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Currently, journal papers contain numerous examples of the use of heavy-tailed distributions for applied research on various complex systems. Models of extreme data are usually limited to a small set of distribution shapes that in this field of applied research historically been used. It is possible to increase the composition of the set of probability distributions shapes through comparing the measures of the distribution shapes and choosing the most suitable implementations. The example of a beta distribution of the second kind shown that the lack of definability of the moments of heavy-tailed implementations of the beta family of distributions limits the applicability of the existing classical methods of moments for studying the distributions shapes when are characterized heavy tails. For this reason, the development of new methods for comparing distributions based on quantile shape measures free from the restrictions on the shape parameters remains relevant study the possibility of constructing a space of quantile measures of shapes for comparing distributions with heavy tails. The operation purpose consists in computer research of creation possibility of space of the quantile’s measures for the comparing of distributions property with heavy tails. On the basis of computer simulation there the distributions implementations in measures space of shapes were been shown. Mapping distributions in space only of the parametrical measures of shapes has shown that the imposition of regions for heavy tails distribution made impossible compare the shape of distributions belonging to different type in the space of quantile measures of skewness and kurtosis. It is well known that shape information measures such as entropy and entropy uncertainty interval contain additional information about the shape measure of heavy-tailed distributions. In this paper, a quantile entropy coefficient is proposed as an additional independent measure of shape, which is based on the ratio of entropy and quantile uncertainty intervals. Also estimates of quantile entropy coefficients are obtained for a number of well-known heavy-tailed distributions. The possibility of comparing the distributions shapes with realizations of the beta distribution of the second kind is illustrated by the example of the lognormal distribution and the Pareto distribution. Due to mapping the position of stable distributions in the three-dimensional space of quantile measures of shapes estimate made it possible the shape parameters to of the beta distribution of the second kind, for which shape is closest to the Lévy shape. From the paper material it follows that the display of distributions in the three-dimensional space of quantile measures of the forms of skewness, kurtosis and entropy coefficient significantly expands the possibility of comparing the forms for distributions with heavy tails.

In this paper, we consider the problem of restoring the correspondence matrix based on the observations of real correspondences in Moscow. Following the conventional approach [Gasnikov et al., 2013], the transport network is considered as a directed graph whose edges correspond to road sections and the graph vertices correspond to areas that the traffic participants leave or enter. The number of city residents is considered constant. The problem of restoring the correspondence matrix is to calculate all the correspondence from the $i$ area to the $j$ area.

To restore the matrix, we propose to use one of the most popular methods of calculating the correspondence matrix in urban studies — the entropy model. In our work, which is based on the work [Wilson, 1978], we describe the evolutionary justification of the entropy model and the main idea of the transition to solving the problem of entropy-linear programming (ELP) in calculating the correspondence matrix. To solve the ELP problem, it is proposed to pass to the dual problem. In this paper, we describe several numerical optimization methods for solving this problem: the Sinkhorn method and the Accelerated Sinkhorn method. We provide numerical experiments for the following variants of cost functions: a linear cost function and a superposition of the power and logarithmic cost functions. In these functions, the cost is a combination of average time and distance between areas, which depends on the parameters. The correspondence matrix is calculated for multiple sets of parameters and then we calculate the quality of the restored matrix relative to the known correspondence matrix.

We assume that the noise in the restored correspondence matrix is Gaussian, as a result, we use the standard deviation as a quality metric. The article provides an overview of gradient-free optimization methods for solving non-convex problems. Since the number of parameters of the cost function is small, we use the grid search method to find the optimal parameters of the cost function. Thus, the correspondence matrix calculated for each set of parameters and then the quality of the restored matrix is evaluated relative to the known correspondence matrix. Further, according to the minimum residual value for each cost function, we determine for which cost function and at what parameter values the restored matrix best describes real correspondence.

