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Young, M.

Publications and source records attributed to Young, M..

At least 37 records · Page 2
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NASA NTRS2016

Exploration Analysis of Carbon Dioxide Levels and Ultrasound Measures of the Eye During ISS Missions

Enhanced screening for the Visual Impairment/Intracranial Pressure (VIIP) Syndrome, including in-flight ultrasound, was implemented in 2010 to better characterize the changes in vision observed in some long-duration crewmembers. Suggested possible risk factors for VIIP include cardiovascular changes, diet, anatomical and genetic factors, and environmental conditions. As a potent vasodilator, carbon dioxide (CO (sub 2)), which is chronically elevated on the International Space Station (ISS) relative to typical indoor and outdoor ambient levels on Earth, seems a plausible contributor to VIIP. In an effort to understand the possible associations between CO (sub 2) and VIIP, this study analyzes the relationship between ambient CO (sub 2) levels on ISS and ultrasound measures of the eye obtained from ISS fliers. CO (sub 2) measurements will be pulled directly from Operational Data Reduction Complex for the Lab and Node 3 major constituent analyzers (MCAs) on ISS or from sensors located in the European Columbus module, as available. CO (sub 2) measures between ultrasound sessions will be summarized using standard time series class metrics in MATLAB including time-weighted means and variances. Cumulative CO (sub 2) exposure metrics will also be developed. Regression analyses will be used to quantify the relationships between the CO (sub 2) metrics and specific ultrasound measures. Generalized estimating equations will adjust for the repeated measures within individuals. Multiple imputation techniques will be used to adjust for any possible biases in missing data for either CO (sub 2) or ultrasound measures. These analyses will elucidate the possible relationship between CO (sub 2) and changes in vision and also inform future analysis of inflight VIIP data.

Young, M.↗
NASA NTRS2016

Clinical Outcome Metrics for Optimization of Robust Training

Introduction: The emphasis of this research is on the Human Research Program (HRP) Exploration Medical Capability's (ExMC) "Risk of Unacceptable Health and Mission Outcomes Due to Limitations of In-Flight Medical Capabilities." Specifically, this project aims to contribute to the closure of gap ExMC 2.02: We do not know how the inclusion of a physician crew medical officer quantitatively impacts clinical outcomes during exploration missions. The experiments are specifically designed to address clinical outcome differences between physician and non-physician cohorts in both near-term and longer-term (mission impacting) outcomes. Methods: Medical simulations will systematically compare success of individual diagnostic and therapeutic procedure simulations performed by physician and non-physician crew medical officer (CMO) analogs using clearly defined short-term (individual procedure) outcome metrics. In the subsequent step of the project, the procedure simulation outcomes will be used as input to a modified version of the NASA Integrated Medical Model (IMM) to analyze the effect of the outcome (degree of success) of individual procedures (including successful, imperfectly performed, and failed procedures) on overall long-term clinical outcomes and the consequent mission impacts. The procedures to be simulated are endotracheal intubation, fundoscopic examination, kidney/urinary ultrasound, ultrasound-guided intravenous catheter insertion, and a differential diagnosis exercise. Multiple assessment techniques will be used, centered on medical procedure simulation studies occurring at 3, 6, and 12 months after initial training (as depicted in the following flow diagram of the experiment design). Discussion: Analysis of procedure outcomes in the physician and non-physician groups and their subsets (tested at different elapsed times post training) will allow the team to 1) define differences between physician and non-physician CMOs in terms of both procedure performance (pre-IMM analysis) and overall mitigation of the mission medical impact (IMM analysis); 2) refine the procedure outcome and clinical outcome metrics themselves; 3) refine or develop innovative medical training products and solutions to maximize CMO performance; and 4) validate the methods and products of this experiment for operational use in the planning, execution, and quality assurance of the CMO training process The team has finalized training protocols and developed a software training/testing tool in collaboration with Butler Graphics (Detroit, MI). In addition to the "hands on" medical procedure modules, the software includes a differential diagnosis exercise (limited clinical decision support tool) to evaluate the diagnostic skills of participants. Human subject testing will occur over the next year.

Ebert, D.↗
NASA NTRS2016

Exploratory Analysis of Carbon Dioxide Levels and Ultrasound Measures of the Eye During ISS Missions

Carbon dioxide (CO2) levels on ISS have typically averaged 2.3 to 5.3mm Hg, with large fluctuations occurring over periods of hours and days. CO2 has effects on cerebral vascular tone, resulting in vasodilation and alteration of cerebral blood flow(CBF). Increased CBF leads to elevated intracranial pressure(ICP), which is a factor leading to visual disturbance, headaches, and other central nervous system symptoms. Ultrasound of the optic nerve provides a surrogate measurement of ICP. Inflight ultrasounds were implemented as an enhanced screening tool for the Visual Impairment/Intracranial Pressure (VIIP) Syndrome. This analysis examines the relationships between ambient CO2 levels on ISS and ultrasound measures of the eye in an effort to understand how CO2 may be associated with VIIP and to inform future analysis of inflight VIIP data. Results as shown in Figure2, there was a large timeframe where CO2 readings were removed due to sensor fault errors(see Limitations), from June 2011 to January 2012. After extensive cleaning of the CO2 data, metrics for all of the data were calculated (Table2). Preliminary analyses showed possible associations between variability measures of CO2 and AP diameter (Figure3),and average CO2 exposure and ONSD(Figure4). Adjustments for multiple comparisons were not made due to the exploratory nature of the analysis.

