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At least 181 records · Page 10

Using DNA Damage to Investigate the Individual Variability of Human Sensitivity to Ionizing Radiation

High-LET ionizing radiation is a major occupational health hazard for astronauts, but risk assessment remains elusive due to limited epidemiological data. Identifying genetic factors modulating the individual radiation response may be the most effective strategy to provide individualized risk management for long-duration high-radiation missions. We have started tackling the challenge of predicting individual risks by identifying human genetic loci associated with various radiation sensitivity phenotypes in primary blood mononuclear cells from a relatively large healthy human cohort. To date, we have performed the isolation of PBMCs from 768 subjects of the same ethnicity, and irradiated PBMCs from 576 subjects with 1 and 3 particles/100µm2 of 600 MeV/n 56Fe, 350 MeV/n 40Ar and 350 MeV/n 28Si ions. The phenotypes of interest were: number of radiation-induced foci (or RIFs), CellROX oxidative stress responses and cell death, at 4h and 24h following irradiation. We have observed a significant inter-individual variability at 0 Gy between the 576 studied subjects, with a mean fold difference between the 10% lowest and highest responders of 5.6 of RIFs/cell, 7.9 in mean CellRox intensity, and 9.3 in percentage of dead cells. In order to better assess genetic factors influencing DNA repair, we used a metric previously introduced by our group to sort out radiation sensitivity phenotypes in mice: i.e. the ratio of the first to the second slope of RIFs/cell (between 0 and 1, and between 1 and 3 particle/100µm2). Preliminary data on 192 individuals showed a distribution of low-dose responders (ratio > 1) to high-dose responders (ratio < 1) at 4h of 12%, 55% and 52% respectively for Fe, Ar and Si. The average value for the first and the second slopes was very similar for the two lowest LET (0.10 [-0.26;0.58] and 0.09 [-0.45;0.41] for Ar, 0.07 [-0.27;0.38] and 0.08 [-0.19;0.42] for Si), indicating a linear dose response across both fluence. Fe showed clear saturation for the highest dose with a slope of -0.09 [-0.86;1.51] against 0.68 [-2.21;2.20] for the low dose range, which probably reflects that many PBMCs are beyond repair at the high dose. Note that other significances were found for additional factors such as BMI and age whereas none were found for sex. GWAS will be performed on all phenotypes upon completion of measurements.

Pariset, E.↗

Using DNA Damage to Investigate the Individual Variability of Human Sensitivity to Ionizing Radiation

High-LET ionizing radiation is a major occupational health hazard for astronauts, but risk assessment remains elusive due to limited epidemiological data. Identifying genetic factors modulating the individual radiation response may be the most effective strategy to provide individualized risk management for long-duration high-radiation missions. We have started tackling the challenge of predicting individual risks by identifying human genetic loci associated with various radiation sensitivity phenotypes in primary blood mononuclear cells from a relatively large healthy human cohort. To date, we have performed the isolation of PBMCs from 768 subjects of the same ethnicity, and irradiated PBMCs from 576 subjects with 1 and 3 particles/100µm2 of 600 MeV/n 56Fe, 350 MeV/n 40Ar and 350 MeV/n 28Si ions. The phenotypes of interest were: number of radiation-induced foci (or RIFs), CellROX oxidative stress responses and cell death, at 4h and 24h following irradiation. We have observed a significant inter-individual variability at 0 Gy between the 576 studied subjects, with a mean fold difference between the 10% lowest and highest responders of 5.6 of RIFs/cell, 7.9 in mean CellRox intensity, and 9.3 in percentage of dead cells. In order to better assess genetic factors influencing DNA repair, we used a metric previously introduced by our group to sort out radiation sensitivity phenotypes in mice: i.e. the ratio of the first to the second slope of RIFs/cell (between 0 and 1, and between 1 and 3 particle/100µm2). Preliminary data on 192 individuals showed a distribution of ?low-dose responders? (ratio > 1) to ?high-dose responders? (ratio < 1) at 4h of 12%, 55% and 52% respectively for Fe, Ar and Si. The average value for the first and the second slopes was very similar for the two lowest LET (0.10 [-0.26;0.58] and 0.09 [-0.45;0.41] for Ar, 0.07 [-0.27;0.38] and 0.08 [-0.19;0.42] for Si), indicating a linear dose response across both fluence. Fe showed clear saturation for the highest dose with a slope of -0.09 [-0.86;1.51] against 0.68 [-2.21;2.20] for the low dose range, which probably reflects that many PBMCs are beyond repair at the high dose. Note that other significances were found for additional factors ? such as BMI and age ? whereas none were found for sex. GWAS will be performed on all phenotypes upon completion of measurements.

