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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

Machine Learning Prototype App For Recognition of Fruits

As the incidence of obesity and associated negative health consequences is rising, it becomes crucial to monitor the dietary choices of individuals. Unfortunately, traditional methods to collect this information involve collecting food frequency questionnaires from individuals using paper. Electronic food trackers have been developed to collect food data, but they require participants to manually label and describe the content of their meals, and which may be difficult for researchers to interpret in a standardized fashion. Machine learning, however, provides an easy and efficient method for both participants and researchers to label food items with standardized descriptions. This project aims to create a prototype phone application that can identify and label photos of apples. This is done by making a machine learning model through Turicreate, a python module, which is then implemented into an iOS app through Xcode and Swift. The modules used in Swift include CoreML and AVFoundation. This machine learning application will be incorporated with a MealLogger phone app that is also under development. The MealLogger app will be used to keep track of participants' calorie intake and other personal details throughout the sleep study. The machine learning model will present several potential identities of the foods found in the photo, and the user will only need to select the correct option. This will be a user-friendly method for participants to easily log their food consumption without the hard work of manually inputting each and every description. Some limitations to this project include the wide variety of food, including those within different cultures. To deal with this, the model will include the most generic food categories, which the participant may select, and produce a drop-down menu of more specific dishes under that specified category, with the option of self-input. Additional questionnaires may be implemented according to the food type selected This will allow the process to be quick and easy, but also specific for the purpose of analysis. The release of the application will require a much longer process, but the machine learning prototype presents a first step toward an application that may change data analysis for researchers interested in collecting food intake from individuals living in the real world.

Food tracker↗
NASA NTRSDate not supplied

Caffeine Consumption Aboard the International Space Station

INTRODUCTION: Caffeine is the most widely used performance-enhancing drug on Earth and astronaut crews have access to liquid coffee. While caffeine is a potent countermeasure to improve alertness and performance, it can also interfere with sleep. This can lead to performance deficits on the following day, driving a cycle of caffeine use to counter the effects of caffeine-induced sleep disruption. Caffeine availability may be limited during future Artemis and/or Mars missions. Accordingly, it is important that we 1) determine the prevalence of caffeine use among astronauts, 2) characterize the impact of caffeine on performance, and 3) characterize the impact of caffeine on sleep. Our aim in this study is to describe the use of caffeine aboard the ISS and begin to examine the relationship between caffeine use and sleep and performance outcomes. METHODS: Daily caffeine consumption was determined from food and beverage intake tracking for 25 astronauts on 6 month International Space Station (ISS) missions. Data were recorded using the ISS Food Intake Tracker iPad App or other detailed recording technique. On average, crew recorded dietary intake on 179.7±68.6 (mean±SD) days inflight. RESULTS: Astronauts consumed 97±92 mg caffeine per day. All astronauts (25/25) in this study consumed caffeine at some point during flight, though the frequency, amounts, and regularity differed across crewmembers. Approximately a quarter of crewmembers were regular caffeine consumers (6/25), i.e., they ingested at least 90 mg caffeine (equivalent to one cup of coffee) on 90% of inflight days.

fatigue↗
NASA NTRS2006

Novel Concept for LSS Based on Advanced Microalgal Biotechnologies

One of the key issues for successful human space exploration is biomedical life support in hostile space and planetary environments that otherwise cannot sustain life. Bioregenerative life support systems (LSS) are one of the options for atmospheric regeneration. To date, no bioregenerative LSS has shown capability for 100% air regeneration. Nor have these LSS been robust enough to simultaneously provide a regenerable complete food source. In contrast to microalgae, traditional plant approaches, e.g. wheat and lettuce, are lacking essential amino acids, vitamins, and micronutrients. Moreover, the rate of photosynthesis by microalgae significantly exceeds that of high plants. Nevertheless, the employment of microalgae in LSS technology was restricted, until recently, due to high water demands. Also the per person requirement of a 40L volume of microalgae in a photobioreactor, to provide daily O2 production, made an algae-based approach less attractive. By employing a vertically stacked membrane bioreactor, coupled with a solar tracker and photon-delivery system, a lightweight air revitalization system for space based applications, with minimal water requirements, can be developed. Our preliminary estimations suggest that a membrane bioreactor, 8m3 in volume, comprised of 80m2 (twenty 2m x 2m membranes, each spaced 10 cm apart), and a total of 70L of water could produce 2.7 kg of dried microalgal biomass that would supply the energy and essential amino acid requirements, as well as producing sufficient O2 for the daily needs of a 15 member crew. Research on the biochemical content of edible blue-green alga Spirulina (Arthrospira) platensis shows a wide spectrum of stable Spirulina mutants with an enhanced content of amino acids, -carotene, and phycobilliprotein c-phycocyanin. Feeding animals suffering from radiation-induced lesions, c-phycocyanin, extracted from strain 27G, led to a correction in the decrement of dehydrogenase activity and energy-rich phosphate levels, as well as improved antioxidant defense and pyruvate levels, compared to untreated animals. Experimental anemia in rats was corrected by feeding Spirulina platensis strains 198B and 27G, (with an enhanced content of methionine, phycobiliproteins and carotenoids). Spirulina was recently shown by Ananyev et al, 2005, to be an oxygenic organism with the highest level of photosystem II activity (O2 production). We propose therefore to develop a design for membrane-based photoreactors for Lunar and Mars exploration habitat LSS, for the cultivation of genetically modified strains of Spirulina to scrub CO2 and supply astronauts with O2, protein, vitamins, and immunostimulators.

Brown, I.↗