aerospace commercial industries. An approach is presented for early distribution of this information via the ISS Evolution Data book that includes ISS baseline system information, baseline utilization and operations plans, advanced technologies, future utilization opportunities, ISS evolution and Design Reference Missions (DRM). This information source and tool can be used as catalyst in the commercial world for the generation of ideas and options to enhance the current capabilities of the ISS.

Jorgensen, Catherine A.↗

KDD Services at the Goddard Earth Sciences Distributed Active Archive Center

NASA's Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) processes, stores and distributes earth science data from a variety of remote sensing satellites. End users of the data range from instrument scientists to global change and climate researchers to federal agencies and foreign governments. Many of these users apply data mining techniques to large volumes of data (up to 1 TB) received from the GES DAAC. However, rapid advances in processing power are enabling increases in data processing that are outpacing tape drive performance and network capacity. As a result, the proportion of data that can be distributed to users continues to decrease. As mitigation, we are migrating more data mining and mining preparation activities into the data center in order to reduce the data volume that needs to be distributed and to offer the users a more useful and manageable product. This migration of activities faces a number of technical and human-factor challenges. As data reduction and mining algorithms are normally quite specific to the user's research needs, the user's algorithm must be integrated virtually unchanged into the archive environment. Also, the archive itself is busy with everyday data archive and distribution activities and cannot be dedicated to, or even impacted by, the mining activities. Therefore, we schedule KDD 'campaigns' (similar to reprocessing campaigns), during which we schedule a wholesale retrieval of specific data products, offering users the opportunity to extract information from the data being retrieved during the campaign.

Lynnes, Christopher↗

Evaluation of a Tactical Surface Metering Tool for Charlotte Douglas International Airport via Human-in-the-Loop Simulation

NASA has been working with the FAA and aviation industry partners to develop and demonstrate new concepts and technologies that integrate arrival, departure, and surface traffic management capabilities. In March 2017, NASA conducted a human-in-the-loop (HITL) simulation for integrated surface and airspace operations, modeling Charlotte Douglas International Airport, to evaluate the operational procedures and information requirements for the tactical surface metering tool, and data exchange elements between the airline controlled ramp and ATC Tower. In this paper, we focus on the calibration of the tactical surface metering tool using various metrics measured from the HITL simulation results. Key performance metrics include gate hold times from pushback advisories, taxi-in-out times, runway throughput, and departure queue size. Subjective metrics presented in this paper include workload, situational awareness, and acceptability of the metering tool and its calibration.

Verma, Savita↗

Dose, LET, time and strain dependence of radiation-induced 53BP1 foci in 15 mouse strains ex vivo and associations to in vivo radiation susceptibility

We present a comparative analysis on the repair of radiation-induced DNA damage ex vivo in 15 strains of mice, including 5 inbred reference strains and 10 collaborative-cross strains, of both sexes. Non-immortalized primary skin fibroblasts derived from 76 mice were subjected to both low- and high-LET radiation (0.1, 1 and 4 Gy of X rays; 1.1 and 3 particles/100μm2 of 350 MeV/n 40Ar and 600 MeV/n 56Fe). Automated image quantification of 53BP1 radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET. Similarly to what we had previously reported for immortalized human cell lines [1], we observed a saturation of RIF number with dose at 4h post-irradiation, with more RIF/Gy for lower LET (X rays and 40Ar) compared to 56Fe. However at later time points (24h and above), the trend was inverted with more RIF/Gy for higher LET. Our data suggest that multiple DSBs cluster into RIF: as the linear density of DSBs increases with LET, so does the probability of having more DSBs per RIF, which makes it more difficult for cells to fully resolve high-LET-induced RIF, explaining the hypersensitivity to high-LET radiation despite a low number of RIF. Taking into account the amount of clustering at a given dose and LET, but also the kinetics of DNA damage repair, we introduced a novel mathematical formalism to evaluate the number of remaining RIF over time. We showed that the newly introduced kinetic metrics can be used as surrogate biomarkers for in vivo radiation toxicity, with potential applications in radiotherapy and human space exploration. In particular, we observed an association between the repairable fraction of RIF measured in vitro and survival levels of immune cells collected from irradiated mice. Moreover, the speed of DNA damage repair correlated with spontaneous cancer incidence data collected from the Mouse Tumor Biology database, suggesting a relationship between the efficiency of DSB repair after irradiation and cancer risk. In addition to the efficacy of repair and persistent RIF levels, even the amount of spontaneous foci without irradiation was shown to be strain dependent, indicating that these phenotypes are at least partially driven by genetics, and supporting their potential as indicators of individual radiation sensitivity. [1] Neumaier, T., et al., PNAS, 2012 (8) 109:443