Pariset, E.↗

Program Promotion Can Distort Space Systems Engineering and Deny Risk

NASA's spectacular success in the Apollo moon landings was achieved against the odds by an obsessive dedication to reducing the great risk. But risk analysis predicted so many astronaut fatalities that it was thought to be unreasonably pessimistic and potentially damaging to the Apollo program. Risk analysis was discontinued, risk was neglected in space shuttle engineering, and so the space shuttle design was unnecessarily dangerous. Since the Apollo era it has been understood that long human space missions would recycle oxygen and water to avoid the very high launch cost of directly supplying them. The development of recycling systems was justified by the need to increase material closure and reduce launch mass. When it was recognized that increasing closure leads to rapidly diminishing returns, the program goal was changed to reducing launch mass and reliability, cost, and risk were considered irrelevant. Systems engineering and especially the discouraging problems of risk and cost have been deliberately ignored because they detract from program promotion, with unfortunate results. Current human launch system design does account for risk and the result strongly resembles Apollo. Current life support design continues to assume recycling, even though the recent great reduction in launch cost now allows direct supply of oxygen and water with significantly better quality, reliability, cost, and risk.

Advocacy↗

Improved age- and gender-specific radiation risk models applied on cohorts of Swedish patients

The aim of this study is to implement lifetime attributable risk (LAR) predictions for radiation induced cancers for Swedish cohorts of patients of various age and sex, undergoing diagnostic investigations by nuclear medicine methods. Methods: Calculations are performed on Swedish groups of patients with Paget's disease and with bone metastases from prostatic cancer and diagnosed with bone scintigraphy with an administration of 500 MBq 99m Tc-phosphonate. Results: The inclusion of patient survival rates into the calculations lowers the induced radiation cancer risk, as it takes into account that cohorts of patients have shorter predicted survival times than the general population. Conclusion: LAR estimations could be valuable for referring physicians, nuclear medicine physicians, nurses, medical physicists, radiologists, and oncologists and as well as ethical committees for risk estimates for specific subgroups of patients. Caution is however advised with respect to application of LAR predictions to individuals (because of individual sensitivities, circumstances, etc.).

61 RADIATION PROTECTION AND DOSIMETRY↗

Leveraging NASA Soil Moisture Active Passive for Assessing Fire Susceptibility and Potential Impacts over Australia and California

Wildfires are a major concern around the globe because of the immediate impact they have on people's lives, local ecosystems, and the environment. Soil moisture is one of the most important factors that influences wildfire occurrences and spread. However, it is also one of the most challenging hydrological variables to measure routinely and accurately. Therefore, soil moisture is significantly underutilized in operational wildfire risk applications. Thus, the aim here is to use a well-established operational soil moisture product to isolate the soil moisture-fire relationship and assess the utility of using soil moisture as a leading indicator of potential fire risk. We evaluated the value of remotely-sensed soil moisture observations from the Soil Moisture Active Passive (SMAP) sensor for monitoring and predicting fire risk in Australia and California. We quantified the relationship between observed fire activity and soil moisture conditions and analyzed the soil moisture conditions for two extreme fire events. Our findings show that fire activity is strongly associated with soil moisture anomalies. Lagged correlation analysis demonstrated that a remote-sensing based soil moisture product could predict fire activity with a 1-2 month lead-time. Soil moisture anomalies consistently decreased in the months preceding fire occurrence, often from normal to drier conditions, according to a spatiotemporal analysis of soil moisture in two extreme fire events. Overall, our findings indicate that soil moisture conditions prior to large wildfires can aid in their prediction and operational satellite-based soil moisture products such as the one used here have real value for supporting wildfire susceptibility and impacts.

