SMAR Sessions

This slide presentation is a series of educational presentations that are on the statistical function of analysis of variance (ANOVA). Analysis of Variance (ANOVA) examines variability between groups, relative to within groups, to determine whether there's evidence that the groups are not from the same population. One other presentation reviews hypothesis testing

Integrated Resistance and Aerobic Training Maintains Cardiovascular and Skeletal Muscle Fitness During 14 Days of Bed Rest

Background: Known incompatibilities exist between resistance and aerobic training. Of particular importance are findings that concurrent resistance and aerobic training reduces the effectiveness of the resistance training and limits skeletal muscle adaptations (example: Dudley & Djamil, 1985). Numerous unloading studies have documented the effectiveness of resistance training alone for the maintenance of skeletal muscle size and strength. However the practical applications of those studies are limited because long ]duration crew members perform both aerobic and resistance exercise throughout missions/spaceflight. To date, such integrated training on the International Space Station (ISS) has not been fully effective in the maintenance of skeletal muscle function. Purpose: The purpose of this study was to evaluate the efficacy of high intensity concurrent resistance and aerobic training for the maintenance of cardiovascular fitness and skeletal muscle strength, power and endurance over 14 days of strict bed rest. Methods: 9 subjects (8 male and 1 female; 34.5 +/- 8.2 years) underwent 14 days of bed rest with concurrent training. Resistance and aerobic training were integrated as shown in table 1. Days that included 2 exercise sessions had a 4-8 hour rest between exercise bouts. The resistance training consisted of 3 sets of 12 repetitions of squat, heel raise, leg press and hamstring curl exercise. Aerobic exercise consisted of periodized interval training that included 30 sec, 2 min and 4 min intervals alternating by day with continuous aerobic exercise

Intermediate/Advanced Research Design and Statistics

The purpose of this module is To provide Institutional Researchers (IRs) with an understanding of the principles of advanced research design and the intermediate/advanced statistical procedures consistent with such design

Contributions of Astronauts Aerobic Exercise Intensity and Time on Change in VO2peak during Spaceflight

There is considerable variability among astronauts with respect to changes in maximal aerobic capacity (VO2peak) during International Space Station (ISS) missions, ranging from a 5% increase to 30% decline. Individual differences may be due to in-flight aerobic exercise time and intensity. PURPOSE: To evaluate the effects of in-flight aerobic exercise time and intensity on change in VO2peak during ISS missions. METHODS: Astronauts (N=11) performed peak cycle tests approx 60 days before flight (L-60), on flight day (FD) approx 14, and every approx 30 days thereafter. Metabolic gas analysis and heart rate (HR) were measured continuously during the test using the portable pulmonary function system. HR and duration of each in-flight cycle ergometer and treadmill (TM) session were recorded and averaged in time segments corresponding to each peak test. Mixed effects linear regression with exercise mode (TM or cycle) as a categorical variable was used to assess the contributions of exercise intensity (%time >70% peak HR or %time >90% peak HR) and time (min/wk), adjusted for body weight, on %change in VO2peak during the mission, and incorporating the repeated-measures experimental design. RESULTS: 110 observations were included in the model (4-6 peak cycle tests per astronaut, 2 exercise devices). VO2peak was reduced from preflight throughout the mission (FD14: 13+/-13% and FD 105: 8+/-10%). Exercise intensity (%peak HR: FD14=66+/-14; FD105=75+/-8) and time (min/wk: FD14=82+/-46; FD105=158+/-40) increased during flight. The models showed main effects for exercise time and intensity with no interactions between time, intensity, and device (70% peak HR: time [z-score=2.39; P=0.017], intensity [z-score=3.51; P=0.000]; 90% peak HR: time [zscore= 3.31; P=0.001], intensity [z-score=2.24; P=0.025]). CONCLUSION: Exercise time and intensity independently contribute to %change in VO2peak during ISS missions, indicating that there are minimal values for exercise time and intensity required to maintain VO2peak. As the FD105 average exercise intensity and time did not prevent a decline in VO2peak from preflight, astronauts' exercise prescriptions should target at least 160 min of weekly aerobic exercise at an average above 75% peak HR with increased time at intensities above 90% of peak HR starting early in the mission