Radiation, DNA damage, repair kinetics↗

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗

Earth-Independent Medical Operations (EIMO) Concept of Operations

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

Earth-Independent Medical Operations (EIMO) Concept of Operations (ConOps)

Compared to the current paradigm for crew health in low-Earth orbit and Lunar missions that rely on constant communication with Mission Control, there is an anticipated shift in medical operations for deep-space exploration missions. This shift stems from mission constraints imposed by the considerable distance from Earth, which include resource limitations due to a lack of resupply, mass, power, volume, and data limitations, challenges imposed by communication latency and the inability to evacuate in case of emergencies. To transition towards a more self-reliant medical approach, a comprehensive strategy is essential to progressively enable crew autonomy and mitigate mission success risks in the challenging environment of space. This transformative shift is collectively referred to as "Earth-Independent Medical Operations" (EIMO), signifying the gradual transfer of medical care and decision-making from terrestrial resources to space-based assets. This transition is aimed at bolstering astronaut health and performance while simultaneously reducing the overall risks associated with space missions. The constraints related to EIMO necessitate an integrated development of medical systems, featuring interoperability with mission planning, vehicle design, spacesuit design, and data architecture. This integration is vital in establishing a robust medical infrastructure that not only supports the well-being of astronauts but also ensures the success of the mission as a whole. The Human Research Program (HRP) Exploration Medical Capability (ExMC) Element has developed a model-based Concept of Operations (ConOps) outlining an initial vision for EIMO. Within this ConOps, a comprehensive view is presented, encompassing stakeholder needs, system objectives, and system goals associated with EIMO. Additionally, it provides illustrative examples of the various activities (scenarios) for which the system will be employed during missions. The selection of these activities has been meticulous, aiming to encompass a wide spectrum of medical conditions, including those falling under different risk categories, such as low-likelihood-low-consequence, low-likelihood-high-consequence, and high-likelihood-low-consequence. The selection of these activities (scenarios) effectively encompasses the wide range of medical events situated within an assumed probability-consequence bell curve. In each scenario, at least one of the five main EIMO components identified is captured. Those EIMO components are: Pre-mission Planning, Acute and Emergent Management Decision Making, Prolonged Medical Management Decision Making, Supplies and Resource Management, and Task Load Management. The ConOps was developed by a multidisciplinary team consisting of systems engineers, scientists, and clinicians across NASA and aims to serve as an initial recommendation to gradually and safely enabling crew autonomy for Mars missions and beyond.

Earth Independent Medical Operations↗

Li-ion Battery Material phase prediction through Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are widely adopted in many industrial applications. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Therefore, it can eventually help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. However, these images often suffer from low image contrast between multiple material constituents , making it difficult for humans to distinguish and characterize these constituents through visualization. A minor error in detecting distributions among the material constituents can lead to a high error in the calculated parameters of material properties.We present a novel hierarchical curriculum learning framework to address the complex task of estimating material constituent distribution in battery electrodes. To provide spatially smooth prediction, our framework comprises three modules: (i) an uncertainty-aware model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a technique to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator to appropriately fuse the local and global effects towards obtaining the final distribution.

