All issues

The technology of creating patterns from natural language words (concepts) based on text data in the bag of words model is considered. Patterns are used to reduce the dimension of the original space in the description of documents and search for semantically related words by topic. The process of dimensionality reduction is implemented through the formation of patterns of latent features. The variety of structures of document relations is investigated in order to divide them into themes in the latent space.

It is considered that a given set of documents (objects) is divided into two non-overlapping classes, for the analysis of which it is necessary to use a common dictionary. The belonging of words to a common vocabulary is initially unknown. Class objects are considered as opposition to each other. Quantitative parameters of oppositionality are determined through the values of the stability of each feature and generalized assessments of objects according to non-overlapping sets of features.

To calculate the stability, the feature values are divided into non-intersecting intervals, the optimal boundaries of which are determined by a special criterion. The maximum stability is achieved under the condition that the boundaries of each interval contain values of one of the two classes.

The composition of features in sets (patterns of words) is formed from a sequence ordered by stability values. The process of formation of patterns and latent features based on them is implemented according to the rules of hierarchical agglomerative grouping.

A set of latent features is used for cluster analysis of documents using metric grouping algorithms. The analysis applies the coefficient of content authenticity based on the data on the belonging of documents to classes. The coefficient is a numerical characteristic of the dominance of class representatives in groups.

To divide documents into topics, it is proposed to use the union of groups in relation to their centers. As patterns for each topic, a sequence of words ordered by frequency of occurrence from a common dictionary is considered.

The results of a computational experiment on collections of abstracts of scientific dissertations are presented. Sequences of words from the general dictionary on 4 topics are formed.

The spatiotemporal dynamics of a three-component model for food web is considered. The model describes the interactions among resource, prey and predator that consumes both species. In a previous work, the author analyzed the model without taking into account spatial heterogeneity. This study continues the model study of the community considering the diffusion of individuals, as well as directed movements of the predator. It is assumed that the predator responds to the spatial change in the resource and prey density by occupying areas where species density is higher or avoiding them. Directed predator movement is described by the advection term, where velocity is proportional to the gradient of resource and prey density. The system is considered on a one-dimensional domain with zero-flux conditions as boundary ones. The spatiotemporal dynamics produced by model is determined by the system stability in the vicinity of stationary homogeneous state with respect to small inhomogeneous perturbations. The paper analyzes the possibility of wave instability leading to the emergence of autowaves and Turing instability, as a result of which stationary patterns are formed. Sufficient conditions for the existence of both types of instability are obtained. The influence of local kinetic parameters on the spatial structure formation was analyzed. It was shown that only Turing instability is possible when taxis on the resource is positive, but with a negative taxis, both types of instability are possible. The numerical solution of the system was found by using method of lines (MOL) with the numerical integration of ODE system by means of splitting techniques. The spatiotemporal dynamics of the system is presented in several variants, realizing one of the instability types. In the case of a positive taxis on the prey, both autowave and stationary structures are formed in smaller regions, with an increase in the region size, Turing structures are not formed. For negative taxis on the prey, stationary patterns is observed in both regions, while periodic structures appear only in larger areas.

The paper proposes a set of fairly simple analysis algorithms that can be used to analyze a wide range of protein-protein interactions. In this work, we jointly use the methods of Brownian and molecular dynamics to describe the process of formation of a complex of plastocyanin and cytochrome f proteins in higher plants. In the diffusion-collision complex, two clusters of structures were revealed, the transition between which is possible with the preservation of the position of the center of mass of the molecules and is accompanied only by a rotation of plastocyanin by 134 degrees. The first and second clusters of structures of collisional complexes differ in that in the first cluster with a positively charged region near the small domain of cytochrome f, only the “lower” plastocyanin region contacts, while in the second cluster, both negatively charged regions. The “upper” negatively charged region of plastocyanin in the first cluster is in contact with the amino acid residue of lysine K122. When the final complex is formed, the plastocyanin molecule rotates by 69 degrees around an axis passing through both areas of electrostatic contact. With this rotation, water is displaced from the regions located near the cofactors of the molecules and formed by hydrophobic amino acid residues. This leads to the appearance of hydrophobic contacts, a decrease in the distance between the cofactors to a distance of less than 1.5 nm, and further stabilization of the complex in a position suitable for electron transfer. Characteristics such as contact matrices, rotation axes during the transition between states, and graphs of changes in the number of contacts during the modeling process make it possible to determine the key amino acid residues involved in the formation of the complex and to reveal the physicochemical mechanisms underlying this process.

