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A New Machine Learning Based Analysis for Improving Satellite Retrieved Atmospheric Composition Data: OMI SO2 as an Example

Despite recent progress, satellite retrievals of anthropogenic SO2 still suffer from relatively low signal-tonoise ratios. In this study, we demonstrate a new machine learning data analysis method to improve the quality of satellite SO2 products. In the absence of large ground-truth datasets for SO2, we start from SO2 slant column densities (SCDs) retrieved from the Ozone Monitoring Instrument (OMI) using a data-driven, physically based algorithm and calculate the ratio between the SCD and the root mean square (rms) of the fitting residuals for each pixel. To build the training data, we select presumably clean pixels with small SCD / rms ratios (SRRs) and set their target SCDs to zero. For polluted pixels with relatively large SRRs, we set the target to the original retrieved SCDs. We then train neural networks (NNs) to reproduce the target SCDs using predictors including SRRs for individual pixels, solar zenith, viewing zenith and phase angles, scene reflectivity, and O3 column amounts, as well as the monthly mean SRRs. For data analysis, we employ two NNs: (1) one trained daily to produce analyzed SO2 SCDs for polluted pixels each day and (2) the other trained once every month to produce analyzed SCDs for less polluted pixels for the entire month. Test results for 2005 show that our method can significantly reduce noise and artifacts over background regions. Over polluted areas, the monthly mean NN-analyzed and original SCDs generally agree to within ±15 %, indicating that our method can retain SO2 signals in the original retrievals except for large volcanic eruptions. This is further confirmed by running both the NN-analyzed and original SCDs through a topdown emission algorithm to estimate the annual SO2 emissions for ∼ 500 anthropogenic sources, with the two datasets yielding similar results. We also explore two alternative approaches to the NN-based analysis method. In one, we employ a simple linear interpolation model to analyze the original SCD retrievals. In the other, we develop a PCA–NN algorithm that uses OMI measured radiances, transformed and dimension-reduced with a principal component analysis (PCA) technique, as inputs to NNs for SO2 SCD retrievals. While the linear model and the PCA–NN algorithm can reduce retrieval noise, they both underestimate SO2 over polluted areas. Overall, the results presented here demonstrate that our new data analysis method can significantly improve the quality of existing OMI SO2 retrievals. The method can potentially be adapted for other sensors and/or species and enhance the value of satellite data in air quality research and applications.

Can Li↗

Lana chimpanzee learns to count by 'numath' - A summary of a videotaped experimental report

Computerized training programs whereby an adult female chimpanzee learned to use a joystick to remove from a screen the number of boxes appropriate to the value of a randomly selected Arabic numeral 1, 2, or 3, are studied. Initial training provided a variety of cues, both numeric and otherwise, to support correct performance. In the final test, the ape was correct on over 80 percent of trials in which there was no residual feedback of intratrial events and where only her memory of those events could provide the cue to indicate that she had removed boxes in accordance with the value of the target numbers and should terminate the trial.

Rumbaugh, Duane M.↗

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

On compositional variations among lunar anorthosites

Ferroan anorthosite (FAN) is the most abundant 'pristine' highlands igneous rock in the Apollo sample collection. The presence of substantial FAN in the lunar crust is one argument used in favor of a global magma ocean on which crystallizing plagioclase could float. Information about the composition of the proposed magma ocean or whatever liquids might have been parental to FAN is sparse. As a first step toward learning about the nature of the FAN parent and the processes by which FAN attained its compositional characteristics, attention is given to the concentrations for a number of major and trace elements whose behavior during magmatic processes is somewhat understood. Serious difficulties are found with both FAN and the Marcy anorthosite in interpreting incompatible trace element concentrations in the plagioclases or the whole rocks in terms of residues from parent liquids. A description is presented of the nature of these difficulties.

Haskin, L. A.↗

Lessons Learned from OSIRIS-Rex Autonomous Navigation Using Natural Feature Tracking

