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The dynamics of public attention to COVID-19 epidemic is studied. The level of public attention is described by the daily number of search requests in Google made by users from a given country. In the empirical part of the work, data on the number of requests and the number of infected cases for a number of countries are considered. It is shown that in all cases the maximum of public attention occurs earlier than the maximum daily number of newly infected individuals. Thus, for a certain period of time, the growth of the epidemics occurs in parallel with the decline in public attention to it. It is also shown that the decline in the number of requests is described by an exponential function of time. In order to describe the revealed empirical pattern, a mathematical model is proposed, which is a modification of the model of the decline in attention after a one-time political event. The model develops the approach that considers decision-making by an individual as a member of the society in which the information process takes place. This approach assumes that an individual’s decision about whether or not to make a request on a given day about COVID is based on two factors. One of them is an attitude that reflects the individual’s long-term interest in a given topic and accumulates the individual’s previous experience, cultural preferences, social and economic status. The second is the dynamic factor of public attention to the epidemic, which changes during the process under consideration under the influence of informational stimuli. With regard to the subject under consideration, information stimuli are related to epidemic dynamics. The behavioral hypothesis is that if on some day the sum of the attitude and the dynamic factor exceeds a certain threshold value, then on that day the individual in question makes a search request on the topic of COVID. The general logic is that the higher the rate of infection growth, the higher the information stimulus, the slower decreases public attention to the pandemic. Thus, the constructed model made it possible to correlate the rate of exponential decrease in the number of requests with the rate of growth in the number of cases. The regularity found with the help of the model was tested on empirical data. It was found that the Student’s statistic is 4.56, which allows us to reject the hypothesis of the absence of a correlation with a significance level of 0.01.

In the last quarter of the twentieth century, the nature of global demographic and economic development began to change rapidly: the continuously accelerating growth of the main characteristics that took place over the previous two hundred years was replaced by a sharp slowdown. In the context of these changes, the role of a long-term forecast of global dynamics is increasing. At the same time, the forecast should be based not on inertial projection of past trends into future periods, but on mathematical modeling of fundamental patterns of historical development. The article presents preliminary results of research on mathematical modeling and forecasting of global demographic and economic dynamics based on this approach. The basic dynamic equations reflecting this dynamics are proposed, the modification of these equations in relation to different historical epochs is justified. For each historical epoch, based on the analysis of the corresponding system of equations, a phase portrait was determined and its features were analyzed. Based on this analysis, conclusions were drawn about the patterns of world development in the period under review.

It is shown that mathematical description of technology development is important for modeling historical dynamics. A method for describing technological dynamics is proposed, on the basis of which the corresponding mathematical equations are proposed.

Three stages of historical development are considered: the stage of agrarian society (before the beginning of the XIX century), the stage of industrial society (XIX–XX centuries) and the modern era. The proposed mathematical model shows that an agrarian society is characterized by cyclical demographic and economic dynamics, while an industrial society is characterized by an increase in demographic and economic characteristics close to hyperbolic.

The results of mathematical modeling have shown that humanity is currently moving to a fundamentally new phase of historical development. There is a slowdown in growth and the transition of human society into a new phase state, the shape of which has not yet been determined. Various options for further development are considered.

We comsider a model of the dynamics a political system of several parties, accompanied and controlled by the growth of social tension. A system of nonlinear ordinary differential equations is proposed with respect to fractions and an additional scalar variable characterizing the magnitude of tension in society the change of each party is proportional to the current value multiplied by a coefficient that consists of an influx of novice, a flow from competing parties, and a loss due to the growth of social tension. The change in tension is made up of party contributions and own relaxation. The number of parties is fixed, there are no mechanisms in the model for combining existing or the birth of new parties.

To study of possible scenarios of the dynamic processes of the model we derive an approach based on the selection of conditions under which this problem belongs to the class of cosymmetric systems. For the case of two parties, it is shown that in the system under consideration may have two families of equilibria, as well as a family of limit cycles. The existence of cosymmetry for a system of differential equations is ensured by the presence of additional constraints on the parameters, and in this case, the emergence of continuous families of stationary and nonstationary solutions is possible. To analyze the scenarios of cosymmetry breaking, an approach based on the selective function is applied. In the case of one political party, there is no multistability, one stable solution corresponds to each set of parameters. For the case of two parties, it is shown that in the system under consideration may have two families of equilibria, as well as a family of limit cycles. The results of numerical experiments demonstrating the destruction of the families and the implementation of various scenarios leading to the stabilization of the political system with the coexistence of both parties or to the disappearance of one of the parties, when part of the population ceases to support one of the parties and becomes indifferent are presented.

This model can be used to predict the inter-party struggle during the election campaign. In this case necessary to take into account the dependence of the coefficients of the system on time.