Schaefer, C.↗
NASA NTRS2016

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

Probability Theory↗
NASA NTRS2016

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

medical equipment↗
NASA NTRS2016

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

risk assessment↗
NASA NTRS2016

Integrated Mecical Model (IMM) 4.0 Verification and Validation (VV) Testing (HRP IWS 2016)

Timeline, partial treatment, and alternate medications were added to the IMM to improve the fidelity of this model to enhance decision support capabilities. Using standard design reference missions, IMM VV testing compared outputs from the current operational IMM (v3) with those from the model with added functionalities (v4). These new capabilities were examined in a comparative, stepwise approach as follows: a) comparison of the current operational IMM v3 with the enhanced functionality of timeline alone (IMM 4.T), b) comparison of IMM 4.T with the timeline and partial treatment (IMM 4.TPT), and c) comparison of IMM 4.TPT with timeline, partial treatment and alternative medication (IMM 4.0).

risk assessment↗
NASA NTRS2016

Qualitative Validation of the IMM Model for ISS and STS Programs

To validate and further improve the Integrated Medical Model (IMM), medical event data were obtained from 32 ISS and 122 STS person-missions. Using the crew characteristics from these observed missions, IMM v4.0 was used to forecast medical events and medical resource utilization. The IMM medical condition incidence values were compared to the actual observed medical event incidence values, and the IMM forecasted medical resource utilization was compared to actual observed medical resource utilization. Qualitative comparisons of these parameters were conducted for both the ISS and STS programs. The results of these analyses will provide validation of IMM v4.0 and reveal areas of the model requiring adjustments to improve the overall accuracy of IMM outputs. This validation effort should result in enhanced credibility of the IMM and improved confidence in the use of IMM as a decision support tool for human space flight.

risk assessment↗
NASA NTRS2015

Integrated Medical Model (IMM) 4.0 Enhanced Functionalities

The Integrated Medical Model is a probabilistic simulation model that uses input data on 100 medical conditions to simulate expected medical events, the resources required to treat, and the resulting impact to the mission for specific crew and mission characteristics. The newest development version of IMM, IMM v4.0, adds capabilities that remove some of the conservative assumptions that underlie the current operational version, IMM v3. While IMM v3 provides the framework to simulate whether a medical event occurred, IMMv4 also simulates when the event occurred during a mission timeline. This allows for more accurate estimation of mission time lost and resource utilization. In addition to the mission timeline, IMMv4.0 features two enhancements that address IMM v3 assumptions regarding medical event treatment. Medical events in IMMv3 are assigned the untreated outcome if any resource required to treat the event was unavailable. IMMv4 allows for partially treated outcomes that are proportional to the amount of required resources available, thus removing the dichotomous treatment assumption. An additional capability IMMv4 is to use an alternative medical resource when the primary resource assigned to the condition is depleted, more accurately reflecting the real-world system. The additional capabilities defining IMM v4.0the mission timeline, partial treatment, and alternate drug result in more realistic predicted mission outcomes. The primary model outcomes of IMM v4.0 for the ISS6 mission, including mission time lost, probability of evacuation, and probability of loss of crew life, are be compared to those produced by the current operational version of IMM to showcase enhanced prediction capabilities.

Spae Adaptation Syndrome↗
NASA NTRS2015

Integrated Medical Model (IMM) Project Verification, Validation, and Credibility (VVandC)

The Integrated Medical Model (IMM) Project supports end user requests by employing the Integrated Medical Evidence Database (iMED) and IMM tools as well as subject matter expertise within the Project. The iMED houses data used by the IMM. The IMM is designed to forecast relative changes for a specified set of crew health and mission success risk metrics by using a probabilistic model based on historical data, cohort data, and subject matter expert opinion. A stochastic approach is taken because deterministic results would not appropriately reflect the uncertainty in the IMM inputs. Once the IMM was conceptualized, a plan was needed to rigorously assess input information, framework and code, and output results of the IMM, and ensure that end user requests and requirements were considered during all stages of model development and implementation, as well as lay the foundation for external review and application. METHODS: In 2008, the Project team developed a comprehensive verification and validation (VV) plan, which specified internal and external review criteria encompassing 1) verification of data and IMM structure to ensure proper implementation of the IMM, 2) several validation techniques to confirm that the simulation capability of the IMM appropriately represents occurrences and consequences of medical conditions during space missions, and 3) credibility processes to develop user confidence in the information derived from the IMM. When the NASA-STD-7009 (7009) [1] was published, the Project team updated their verification, validation, and credibility (VVC) project plan to meet 7009 requirements and include 7009 tools in reporting VVC status of the IMM. Construction of these tools included meeting documentation and evidence requirements sufficient to meet external review success criteria. RESULTS: IMM Project VVC updates are compiled recurrently and include updates to the 7009 Compliance and Credibility matrices. Reporting tools have evolved over the lifetime of the IMM Project to better communicate VVC status. This has included refining original 7009 methodology with augmentation from the HRP NASA-STD-7009 Guidance Document working group and the NASA-HDBK-7009 [2]. End user requests and requirements are being satisfied as evidenced by ISS Program acceptance of IMM risk forecasts, transition to an operational model and simulation tool, and completion of service requests from a broad end user consortium including operations, science and technology planning, and exploration planning. IMM v4.0 is slated for operational release in the FY015 and current VVC assessments illustrate the expected VVC status prior to the completion of customer lead external review efforts. CONCLUSIONS: The VVC approach established by the IMM Project of incorporating Project-specific recommended practices and guidelines for implementing the 7009 requirements is comprehensive and includes the involvement of end users at every stage in IMM evolution. Methods and techniques used to quantify the VVC status of the IMM Project represented a critical communication tool in providing clear and concise suitability assessments to IMM customers. These processes have not only received approval from the local NASA community but have also garnered recognition by other federal agencies seeking to develop similar guidelines in the medical modeling community.