Monkeypox is a disease reemerging in 2022 which is caused by the monkeypox virus (MPV). This disease can be transmitted not only from rodents to humans, but also from humans to other humans, and even from the environment to humans. In this work, we propose a mathematical model to capture the dynamics of monkeypox transmission which involve three modes of transmission, namely, from rodents to rodents, rodents to humans, and from humans to other humans. In addition to the basic reproduction number, we investigate the stability of all equilibrium points analytically, including an implicit endemic equilibrium by applying the center manifold theorem. Moreover, the vaccination as an alternative solution to eradicate the monkeypox transmission is discussed and solved as an optimal control problem. The results of this study show that the transmission of monkeypox is directly affected by the internal infection rates of each population, i. e., the infection rate of the susceptible human by an infected human and the infection rate of the susceptible rodent by an infected rodent. Furthermore, the external infection rates, i. e., the infection rate of the susceptible human by an infected rodent also affects the transmission of monkeypox although it does not affect the basic reproduction number directly.

Despite the widespread use of cancer chemotherapy drugs, the molecular mechanisms of action of many of them remain unclear. Some of these drugs, such as taxol, are known to affect the dynamics of microtubule assembly and stop the process of cell division in prophase-prometaphase. Recently, new spatial structures of microtubules and individual tubulin oligomers have emerged associated with various regulatory proteins and cancer chemotherapy drugs. However, knowledge of the spatial structure in itself does not provide information about the mechanism of action of drugs.

In this work, we applied the molecular dynamics method to study the behavior of taxol-bound tubulin oligomers and used our previously developed method for analyzing the conformation of tubulin protofilaments, based on the calculation of modified Euler angles. Recent structures of microtubule fragments have demonstrated that tubulin protofilaments bend not in the radial direction, as many researchers assume, but at an angle of approximately 45◦ from the radial direction. However, in the presence of taxol, the bending direction shifts closer to the radial direction. There was no significant difference between the mean bending and torsion angles of the studied tubulin structures when bound to the various natural regulatory ligands, guanosine triphosphate and guanosine diphosphate. The intra-dimer bending angle was found to be greater than the interdimer bending angle in all analyzed trajectories. This indicates that the bulk of the deformation energy is stored within the dimeric tubulin subunits and not between them. Analysis of the structures of the latest generation of tubulins indicated that the presence of taxol in the tubulin beta subunit pocket allosterically reduces the torsional rigidity of the tubulin oligomer, which could explain the underlying mechanism of taxol’s effect on microtubule dynamics. Indeed, a decrease in torsional rigidity makes it possible to maintain lateral connections between protofilaments, and therefore should lead to the stabilization of microtubules, which is what is observed in experiments. The results of the work shed light on the phenomenon of dynamic instability of microtubules and allow to come closer to understanding the molecular mechanisms of cell division.

This paper studies a model of a population with non-overlapping generations and density-dependent regulation of birth rate. The population breeds seasonally, and its reproductive potential is determined genetically. The model proposed combines an ecological dynamic model of a limited population with non-overlapping generations and microevolutionary model of its genetic structure dynamics for the case when adaptive trait of birth rate controlled by a single diallelic autosomal locus with allelomorphs A and a. The study showed the genetic composition of the population, namely, will it be polymorphic or monomorphic, is mainly determined by the values of the reproductive potentials of heterozygote and homozygotes. Moreover, the average reproductive potential of mature individuals and intensity of self-regulation processes determine population dynamics. In particularly, increasing the average value of the reproductive potential leads to destabilization of the dynamics of age group sizes. The intensity of self-regulation processes determines the nature of emerging oscillations, since scenario of stability loss of fixed points depends on the values of this parameter. It is shown that patterns of occurrence and evolution of cyclic dynamics regimes are mainly determined by the features of life cycle of individuals in population. The life cycle leading to existence of non-overlapping generation gives isolated subpopulations in different years, which results in the possibility of independent microevolution of these subpopulations and, as a result, the complex dynamics emergence of both stage structure and genetic one. Fixing various adaptive mutations will gradually lead to genetic (and possibly morphological) differentiation and to differences in the average reproductive potentials of subpopulations that give different values of equilibrium subpopulation sizes. Further evolutionary growth of reproductive potentials of limited subpopulations leads to their number fluctuations which can differ in both amplitude and phase.