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (Osiris-REx) spacecraft is scheduled to launch in September, 2016 to embark on an asteroid sample return mission. It is expected to rendezvous with the asteroid, Bennu, navigate to the surface, collect a sample (July 20), and return the sample to Earth (September 23). The original mission design called for using one of two Flash Lidar units to provide autonomous navigation to the surface. Following Preliminary design and initial development of the Lidars, reliability issues with the hardware and test program prompted the project to begin development of an alternative navigation technique to be used as a backup to the Lidar. At the critical design review, Natural Feature Tracking (NFT) was added to the mission. NFT is an onboard optical navigation system that compares observed images to a set of asteroid terrain models which are rendered in real-time from a catalog stored in memory on the flight computer. Onboard knowledge of the spacecraft state is then updated by a Kalman filter using the measured residuals between the rendered reference images and the actual observed images. The asteroid terrain models used by NFT are built from a shape model generated from observations collected during earlier phases of the mission and include both terrain shape and albedo information about the asteroid surface. As a result, the success of NFT is highly dependent on selecting a set of topographic features that can be both identified during descent as well as reliably rendered using the shape model data available. During development, the OSIRIS-REx team faced significant challenges in developing a process conducive to robust operation. This was especially true for terrain models to be used as the spacecraft gets close to the asteroid and higher fidelity models are required for reliable image correlation. This paper will present some of the challenges and lessons learned from the development of the NFT system which includes not just the flight hardware and software but the development of the terrain models used to generate the onboard rendered images.

Navigation↗

Developing Formal Correctness Properties from Natural Language Requirements

This viewgraph presentation reviews the rationale of the program to transform natural language specifications into formal notation.Specifically, automate generation of Linear Temporal Logic (LTL)correctness properties from natural language temporal specifications. There are several reasons for this approach (1) Model-based techniques becoming more widely accepted, (2) Analytical verification techniques (e.g., model checking, theorem proving) significantly more effective at detecting types of specification design errors (e.g., race conditions, deadlock) than manual inspection, (3) Many requirements still written in natural language, which results in a high learning curve for specification languages, associated tools and increased schedule and budget pressure on projects reduce training opportunities for engineers, and (4) Formulation of correctness properties for system models can be a difficult problem. This has relevance to NASA in that it would simplify development of formal correctness properties, lead to more widespread use of model-based specification, design techniques, assist in earlier identification of defects and reduce residual defect content for space mission software systems. The presentation also discusses: potential applications, accomplishments and/or technological transfer potential and the next steps.

requirements engineering↗

The IRAC Shutter Mechanism: Residual Magnetism and the Rotary Solenoid

The Infrared Array Camera (IRAC) Shutter mechanism was originally presented in the paper, 'A Low Power Cryogenic Shutter Mechanism for Use on Infrared Imagers' at the 34th Aerospace Mechanisms Symposium, May 2000. At that time, the shutter was believed to be performing flawlessly and there was every indication it would continue to do so. In early spring of 2001, the calibration shutter, a rotary solenoid designed to be fail-safe open, remained in a closed state with no power to the electromagnetic coils. The ensuing investigation, subsequent testing, proposed remedy, and lessons learned are the focus of this paper.

Schwinger, Scott↗

Microbial Monitoring of the International Space Station

Humans living and working in the harsh environment of space present many challenges for habitability engineers and microbiologists. Spacecraft must provide an internal environment in which physical (gas composition, pressure, temperature, and humidity), chemical, and biological environmental parameters are maintained at safe levels. Microorganisms are ubiquitous and will accompany all human-occupied spacecraft, but if biological contamination were to reach unacceptable levels, long-term human space flight would be impossible. Prevention of microbiological problems, therefore, must have a high priority. Historically, prevention of infectious disease in the crew has been the highest priority, but experience gained from the NASA-Mir program showed that microbial contamination of vehicle and life-support systems, such as biofouling of water and food, are of equal importance. The major sources of microbiological risk factors for astronauts include food, drinking water, air, surfaces, payloads, research animals, crew members, and personnel in close contact with the astronauts. In our efforts to eliminate or mitigate the negative effects of microorganisms in spacecraft, the National Aeronautics and Space Administration (NASA) implemented comprehensive microbial analyses of the major risk factors. This included the establishment of acceptability requirements for food, water, air, surfaces, and crew members. A robust monitoring program was then implemented to verify that the risks were within acceptable limits. Prevention of microbiological problems is preferred over mitigation of problems during flight, and preventive steps must begin very early in the design phase. Spacecraft development must include requirements to control free water from humidity, condensate, hygiene activities, and other releases. If water is available, microbes are likely to grow because sufficient nutrients are potentially available. Materials selected for the spacecraft must not promote or support microbial growth. Air filtration can dramatically reduce the number of airborne bacteria, fungi, and particulates in spacecraft breathing air. Waterborne bacteria can be reduced to acceptable levels by thermal inactivation of bacteria during water processing, along with a residual biocide, and filtration at the point of use can ensure safety. System design must include onboard capability to achieve recovery of the system from contamination. Robust housekeeping procedures that include periodic cleaning and disinfection will prevent high levels of microbial growth on surfaces. Food for consumption in space must be thoroughly tested for excessive microbial content and pathogens before launch. Thorough preflight examination of flight crews, consumables, payloads, and the environment can greatly reduce pathogens in spacecraft. Many of the lessons learned from the Space Shuttle and previous programs were applied in the early design phase of the International Space Station, resulting in the safest space habitat to date. This presentation describes the monitoring program for the International Space Station and will summarize results from preflight and on-orbit monitoring.

