All issues

Heart rate (HR) is the most affordable indicator for measuring. In order to control the individual response to physical exercises of different load types heart rate is measured when the athletes perform different types of muscular work (strength machines, various types of training and competitive exercises). The magnitude of heart rate and its dynamics during muscular work and recovery can be objectively judged on the functional status of the cardiovascular system of an athlete, the level of its individual physical performance, as well as an adaptive response to a particular exercise. However, the heart rate is not an independent determinant of the physical condition of an athlete. HR size is formed by the interaction of the basic physiological mechanisms underlying cardiac hemodynamic ejection mode. Heart rate depends on one hand, on contractility of the heart, the venous return, the volumes of the atria and ventricles of the heart and from vascular heart load, the main components of which are elastic and peripheral resistance of the arterial system on the other hand. The values of arterial system vascular resistances depend on the power of muscular work and its duration. HR sensitivity to changes in heart load and vascular contraction was determined in athletes by pair regression analysis simultaneously recorded heart rate data, and peripheral $(R)$ and elastic $(E_a)$ resistance (heart vascular load), and the power $(W)$ of heartbeats (cardiac contractility). The coefficients of sensitivity and pair correlation between heart rate indicators and vascular load and contractility of left ventricle of the heart were determined in athletes at rest and during the muscular work on the cycle ergometer. It is shown that increase in both ergometer power load and heart rate is accompanied by the increase of correlation coefficients and coefficients of the heart rate sensitivity to $R$, $E_a$ and $W$.

This work is devoted to the analysis of conformational changes in tubulin dimers and tetramers, in particular, the assessment of the bending of microtubule protofilaments. Three recently exploited approaches for estimating the bend of tubulin protofilaments are reviewed: (1) measurement of the angle between the vector passing through the H7 helices in $\alpha$ and $\beta$ tubulin monomers in the straight structure and the same vector in the curved structure of tubulin; (2) measurement of the angle between the vector, connecting the centers of mass of the subunit and the associated GTP nucleotide, and the vector, connecting the centers of mass of the same nucleotide and the adjacent tubulin subunit; (3) measurement of the three rotation angles of the bent tubulin subunit relative to the straight subunit. Quantitative estimates of the angles calculated at the intra- and inter-dimer interfaces of tubulin in published crystal structures, calculated in accordance with the three metrics, are presented. Intra-dimer angles of tubulin in one structure, measured by the method (3), as well as measurements by this method of the intra-dimer angles in different structures, were more similar, which indicates a lower sensitivity of the method to local changes in tubulin conformation and characterizes the method as more robust. Measuring the angle of curvature between H7-helices (method 1) produces somewhat underestimated values of the curvature per dimer. Method (2), while at first glance generating the bending angle values, consistent the with estimates of curved protofilaments from cryoelectron microscopy, significantly overestimates the angles in the straight structures. For the structures of tubulin tetramers in complex with the stathmin protein, the bending angles calculated with all three metrics varied quite significantly for the first and second dimers (up to 20% or more), which indicates the sensitivity of all metrics to slight variations in the conformation of tubulin dimers within these complexes. A detailed description of the procedures for measuring the bending of tubulin protofilaments, as well as identifying the advantages and disadvantages of various metrics, will increase the reproducibility and clarity of the analysis of tubulin structures in the future, as well as it will hopefully make it easier to compare the results obtained by various scientific groups.

Segmentation of medical image is one of the most challenging tasks in analysis of medical image. It classifies the organs pixels or lesions from medical images background like MRI or CT scans, that is to provide critical information about the human organ’s volumes and shapes. In scientific imaging field, medical imaging is considered one of the most important topics due to the rapid and continuing progress in computerized medical image visualization, advances in analysis approaches and computer-aided diagnosis. Digital image processing becomes more important in healthcare field due to the growing use of direct digital imaging systems for medical diagnostics. Due to medical imaging techniques, approaches of image processing are now applicable in medicine. Generally, various transformations will be needed to extract image data. Also, a digital image can be considered an approximation of a real situation includes some uncertainty derived from the constraints on the process of vision. Since information on the level of uncertainty will influence an expert’s attitude. To address this challenge, we propose novel framework involving interval concept that consider a good tool for dealing with the uncertainty, In the proposed approach, the medical images are transformed into interval valued representation approach and entropies are defined for an image object and background. Then we determine a threshold for lower-bound image and for upper-bound image, and then calculate the mean value for the final output results. To demonstrate the effectiveness of the proposed framework, we evaluate it by using synthetic image and its ground truth. Experimental results showed how performance of the segmentation-based entropy threshold can be enhanced using proposed approach to overcome ambiguity.