Muscle contraction is controlled by Ca2+ ions via regulatory proteins, troponin and tropomyosin, associated with thin actin filaments in sarcomeres. Depending on the Ca2+ concentration, the thin filament rearranges so that tropomyosin moves along its surface, opening or closing access to actin for the motor domains of myosin molecules, and causing contraction or relaxation, respectively. Numerous point amino acid substitutions in tropomyosin are known, leading to genetic pathologies — myo- and cardiomyopathies caused by changes in the structural and functional properties of the thin filament. The results of molecular dynamics modeling of a fragment of a thin filament of cardiac muscle sarcomeres formed by fibrillar actin and wildtype tropomyosin or with amino acid substitutions: the double stabilizing substitution D137L/G126R and the cardiomyopathic substitution S215L are presented. For numerical calculations, we used a new model of a thin filament fragment containing 26 actin monomers and 4 tropomyosin dimers, with a refined structure of the region of overlap of neighboring tropomyosin molecules in each of the two tropomyosin strands. The simulation results showed that tropomyosin significantly increases the bending stiffness of the thin filament, as previously found experimentally. The double stabilizing replacement D137L/G126R leads to a further increase in this rigidity, and the replacement S215L, on the contrary, leads to its decrease, which also corresponds to experimental data. At the same time, these substitutions have different effects on the angular mobility of the actin helix and only slightly modulate the angular mobility of tropomyosin cables relative to the actin helix and the population of hydrogen bonds between negatively charged tropomyosin residues and positively charged actin residues. The results of the verification of the new model demonstrate that its quality is sufficient for the numerical study of the effect of single amino acid substitutions on the structure and dynamics of thin filaments and study the effects leading to dysregulation of muscle contraction. This model can be used as a useful tool for elucidating the molecular mechanisms of some genetic diseases and assessing the pathogenicity of newly discovered genetic variants.

Laminar-turbulent transition is the subject of an active research related to improvement of economic efficiency of air vehicles, because in the turbulent boundary layer drag increases, which leads to higher fuel consumption. One of the directions of such research is the search for efficient methods, that can be used to find the position of the transition in space. Using this information about laminar-turbulent transition location when designing an aircraft, engineers can predict its performance and profitability at the initial stages of the project. Traditionally, $e^N$ method is applied to find the coordinates of a laminar-turbulent transition. It is a well known approach in industry. However, despite its widespread use, this method has a number of significant drawbacks, since it relies on parallel flow assumption, which limits the scenarios for its application, and also requires computationally expensive calculations in a wide range of frequencies and wave numbers. Alternatively, flow analysis can be done by using Dynamic Mode Decomposition, which allows one to analyze flow disturbances using flow data directly. Since Dynamic Mode Decomposition is a dimensionality reduction method, the number of computations can be dramatically reduced. Furthermore, usage of Dynamic Mode Decomposition expands the applicability of the whole method, due to the absence of assumptions about the parallel flow in its derivation.

The presented study proposes an approach to finding the location of a laminar-turbulent transition using the Dynamic Mode Decomposition method. The essence of this approach is to divide the boundary layer region into sets of subregions, for each of which the transition point is independently calculated, using Dynamic Mode Decomposition for flow analysis, after which the results are averaged to produce the final result. This approach is validated by laminar-turbulent transition predictions of subsonic and supersonic flows over a 2D flat plate with zero pressure gradient. The results demonstrate the fundamental applicability and high accuracy of the described method in a wide range of conditions. The study focuses on comparison with the $e^N$ method and proves the advantages of the proposed approach. It is shown that usage of Dynamic Mode Decomposition leads to significantly faster execution due to less intensive computations, while the accuracy is comparable to the such of the solution obtained with the $e^N$ method. This indicates the prospects for using the described approach in a real world applications.