Pierson, Duane L.↗

GOES-17 Magnetometer On-Orbit Calibration Design and Results

The Geostationary Operational Environmental Satellite-R (GOES-R) is a series of four NOAA weather satellites. Each spacecraft flies a Magnetometer instrument which includes two boom mounted fluxgate sensors located 6.3 and 8.5 meters from the spacecraft. Sensor readings are corrupted by both internal (bias and scale factor) and external (spacecraft emitted fields and misalignments) error sources. In order to estimate the bias, an on-orbit calibration is performed, slewing the spacecraft about multiple axes and then performing a fit of the data to determine zero offset and misalignment terms. The first satellite in the series, GOES-16 was launched in November 2016. Its magnetometer calibration maneuver was found to be inadequate providing insufficient rotation about orthogonal axes. The uncertainty in the estimated biases was found to be in the 3-5 nanotesla range, exceeding the magnetometer accuracy requirement of 1.0 nanotesla. Based on lessons learned, the maneuver was redesigned to provide multiple 360 degree rotations about two orthogonal axes, providing optimal visibility into bias and misalignment. Varying ambient fields over the duration of the calibration maneuvers, corrupts the ability to accurately determine parameters of interest. To address this issue, rather than assuming a constant field for the duration of the maneuver, a non-linear least squares filter was employed that uses a series of spline functions to better fit the ambient field. The number of splines can be varied to minimize the least squares filter residuals. Simulations were performed using 360 days of GOES-16 data to bound the uncertainty in the biases for given residuals of the fit to the ambient field. Following the launch of the second satellite in the series, GOES-17 in March 2018, the new calibration maneuver and enhanced bias estimation algorithm were exercised twice. Based on the residuals of the fit, the uncertainty of the estimated zero offset was reduced by an order of magnitude from 3-5 nanotesla to approximately 0.4 nanotesla per axis. This paper provides details of the maneuver design and the innovative algorithm used to estimate the GOES-17 biases and misalignments.

GOES-17↗

Metal Cutting Theory and Friction Stir Welding Tool Design

Friction Stir Welding (FSW) is a relatively new industrial process that was invented at The Weld Institute (TWI, United Kingdom) and patented in 1992 under research funded by in part by the National Aeronautics and Space Administration (NASA). Often quoted advantages of the process include good strength and ductility along with minimization of residual stress and distortion. Less well advertised are the beneficial effects of this solid state welding process in the field of occupational and environmental safety. It produces superior weld products in difficult to weld materials without producing any toxic fumes or solid waste that must be controlled as hazardous waste. In fact, it reduces noise pollution in the workspace as well. In the early days of FSW, most welding was performed on modified machine tools, in particular on milling machines with modified milling cutters. In spite of the obvious milling heritage of the process, the techniques and lessons learned from almost 250 years of successful metalworking with milling machines have not been applied in the field of modern Friction Stir Welding. The goal of the current research was to study currently successful FSW tools and parameterize the process in such a way that the design of new tools for new materials could be accelerated. Along the way, several successful new tooling designs were developed for current issues at the Marshall Space Flight Center with accompanying patent disclosures