Nazmus Sazib↗

Hydraulically‐vulnerable trees survive on deep‐water access during droughts in a tropical forest

Summary Deep‐water access is arguably the most effective, but under‐studied, mechanism that plants employ to survive during drought. Vulnerability to embolism and hydraulic safety margins can predict mortality risk at given levels of dehydration, but deep‐water access may delay plant dehydration. Here, we tested the role of deep‐water access in enabling survival within a diverse tropical forest community in Panama using a novel data‐model approach. We inversely estimated the effective rooting depth (ERD, as the average depth of water extraction), for 29 canopy species by linking diameter growth dynamics (1990–2015) to vapor pressure deficit, water potentials in the whole‐soil column, and leaf hydraulic vulnerability curves. We validated ERD estimates against existing isotopic data of potential water‐access depths. Across species, deeper ERD was associated with higher maximum stem hydraulic conductivity, greater vulnerability to xylem embolism, narrower safety margins, and lower mortality rates during extreme droughts over 35 years (1981–2015) among evergreen species. Species exposure to water stress declined with deeper ERD indicating that trees compensate for water stress‐related mortality risk through deep‐water access. The role of deep‐water access in mitigating mortality of hydraulically‐vulnerable trees has important implications for our predictive understanding of forest dynamics under current and future climates.

54 ENVIRONMENTAL SCIENCES↗

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗

Robust Solution Approach for Bilevel Demand Response Game at Distribution Level

In this paper, a bilevel electricity pricing and demand response game between a distribution system operator (DSO) and load aggregators (LAs) is considered, and a robust decision model is proposed for the DSO to deal with the uncertainties from the wholesale market prices and demand consumptions of LAs. With the max-min objective at the upper level, the robust bilevel model is converted into a single level model by the Karush-Kuhn-Tucker (KKT) conditions and prime-dual transformation. Several groups of experiments have been conducted based on different preferences on uncertainty gaps and peak load reductions to show its effectiveness. After-the-fact scenario analysis has indicated that the robust solution is more beneficial in reducing the risk of inaccurate predictions as compared to the risk neutral strategy.

Chen, Yang↗

Pre-flight risk assessment in Emergency Medical Service (EMS) helicopters

The Emergency Medical Service (EMS) industry has been the subject of several television and newspaper articles (Harvey and Jensen, 1987) which emphasized the negative aspects, (e.g., fatalities and high accident rates), rather than the life saving services performed. Until recently, the accident rate of the EMS industry has been five times as high as that of other civil helicopters. This high accident rate has been coupled with the dramatic rise in the number of programs. The industry has built from a single service at its inception in 1972, to over 180 in 1987 (Spray, 1987), to the point that 93 percent of the contiguous U.S. is now covered by some type of EMS service. These factors prompted the National Transportation Safety Board (NTSB) to study the accidents that occurred between May 11, 1978 and December 3, 1986 (NTSB, 1988). The NTSB report concluded that 'Sound pilot judgment is central to safe flight operations.' They further stated that '... factors unique to EMS helicopter operations--such as the influence of the mission itself, program competition, and EMS program management perspectives--can drastically influence pilot judgment during the EMS mission.' One of the most difficult decisions that a pilot must make is whether to accept or decline a mission. A pre-flight risk assessment system (SAFE) was developed at NASA-Ames Research Center for civil EMS operations to aid pilots in making this decision objectively. The ability of the SAFE system to predict mission risk profiles was tested at an EMS facility. The results of this field study demonstrated that the usefulness of SAFE was highly dependent on the type of mission flown. SAFE is now being modified so that it can 'learn' with each mission flown. For example, after flying a mission to a particular site, an EMS pilot would input information about this mission into the system, such as new buildings, wires, or approach procedures. Then, the next time a pilot flew a similar mission or one to the same area, this additional information would be taken into account in computing a risk assessment.