The question of distribution of citizens expenses in modern Russia is experimentally investigated. New cars were chosen as representative group of the acquired goods as well as earlier. Results of the analysis of sales of new cars for 2007–2009 are presented below. Main “body” of density of probability to find certain number of cars depending on their price, since some initial price up to ~ k$60, is an exponential distribution. The found feature of distribution (unlike 2003–2005) was an existence of minimum price. For expensive cars (distribution “tail”), the asymptotic form is the Pareto distribution with a hyperbole exponent a little greater, than measured earlier for 2003–2005. The results turned up to be similar to direct measurements of distribution of tax declarations on their size, submitted to the USA in 2004 where exponential distribution of the income of citizens, since some minimum, with some asymptotic in the form of Pareto's distribution also was observed.

Original representation of statistical digital model of measurement of a macroroughness on a local site (to 15) consisting of determined (bias), correlated (standard periodic making and periodic deviations from flatness) and actually casual making (values of a macroroughness) Is offered.

A simple model was developed to describe the dependence of net CO₂ exchange in a sphagnum peat bog as a function of incoming solar radiation, air temperature, and soil moisture. It was parameterized using the field measurement data from two neighboring sites in an undisturbed peat bog (the pine mire with shrub and sphagnum and the shrub-sphagnum mire with rare pine) in Moscow Region. Measurements were conducted during the second part of the growing season, when the groundwater level was below 30 cm. It was shown that is a key parameter influencing the photosynthesis and respiration rates of a sphagnum moss and peat soil. The developed model allows to explain from 71 % to 74 % of the variation of CO₂ exchange in the peat bog.

Radiopharmaceuticals with iodine radioisotopes are now widely used in imaging and non-imaging methods of nuclear medicine. When evaluating the results of radionuclide studies of the structural and functional state of organs and tissues, parallel modeling of the kinetics of radiopharmaceuticals in the body plays an important role. The complexity of such modeling lies in two opposite aspects. On the one hand, excessive simplification of the anatomical and physiological characteristics of the organism when splitting it to the compartments that may result in the loss or distortion of important clinical diagnosis information, on the other – excessive, taking into account all possible interdependencies of the functioning of the organs and systems that, on the contrary, will lead to excess amount of absolutely useless for clinical interpretation of the data or the mathematical model becomes even more intractable. Our work develops a unified approach to the construction of mathematical models of the kinetics of radiopharmaceuticals with iodine isotopes in the human body during diagnostic and therapeutic procedures of nuclear medicine. Based on this approach, three- and four-compartment pharmacokinetic models were developed and corresponding calculation programs were created in the C⁺⁺ programming language for processing and evaluating the results of radionuclide diagnostics and therapy. Various methods for identifying model parameters based on quantitative data from radionuclide studies of the functional state of vital organs are proposed. The results of pharmacokinetic modeling for radionuclide diagnostics of the liver, kidney, and thyroid using iodine-containing radiopharmaceuticals are presented and analyzed. Using clinical and diagnostic data, individual pharmacokinetic parameters of transport of different radiopharmaceuticals in the body (transport constants, half-life periods, maximum activity in the organ and the time of its achievement) were determined. It is shown that the pharmacokinetic characteristics for each patient are strictly individual and cannot be described by averaged kinetic parameters. Within the framework of three pharmacokinetic models, “Activity–time” relationships were obtained and analyzed for different organs and tissues, including for tissues in which the activity of a radiopharmaceutical is impossible or difficult to measure by clinical methods. Also discussed are the features and the results of simulation and dosimetric planning of radioiodine therapy of the thyroid gland. It is shown that the values of absorbed radiation doses are very sensitive to the kinetic parameters of the compartment model. Therefore, special attention should be paid to obtaining accurate quantitative data from ultrasound and thyroid radiometry and identifying simulation parameters based on them. The work is based on the principles and methods of pharmacokinetics. For the numerical solution of systems of differential equations of the pharmacokinetic models we used Runge–Kutta methods and Rosenbrock method. The Hooke–Jeeves method was used to find the minimum of a function of several variables when identifying modeling parameters.

