No Differences in Strength Improvements Following Low- or High-Volume Resistance Training

Resistance training is a widely used modality for improving muscular strength and reducing risks of injury, which is vital to counteracting physical declines associated with aging and poor health. Despite this, the minimal effective training dose for improving muscular strength has yet to be fully elucidated. PURPOSE: The purpose of this study was to examine the role of training volume (number of sets per session) on muscular strength changes following 8 weeks of progressive resistance training. METHODS: Fourteen and 12 trained males (Mean±SD; Age: 23±3y) and females (Age: 20±1y) participated in 8 weeks of supervised 3x/week progressive resistance training. Experimental sessions consisted of 3-5 repetition maximum testing both pre- and post-intervention, in accordance with the protocol outlined by the NSCA, in the following exercises: leg press (LP), bench press (BP), horizontal row (ROW), barbell Romanian deadlift (RDL), dumbbell overhead press (OHP), and lat pulldown (LAT). Following baseline strength testing, each participant was randomly allocated to either a low volume (LV; n=12 (5F)) or high volume (HV; n=14 (7F)) training group, completing 2 or 4 sets per exercise per training visit, respectively. Across all 8 weeks, participants completed each lift twice weekly, and loads were adjusted based on exercise performance using the autoregulated progressive resistance exercise protocol. Each group completed the same repetitions in their first sets, but completed the last set of every exercise until volitional failure. Percent change for each exercise was calculated as the difference between baseline strength (kgs) and post-training strength (kgs), expressed as a percentage of baseline strength. To examine the effect of group and exercise on the change in strength, a 2 (Group) × 6 (Exercise) analysis of covariance (ANCOVA) was performed, covarying for pre-test strength. In the event of a significant F test, the Bonferroni-corrected dependent-samples t-test was used. Values are presented as estimated marginal means ± standard error. RESULTS: There was no significant Group × Exercise interaction effect on percent strength change (p=0.754), nor a main effect of Group (p=0.397). However, there was a significant effect of Exercise (p\u3c0.001). Post-hoc analyses indicated, when collapsing across training groups, improvements in strength were greater in LP when compared to BP (40.6±6.8%; p\u3c0.001), RDL (26.9±6.1%; p\u3c0.001), OHP (37.4±7.9%; p\u3c0.001), and LAT (22.7±6.8%; p=0.015). Additionally, greater strength improvements were seen in ROW when compared to BP (29.7±4.5%, p\u3c0.001), RDL (16.0±4.6%, p\u3c0.001), and OHP (26.5±4.8%, p\u3c0.001). Finally, LAT experienced greater strength increases than both BP (17.8±4.5%, p\u3c0.01) and OHP (14.6±4.7%, p=0.036). There were no additional significant differences between exercises (p=0.054-0.999). CONCLUSION: Our findings suggest that a resistance training volume of as few as 2 sets per exercise twice weekly is adequate to induce muscular strength adaptations in previously trained young adults. Further examination is needed to determine if upper and lower body exercises require differing volumes to elicit similar adaptations

Tests of Bayesian Model Selection Techniques for Gravitational Wave Astronomy

The analysis of gravitational wave data involves many model selection problems. The most important example is the detection problem of selecting between the data being consistent with instrument noise alone, or instrument noise and a gravitational wave signal. The analysis of data from ground based gravitational wave detectors is mostly conducted using classical statistics, and methods such as the Neyman-Pearson criteria are used for model selection. Future space based detectors, such as the \emph{Laser Interferometer Space Antenna} (LISA), are expected to produced rich data streams containing the signals from many millions of sources. Determining the number of sources that are resolvable, and the most appropriate description of each source poses a challenging model selection problem that may best be addressed in a Bayesian framework. An important class of LISA sources are the millions of low-mass binary systems within our own galaxy, tens of thousands of which will be detectable. Not only are the number of sources unknown, but so are the number of parameters required to model the waveforms. For example, a significant subset of the resolvable galactic binaries will exhibit orbital frequency evolution, while a smaller number will have measurable eccentricity. In the Bayesian approach to model selection one needs to compute the Bayes factor between competing models. Here we explore various methods for computing Bayes factors in the context of determining which galactic binaries have measurable frequency evolution. The methods explored include a Reverse Jump Markov Chain Monte Carlo (RJMCMC) algorithm, Savage-Dickie density ratios, the Schwarz-Bayes Information Criterion (BIC), and the Laplace approximation to the model evidence. We find good agreement between all of the approaches.Comment: 11 pages, 6 figure

The Positive Effects of Acute Resistance Exercise on Blood Lipid Profiles in College-Aged Men