Shively, R. J.↗

Predictive analytics to direct clinical attention to complex patients with elevated suicide risk: enhancement of the Veterans Health Administration REACH VET model

Suicide is a major public health concern, particularly among Veterans. The U.S. Department of Veterans Affairs Veterans Health Administration (VHA) employs the Recovery Engagement and Coordination for Health–Veterans Enhanced Treatment (REACH VET) model to prioritise high-risk patients for targeted clinical attention. REACH VET 1.0 (RV 1.0) was developed on 2008–2011 data. To reflect changes in clinical practice and populations, VHA updated it to REACH VET 2.0 (RV 2.0). This study describes its development and validation. RV 2.0 used longitudinal data from 7,248,170 VHA patients (4,967 suicide deaths) in 2018–2019, with 650 time-varying demographic, clinical and area-level predictors derived from a 2-year lookback (2016–2019). An ensemble of Elastic-Net logistic regression models was trained on 2018 data and evaluated monthly at the population level in 2019, focusing on the top 0.1% intervention risk tier. Analyses assessed model discrimination, suicide detection, risk concentration, subgroup consistency (sex, age and race/ethnicity) and performance relative to RV 1.0 using the same percentile-based risk strata. RV 2.0 outperformed RV 1.0 across all risk strata, with better discrimination (C-statistic 0.76 vs 0.69) and consistent performance across demographic subgroups. Within the top 0.1% of predicted risk, RV 2.0 identified more deaths, higher suicide rates and greater mortality risk concentration both when averaged across the 12 monthly 2019 test sets (5.6 vs 3.6; 83.6 vs 53.7 per 100,000 person-years; 21.0 vs 14.1) and when annualised for 2019 (67 vs 43; 2.7% vs 1.7%; 1,003 vs 644 per 100,000 person-years; 26.7 vs 17.1). RV 2.0 improves suicide risk stratification among Veterans, demonstrating better performance and consistent prediction across subgroups and highlighting the need for regular model updates and evaluation.

Peluso, Alina [Oak Ridge National Laboratory (ORNL↗

Linking Threat Agents to Targeted Organizations: A Pipeline for Enhanced Cybersecurity Risk Metrics

In this study, we present a methodology leveraging Large Language Models (LLMs) to transform Cybersecurity Threat Intelligence (CTI) narratives into actionable insights for individual organizations. Our approach automates the extraction of machine-readable adversary SKRAM (Skills, Knowledge, Resources, Authorities, and Motivation) attributes from open-source reports, extending LLM utility beyond typical interactions. This innovation enables precise, automated assessments of cybersecurity risks posed by various adversaries. Using a chain-of-thought and multi-shot prompting strategy, our methodology advances the automation of cybersecurity feature extraction for new machine-learning models that predict the risk of adversary targeting. This approach is refined using a substantial dataset of over 150 analyst-validated threat reports and synthetic organizational data from 900 companies. Here, by bootstrapping the training data with a rule-based heuristic over synthetic data, we have developed a high-accuracy machine-learning model that allows entities to dynamically prioritize threats and defensive actions.

Cyber Threat Intelligence↗

Using an Ultrasonic Instrument to Size Extravascular Bubbles

In an ongoing development project, microscopic bubbles in extravascular tissue in a human body will be detected by use of an enhanced version of the apparatus described in Ultrasonic Bubble- Sizing Instrument (MSC-22980), NASA Tech Briefs, Vol. 24, No. 10 (October 2000), page 62. To recapitulate: The physical basis of the instrument is the use of ultrasound to excite and measure the resonant behavior (oscillatory expansion and contraction) of bubbles. The resonant behavior is a function of the bubble diameter; the instrument exploits the diameter dependence of the resonance frequency and the general nonlinearity of the ultrasonic response of bubbles to detect bubbles and potentially measure their diameters. In the cited prior article, the application given most prominent mention was the measurement of gaseous emboli (essentially, gas bubbles in blood vessels) that cause decompression sickness and complications associated with cardiopulmonary surgery. According to the present proposal, the instrument capabilities would be extended to measure extravascular bubbles with diameters in the approximate range of 1 to 30 m. The proposed use of the instrument could contribute further to the understanding and prevention of decompression sickness: There is evidence that suggests that prebreathing oxygen greatly reduces the risk of decompression sickness by reducing the number of microscopic extravascular bubbles. By using the ultrasonic bubble-sizing instrument to detect and/or measure the sizes of such bubbles, it might be possible to predict the risk of decompression sickness. The instrument also has potential as a tool to guide the oxygen-prebreathing schedules of astronauts; high-altitude aviators; individuals who undertake high-altitude, low-opening (HALO) parachute jumps; and others at risk of decompression sickness. For example, an individual at serious risk of decompression sickness because of high concentrations of extravascular microscopic bubbles could be given a warning to continue to prebreathe oxygen until it was safe to decompress.

