Ministry of Emergency Situations

The analysis of annealing parameters effect on foam glass structural characteristics in order to purposefully control its properties is presented. The main attention is paid to the mathematical modeling of heat transfer processes and foam glass sample stress-strain state at the technological stage of annealing. The mathematical modeling methods for glass and foam glass annealing evolution is considered, various modeling approaches, including algebraic equations, integral and differential models, relaxation kinetic theory, numerical methods, and discrete modeling are analyzed. The study highlights that to understand the mechanisms of the heat transfer and the foam glass structure formation for production optimization is especially important.

The aim is to analyze deaths in armed conflicts in regions of the world over the past 10 years from 2015 to 2024. Research materials and methods. The object of the study was the electronic database on armed conflicts UCDP/PRIO [https://ucdp.uu.se/]. The indicators of armed conflicts and deaths in them were calculated by region (Europe, Asia, America, Africa and the Middle East). Statistical processing of the results was carried out in Microsoft Excel 2007 spreadsheets. The dynamics of the indicators were assessed with using the analysis of dynamic series and the calculation of a second-order polynomial trend. Research results and their analysis. 1,754 armed conflicts were recorded in the world over 10 years (2015–2024), including 557 (31.8%) state and 792 (45.2%) non-state. 1 million 489.3 thousand people died in armed conflicts, 1 million 187.2 thousand (79.7%) in state and 213 thousand (14.3%) in non-state conflicts. There is a trend towards an increase in the number of armed conflicts in the world and the number of people killed in them. The number of combatants killed in state conflicts was 81.2%, civilians – 11.5%, unidentified persons – 7.3%, and in non-state conflicts – 25.4%, 6.5 and 68.1%, respectively. The average annual individual risk of dying as a result of armed conflicts in the world was 19.3 · 10–6 deaths/(person year ), including 15.3 · 10–6 in state conflicts and 2.7 · 10–6 deaths/(person year ) in non-state conflicts. The number of deaths can be extrapolated to sanitary losses and, thus, optimize the forces and resources of disaster medicine.

Introduction. Obesity is a chronic disease caused by excessive accumulation of adipose tissue in the body, whereby genetic characteristics of patients play a significant role. Firefighters of the Federal Fire Service (FFS) of the EMERCOM of Russia are among those at risk of obesity due to occupational stress factors. The objective is to analyze the correlation between the polymorphic variants of vitamin D receptor and the MCM6 gene, the latter associated with lactose intolerance, on the one hand, ang the risk of obesity, on the other hand, among the FFS firefighters of the EMERCOM of Russia. Methods. Methodology. A total of 109 male employees of the FFS of the EMERCOM of Russia aged 19–45 years were examined. The genetic status was assessed by single nucleotide polymorphisms: BsmI, A>G (rs1544410) of the vitamin D receptor gene and 13910 C>T (rs4988235) of the MCM6 gene. Results and analysis. The analysis of anthropometric and medical history data showed that firefighters showing lactase persistence genotype have higher body mass than those having lactose intolerance genotypes; the former have a higher obesity prevalence compared to other groups. The vitamin D receptor genotype is also associated with higher body weight and BMI among firefighters. Genotypes associated with an increased risk of high body mass and obesity were identified: AA/TT and AA/TC homozygosity of the A allele of the vitamin D receptor gene and carrying homozygous or heterozygous T allele of the MCM6 gene. The risk of obesity in such genotypes is nearly ten times higher, with the relative risk (RR) equal to 9.38. Conclusion. The findings demonstrate the efficiency of hereditary risk factor analysis associated with obesity among the FFS employees of the EMERCOM of Russia.

This article analyzes methods and approaches for predicting incident development using social media information. It demonstrates the relevance of the research topic and demonstrates that existing methods and approaches have several shortcomings that prevent them from being adequately utilized to address the needs of EMERCOM of Russia. In the article's conclusion, the author concludes that it would be beneficial to develop a new, proprietary methodology that would address the identified shortcomings.

Objectives. In a measuring system based on the inductive transmission of information from a moving structure to a stationary signal receiver, the signal carrying useful information about the parameters of the moving structure is formed by a magnetic system containing a permanent magnet mounted on the stationary part of the measuring system. The magnetic field of the permanent magnet (MFPM) determines the magnetic flux, and, consequently, the induction current in a conducting coil located on the moving structure. In order to theoretically justify the parameters of the measuring system including the optimization of its components, a simple and easy-to-use analytical model of the useful signal for determining the requirements for the mathematical description of the MFPM is required. The use of known solutions for developing an analytical model of the useful signal of the measuring system is complicated by the need to use inverse trigonometric functions or the results of numerical calculations. The present work sets out to obtain an exact solution to the problem of calculating the MFPM and on this basis to develop a simple, convenient analytical model of the normal component of the magnetic induction vector (NCMIV) of a permanent magnet used to develop an analytical model of the useful signal.Methods. The equivalent solenoid method was used along with mathematical analysis approaches.Results. An exact solution for calculating the normal component of the magnetic induction vector of the parallelepipedshaped permanent magnet was obtained. Based on this, a straightforward and easy-to-use analytical model of the NCMIV was developed, which closely approximates the formula derived for the exact solution.Conclusions. The developed analytical model of the NCMIV can be used for theoretical development of an analytical model of the useful signal of a measuring system with inductive transmission of information about the parameters of a moving structure to a stationary signal receiver.

