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At least 55 records · Page 3

Exercise Training During Bed Rest Attenuates Deconditioning

A 30-day 6 deg. head-down bed rest study was conducted to evaluate high-intensity, short-duration, alternating isotonic cycle ergometer exercise (ITE) training and high-intensity intermittent isokinetic exercise (IKE) training regiments designed to maintain peak VO2 and muscle mass, strength, and endurance at ambulatory control levels throughout prolonged bed rest. Other elements of the deconditioning (acclimation) syndrome, such as proprioception, psychological performance, hypovolemia, water balance, body composition, and orthostatic tolerance, were also measured. Compared with response during bed rest of the no exercise (NOE) control group: the ITE training regimen (a) maintained work capacity (peak VO2), (b) maintained plasma and red cell volume, (c) induced positive body water balance, (d) decreased quality of sleep and mental concentration, and (e) had no effect on the decrease in orthostatic tolerance; the IKE training regimen (a) attenuated the decrease in peak VO2 by 50%, (b) attenuated loss of red cell volume by 40%, but had no effect on loss of plasma volume, (c) induced positive body water balance, (d) had no adverse effect on quality of sleep or concentration, and (e) had no effect on the decrease in orthostatic tolerance. These findings suggest that various elements of the deconditioning syndrome can be manipulated by duration and intensity of ITE or IKE training regiments, and that several different training protocols will be required to maintain or restore physiological and psychological performance of individuals confined to prolonged bed rest.

Greenleaf, J. E.↗

The effect of wave breaking on wave spectrum in water of finite depth

An approximate method is devised to compute the energy-containing portion of the spectrum of waves in water of finite depth, taking into account the effect of wave breaking. It is assumed that there exists a linear and Gaussian ideal wave train whose spectrum is first calculated using the wave energy flux balance equation without considering wave breaking. The Miche wave-breaking criterion for waves in water of finite depth is then applied to limit the wave elevation and establish an expression for the breaking wave elevation in terms of the elevation and elevation's second time derivative of the ideal waves. Simple expressions for the mean value, the mean square value, and the spectrum of the breaking waves are then obtained, and numerical results are presented graphically.

Tung, C. C.↗

Intensive Exercise Training During Bed Rest Attenuates Deconditioning

Intensive exercise training during bed rest attenuates deconditioning. Med. Sci. Sports Exerc., Vol. 29, No. 2, pp. 207-215, 1997. A 30-d 6 deg head-down bed rest project was conducted to evaluate variable high-intensity, short-duration, isotonic cycle ergometer exercise (ITE) training and high-intensity intermittent resistive isokinetic exercise (IKE) training regimens designed to maintain peak VO2 and muscle mass, strength, and endurance at ambulatory control levels throughout prolonged bed rest. Other elements of the deconditioning (adaptive) syndrome, such as proprioception, psychological performance, hypovolemia, water balance, body composition, and orthostatic tolerance, were also measured. Major findings are summarized in this paper. Compared with response during bed rest of the no exercise (NOE) control group: the ITE training regimen (a) maintained work capacity (peak VO2), (b) maintained plasma and red cell volumes, (c) induced positive body water balance, (d) decreased quality of sleep and mental concentration, and (e) had no effect on the decrease in orthostatic tolerance; the IKE training regimen (f) attenuated the decrease in peak VO2 by 50%, (g) attenuated loss of red cell volume by 40% but had no effect on loss of plasma volume, (b) induced positive body water balance, (i) had no adverse effect on quality of sleep or concentration, and 0) had no effect on the decrease in orthostatic tolerance. These findings suggest that various elements of the deconditioning syndrome can be manipulated by duration and intensity of ITE or IKE training regimens and that several different training protocols will be required to maintain or restore physiological and psychological performance of individuals confined to prolonged bed rest.