Low- to moderate-intensity exercise has been widely recommended for people at any age to improve cardiovascular health due to its positive effects on blood lipids and lipoproteins. Recently, many people have been participating in not only low- to moderate-intensity, but high-intensity exercise as well in order to improve their cardiovascular health. However, it is unclear whether high-intensity exercise, particularly resistance exercise, can positively influence blood lipids and lipoproteins. Purpose: The current study examined the effects of low- and high-intensity of resistance exercise on changes in blood lipids and lipoproteins. Methods: In a randomized, cross-over design, 10 healthy recreationally resistance-trained (at least 3 to 6 days per week for a minimum of one year) college-aged men participated in the study. The participants performed a lower body resistance exercise, consisting of the leg press and unilateral knee extension, at two different exercise intensities (low-intensity: 50% of 1-RM and high-intensity: 80% of 1-RM). The volume of the intensities of exercise was similar. Overnight fasting blood samples were collected at baseline and 3-hr, 24-hr, and 48-hr post exercise for each intensity to determine blood lipids and lipoproteins (TC, Lp(a), VLDL-C, LDL-C, and HDL-C). A 2 (intensity) X 4 (time) ANOVA with repeated measures was used to examine the mean differences in intensity and time on blood lipids and lipoproteins. The Bonferroni pairwise comparisons were conducted as post hoc to locate the significant mean differences. If a significant interaction was found, the follow-up simple effects test was conducted. A p-value \u3c .05 was set for the statistical significance. Results: Either low- or high-intensity resistance exercise did not significantly alter Lp(a), VLDL-C, or HDL-C. However, regardless of the intensity, LDL (p = .045) and TC (p = .028) significantly decreased by 7.90 (8.76 ± 0.32 mg/dL) and 6.80% (11.34 ± 0.93 mg/dL), respectively, at 48-hr post exercise. Conclusion: Regardless of the intensity level, resistance exercise may positively alter blood lipid profiles by decreasing TC and LDL-C in recreationally-trained men. Therefore, the current study suggests that high-intensity resistance exercise can also be an effective method to improve cardiovascular health

A Review of Weight Control Strategies and Their Effects on the Regulation of Hormonal Balance

The estimated prevalence of obesity in the USA is 72.5 million adults with costs attributed to obesity more than 147 billion dollars per year. Though caloric restriction has been used extensively in weight control studies, short-term success has been difficult to achieve, with long-term success of weight control being even more elusive. Therefore, novel approaches are needed to control the rates of obesity that are occurring globally. The purpose of this paper is to provide a synopsis of how exercise, sleep, psychological stress, and meal frequency and composition affect levels of ghrelin, cortisol, insulin GLP-1, and leptin and weight control. We will provide information regarding how hormones respond to various lifestyle factors which may affect appetite control, hunger, satiety, and weight control

Effects of Capsaicin and Evodiamine Ingestion on Energy Expenditure and Fat Oxidation at Rest and After Moderately-Intense Exercise in Young Men

Capsaicin and evodiamine are two thermogenic agents each recognized for their ability to stimulate the sympathetic nervous system and are thus found in many dietary supplements. Therefore, the purpose of this study was to observe the effects that capsaicin and evodiamine have on hemodynamics, energy expenditure, and markers of lipid oxidation while at rest and after a single bout of moderate-intensity exercise in young men. In a randomized, cross-over design, 11 men orally ingested 500 mg of capsaicin, evodiamine, or placebo while at rest after 30 minutes of resting energy expenditure assessment using open-circuit spirometry. After an additional 30 minutes of rest after supplement ingestion, resting energy expenditure was assessed again for 30 minutes. After the second resting energy expenditure assessment, treadmill exercise was performed until expending approximately 500 kilocalories (~30 minutes) at 65% peak oxygen consumption. Energy expenditure was assessed for another 30 minutes into the post-exercise period. Heart rate and blood pressure, core temperature, and venous blood samples were obtained 30 minutes before and one hour after supplement ingestion (i.e. immediately pre-exercise), and immediately after and 45 minutes post-exercise. Markers of lipid oxidation (serum glycerol, free fatty acids, serum glucose, epinephrine, and norepinephrine) were determined spectrophotometrically and with ELISA. Two-way analyses of variance (ANOVA) were performed for each dependent variable (p ≤ 0.05). Significant main effects for Time existed for hemodynamics, energy expenditure, serum catecholamines and markers of fat oxidation immediately following exercise (p \u3c 0.05). However, no significant Supplement x Time interactions were noted for any criterion variable (p \u3e 0.05), suggesting no preferential difference between supplements. Neither capsaicin nor evodiamine, at a single dose of 500 mg, are effective at inducing thermogenesis and increasing fat oxidation at rest or during exercise in young men

LISA Data Analysis using MCMC methods

The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analyses and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we super-cool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.Comment: 14 pages, 7 figure

Constraints on Automorphic Forms of Higher Derivative Terms from Compactification

By dimensionally reducing the higher derivative corrections of ten-dimensional IIB theory on a torus we deduce constraints on the E_{n+1} automorphic forms that occur in d=10-n dimensions. In particular we argue that these automorphic forms involve the representation of E_{n+1} with fundamental weight \lambda^{n+1}, which is also the representation to which the string charges in d dimensions belong. We also consider a similar calculation for the reduction of higher derivative terms in eleven-dimensional M-theory.Comment: Minor corrections, to appear in JHE

The Noncommutative Bion Core

We examine noncommutative solutions of the nonabelian theory on the world-volume of N coincident D-strings. These solutions can be interpreted in terms of noncommutative geometry as funnels describing the nonabelian D-string expanding out into an orthogonal D3-brane. These configurations are `dual' to the bion solutions in the abelian world-volume theory of the D3-brane. In the latter, a charge N magnetic monopole describes N D-strings attached to the D3-brane with a spike deformation of the world-volume. The noncommutative D-string solutions give a reliable account of physics at the core of the monopole, where the bion description is expected to breakdown. In the large N limit, we find good agreement between the two points of view, including the energy, couplings to background fields, and the shape of the funnel. We also study fluctuations traveling along the D-string, again obtaining agreement in the large N limit. At finite N, our results give a limit on the number of modes that can travel to infinity along the N D-strings attached to the D3-brane.Comment: 22 pages, refs adde