Background. The widespread use of the Internet has seriously transformed the life of a modern person, providing him with huge amounts of information for various occasions, both objective and falsified. The network levels out differences in geographical locations, smooths out linguistic barriers, allows one to instantly receive information from the most remote corners of the world, turning into a source of information necessary for study and work, a means of communication, entertainment, income, including prosocial and delinquent ways of self-realization and self-affirmation. Part of the new «norm» in the era of globalization have become practices of autoaggressive behavior - piercing, tattooing, smoking, etc. The younger the child, the more actively the network shapes his worldview, interests, values. The cult of individual success, actively represented on the Internet, gives rise to a feeling of failure, causing a desire to relieve tension through aggressive statements addressed to other people, cyberbullying, etc., which are easier to implement in the virtual space, using anonymous mode or a fake account. Aggressive behavior is formed in the family. Parents who resort to various types of violence form disharmonious ideas about their own «I» in their growing children. In autoaggressive behavior, the emphasis shifts from the external world to the internal one, leading to socio-psychological maladaptation in the long run. Theaimof the study is to analyze the autoaggression phenomenon. Materials and methods. The work uses methods of theoretical analysis of literature, induction, deduction, abstraction. Results. Self-aggression is a consequence of adaptation to conditions that exceed a person's adaptive capabilities, which provokes an increase in somatic and mental illnesses and increases the risk of suicidal behavior. Biological and socio-psychological reasons underlie autoaggression. The negative impact of the reference environment causes object self-perception, personal inflation, reducing the restrictive role of social norms and prohibitions. «Chronic» self-aggression programs a destructive life scenario.

Objective. The aim of the study is to examine approaches to creating an intelligent system, the implementation of which can affect the quality of decisions made by the fire extinguishing manager (FEM) in the process of managing personnel during fire extinguishing. Method. The work uses methods of statistical analysis, control theory, data processing methods and the implementation of production rules for indexing, hashing and clustering of the received information for its further transformation into a knowledge base. Result. The paper presents statistical data on injuries and deaths of fire and rescue unit personnel from thermal consequences caused by the movement of gaseous masses at capital construction sites. The research cycle on defining and applying artificial intelligence methods and algorithms in the process of managing combat operations at the call site is continued. The inadequacy of studies of the smoke-forming ability of building materials affecting the personnel of the Russian Emergencies Ministry at the call site is determined. Conclusion. An algorithm for creating a database of images of smoke generated during combustion of various substances and materials that constitute the main combustible load in the premises of objects of different functional purposes is formulated, and a classifier of smoke images depending on the fire load is proposed. An example of a description of the structure of the database being formed based on existing simulation models and software products is given. A model for forming a knowledge base of the RTP for smoke analysis depending on the type of combustible load is presented.

Every year, the management bodies of the unified state system for emergency prevention and elimination carry out advance preparations for the flood period. However, statistics do not show a decrease in the number of deaths and injuries in floods. This situation is due to the lack of an integrated approach to the systematic assessment and consideration of a set of interrelated factors that determine the social risk of death in floods. A scientific and methodological apparatus for the integral assessment of the societal risk caused by floods was developed. The study is based on the analysis and synthesis of the results of theoretical research, as well as the classification and formalization of the results of empirical research. The scientific and methodological apparatus includes fundamental concepts, metrics of societal risk, models and methods that provide a systematic and multifactorial approach to such an assessment. An algorithm for obtaining an integral indicator of the level of societal risk of such emergencies for a municipality is described, which includes three models: a model of the environment as a digital twin of the area prone to floods; a model of probabilistic assessment of flood hazard depending on the natural and climatic conditions of the modeling region, as well as a digital model of the population of a municipality exposed to the damaging factors of flood water. The algorithm takes into account the probability of timely evacuation of the population during a flood. Finally, the parametric law of human injury through the probability of loss of stability in flood water has been determined. The research was based on the use of hydrology methods, geoinformatics, mathematical modeling, descriptive and predictive statistics, and machine learning. The developed scientific and methodological apparatus can be used in municipalities when solving issues of local importance aimed at protecting the population and the territory of the settlement from emergencies caused by floods.

Understanding and mapping forest fire vulnerability is essential for informed landscape management and disaster risk reduction, especially in the context of increasing anthropogenic and climatic pressures. This study aims to model and spatially predict forest fire vulnerability across Romania using two machine learning algorithms: MaxEnt and XGBoost. We integrated forest fire occurrence data from 2006 to 2024 with a suite of climatic, topographic, ecological, and anthropogenic predictors at a 250 m spatial resolution. MaxEnt, based on presence-only data, achieved moderate predictive performance (AUC = 0.758), while XGBoost, trained on presence–absence data, delivered higher classification accuracy (AUC = 0.988). Both models revealed that the impact of environmental variables on forest fire occurrence is complex and heterogeneous, with the most influential predictors being the Fire Weather Index, forest fuel type, elevation, and distance to human proximity features. The resulting vulnerability and uncertainty maps revealed hotspots in Sub-Carpathian and lowland regions, especially in Mehedinți, Gorj, Dolj, and Olt counties. These patterns reflect historical fire data and highlight the role of transitional agro-forested landscapes. This study delivers a replicable, data-driven approach to wildfire risk modelling, supporting proactive management and emphasising the importance of integrating vulnerability assessments into planning and climate adaptation strategies.