Greenleaf, John E.↗

Balance System

TherEx Inc.'s AT-1 Computerized Ataxiameter precisely evaluates posture and balance disturbances that commonly accompany neurological and musculoskeletal disorders. Complete system includes two-strain gauged footplates, signal conditioning circuitry, a computer monitor, printer and a stand-alone tiltable balance platform. AT-1 serves as assessment tool, treatment monitor, and rehabilitation training device. It allows clinician to document quantitatively the outcome of treatment and analyze data over time to develop outcome standards for several classifications of patients. It can evaluate specifically the effects of surgery, drug treatment, physical therapy or prosthetic devices.

Source record↗

Crew State and Risk Model Development to Predict Hydration Status During Extravehicular Activity Training Events

Introduction: Hydration is critical for optimal human health and performance and dehydration can lead to impaired cardiovascular function, thermal dysregulation, decreased blood plasma volume, and cognitive impacts, particularly during physical activity. Prolonged and repeated extravehicular activities (EVA) without sufficiently available drinking water may increase risk for dehydration, which could impair crew health and impact mission success. Understanding hydration needs and potential effects on health and performance are necessary to optimize crew well-being and enable successful EVA objectives. This study aims to develop a model of hydration status during EVA using water balance techniques. Methods: Water balance measures were collected on 15 healthy astronauts who performed ≈6-hour simulated microgravity extravehicular activity (EVA) training in the NASA Neutral Buoyancy Laboratory (NBL). Data collected included pre-and post-EVA nude body weight (BW), maximum absorption garment (MAG) weight, Disposable In-suit Drink Bag (DIDB) weight, urine specific gravity (USG), and extra pre-EVA intake (W). Variables were combined to create the water balance model as pre-EVA (Hn)= BWn+ MAGn+ DIDBn+ Wnand post EVA (Hn+1) = BWn+1+ MAGn+1+ DIDBn+1. Urine specific gravity values were used to refine water balance measures into hydration categories: Hydrated, Marginally Hydrated, and Dehydrated. Results: Pre-EVA modeling indicated53% of crew were hydrated, 20% were marginally hydrated, and 27% were dehydrated. Alternately, Hn+1 showed 13% of crew remained hydrated, 47% were marginally hydrated, and 40% were dehydrated at the end of the EVA. Furthermore, 75% of the crewmembers who started sufficiently hydrated finished the run marginally hydrated or dehydrated. According to USG indices presented by Casa and Lawrence, et al. (2000), only 25% of the crew started and remained hydrated throughout the EVA, and those who were dehydrated at the outset stayed dehydrated. Conclusion: Model outcomes assessing hydration status during 6-hour simulated microgravity EVAs demonstrate the necessity to further address hydration requirements for optimal human performance during spaceflight and EVA. This study enables additional baseline development of the Crew State and Risk Model Hydration, Nutrition, and Waste Management component that aims to provide individualized crew state and risk predictions during EVAs. Reference: Casa, D. J., Armstrong, L. E., et al. (2000). National Athletic Trainers’ Association Position Statement: Fluid Replacement for Athletes. Journal of Athletic Training, 35:212-224.

L Cooper↗

The Instrumented Walking and Turning Test to Evaluate Suited Gait Dynamics and Performance in Extravehicular Activity Training Environments