Authors describe a two-stage traffic assignment model. It contains of two blocks. The first block consists of a model for calculating a correspondence (demand) matrix, whereas the second block is a traffic assignment model. The first model calculates a matrix of correspondences using a matrix of transport costs (it characterizes the required volumes of movement from one area to another, it is time in this case). To solve this problem, authors propose to use one of the most popular methods of calculating the correspondence matrix in urban studies — the entropy model. The second model describes exactly how the needs for displacement specified by the correspondence matrix are distributed along the possible paths. Knowing the ways of the flows distribution along the paths, it is possible to calculate the cost matrix. Equilibrium in a two-stage model is a fixed point in the sequence of these two models. In practice the problem of finding a fixed point can be solved by the fixed-point iteration method. Unfortunately, at the moment the issue of convergence and estimations of the convergence rate for this method has not been studied quite thoroughly. In addition, the numerical implementation of the algorithm results in many problems. In particular, if the starting point is incorrect, situations may arise where the algorithm requires extremely large numbers to be computed and exceeds the available memory even on the most modern computers. Therefore the article proposes a method for reducing the problem of finding the equilibrium to the problem of the convex non-smooth optimization. Also a numerical method for solving the obtained optimization problem is proposed. Numerical experiments were carried out for both methods of solving the problem. The authors used data for Vladivostok (for this city information from various sources was processed and collected in a new dataset) and two smaller cities in the USA. It was not possible to achieve convergence by the method of fixed-point iteration, whereas the second model for the same dataset demonstrated convergence rate $k^{-1.67}$.

We consider one of the problems of transport modelling — searching the equilibrium distribution of traffic flows in the network. We use the classic Beckman’s model to describe time costs and flow distribution in the network represented by directed graph. Meanwhile agents’ behavior is not completely rational, what is described by the introduction of Markov logit dynamics: any driver selects a route randomly according to the Gibbs’ distribution taking into account current time costs on the edges of the graph. Thus, the problem is reduced to searching of the stationary distribution for this dynamics which is a stochastic Nash – Wardrope equilibrium in the corresponding population congestion game in the transport network. Since the game is potential, this problem is equivalent to the problem of minimization of some functional over flows distribution. The stochasticity is reflected in the appearance of the entropy regularization, in contrast to non-stochastic case. The dual problem is constructed to obtain a solution of the optimization problem. The universal primal-dual gradient method is applied. A major specificity of this method lies in an adaptive adjustment to the local smoothness of the problem, what is most important in case of the complex structure of the objective function and an inability to obtain a prior smoothness bound with acceptable accuracy. Such a situation occurs in the considered problem since the properties of the function strongly depend on the transport graph, on which we do not impose strong restrictions. The article describes the algorithm including the numerical differentiation for calculation of the objective function value and gradient. In addition, the paper represents a theoretical estimate of time complexity of the algorithm and the results of numerical experiments conducted on a small American town.

This paper considers various approaches to averaging the generalized travel costs calculated for different modes of travel in the transportation network. The mode of transportation is understood to mean both the mode of transport, for example, a car or public transport, and movement without the use of transport, for example, on foot. The task of calculating the trip matrices includes the task of calculating the total matrices, in other words, estimating the total demand for movements by all modes, as well as the task of splitting the matrices according to the mode, also called modal splitting. To calculate trip matrices, gravitational, entropy and other models are used, in which the probability of movement between zones is estimated based on a certain measure of the distance of these zones from each other. Usually, the generalized cost of moving along the optimal path between zones is used as a distance measure. However, the generalized cost of movement differs for different modes of movement. When calculating the total trip matrices, it becomes necessary to average the generalized costs by modes of movement. The averaging procedure is subject to the natural requirement of monotonicity in all arguments. This requirement is not met by some commonly used averaging methods, for example, averaging with weights. The problem of modal splitting is solved by applying the methods of discrete choice theory. In particular, within the framework of the theory of discrete choice, correct methods have been developed for averaging the utility of alternatives that are monotonic in all arguments. The authors propose some adaptation of the methods of the theory of discrete choice for application to the calculation of the average cost of movements in the gravitational and entropy models. The transfer of averaging formulas from the context of the modal splitting model to the trip matrix calculation model requires the introduction of new parameters and the derivation of conditions for the possible value of these parameters, which was done in this article. The issues of recalibration of the gravitational function, which is necessary when switching to a new averaging method, if the existing function is calibrated taking into account the use of the weighted average cost, were also considered. The proposed methods were implemented on the example of a small fragment of the transport network. The results of calculations are presented, demonstrating the advantage of the proposed methods.

