The series "Studies in Big Data" (SBD) publishes new developments and advances in the various areas of Big Data-quickly and with a high quality. The intent is to cover the theory, research, development, and applications of Big Data, as embedded in the fields of engineering, computer science, physics, economics and life sciences. The books of the series refer to the analysis and understanding of large, complex, and/or distributed data sets generated from recent digital sources coming from sensors or other physical instruments as well as simulations, crowd sourcing, social networks or other internet transactions, such as emails or video click streams and other. The series contains monographs, lecture notes and edited volumes in Big Data spanning the areas of computational intelligence incl. neural networks, evolutionary computation, soft computing, fuzzy systems, as well as artificial intelligence, data mining, modern statistics and Operations research, as well as self-organizing systems. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution, which enable both wide and rapid dissemination of research output.
Background Interaction of physical activity and overall immune profile is very complex and depends on the intensity, duration and frequency of undertaken physical activity, the exposure to cytomegalovirus (CMV) infection and the age-related changes in the immune system. Daily physical activity, which particularly influences immunity, declines dramatically with age. Therefore, the aim of the study was to explain whether physical activity sustained throughout life can attenuate or reverse immunosenescence. Methods Ninety-nine older adults (60–90 years) were recruited for the study. According to the 6-min walk test (6WMT), the Åstrand-Ryhming bike test (VO2max) and Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire, the individuals were classified as physically active (n = 34) and inactive (n = 20) groups. The analysis of T lymphocytes between active vs. inactive participants was performed using eight-parameter flow cytometry. Results Analysis of the baseline peripheral naïve and memory T lymphocytes showed a significant relationship of lifestyle exercise with the CD4/CD8 ratio. Above 50% of physically active participants demonstrated the CD4/CD8 ratio ≥ 1 or ≤ 2.5 contrary to the inactive group who showed the ratio < 1. The older adults with the result of 6WMT > 1.3 m/s and VO2max > 35 mL/kg/min had a significantly higher CD4+CD45RA+ T lymphocyte percentage and also a higher ratio of CD4+CD45RA+/CD4+CD45RO+. Interestingly, in active older adults with IgG CMV+ (n = 30) the count of CD4+CD45RA+ T lymphocytes was higher than in the inactive group with IgG CMV+ (n = 20). Conclusion Based on the flow cytometry analysis, we concluded that lifestyle exercise could lead to rejuvenation of the immune system by increasing the percentage of naïve T lymphocytes or by reducing the tendency of the inverse CD4/CD8 ratio.
Abstract-Discrete linear repetitive processes are a distinct class of two-dimensional (2-D) linear systems with applications in areas ranging from long-wall coal cutting through to iterative learning control schemes. The feature which makes them distinct from other classes of 2-D linear systems is that information propagation in one of the two independent directions only occurs over a finite duration. This, in turn, means that a distinct systems theory must be developed for them. In this paper a complete characterization of stability and so-called pass controllability (and several resulting features), essential building blocks for a rigorous systems theory, under a general set of initial, or boundary, conditions is developed. Finally, some significant new results on the problem of stabilization by choice of the pass state initial vector sequence are developed.
The Probability Density Function (PDF) is a key concept in statistics. Constructing the most adequate PDF from the observed data is still an important and interesting scientific problem, especially for large datasets. PDFs are often estimated using nonparametric data-driven methods. One of the most popular nonparametric method is the Kernel Density Estimator (KDE). However, a very serious drawback of using KDEs is the large number of calculations required to compute them, especially to find the optimal bandwidth parameter. In this paper we investigate the possibility of utilizing Graphics Processing Units (GPUs) to accelerate the finding of the bandwidth. The contribution of this paper is threefold: (a) we propose algorithmic optimization to one of bandwidth finding algorithms, (b) we propose efficient GPU versions of three bandwidth finding algorithms and (c) we experimentally compare three of our GPU implementations with the ones which utilize only CPUs. Our experiments show orders of magnitude improvements over CPU implementations of classical algorithms.
The problem of fast computation of multivariate kernel density estimation (KDE) is still an open research problem. In our view, the existing solutions do not resolve this matter in a satisfactory way. One of the most elegant and efficient approach utilizes the fast Fourier transform. Unfortunately, the existing FFT-based solution suffers from a serious limitation, as it can accurately operate only with the constrained (i.e., diagonal) multivariate bandwidth matrices. In this paper we describe the problem and give a satisfactory solution. The proposed solution may be successfully used also in other research problems, for example for the fast computation of the optimal bandwidth for KDE.
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