Background and aims: Walking will be required for many exploration tasks on the Moon during the Artemis program. Walking in a straight line on the confined floorspace of a testing area, and repetitive treadmill walking that requires no change in direction may not adequately reflect the balance and coordination required during ambulation. Also, performance of turning maneuvers may be affected differently in different extravehicular activity (EVA) training facilities that simulate partial gravity. For example, the Neutral Buoyancy Lab (NBL) simulates lunar gravity by adding weight to underwater subjects to alter buoyancy and achieve the equivalent ground reaction force of 1/6 of Earth’s gravity (1/6G), whereas the Active Response Gravity Offload System (ARGOS) uses a computer controlled overhead suspension system programmed to continuously offload a percentage of a subject’s weight to simulate 1/6G. The degree to which dynamic movements such as turning are comparable across these EVA training facilities has not yet been evaluated. The instrumented gait test helps NASA scientists and engineers evaluate gait dynamics and performance in suited conditions, and this test demonstrates the unique characteristics and limitations of EVA training facilities. We developed an instrumented walking and turning test using inertial measurement units (IMUs) and conducted the test at NASA’s EVA training facilities. Results were used to compare suited walking and turning characteristics in the ARGOS and the NBL. Methods: Subjects donned the Mark III space suit during offloading with the ARGOS spreader bar gimbal and donned the Z2.5 space suit while underwater in the NBL with weights and floatation added to achieve realistic suit center of gravity. The test team securely attached three Opal (APDM, OR, USA) wireless IMUs on the space suit for each test run: one on the middle of the hard upper torso, and one on the left and on the right ankle bearings. During the NBL tests, the IMUs were encased in a waterproof housing (GoPro) with foam added to create a tighter fit. At both testing facilities, 6.3 m x 1.0 m (LxW) walking lines were marked, and a cone for turning or walking around was located at the end of the walking path with another line on the other side of the cone to indicate the stopping point after walking around the cone. Under simulated 1/6G, subjects began by standing at the marked line with their arms folded across the chest, they then walked at a preferred speed along the straight walking path until they reached the end, turned 180 degrees around the cone, and finally stopped at the marked stopping point. All IMU data recorded during testing were automatically saved to the internal memory. Then, raw IMU signals were processed using custom MATLAB (Mathworks, MA, USA) code to compare gait parameters during both the walking and the turning components of the task. These parameters included time (s), speed (m/s for walking and rad/s for turning), step number (n) and walk:turn time ratio (% time spent straight walking versus turning). Results: Less time, faster gait, fewer steps, and higher walk:turn ratio during both walking and turning components were exhibited during tests performed at the ARGOS versus those performed at the NBL. During the NBL tests, the slower walking speed continued at the same rate throughout a U-shape turn. During the ARGOS tests, the subjects performed shorter and tighter turns at 4 times the speed of the NBL turns because they walked 30% faster and the vertical offloading system gave them more support. Conclusion: Our data show that the differences in walking and turning parameters during the NBL tests may be due to the high viscosity in the water environment where the motion of the lower limbs was slow and did not reach full flexion and extension. These tests improve the current knowledge of testing environments in preparation for EVAs on the lunar surface.

Kyoung Jae Kim↗

A reinforcement learning-based architecture for fuzzy logic control

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Berenji, Hamid R.↗

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Tan, Bin↗

The Franco-American macaque experiment

The details of studies to be carried out jointly by French and American teams on two rhesus monkeys prepared for future experiments aboard the Space Shuttle are discussed together with the equipment involved. Seven science discipline teams were formed, which will study the effects of flight and/or weightlessness on the bone and calcium metabolism, the behavior, the cardiovascular system, the fluid balance and electrolytes, the muscle system, the neurovestibular interactions, and the sleep/biorhythm cycles. New behavioral training techniques were developed, in which the animals were trained to respond to behavioral tasks in order to measure the parameters involving eye/hand coordination, the response time to target tracking, visual discrimination, and muscle forces used by the animals. A large data set will be obtained from different animals on the two to three Space Shuttle flights; the hardware technologies developed for these experiments will be applied for primate experiments on the Space Station.

Cipriano, Leonard F.↗

Predictive Measures of Locomotor Performance on an Unstable Walking Surface

Locomotion requires integration of visual, vestibular, and somatosensory information to produce the appropriate motor output to control movement. The degree to which these sensory inputs are weighted and reorganized in discordant sensory environments varies by individual and may be predictive of the ability to adapt to novel environments. The goals of this project are to: 1) develop a set of predictive measures capable of identifying individual differences in sensorimotor adaptability, and 2) use this information to inform the design of training countermeasures designed to enhance the ability of astronauts to adapt to gravitational transitions improving balance and locomotor performance after a Mars landing and enhancing egress capability after a landing on Earth.