Tabassum, Anika↗

AI-Enabled Robotic NDE for Structural Damage Assessment and Repair

The aim of this paper is to develop the concept and a prototype of an intelligent mobile robotic platform that is integrated with nondestructive evaluation (NDE) capabilities for autonomous live inspection and repair. In many industrial environments, such as the application of power plant boiler inspection, human inspectors often have to perform hazardous and challenging tasks. There is a significant chance of injury, considering the confined spaces and limited visibility of the inspection environment and hazards such as pressurization and improper water levels. In order to provide a solution to eliminate these dangers, the concept of a new robotic system was developed and prototyped that is capable of autonomously sweeping the region to be inspected. The robot design contains systematic integration of components from robotics, NDE, and artificial intelligence (AI). A magnetic track system is used to navigate over the vertical steel structures required for examination. While moving across the inspection area, the robot uses an NDE sensor to acquire data for inspection and repair. This paper presents a design of a portable NDE scanning system based on eddy current array probes, which can be customized and installed on various mobile robot platforms. Machine learning methods are applied for semantic segmentation that will simultaneously localize and recognize defects without the need of human intervention. Experiments were conducted that show the NDE and repair capabilities of the system. Improvements in human safety and structural damage prevention, as well as lowering the overall costs of maintenance, are possible through the implementation of this robotic NDE system.

Materials Science↗

Navigation Performance Overview of Gateway During a Lunar Lander Mission

Starting with Artemis IV, the human lander system (HLS) missions will utilize the Gateway as a staging point in a near rectilinear halo orbit (NRHO) between cislunar space and the lunar surface. The presence of a crew, Orion, and HLS will cause significant perturbations from docking and venting, while attitude requirements on Gateway can cause structural antenna blockage. The HLS mission timeline and perturbations are simulated considering antenna blockage to ground stations. Simulated DSN tracking data is generated and processed to produce a navigation state estimate for orbit maintenance maneuver (OMM) targeting. The starting epoch is varied to adjust tracking availability, and the volume of tracking data processed is reduced. Separately, the observability of perturbations in the NRHO with two-way tracking data is analyzed. The mission is simulated with imperfect knowledge of venting perturbations, and finally the estimation errors from propagating an estimated state from data cutoff (DCO) to maneuvers are investigated.

Clark P Newman↗

Muscle sympathetic nerve responses to physiological changes in prostaglandin production in humans

Previous studies suggest that prostaglandins may contribute to exercise-induced increases in muscle sympathetic nerve activity (MSNA). To test this hypothesis, MSNA was measured at rest and during exercise before and after oral administration of ketoprofen, a cyclooxygenase inhibitor, or placebo. Twenty-one subjects completed two bouts of graded dynamic and isometric handgrip to fatigue. Each exercise bout was followed by 2 min of postexercise muscle ischemia. The second exercise bouts were performed after 60 min of rest in which 11 subjects were given ketoprofen (300 mg) and 10 subjects received a placebo. Ketoprofen significantly lowered plasma thromboxane B(2) in the drug group (from 36 +/- 6 to 22 +/- 3 pg/ml, P < 0.04), whereas thromboxane B(2) in the placebo group increased from 40 +/- 5 to 61 +/- 9 pg/ml from trial 1 to trial 2 (P < 0.008). Ketoprofen and placebo did not change sympathetic and cardiovascular responses to dynamic handgrip, isometric handgrip, and postexercise muscle ischemia. There was no relationship between thromboxane B(2) concentrations and MSNA or arterial pressure responses during both exercise modes. The data indicate that physiological increases or decreases in prostaglandins do not alter exercise-induced increases in MSNA and arterial pressure in humans. These findings suggest that contraction-induced metabolites other than prostaglandins mediate MSNA responses to exercise in humans.