Math: The Gateway to Great Careers

This slide presentation examines the role of mathematical proficiency and how it relates to advantages in careers. It emphasises the role of math in attaining entrance to college, graduate schools, and a career that is interesting and well paying

Sweat Rates During Continuous and Interval Aerobic Exercise: Implications for NASA Multipurpose Crew Vehicle (MPCV) Missions

Aerobic deconditioning is one of the effects spaceflight. Impaired crewmember performance due to loss of aerobic conditioning is one of the risks identified for mitigation by the NASA Human Research Program. Missions longer than 8 days will involve exercise countermeasures including those aimed at preventing the loss of aerobic capacity. The NASA Multipurpose Crew Vehicle (MPCV) will be NASA's centerpiece architecture for human space exploration beyond low Earth orbit. Aerobic exercise within the small habitable volume of the MPCV is expected to challenge the ability of the environmental control systems, especially in terms of moisture control. Exercising humans contribute moisture to the environment by increased respiratory rate (exhaling air at 100% humidity) and sweat. Current acceptable values are based on theoretical models that rely on an "average" crew member working continuously at 75% of their aerobic capacity (Human Systems Integration Requirements Document). Evidence suggests that high intensity interval exercise for much shorter durations are equally effective or better in building and maintaining aerobic capacity. This investigation will examine sweat and respiratory rates for operationally relevant continuous and interval aerobic exercise protocols using a variety of different individuals. The results will directly inform what types of aerobic exercise countermeasures will be feasible to prescribe for crewmembers aboard the MPCV

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R~, the correlation matrix of associated t-statistics is also studied. In general R~ depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons

Metabolic Assessment of Suited Mobility Using Functional Tasks

Existing methods for evaluating extravehicular activity (EVA) suit mobility have typically focused on isolated joint range of motion or torque, but these techniques have little to do with how well a crewmember functionally performs in an EVA suit. To evaluate suited mobility at the system level through measuring metabolic cost (MC) of functional tasks

Characterization of Carbon Dioxide Washout Measurement Techniques in the Mark-III Space Suit

A space suit must provide adequate carbon dioxide (CO2) washout inside the helmet to prevent symptoms of hypercapnia. In the past, an oronasal mask has been used to measure the inspired air of suited subjects to determine a space suit's CO2 washout capability. While sufficient for super-ambient pressure testing of space suits, the oronasal mask fails to meet several human factors and operational criterion needed for future sub-ambient pressure testing (e.g. compatibility with a Valsalva device). This paper describes the evaluation of a nasal cannula as a device for measuring inspired air within a space suit. Eight test subjects were tasked with walking on a treadmill or operating an arm ergometer to achieve target metabolic rates of 1000, 2000, and 3000 British thermal units per hour (BTU/hr), at flow rates of 2, 4, and 6 actual cubic feet per minute (ACFM). Each test configuration was conducted twice, with subjects instructed to breathe either through their nose only, or however they felt comfortable. Test data shows that the nasal cannula provides more statistically consistent data across test subjects than the oronasal mask used in previous tests. The data also shows that inhaling/exhaling through only the nose provides a lower sample variance than a normal breathing style. Nose-only breathing reports better CO2 washout due to several possible reasons, including a decreased respiratory rate, an increased tidal volume, and because nose-only breathing directs all of the exhaled CO2 down and away from the oronasal region. The test subjects in this study provided feedback that the nasal cannula is comfortable and can be used with the Valsalva device

Pre/Post Data Analysis - Simple or Is It?

This slide presentation reviews some of the problems of data analysis in analyzing pre and post data. Using as an example, ankle extensor strength (AES) experiments, to measure bone density loss during bed rest, the presentation discusses several questions: (1) How should we describe change? (2) Common analysis methods for comparing post to pre results. (3) What do we mean by "% change"? and (4) What are we testing when we compare % changes