The paper considers the basic model of competitive interactions and its use for the analysis and description of social processes. The peculiarity of the model is that it describes the interaction of several competing actors, while actors can vary the strategy of their actions, in particular, form coalitions to jointly counter a common enemy. As a result of modeling, various modes of competitive interaction were identified, their classification was conducted, and their features were described. In the course of the study, the attention is paid to the so-called “rough” (according to A.A. Andronov) cases of the implementation of competitive interaction, which until now have rarely been considered in the scientific literature, but are quite common in real life. Using a basic mathematical model, the conditions for the implementation of various modes of competitive interactions are considered, the conditions for the transition from one mode to another are determined, examples of the implementation of these modes in the economy, social and political life are given. It is shown that with a relatively low level of competition, which is non-antagonistic in nature, competition can lead to an increase in the activity of interacting actors and to overall economic growth. Moreover, in the presence of expanding resource opportunities (as long as such opportunities remain), this growth may have a hyperbolic character. With a decrease in resource capabilities and increased competition, there is a transition to an oscillatory mode, when weaker actors unite to jointly counteract stronger ones. With a further decrease in resource opportunities and increased competition, there is a transition to the formation of stable hierarchical structures. At the same time, the model shows that at a certain moment there is a loss of stability, the system becomes “rough” according to A.A. Andronov and sensitive to fluctuations in parameter changes. As a result, the existing hierarchies may collapse and be replaced by new ones. With a further increase in the intensity of competition, the actor-leader completely suppresses his opponents and establishes monopolism. Examples from economic, social, and political life are given, illustrating the patterns identified on the basis of modeling using the basic model of competition. The obtained results can be used in the analysis, modeling and forecasting of socioeconomic and political processes.

We propose a four-component model of a plankton community with discrete time. The model considers the competitive relationships of phytoplankton groups exhibited between each other and the trophic characteristics zooplankton displays: it considers the division of zooplankton into predatory and non-predatory components. The model explicitly represents the consumption of non-predatory zooplankton by predatory. Non-predatory zooplankton feeds on phytoplankton, which includes two competing components: toxic and non-toxic types, with the latter being suitable for zooplankton food. A model of two coupled Ricker equations, focused on describing the dynamics of a competitive community, describes the interaction of two phytoplanktons and allows implicitly taking into account the limitation of each of the competing components of biomass growth by the availability of external resources. The model describes the prey consumption by their predators using a Holling type II trophic function, considering predator saturation.

The analysis of scenarios for the transition from stationary dynamics to fluctuations in the population size of community members showed that the community loses the stability of the non-trivial equilibrium corresponding to the coexistence of the complete community both through a cascade of period-doubling bifurcations and through a Neimark – Sacker bifurcation leading to the emergence of quasi-periodic oscillations. Although quite simple, the model proposed in this work demonstrates dynamics of comunity similar to that natural systems and experiments observe: with a lag of predator oscillations relative to the prey by about a quarter of the period, long-period antiphase cycles of predator and prey, as well as hidden cycles in which the prey density remains almost constant, and the predator density fluctuates, demonstrating the influence fast evolution exhibits that masks the trophic interaction. At the same time, the variation of intra-population parameters of phytoplankton or zooplankton can lead to pronounced changes the community experiences in the dynamic mode: sharp transitions from regular to quasi-periodic dynamics and further to exact cycles with a small period or even stationary dynamics. Quasi-periodic dynamics can arise at sufficiently small phytoplankton growth rates corresponding to stable or regular community dynamics. The change of the dynamic mode in this area (the transition from stable dynamics to quasi-periodic and vice versa) can occur due to the variation of initial conditions or external influence that changes the current abundances of components and shifts the system to the basin of attraction of another dynamic mode.