Payton, Lewis N.↗

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗

Residual Gas Effects on Detached Solidification in Microgravity

Many microgravity directional solidification experiments yielded ingots with portions that grew without contacting the ampoule wall, leading to greatly improved crystallographic perfection. Our long-term goal is to make such detached solidification reproducible, which requires a full understanding of the mechanisms underlying it. Our Moving Meniscus Model of steady-state detachment predicts that it depends strongly on the surface tension of the melt and the advancing contact angle with the ampoule wall. Detached solidification is more likely when the contact angle for the melt on the ampoule wall is high, i.e. non-wetting. It has been claimed that impurities increase the contact angle. The objective of the current project is to determine the influence of residual gases on the surface tension and contact angle of molten semiconductors on typical ampoule materials. We are focusing on determining the influence of oxygen on the contact angle of molten InSb on clean silica ('quartz'), including the advancing and retreating contact angles in addition to the usual equilibrium contact angle. We have created a gas flow system that allows us to control the oxygen partial pressure over a sessile drop of InSb on a horizontal quartz surface. The cell is slowly tilted while videotaping to reveal the contact angles on the two sides of the drop just prior to it rolling down the surface. Thus far, we have learned the following: (1) Molten InSb readily forms an oxide layer in the presence of the trace amounts of oxygen found in high purity argon; (2) This oxide contains a substantial amount of Ga, which presumably is a trace contaminant that is not detectable in the starting material; (3) The addition of 10% hydrogen to the argon gas is sufficient to reduce the oxide and produce a clean drop; (4) An infrared filter must precede the video camera in order to produce a sharp image of the drop for later image analysis; (5) Tilting the surface on which the drop rests causes the two sides of the drop to display different contact angles, reflecting contact line sticking; (6) Vibration strongly accelerates the approach of the drop to its final shape on a horizontal surface by helping to overcome sticking of the contact line; (7) Oscillation of the drop surface due to vibration appears to increase as the surface is inclined from horizontal. Presumably, the angle at which the drop rolls down the surface is also reduced by vibration. This observation is particularly significant, as the meniscus must move along the ampoule wall during detached solidification.

Regel, Liya L.↗

Precision Agriculture: Changing the Face of Farming

To a large extent our work has grown out of the remote sensing technology and conceptual framework developed by geologists. For example the drive to look at the physics of reflectance and atmospheric corrections is rooted in work done in the early 1980s by the United States Geological Survey and NASA. Our work on emissivity and thermal behavior of plants pulls on research done using the Thermal Infrared Multispectral Scanner, an instrument originally conceived for geologic applications. Even our ability to geometrically map the airborne imagery onto the globe was explicitly developed because of need to map sediment flow patterns in along the coast of Louisiana. Growing from this base we have learned much in the last few years and believe our integration of geologic remote sensing with the other fields of expertise was a wise investment. Clearly none of the specialties alone could develop, let alone test, the basic approach we are now finding so powerful. This is the path that will ultimately give the information needed by the farmer. We also recognize how small a portion of the total problem has been solved. Having developed the basic logic, built proto-type tools and performed initial tests everything else remains to be done. And problems, scientific and practical, are everywhere. We have not established sensitivities. We have not robustly segregated the contributions of crop residue, soil moisture, shadows, plant and soil to the energy leaving the surface. What we do is extremely expensive and difficult. It is experimental in methodology and uses research oriented tools. We are constantly alive to the practicality of moving our results into commercial applications. We know another airborne instrument will have to be available. Atmospheric parameters will have to be measured automatically. The software will have to be re-written for speed. At times the list of problems seems endless. But the potential is also enormous. Agriculture is a huge portion of our economy. Just a one percent increase in efficiency is a $2,000,000 change. We all depend on farmers, literally for the bread we eat. No other activity of man even has an impact on the land that farming has. If application of precision agriculture can nelp farmers manage their land better, we all may benefit.

Rickman, D.↗

Lessons Learned from the AIRS Pre-Flight Radiometric Calibration

The Atmospheric Infrared Sounder (AIRS) instrument flies on the NASA Aqua satellite and measures the upwelling hyperspectral earth radiance in the spectral range of 3.7-15.4 micron with a nominal ground resolution at nadir of 13.5 km. The AIRS spectra are achieved using a temperature controlled grating spectrometer and HgCdTe infrared linear arrays providing 2378 channels with a nominal spectral resolution of approximately 1200. The AIRS pre-flight tests that impact the radiometric calibration include a full system radiometric response (linearity), polarization response, and response vs scan angle (RVS). We re-derive the AIRS instrument radiometric calibration coefficients from the pre-flight polarization measurements, the response vs scan (RVS) angle tests as well as the linearity tests, and a recent lunar roll test that allowed the AIRS to view the moon. The data and method for deriving the coefficients is discussed in detail and the resulting values compared amongst the different tests. Finally, we examine the residual errors in the reconstruction of the external calibrator blackbody radiances and the efficacy of a new radiometric uncertainty model. Results show the radiometric calibration of AIRS to be excellent and the radiometric uncertainty model does a reasonable job of characterizing the errors.

Sounder↗

Close binding of identity and location in visual feature perception

The binding of identity and location information in disjunctive feature search was studied. Ss searched a heterogeneous display for a color or a form target, and reported both target identity and location. To avoid better than chance guessing of target identity (by choosing the target less likely to have been seen), the difficulty of the two targets was equalized adaptively; a mathematical model was used to quantify residual effects. A spatial layout was used that minimized postperceptual errors in reporting location. Results showed strong binding of identity and location perception. After correction for guessing, no perception of identity without location was found. A weak trend was found for accurate perception of target location without identity. We propose that activated features generate attention-calling "interrupt" signals, specifying only location; attention then retrieves the properties at that location.