Magari, Patrick J.↗

Cross-Cultural Perspectives of Service Quality and Risk in Air Transportation

This study compares US and Korean customers in terms of their perceptions of airline service quality based on SERVPERF and industry-based measures, as well as their perceptions of risks involved in the airline choice. SERVPERF is a set of multi-dimensional measures of customer evaluations of service quality. The results indicate that: (1) US passengers are generally more satisfied with their airline service than Korean customers on most of the SERVPERF dimensions; (2) Koreans are generally more satisfied with the bumping procedures whereas US participants feel more satisfied with the airline's baggage handling, operations/safety, and connections; and (3) US participants perceive higher levels of performance and financial risks whereas Koreans feel greater social risk in choosing an airline. This study also examines the SERVPERF, industry-based measure, and perceived risk in predicting customer satisfaction with, and intention to repatronize the airline. The results suggest that US customers consider service reliability, in-flight comfort, and connections as the key factors determining satisfaction with airline service whereas Korean passengers generally regard reliability, assurance, and risk factors as predictors of satisfaction. The determining factors of customer intention to repatronize the airline are reliability and empathy for US, and reliability and overall risk for Korean customers. The study demonstrates the applicability of SERVPERF as a cross-cultural tool and indicates the importance of perceived risk in cross-cultural studies.

Cunningham, Lawrence F.↗

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

Enigine Icing↗

Preliminary Results From a Heavily Instrumented Engine Ice Crystal Icing Test in a Ground Based Altitude Test Facility

Preliminary results from the heavily instrumented ALF502R-5 engine test conducted in the NASA Glenn Research Center Propulsion Systems Laboratory are discussed. The effects of ice crystal icing on a full scale engine is examined and documented. This same model engine, serial number LF01, was used during the inaugural icing test in the Propulsion Systems Laboratory facility. The uncommanded reduction of thrust (rollback) events experienced by this engine in flight were simulated in the facility. Limited instrumentation was used to detect icing on the LF01 engine. Metal temperatures on the exit guide vanes and outer shroud and the load measurement were the only indicators of ice formation. The current study features a similar engine, serial number LF11, which is instrumented to characterize the cloud entering the engine, detect/ characterize ice accretion, and visualize the ice accretion in the region of interest. Data were acquired at key LF01 test points and additional points that explored: icing threshold regions, low altitude, high altitude, spinner heat effects, and the influence of varying the facility and engine parameters. For each condition of interest, data were obtained from some selected variations of ice particle median volumetric diameter, total water content, fan speed, and ambient temperature. For several cases the NASA in-house engine icing risk assessment code was used to find conditions that would lead to a rollback event. This study further helped NASA develop necessary icing diagnostic instrumentation, expand the capabilities of the Propulsion Systems Laboratory, and generate a dataset that will be used to develop and validate in-house icing prediction and risk mitigation computational tools. The ice accretion on the outer shroud region was acquired by internal video cameras. The heavily instrumented engine showed good repeatability of icing responses when compared to the key LF01 test points and during day-to-day operation. Other noticeable observations are presented.