Clinical Trial↗

Rapid Biochemical Analysis on the International Space Station (ISS): Preparing for Human Exploration of the Moon and Mars

The Lab-on-a-Chip Application Development - Portable Test System, known as LOCAD-PTS, was launched to the International Space Station (ISS) aboard Space Shuttle Discovery (STS-116) on December 9th,2006. Since that time, it has remained onboard ISS and has been operated by the crew on 10 separate occasions LOCAD-PTS is a handheld device for rapid biochemical analysis; it consists of a spectrophotometer, a series of interchangeable cartridges, a pipette and several clean/sterilized swabbing kits to obtain samples from ISS surfaces. Sampling, quantitative analysis and data retrieval is performed onboard, therefore reducing the need to return samples to Earth. Less than 20 minutes are required from sampling to data, significantly faster than existing culture-based methods on ISS, which require 3-5 days. Different cartridges are available for the detection of different target molecules (simply by changing the formulation within each cartridge), thereby maximizing the benefit and applications addressed by a single instrument. Initial tests on ISS have focused on the detection of the bact.erial macromolecule endotoxin, a component of bacterial cell walls. LOCAD-PTS detects endotoxin with a cartridge that contains a formulation known as Limulus Amebocyte Lysate (LAL) assay. LAL is derived from blood of the horseshoe crab, Limulus polyphemus, and detects enodotoxin with an enzyme cascade that triggers generation Of a yellow colored dye, p-nitroanaline. The more p-nitroanaline product, the more endotoxin is in the original sample. To enable quantitative analysis, the absorbance of this color is measured by LOCAD-PTS through a 395 nm filter and compared with an internal calibration curve, to provide a reading on the LED display that ranges from 0.05 Endotoxin Units (EU)/ml to 5 EU/ml. Several surface sites were analyzed within ISS between March 2007 and February 2008, including multiple locations in the US Laboratory Destiny, Node 1 Unity, AMock, and Service Module Zvezda. The goals of this initial study were to i) test the cleanliness of reagents/supplies on orbit, ii) test the crew's ability to collect and process a sample in microgravity without contamination, iii) demonstrate nominal function of the LOCAD-PTS, and iv) provide a general survey of endotoxin within the ISS. The surface sites varied greatly in terms of their frequency-of-use and material texture/composition; from relatively smooth aluminum, to fabric, to the room temperature vulcanizing (RTV) rubber of a Extravehicular Mobility Unit (EMU) spacesuit. Results showed that: i) the swabbing kits and reagents remained clean on orbit, ii) the crew could collect and process a sample without contamination, and iii) the LOCAD-PTS functioned nominally in > 99% of the 55 tests completed. We will present detailed results of the survey of endotoxin on ISS surfaces. These results and technology are important in the near-term - by providing an extra tool in the toolbox for ISS microbial monitoring. They are also important in the longer term as valuable preparation for human exploration of the Moon and Mars. One of the proposed science goals for the human exploration of Mars will be to detect and characterize any indigenous biological molecules that may exist on the Martian surface. To achieve that goal, the crew must have the technology available onboard to differentiate indigenous biology from any terrestrial biological material brought to Mars by the spacecraft and crew (termed 'forward contamination'). The LAL assay is already one of the official methods used by NASA's planetary protection program to certify cleanliness of interplanetary robotic spacecraft prior to launch; and therefore endotoxin is a good marker of forward contamination (as well as other microbial molecules detectable with LOCAD-PTS e.g. box-1, 3-glucan and lipoteichoic acid). Furthermore, the distribution and abundance of these molecules on the ISS provides a good indicator of what to expect on the Crew Exploratioehicle Orion, the lunar lander Antares, and future crewed spacecraft destined for Mars. In addition, technology such as LOCAD-PTS has been proposed to help evaluate forward contamination during lunar surface operations by the crew, as preparation for the human exploration of Mars.