Orientation↗

Protecting Neural Structures and Cognitive Function During Prolonged Space Flight by Targeting the Brain Derived Neurotrophic Factor Molecular Network

Brain derived neurotrophic factor (BDNF) is the main activity-dependent neurotrophin in the human nervous system. BDNF is implicated in production of new neurons from dentate gyrus stem cells (hippocampal neurogenesis), synapse formation, sprouting of new axons, growth of new axons, sprouting of new dendrites, and neuron survival. Alterations in the amount or activity of BDNF can produce significant detrimental changes to cortical function and synaptic transmission in the human brain. This can result in glial and neuronal dysfunction, which may contribute to a range of clinical conditions, spanning a number of learning, behavioral, and neurological disorders. There is an extensive body of work surrounding the BDNF molecular network, including BDNF gene polymorphisms, methylated BDNF gene promoters, multiple gene transcripts, varied BDNF functional proteins, and different BDNF receptors (whose activation differentially drive the neuron to neurogenesis or apoptosis). BDNF is also closely linked to mitochondrial biogenesis through PGC-1alpha, which can influence brain and muscle metabolic efficiency. BDNF AS A HUMAN SPACE FLIGHT COUNTERMEASURE TARGET Earth-based studies reveal that BDNF is negatively impacted by many of the conditions encountered in the space environment, including oxidative stress, radiation, psychological stressors, sleep deprivation, and many others. A growing body of work suggests that the BDNF network is responsive to a range of diet, nutrition, exercise, drug, and other types of influences. This section explores the BDNF network in the context of 1) protecting the brain and nervous system in the space environment, 2) optimizing neurobehavioral performance in space, and 3) reducing the residual effects of space flight on the nervous system on return to Earth

Schmidt, M. A.↗

Next Generation Microbiology Requirements

As humans continue to explore deep into space, microorganisms will travel with them. The primary means to mitigate the risk of infectious disease are a combination of prudent spacecraft design and rigorous operational controls. The effectiveness of these methods are evaluated by microbiological monitoring of spacecraft, food, water, and the crew that is performed preflight, in-flight, and post-flight. Current NASA requirements associated with microbiological monitoring are based on culture-based methodology where microorganisms are grown on a semi-solid growth medium and enumerated. Subsequent identification of the organisms requires specialized labor and large equipment, which historically has been performed on Earth. Requirements that rely strictly on culture-based units limit the use of non-culture based monitoring technology. Specifically, the culture-based "measurement criteria" are Colony Forming Units (CFU, representing the growth of one microorganism at a single location on the agar medium) per a given volume, area, or sample size. As the CFU unit by definition is culture-based, these requirements limit alternative technologies for spaceflight applications. As spaceflight missions such as those to Mars extend further into space, culture-based technology will become difficult to implement due to the (a) limited shelf life of the culture media, (b) mass/volume necessary to carry these consumables, and (c) problems associated with the production of biohazardous material in the habitable volume of the spacecraft. In addition, an extensive amount of new knowledge has been obtained during the Space Shuttle, NASA-Mir, and International Space Station Programs, which gave direction for new or modified microbial control requirements for vehicle design and mission operations. The goal of this task is to develop and recommend a new set of requirements for vehicle design and mission operations, including microbiological monitoring, based upon "lessons learned" and new technology. During 2011, this study focused on evaluating potable water requirements by assembling a forum of internal and external experts from NASA, other federal agencies, and academia. Key findings from this forum included: (1) Preventive design and operational strategies should be stringent and the primary focus of NASA's mitigation efforts, as they are cost effective and can be attained with conventional technology. (2) Microbial monitoring hardware should be simple and must be able to measure the viability of microorganisms in a sample. Multiple monitoring technologies can be utilized as long as at the microorganisms being identified can also be confirmed as viable. (3) Evidence showing alterations in the crew immune function and microbial virulence complicates risk assessments and creates the need for very conservative requirements. (4) One key source of infectious agents will always be the crew, and appropriate preventative measures should be taken preflight. (5) Water systems should be thoroughly disinfected (sterilized if possible) preflight and retain a residual biocide throughout the mission. Future forums will cover requirements for other types of samples, specifically spaceflight food and environmental samples, such as vehicle air and vehicle and cargo surfaces. An interim report on the potable water forum has been delivered to the Human Research Program with a final report on the recommendations for all sample types being delivered in September 2013.

Ott, C. M.↗