As the population of cities grows, the need to plan for the development of transport infrastructure becomes more acute. For this purpose, transport modeling packages are created. These packages usually contain a set of convex optimization problems, the iterative solution of which leads to the desired equilibrium distribution of flows along the paths. One of the directions for the development of transport modeling is the construction of more accurate generalized models that take into account different types of passengers, their travel purposes, as well as the specifics of personal and public modes of transport that agents can use. Another important direction of transport models development is to improve the efficiency of the calculations performed. Since, due to the large dimension of modern transport networks, the search for a numerical solution to the problem of equilibrium distribution of flows along the paths is quite expensive. The iterative nature of the entire solution process only makes this worse. One of the approaches leading to a reduction in the number of calculations performed is the construction of consistent models that allow to combine the blocks of a 4-stage model into a single optimization problem. This makes it possible to eliminate the iterative running of blocks, moving from solving a separate optimization problem at each stage to some general problem. Early work has proven that such approaches provide equivalent solutions. However, it is worth considering the validity and interpretability of these methods. The purpose of this article is to substantiate a single problem, that combines both the calculation of the trip matrix and the modal choice, for the generalized case when there are different layers of demand, types of agents and classes of vehicles in the transport network. The article provides possible interpretations for the gauge parameters used in the problem, as well as for the dual factors associated with the balance constraints. The authors of the article also show the possibility of combining the considered problem with a block for determining network load into a single optimization problem.

The practical application of nuclear medicine demonstrates the continued information deficiency of the algorithms and programs that provide visualization and analysis of medical images. The aim of the study was to determine the principles of optimizing the processing of planar osteostsintigraphy on the basis of сomputer aided diagnosis (CAD) for analysis of texture descriptions of images of metastatic zones on planar scintigrams of skeleton. A computer-aided diagnosis system for analysis of skeletal metastases based on planar scintigraphy data has been developed. This system includes skeleton image segmentation, calculation of textural, histogram and morphometrical parameters and the creation of a training set. For study of metastatic images’ textural characteristics on planar scintigrams of skeleton was developed the computer program of automatic analysis of skeletal metastases is used from data of planar scintigraphy. Also expert evaluation was used to distinguishing ‘pathological’ (metastatic) from ‘physiological’ (non-metastatic) radiopharmaceutical hyperfixation zones in which Haralick’s textural features were determined: autocorrelation, contrast, ‘forth moment’ and heterogeneity. This program was established on the principles of сomputer aided diagnosis researches planar scintigrams of skeletal patients with metastatic breast cancer hearths hyperfixation of radiopharmaceuticals were identified. Calculated parameters were made such as brightness, smoothness, the third moment of brightness, brightness uniformity, entropy brightness. It has been established that in most areas of the skeleton of histogram values of parameters in pathologic hyperfixation of radiopharmaceuticals predominate over the same values in the physiological. Most often pathological hyperfixation of radiopharmaceuticals as the front and rear fixed scintigramms prevalence of brightness and smoothness of the image brightness in comparison with those of the physiological hyperfixation of radiopharmaceuticals. Separate figures histogram analysis can be used in specifying the diagnosis of metastases in the mathematical modeling and interpretation bone scintigraphy. Separate figures histogram analysis can be used in specifying the diagnosis of metastases in the mathematical modeling and interpretation bone scintigraphy.

The biological structure is considered as an open nonequilibrium system which properties can be described on the basis of kinetic equations. New problems with nonequilibrium boundary conditions are introduced. The nonequilibrium distribution tends gradually to an equilibrium state. The region of spatial inhomogeneity has a scale depending on the rate of mass transfer in the open system and the characteristic time of metabolism. In the proposed approximation, the internal energy of the motion of molecules is much less than the energy of translational motion. Or in other terms we can state that the kinetic energy of the average blood velocity is substantially higher than the energy of chaotic motion of the same particles. We state that the relaxation problem models a living system. The flow of entropy to the system decreases in downstream, this corresponds to Shrödinger’s general ideas that the living system “feeds on” negentropy. We introduce a quantity that determines the complexity of the biosystem, more precisely, this is the difference between the nonequilibrium kinetic entropy and the equilibrium entropy at each spatial point integrated over the entire spatial region. Solutions to the problems of spatial relaxation allow us to estimate the size of biosystems as regions of nonequilibrium. The results are compared with empirical data, in particular, for mammals we conclude that the larger the size of animals, the smaller the specific energy of metabolism. This feature is reproduced in our model since the span of the nonequilibrium region is larger in the system where the reaction rate is shorter, or in terms of the kinetic approach, the longer the relaxation time of the interaction between the molecules. The approach is also used for estimation of a part of a living system, namely a green leaf. The problems of aging as degradation of an open nonequilibrium system are considered. The analogy is related to the structure, namely, for a closed system, the equilibrium of the structure is attained for the same molecules while in the open system, a transition occurs to the equilibrium of different particles, which change due to metabolism. Two essentially different time scales are distinguished, the ratio of which is approximately constant for various animal species. Under the assumption of the existence of these two time scales the kinetic equation splits in two equations, describing the metabolic (stationary) and “degradative” (nonstationary) parts of the process.