turbomachinery↗

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Radiation health risks are predominantly derived from low linear energy transfer (LET) terrestrial exposures; however, space radiation includes exposure to high-LET and high-charge, high-energy (HZE) particles. Accurately quantifying the differences in radiation quality between the space and terrestrial radiation environments is important for assessing and predicting health risks for astronauts. Weil et al. 2009 and 2014 used two different inbred mouse strains to study differences in hepatocellular carcinoma (HCC) tumorigenesis after exposures to low- and high- LET radiation. More recently, Edmundson et al. 2020 provided valuable new tumor data in outbred mice that were exposed to low- and high-LET radiation. The present study aims to rigorously investigate a relative biological effectiveness (RBE) factor by leveraging the HCC tumor data from Weil et al. 2009, Weil et al. 2014, and Edmundson et al. 2020. The three experiments were similarly designed, allowing the raw data to be combined into a pooled dataset to estimate excess relative risk (ERR) and excess absolute risk (EAR) models using Bayesian Poisson regression. These effect estimates from the pooled data provide greater power to calculate a data driven RBE. Extensive sensitivity analyses test the robustness of RBE estimates to various model assumptions. The following questions will be explored through the sensitivity analyses: • Is the shape of the dose response different for low-LET radiation and HZE radiation, indicating that RBE is a function of dose? • Does attained age modify the effect estimates differently for low-LET radiation and HZE radiation, indicating RBE is a function of attained age? • Are the effect estimates and RBE estimates different for inbred mouse strains and outbred mouse strains? • Do assumptions about differences in ERR models and EAR models change the estimated RBE? Additional studies would be needed to validate the findings from these exploratory analyses.

Lori J. Chappell↗

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to three combined HZE-irradiated mouse datasets

Radiation health risks are predominantly derived from low linear energy transfer (LET) terrestrial exposures; however, space radiation includes exposure to high-LET and high-charge, high-energy (HZE) particles. Accurately quantifying the differences in radiation quality between the space and terrestrial radiation environments is important for assessing and predicting health risks for astronauts. Weil et al. 2009 and 2014 used two different inbred mouse strains to study differences in hepatocellular carcinoma (HCC) tumorigenesis after exposures to low- and high- LET radiation[1-2]. More recently, Edmondson et al. 2020 provided valuable new tumor data in outbred mice that were exposed to low- and high-LET radiation[3]. The present study aims to rigorously investigate a relative biological effectiveness (RBE) factor by leveraging the HCC tumor data from the three datasets[1-3]. The three experiments were similarly designed, allowing the raw data to be combined into a pooled dataset to estimate excess relative risk (ERR) and excess absolute risk (EAR) models using Bayesian Poisson regression.

Lori J. Chappell↗

Overview of the NASA Earth Action Strategies Wildland Fire Initiative

As part of NASA’s new Earth Action strategy, the Wildland Fire initiative was established, which includes both the NASA Wildland Fire Program (WFP) and the FireSense project. NASA has over 50 years of experience generating data and technology to enhance fire science and operational management. The WFP’s mission is threefold: 1) assemble communities of practice through collaborative efforts with government, academia, and the private sector; 2) co-develop knowledge and applications with relevant partners and stakeholders in the wildfire community; and 3) improve wildland fire management through the transitioning of NASA data, technology, tools, and science to stakeholder organizations. The WFP is focusing on supporting proactive fire management, including situational awareness, preparedness, and risk mitigation. This will be accomplished through selected projects that identify management challenges, relevant to partners and end users, and the NASA data that will be utilized to deliver innovative solutions to enhance the management of wildland fires. Examples include: i) investigation of evaporative stress from OpenET to help predict the risk of wildfire occurrence in watersheds; ii) incorporation of space based LiDAR for the generation of 3-dimensional forest fuel metrics, used to improve wildfire risk and behavior models; iii) integration of global, multi-platform geostationary active-fire data in near-real-time into NASA’s Fire Information for Resource Management System (FIRMS); and iv) identification of post-fire ecohydrological conditions using thermal, multispectral, synthetic aperture radar (SAR), and hyperspectral remotely-sensed data to improve flood hazard forecast models. The FireSense project is a US-focused 5-year project that will focus on delivering NASA’s unique Earth science and technological capabilities to operational agencies, striving towards enhancing fire fighting and air quality management. The project will include airborne campaigns and new technology that will likely have global implications. Initial stakeholder engagement led FireSense to focus on four use-cases focused on the characterization and measurement of: (i) pre-fire fuels conditions, (ii) active fire-dynamics; (iii) post-fire impact and threats; and iv) air quality impacts and forecasting, each-developed with identified stakeholders.

Wildland Fire program↗