Bloomberg, J. J.↗

The Effects of Autogenic Feedback Training Exercise on Heart Rate Variability

INTRODUCTION: The development of Motion Sickness (MS) symptoms is correlated with increased sympathetic influence and irregular patterns of vagal activity. Such autonomic actions can be characterized by indices of heart rate variability (HRV), which reflect autonomic balance through neurocardiac function. Nonpharmacological interventions aimed at attenuating MS symptoms may therefore produce an effect on HRV. One such intervention that has been shown to mitigate MS symptoms is Autogenic Feedback Training Exercise (AFTE), which combines principles of autogenic therapy and biofeedback. AFTE teaches individuals to manipulate various physiological parameters in provocative environments and shows promise as a potential MS intervention in military aviators. The effects of AFTE on HRV have not previously been examined. Understanding HRV changes following AFTE may help to elucidate its indirect effects and inform its implementation for MS mitigation. METHODS: Twenty-four subjects received 2 hours of AFTE over 4 days. Pre- and post-AFTE rotating chair tests, which included stationary periods of baseline data, were conducted to evaluate the effects of AFTE. HRV data were recorded by SOMNOtouch™ NIBP. Post hoc analysis of pre- and post-AFTE short-term HRV (RMSSD, LF, HF, LF/HF) was performed. RESULTS: RMSSD, HF, and LF/HF were not significantly changed following AFTE. However, LF showed a statistically significant (p=0.015) decrease following AFTE. DISCUSSION: AFTE prescribes a respiratory rate of 15 breaths per minute (BPM), which is typically faster than participants’ pre-AFTE BPM (M=12.65). Healthy individuals can increase respiratory sinus arrhythmia (RSA) by slow, deep breathing. However, increasing the respiratory rate to 15 BPM may decrease RSA and subsequently HF. Increasing RSA potentially negates any influence of AFTE on HF, resulting in no significant change. RMSSD is correlated with HF power and was likewise not affected by AFTE. LF power, however, decreased significantly following AFTE, potentially indicating a lower sympathetic response in the post-AFTE measurement.

motion sickness↗

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗

Supervised Machine Learning Approach for Classifying Earth Science Publications

The data collections archived and distributed by the GES DISC NASA data center are widely utilized for various Earth Science studies. As these collections are created, many research works are published regarding these collections' algorithms, their validation, and their applications. As NASA data centers collect these publications for public use, it is helpful to categorize them based on how they relate to their associated datasets. Specifically, whether the publication linked to the GES DISC dataset is using it for applicational research, describing the algorithm used for the dataset creation, validating the dataset, or providing a general overview of the data collection. Currently, this process requires simple manual labeling, and as such, it may be possible to solve via automation. To approach this problem, machine learning classifiers were developed to predict a publication's category. Manually labeled publications were used as the training data for the supervised machine learning algorithms, specifically Random Forest and Multinomial Naïve Bayes. After balancing the dataset and implementing the Multinomial Naïve Bayes algorithm, the classification accuracy achieved was substantially higher than the baseline accuracy, thus significantly improving the efficiency of publication labeling.

Rohan Dayal↗

Combining Satellite Microwave Radiometer and Radar Observations to Estimate Atmospheric Latent Heating Profiles

In this study, satellite passive microwave sensor observations from the TRMM Microwave Imager (TMI) are utilized to make estimates of latent + eddy sensible heating rates (Q1-QR) in regions of precipitation. The TMI heating algorithm (TRAIN) is calibrated, or "trained" using relatively accurate estimates of heating based upon spaceborne Precipitation Radar (PR) observations collocated with the TMI observations over a one-month period. The heating estimation technique is based upon a previously described Bayesian methodology, but with improvements in supporting cloud-resolving model simulations, an adjustment of precipitation echo tops to compensate for model biases, and a separate scaling of convective and stratiform heating components that leads to an approximate balance between estimated vertically-integrated condensation and surface precipitation. Estimates of Q1-QR from TMI compare favorably with the PR training estimates and show only modest sensitivity to the cloud-resolving model simulations of heating used to construct the training data. Moreover, the net condensation in the corresponding annual mean satellite latent heating profile is within a few percent of the annual mean surface precipitation rate over the tropical and subtropical oceans where the algorithm is applied. Comparisons of Q1 produced by combining TMI Q1-QR with independently derived estimates of QR show reasonable agreement with rawinsonde-based analyses of Q1 from two field campaigns, although the satellite estimates exhibit heating profile structure with sharper and more intense heating peaks than the rawinsonde estimates. 2