Self-organization of molecules on a solid surface is one of the promising directions for materials generation with unique magnetic, electrical, and optical properties. They can be widely used in fields such as electronics, optoelectronics, catalysis, and biology. However, the structure and physicochemical properties of adsorbed molecules are influenced by many parameters that must be taken into account when studying the self-organization of molecules. Therefore, the experimental study of such materials is expensive, and quite often it is difficult for various reasons. In such situations, it is advisable to use the mathematical modeling. One of the parameters in the considered adsorption systems is the multiparticle interaction, which is often not taken into account in simulations due to the complexity of the calculations. In this paper, we evaluated the influence of multiparticle interactions on the total energy of the system using the transfer-matrix method and the Materials Studio software package. The model of monocentric adsorption with nearest interactions on a triangular lattice was taken as the basis. Phase diagrams in the ground state were constructed and a number of thermodynamic characteristics (coverage $\theta$, entropy $S$, susceptibility $\xi$) were calculated at nonzero temperatures. The formation of all four ordered structures (lattice gas with $\theta=0$, $(\sqrt{3} \times \sqrt{3}) R30^{\circ}$ with $\theta = \frac{1}{3}$, $(\sqrt{3} \times \sqrt{3})R^{*}30^{\circ}$ with $\theta = \frac{2}{3}$ and densest phase with $\theta = 1$) in a system with only pairwise interactions, and the absence of the phase  $(\sqrt{3}\times \sqrt{3}) R30^\circ$ when only three-body interactions are taken into account, were found. Using the example of an atomistic model of the trimesic acid adsorption layer by quantum mechanical methods we determined that in such a system the contribution of multiparticle interactions is 11.44% of the pair interactions energy. There are only quantitative differences at such values. The transition region from the  $(\sqrt{3} \times \sqrt{3}) R^{*}30^\circ$ to the densest phase shifts to the right by 38.25% at $\frac{\varepsilon}{RT} = 4$ and to the left by 23.46% at $\frac{\varepsilon}{RT} = −2$.

The transition from α-helices to β-strands under external mechanical force in fibrin molecule containing coiled-coils is studied and free energy landscape is resolved. The detailed theoretical modeling of each stage of coiled-coils fragment pulling process was performed. The plots of force (F) as a function of molecule expansion (X) for two symmetrical fibrin coiled-coils (each ∼17 nm in length) show three distinct modes of mechanical behaviour: (1) linear (elastic) mode when coiled-coils behave like entropic springs (F<100−125 pN and X<7−8 nm), (2) viscous (plastic) mode when molecule resistance force does not increase with increase in elongation length (F≈150 pN and X≈10−35 nm) and (3) nonlinear mode (F>175−200 pN and X>40−50 nm). In linear mode the coiled-coils unwind at 2π radian angle, but no structural transition occurs. Viscous mode is characterized by the phase transition from the triple α-spirals to three-stranded parallel β-sheet. The critical tension of α-helices is 0.25 nm per turn, and the characteristic energy change is equal to 4.9 kcal/mol. Changes in internal energy Δu, entropy Δs and force capacity c_f per one helical turn for phase transition were also computed. The observed dynamic behavior of α-helices and phase transition from α-helices to β-sheets under tension might represent a universal mechanism of regulation of fibrillar protein structures subject to mechanical stresses due to biological forces.