Simulation of combat and military operations is the most important scientific and practical task aimed at providing the command of quantitative bases for decision-making. The first models of combat were developed during the First World War (M. Osipov, F. Lanchester), and now they are widely used in connection with the massive introduction of automation tools. At the same time, the models of combat and war do not fully take into account the moral potentials of the parties to the conflict, which motivates and motivates the further development of models of battle and war. A probabilistic model of combat is considered, in which the parameter of combat superiority is determined through the parameter of moral (the ratio of the percentages of the losses sustained by the parties) and the parameter of technological superiority. To assess the latter, the following is taken into account: command experience (ability to organize coordinated actions), reconnaissance, fire and maneuverability capabilities of the parties and operational (combat) support capabilities. A game-based offensive-defense model has been developed, taking into account the actions of the first and second echelons (reserves) of the parties. The target function of the attackers in the model is the product of the probability of a breakthrough by the first echelon of one of the defense points by the probability of the second echelon of the counterattack repelling the reserve of the defenders. Solved the private task of managing the breakthrough of defense points and found the optimal distribution of combat units between the trains. The share of troops allocated by the parties to the second echelon (reserve) increases with an increase in the value of the aggregate combat superiority parameter of those advancing and decreases with an increase in the value of the combat superiority parameter when repelling a counterattack. When planning a battle (battles, operations) and the distribution of its troops between echelons, it is important to know not the exact number of enemy troops, but their capabilities and capabilities, as well as the degree of preparedness of the defense, which does not contradict the experience of warfare. Depending on the conditions of the situation, the goal of an offensive may be to defeat the enemy, quickly capture an important area in the depth of the enemy’s defense, minimize their losses, etc. For scaling the offensive-defense model for targets, the dependencies of the losses and the onset rate on the initial ratio of the combat potentials of the parties were found. The influence of social costs on the course and outcome of wars is taken into account. A theoretical explanation is given of a loss in a military company with a technologically weak adversary and with a goal of war that is unclear to society. To account for the influence of psychological operations and information wars on the moral potential of individuals, a model of social and information influence was used.

The article analyzes empirical data on the long-term demographic and economic dynamics of the countries of the world for the period from the beginning of the 19th century to the present. Population and GDP of a number of countries of the world for the period 1500–2016 were selected as indicators characterizing the long-term demographic and economic dynamics of the countries of the world. Countries were chosen in such a way that they included representatives with different levels of development (developed and developing countries), as well as countries from different regions of the world (North America, South America, Europe, Asia, Africa). A specially developed mathematical model was used for modeling and data processing. The presented model is an autonomous system of differential equations that describes the processes of socio-economic modernization, including the process of transition from an agrarian society to an industrial and post-industrial one. The model contains the idea that the process of modernization begins with the emergence of an innovative sector in a traditional society, developing on the basis of new technologies. The population is gradually moving from the traditional sector to the innovation sector. Modernization is completed when most of the population moves to the innovation sector.

Statistical methods of data processing and Big Data methods, including hierarchical clustering were used. Using the developed algorithm based on the random descent method, the parameters of the model were identified and verified on the basis of empirical series, and the model was tested using statistical data reflecting the changes observed in developed and developing countries during the period of modernization taking place over the past centuries. Testing the model has demonstrated its high quality — the deviations of the calculated curves from statistical data are usually small and occur during periods of wars and economic crises. Thus, the analysis of statistical data on the long-term demographic and economic dynamics of the countries of the world made it possible to determine general patterns and formalize them in the form of a mathematical model. The model will be used to forecast demographic and economic dynamics in different countries of the world.

When making decisions in various fields of human activity, it is often required to create text documents. Traditionally, the study of texts is engaged in linguistics, which in a broad sense can be understood as a part of semiotics — the science of signs and sign systems, while semiotic objects are of different types. The method of rank distributions is widely used for the quantitative study of sign systems. Rank distribution is a set of item names sorted in descending order by frequency of occurrence. For frequency-rank distributions, researchers often use the term «power-law distributions».

In this paper, the rank distribution method is used to analyze the Criminal Code of various countries. The general idea of the approach to solving this problem is to consider the code as a text document, in which the sign is the measure of punishment for certain crimes. The document is presented as a list of occurrences of a specific word (character) and its derivatives (word forms). The combination of all these signs characters forms a punishment dictionary, for which the occurrence frequency of each punishment in the code text is calculated. This allows us to transform the constructed dictionary into a frequency dictionary of punishments and conduct its further research using the V. P. Maslov approach, proposed to analyze the linguistics problems. This approach introduces the concept of the virtual frequency of crime occurrence, which is an assessment measure of the real harm to society and the consequences of the crime committed in various spheres of human life. On this path, the paper proposes a parametrization of the rank distribution to analyze the punishment dictionary of the Special Part of the Criminal Code of the Russian Federation concerning punishments for economic crimes. Various versions of the code are considered, and the constructed model was shown to reflect objectively undertaken over time by legislators its changes for the better. For the Criminal Codes in force in the Federal Republic of Germany and the People’s Republic of China, the texts including similar offenses and analogous to the Russian special section of the Special Part were studied. The rank distributions obtained in the article for the corresponding frequency dictionaries of codes coincide with those obtained by V. P. Maslov’s law, which essentially clarifies Zipf’s law. This allows us to conclude both the good text organization and the adequacy of the selected punishments for crimes.