Maule, J.↗

Functional Sensory-Motor Performance Following Long Term Space Flight: The First Results of "Field Test" Experiment

The effect that extended-duration space flights may have on human space travelers, including exploration missions, is widely discussed at the present time. Specifically, there is an increasing amount of evidence showing that the physical capacity of cosmonauts is significantly reduced after long-duration space flights. It is evident that the most impaired functions are those that rely on gravity, particularly up right posture and gait. Because of the sensorimotor disturbances manifested in the neurology of the posture and gait space flight and postflight changes may also be observed in debilitating motion sickness. While the severity of particular symptoms varies, disturbances in spatial orientation and alterations in the accuracy of voluntary movements are persistently observed after long-duration space flights. At this time most of the currently available data are primarily descriptive and not yet suitable for predicting operational impacts of most sensorimotor decrements observed upon landing on planetary surfaces or asteroids. In particular there are no existing data on the recovery dynamics or functionality of neurological, cardiovascular or muscle performance making it difficult to model or simulate the cosmonauts' activity after landing and develop the appropriate countermeasure that will ensure the rapid and safe recovery of crewmembers immediately after landing in what could be hostile environments. However and as a starting position, the videos we have acquired during recent data collection following the long duration flights of cosmonauts and astronauts walking and performing other tasks shortly after return from space flight speak volumes about their level of deconditioning. A joint Russian-American team has developed a new study specifically to address the changes in crewmembers performance and the recovery of performance with the intent of filling the missing data gaps. The first (pilot) phase of this study includes recording body kinematics and quantifying the coordination and timing of relatively simple basic movements - transition from seated and prone positions to standing, walking, stepping over obstacles, tandem walking, muscle compliance, as well as characteristics of postural sway and orthostatic tolerance. Testing for changes in these parameters have been initiated in the medical tent at the landing site. The first set of experiments showed that during the first hour after landing, cosmonauts and astronauts were able to execute (although slower and with more effort than preflight) simple movements such as egress from a seated or prone position and also to remain standing for 3.5 minutes without exhibiting pronounced cardiovascular changes. More challenging tests, however, demonstrated a prominent reduction in coordination - the obstacle task, for example, was performed at much slower speed and with a marked overestimation of the obstacle height and tandem walking was greatly degraded suggesting significant changes in proprioception, brainstem and vestibular function. There is some speculation that the neural changes, either from the bottom-up or top down may be long lasting; requiring compensatory responses that will modify or mask the adverse responses we have observed. Furthermore, these compensatory responses may actually be beneficial, helping achieve a more rapid adaptation to both weightlessness and a return to earth.

Tomilovskaya, E. S.↗

ZRBA1, a Mixed EGFR/DNA Targeting Molecule, Potentiates Radiation Response Through Delayed DNA Damage Repair Process in a Triple Negative Breast Cancer Model

Purpose: ZRBA1 is a combi-molecule designed to induce DNA alkylating lesions and to block epidermal growth factor receptor (EGFR) TK domain. Inasmuch as ZRBA1 downregulates the EGFR TK-mediated antisurvival signaling and induces DNA damage, we postulated that it might be a radiosensitizer. The aim of this study was to further investigate the potentiating effect of ZRBA1 in combination with radiation and to elucidate the possible mechanisms of interaction between these 2 treatment modalities. Methods and Materials: The triple negative human breast MDA-MB-468 cancer cell line and mouse mammary cancer 4T1 cell line were used in this study. Clonogenic assay, Western blot analysis, and DNA damage analysis were performed at multiple time points after treatment. To confirm our in vitro findings, in vivo tumor growth delay assay was performed. Results: Our results show that a combination of ZRBA1 and radiation increases the radiation sensitivity of both cell lines significantly with a dose enhancement factor of 1.56, induces significant numbers of DNA strand breaks, prolongs higher DNA damage up to 24 hours after treatment, and significantly increases tumor growth delay in a syngeneic mouse model. Conclusions: Our data suggest that the higher efficacy of this combination could be partially due to increased DNA damage and delayed DNA repair process and to the inhibition of EGFR. The encouraging results of this combination demonstrated a significant improvement in treatment efficiency and therefore could be applicable in early clinical trial settings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