The purpose of the present study was to evaluate the effects of aerobic physical training (APT) on heart rate variability (HRV) and cardiorespiratory responses at peak condition and ventilatory anaerobic threshold. Ten young (Y: median = 21 years) and seven middle-aged (MA = 53 years) healthy sedentary men were studied. Dynamic exercise tests were performed on a cycloergometer using a continuous ramp protocol (12 to 20 W/min) until exhaustion. A dynamic 24-h electrocardiogram was analyzed by time (TD) (standard deviation of mean R-R intervals) and frequency domain (FD) methods. The power spectral components were expressed as absolute (a) and normalized units (nu) at low (LF) and high (HF) frequencies and as the LF/HF ratio. Control (C) condition: HRV in TD (Y: 108, MA: 96 ms; P<0.05) and FD -LFa, HFa -was significantly higher in young (1030; 2589 ms 2 /Hz) than in middle-aged men (357; 342 ms 2 /Hz) only during sleep (P<0.05); posttraining effects: resting bradycardia (P<0.05) in the awake condition in both groups; V . O 2 increased for both groups at anaerobic threshold (P<0.05), and at peak condition only in young men; HRV in TD and FD (a and nu) was not significantly changed by training in either groups. The vagal predominance during sleep is reduced with aging. The resting bradycardia induced by short-term APT in both age groups suggests that this adaptation is much more related to intrinsic alterations in sinus node than in efferent vagal-sympathetic modulation. Furthermore, the greater alterations in V . O 2 than in HRV may be related to short-term APT.

SUMMARY Simulation is a standard technique for investigating the sampling distribution of parameter estimators. The bootstrap is a distribution‐free method of assessing sampling variability based on resampling from the empirical distribution; the parametric bootstrap resamples from a fitted parametric model. However, if the parameters of the model are constrained, and the application of these constraints is a function of the realized sample, then the resampling distribution obtained from the parametric bootstrap may become badly biased and overdispersed. Here we discuss such problems in the context of estimating parameters from a bilinear model that incorporates the singular value decomposition (SVD) and in which the parameters are identified by the standard orthogonality relationships of the SVD. Possible effects of the SVD parameter identification are arbitrary changes in the sign of singular vectors, inversion of the order of singular values and rotation of the plotted co‐ordinates. This paper proposes inverse transformation or ‘filtering’ techniques to avoid these problems. The ideas are illustrated by assessing the variability of the location of points in a principal co‐ordinates diagram and in the marginal sampling distribution of singular values. An application to the analysis of a biological data set is described. In the discussion it is pointed out that several exploratory multivariate methods may benefit by using resampling with filtering.

Paper-based devices are a portable, user-friendly, and affordable technology that is one of the best analytical tools for inexpensive diagnostic devices. Three-dimensional microfluidic paper-based analytical devices (3D-μPADs) are an evolution of single layer devices and they permit effective sample dispersion, individual layer treatment, and multiplex analytical assays. Here, we present the rational design of a wax-printed 3D-μPAD that enables more homogeneous permeation of fluids along the cellulose matrix than other existing designs in the literature. Moreover, we show the importance of the rational design of channels on these devices using glucose oxidase, peroxidase, and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) reactions. We present an alternative method for layer stacking using a magnetic apparatus, which facilitates fluidic dispersion and improves the reproducibility of tests performed on 3D-μPADs. We also provide the optimized designs for printing, facilitating further studies using 3D-μPADs.

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