Walton, M.↗
NASA NTRS2015

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Credibility↗
NASA NTRS2013

Measurements of C02 Distribution in Saturn's Atmosphere by Cassini-Infrared Observations

The Fourier transform infrared spectrometer aboard the Cassini spacecraft, inserted in Saturn s orbit in July 2004, has been providing high resolution/high sensitivity infrared (IR) spectra of the Saturnian system. The measurements cover the spectral range of 10-1400/cm with variable spectral resolutions of 0.53 to 15/cm, exhibiting spectral features of a series of trace gases including CO2 and H2O. The observed spectra may be analyzed for retrieval of global P/T and gas density profiles of Saturn. The infrared measurements of Saturn by ISO(SWS) have indicated unexpected large abundances of CO2 in Saturn's atmosphere. The rigorous photochemical models of Saturn's atmosphere that have been developed indicate exogenic oxygen influx of icy dust grains that lead to the production of CO2. The distribution of CO2 in Saturn's atmosphere needs to be confirmed, and the nature of exogenic sources remains to be investigated. This paper presents comprehensive measurements of the CO2 distribution in Saturn's atmosphere by Cassini IR observations.

Abbas, M. M.↗
NASA NTRS2012

Variability Selected Low-Luminosity Active Galactic Nuclei in the 4 Ms Chandra Deep Field-South

The 4 Ms Chandra Deep Field-South (CDF-S) and other deep X-ray surveys have been highly effective at selecting active galactic nuclei (AGN). However, cosmologically distant low-luminosity AGN (LLAGN) have remained a challenge to identify due to significant contribution from the host galaxy. We identify long-term X ray variability (approx. month years, observed frame) in 20 of 92 CDF-S galaxies spanning redshifts approx equals 00.8 - 1.02 that do not meet other AGN selection criteria. We show that the observed variability cannot be explained by X-ray binary populations or ultraluminous X-ray sources, so the variability is most likely caused by accretion onto a supermassive black hole. The variable galaxies are not heavily obscured in general, with a stacked effective power-law photon index of Gamma(sub Stack) approx equals 1.93 +/- 0.13, and arc therefore likely LLAGN. The LLAGN tend to lie it factor of approx equal 6-89 below the extrapolated linear variability-luminosity relation measured for luminous AGN. This may he explained by their lower accretion rates. Variability-independent black-hole mass and accretion-rate estimates for variable galaxies show that they sample a significantly different black hole mass-accretion-rate space, with masses a factor of 2.4 lower and accretion rates a factor of 22.5 lower than variable luminous AGNs at the same redshift. We find that an empirical model based on a universal broken power-law power spectral density function, where the break frequency depends on SMBH mass and accretion rate, roughly reproduces the shape, but not the normalization, of the variability-luminosity trends measured for variable galaxies and more luminous AGNs.

Young, M.↗
NASA NTRS2010

Saturn's Atmospheric Composition from Observations by the Cassini/Composite Infrared Spectrometer

Thermal emission infrared observation of Saturn s atmosphere are being made by the Composite Infrared Spectrometer (CIRS) aboard the Cassini spacecraft since its insertion in Saturn s orbit on July 2nd, 2004. The measurements made in both limb and nadir modes of observations consist of infrared spectra in the 10-1400/cm region with a variable spectral resolution of 0.53/cm and 2.8/cm, and exhibit rotational and vibrational spectral features that may be analyzed for retrieval of the thermal structure and constituent distribution of Saturn s atmosphere. In this paper, we present a comprehensive analysis of the CIRS infrared observed spectra for retrieval of Saturn s atmospheric composition focusing on the distributions of some selected hydrocarbons, phosphine, ammonia, and possible determination of the isotopic ratios of some species with sufficiently strong isolated spectral features. A comparison of the retrieved constituent distributions with the available data in the literature will be made.

Abbas, M. M.↗
NASA NTRS2003

JPL update

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FFRDC library records archives↗