Grecu, Mircea↗

The physiological effects of dehydration caused by sweat loss

The mechanisms of fluid loss in the human body while sweating due to physical exercise are discussed. Trained and untrained persons were examined and compared. Since sweat is hypotonous, a disruption in the hydrosalinic balance occurs; the consequences of this finding, also pertaining to the fluid and electrolytic substitution, are presented. Further explanations on the problem of dehydration refer to reactions of individual organ systems, to alterations in bodily capabilities as well as to questions relating to sex and age.

Israel, S.↗

Advanced Methods for Aircraft Engine Thrust and Noise Benefits: Nozzle-Inlet Flow Analysis

The research is focused on a wide regime of problems in the propulsion field as well as in experimental testing and theoretical and numerical simulation analyses for advanced aircraft and rocket engines. Results obtained are based on analytical methods, numerical simulations and experimental tests at the NASA LaRC and Hampton University computer complexes and experimental facilities. The main objective of this research is injection, mixing and combustion enhancement in propulsion systems. The sub-projects in the reporting period are: (A) Aero-performance and acoustics of Telescope-shaped designs. The work included a pylon set application for SCRAMJET. (B) An analysis of sharp-edged nozzle exit designs for effective fuel injection into the flow stream in air-breathing engines: triangular-round and diamond-round nozzles. (C) Measurement technique improvements for the HU Low Speed Wind Tunnel (HU LSWT) including an automatic data acquisition system and a two component (drag-lift) balance system. In addition, a course in the field of aerodynamics was developed for the teaching and training of HU students.

Morgan, Morris H.↗

System and method for embedding emotion in logic systems

A system, method, and computer readable-media for creating a stable synthetic neural system. The method includes training an intellectual choice-driven synthetic neural system (SNS), training an emotional rule-driven SNS by generating emotions from rules, incorporating the rule-driven SNS into the choice-driven SNS through an evolvable interface, and balancing the emotional SNS and the intellectual SNS to achieve stability in a nontrivial autonomous environment with a Stability Algorithm for Neural Entities (SANE). Generating emotions from rules can include coding the rules into the rule-driven SNS in a self-consistent way. Training the emotional rule-driven SNS can occur during a training stage in parallel with training the choice-driven SNS. The training stage can include a self assessment loop which measures performance characteristics of the rule-driven SNS against core genetic code. The method uses a stability threshold to measure stability of the incorporated rule-driven SNS and choice-driven SNS using SANE.

Curtis, Steven A.↗

JPL's Approach for Helping Flight Project Managers Meet Today's Management Challenges

All across NASA project managers are facing tough new challenges. NASA has imposed increased oversight and the number of projects at Centers such as JPL has exploded from a handful of large projects to a much greater number of smaller ones. Experienced personnel are retiring at increasing rates and younger, less experienced managers are being rapidly promoted up the ladder. Budgets are capped, competition among NASA Centers and Federally Funded Research and Development Centers (FFRDCs) has increased significantly and there is no longer any tolerance to cost overruns. On top of all this, implementation schedules have been reduced by 25 to 50% to reduce run-out costs, making it even more difficult to define requirements, validate heritage assumptions and make accurate cost estimates during the early phases of the life-cycle.JPL's executive management, under the leadership of the Associate Director for Flight Projects and Mission Success, have attempted to meet these challenges by improving operations in five areas: (1) increased standardization, where it is judged to have significant benefit; (2) better balance and more effective partnering between projects and the line management; (3) increased infrastructure support; (4) improved management training; and (5) more effective review and oversight.

oversights↗