Accurate segmentation of liver plays important in contouring during diagnosis and the planning of treatment. Imaging technology analysis and processing are wide usage in medical diagnostics, and therapeutic applications. Liver segmentation referring to the process of automatic or semi-automatic detection of liver image boundaries. A major difficulty in segmentation of liver image is the high variability as; the human anatomy itself shows major variation modes. In this paper, a proposed approach for computed tomography (CT) liver segmentation is presented by combining exponential entropy and fuzzy c-partition. Entropy concept has been utilized in various applications in imaging computing domain. Threshold techniques based on entropy have attracted a considerable attention over the last years in image analysis and processing literatures and it is among the most powerful techniques in image segmentation. In the proposed approach, the computed tomography (CT) of liver is transformed into fuzzy domain and fuzzy entropies are defined for liver image object and background. In threshold selection procedure, the proposed approach considers not only the information of liver image background and object, but also interactions between them as the selection of threshold is done by find a proper parameter combination of membership function such that the total fuzzy exponential entropy is maximized. Differential Evolution (DE) algorithm is utilizing to optimize the exponential entropy measure to obtain image thresholds. Experimental results in different CT livers scan are done and the results demonstrate the efficient of the proposed approach. Based on the visual clarity of segmented images with varied threshold values using the proposed approach, it was observed that liver segmented image visual quality is better with the results higher level of threshold.

The model of the process of using machinery and equipment is considered, which takes into account the probabilistic nature of the process of their operation and sale. It takes into account the possibility of random hidden failures, after which the condition of the machine deteriorates abruptly, as well as the randomly arising need for premature (before the end of its service life) sale of the machine, which requires, generally speaking, random time. The model is focused on assessing the market value and service life of machines in accordance with International Valuation Standards. Strictly speaking, the market value of a used machine depends on its technical condition, but in practice, appraisers only take into account its age, since generally accepted measures of the technical condition of machines do not yet exist. As a result, the market value of a used machine is assumed to be equal to the average market value of similar machines of the corresponding age. For these purposes, appraisers use coefficients that reflect the influence of the age of machines on their market value. Such coefficients are not always justified and do not take into account either the degradation of the machine or the probabilistic nature of the process of its use. The proposed model is based on the anticipation of benefits principle. In it, we characterize the state of the machine by the intensity of the benefits it brings. The machine is subjected to a complex Poisson failure process, and after failure its condition abruptly worsens and may even reach its limit. Situations also arise that preclude further use of the machine by its owner. In such situations, the owner puts the machine up for sale before the end of its service life (prematurely), and the sale requires a random timing. The model allows us to take into account the influence of such situations and construct an analytical relationship linking the market value of a machine with its condition, and calculate the average coefficients of change in the market value of machines with age. At the same time, it is also possible to take into account the influence of inflation and the scrap cost of the machine. We have found that the rate of prematurely sales has a significant impact on the cost of new and used machines. The model also allows us to take into account the influence of inflation and the scrap value of the machine. We have found that the rate of premature sales has a significant impact on the service life and market value of new and used machines. At the same time, the dependence of the market value of machines on age is largely determined by the coefficient of variation of the service life of the machines. The results obtained allow us to obtain more reasonable estimates of the market value of machines, including for the purposes of the system of national accounts.

The paper estimates the recurrence rate of stock indicies S&P100, CAC40, DAX, FTSE, AMEX, ATX, NASDAQ, BEL20. The introduced qunatitative measure of the recurrence rate underlies type I and type II errors. We show that more than three quarters of the indicies’ falls occur on average during the first quarter of the time between them. This result expands from sufficiently large falls, which are observed on average two times a year, over smaller falls, which occur approximately once 1.5–2 months.