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In this paper a model for the formation of sustainable supply chains of raw materials for a timber processing complex is proposed. The model allows one to optimize the plan of purchases from the Russian Commodity Exchange, as well as the plan of manufacturing finished products. The model presents the task of mathematical programming, whereby the company’s profit is used as the objective function, and the input data include the forecasted values of structure and volumes of offers available on the Russian Commodity Exchange, as well as demand for finished products. The recurrence dependencies of the model describe the flow of raw materials at the enterprise’s warehouse, taking into account revenues from purchased lots, transportation time and consumption of resources that are required for production of simulated volumes of products. Constraints of the model represent formalization of the limited flow of financial resources, taking into account sales and warehouse characteristics. The optimization task deals with variables including volumes of daily output of finished products according to a given nomenclature, as well as variables that specify the inclusion of lots into the portfolio of applications purchased on the exchange. The model solution is found using the branch and bound method with preliminary clipping based on the modified Chvatal–Gomory method. One example considers formation of optimal plans for the purchase and sales in a timber processing complex located in the Primorsky Territory (Russia), which does not have its own forest plots providing production with raw materials. The usefulness of the interaction of the enterprise with the timber department of the commodity and raw materials exchange is assessed.

The relevance of the study of mobile learning as an upcoming trend in education in the context of the COVID-19 pandemic is not denied. The study of students’ ability and motivation to use modern technologies of mobile learning is characterized by novelty. However, the problematic issue of studying the motivation of students and teachers for mobile learning in today's pandemic remains relevant. The purpose of the study is to examine some aspects of the formation of students' motivation (intrinsic motivation: interest in the subject of study, understanding of its significance for further career; extrinsic motivation: points, awards, recognition), as well as the role of teachers in this process and the influence of cognitive abilities of a person on their motivation and academic achievement. The study is based on the method of experiment as well as the interviews and analysis of student reports. There were 185 students (19-22 years old) from Sechenov First Moscow State Medical University and Far Eastern Federal University participating in the study. After the participants had listened to an online lecture on the topic "Neuro-linguistic programming", they were asked to make a report on the topic of the same name and expand the information. Next, the students were interviewed. The results showed that 89% of students were interested in the issue and 69% noted a desire to learn more information on this topic; 100% of participants actively use mobile devices with Internet access for educational purposes and, in particular, for making the required report. However, only 12% of respondents believe that mobile learning alone can be used in order to study specialized disciplines at their university. Thus, 43% of students find it difficult to perceive information from the screen of a smartphone (tablet); 61% of students prefer traditional education to mobile learning, which is probably due to the novelty of this process; 65% of respondents noticed that their knowledge is deteriorating due to the use of mobile (distance) learning. In connection with the results obtained, the following recommendations were made to improve the educational process: to explain to students the importance and usefulness of the topic under study; to use adequate pedagogical methods in the context of mobile learning; to provide feedback and the ability to communicate to students during mobile learning; to take into account the personality and learning style of a student; to use all types of intrinsic and extrinsic motivation of students in accordance with specific circumstances. The most popular motivation factors for mobile learning are possibility of improving exam grades (65%), possibility of improving knowledge (25%), and broadening horizons and deep interest in the topic (10%). Developing applications that will take into account the needs of a particular university and specialty will also make a contribution. Teachers are also encouraged to use a play-based approach and a student reward system in order to increase the level of motivation (additional points, a simplified exam scheme, etc.). The practical significance and prospects for further research are presented by the opportunities of increasing students’ motivation in the context of mobile learning, and, consequently, the success of their studies. The results can be used in the comparative study of mobile learning possibilities in modern conditions and teachers’ involvement in it in different countries.

Supply chain management is a burning issue for modern industrial enterprises. To handle this issue, non-linear stochastic models are successfully applied to find the reasonable and efficient solutions. A need to develop a unique method to find the solutions to supply chain management tasks defined as stochastic mixed-integer non-linear programming tasks is determined by the limitations imposed by the general models. The sum of the total raw procurement costs from the Commodity Exchange over the defined planning horizon is taken to be the target function of the unique model, while the binary variables which show whether a purchasing order is included into the procurement plan are used for optimization purposes. Some parameters of model’s limitations are stochastic and consider the uncertainty factor and risks in supplying the required raw materials to the manufacturing site. Branch-and-bound and genetic algorithms are applied at some steps in the developed heuristic algorithm. The algorithm and the model are tested at a major timber processing enterprise in Primorsky Area. Four types of processors over three planning horizons were applied to compare the efficiency of the proposed algorithm with partial application of the genetic algorithm or branch-and-bound method. The findings analysis shows that, unlike the genetic algorithm, the unique one is more stable in terms of uncertainty of the input parameters in comparison with the branch-and-bound method. It provides the solutions in the models with a great number of variables. The algorithm is shown to be universal enough for its further modification in solving more complicated problems of the same class, containing a significantly larger number of probabilistic parameters that describe other uncertainties in the supply of raw materials. Further research is seen to include the development of the proposed algorithm to increase the rate of convergence for its better efficiency.

The purpose of the study is to assess the level of energy supply to the population of the Eastern Europe, Caucasus, and Central Asian (EECCA) countries, taking into account their financial risk and energy efficiency for households as potential socially vulnerable consumers. The research methodology is based on three approaches to determining the energy poverty of the population, as well as the integral index of energy supply to socially vulnerable segments of the population. Based on the results of the three approaches to assessing the level of energy supply to the population of EECCA countries, it has been revealed that its critical indicators are found in Armenia, Georgia, Kyrgyzstan, Moldova, Tajikistan, Turkmenistan, and Ukraine. The multivariate analysis of variance has revealed that, in all EECCA countries, both financial risk and energy efficiency levels have a significant impact. In Azerbaijan, Kazakhstan, and Russia, financial risk has the greatest impact on the level of energy supply to socially vulnerable segments of the population, while in other EECCA countries the energy efficiency factor has the strongest impact. In a number of EECCA countries, households have poor energy supply and require efficient and reliable operation, the introduction of energy-efficient technologies for home maintenance, and the improvement of related programs. The novelty of this study lies in the proposed methodological approach to assessing the supply of energy resources to socially unprotected segments of the population, which makes it possible to determine the impact of financial risk and energy efficiency in EECCA countries.

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Viscoelastic composites are strong and handle vibration damping quite well, which allows them to be used in a wide variety of applications. Thus, there is a need to determine the optimal amount of fiber to ensure high mechanical and dynamic performance with as little interference as possible. The purpose of this work is to find the most appropriate percentage of organic fiber – cellulose derived from corn stalks in a polylactic acid matrix, studying the changes in damping characteristics, tensile strength, bend-test. As parameters for comparison, the coefficient of bending and breaking strength, modules of accumulation and losses, factor C were chosen. It was found that strength indicators decrease with fiber fraction growth. While the damping factor at the glass transition temperature increases. In order to confirm the results obtained, the calculation of the C factor was used. The study investigates the damping factor’s dependence on the mechanical properties. It is shown that there is a correlation between moduli and bending strength with increasing fiber fraction. The scientific novelty of this work is the study of natural viscoelastic composites with different proportions of reinforcing fibers based on mechanical and dynamic characteristics in order to create and apply biodegradable viscoelastic composites in various fields.

The relevant problem of guaranteed supply of high-quality raw materials to a timber processing enterprise that does not have its own sources of raw materials is considered. A method for the formation of sustainable chains of supplying raw materials to a timber processing enterprise was proposed, taking into consideration uncertainties and risks associated with the purchase of raw materials on the mercantile exchange and the implementation of the circuit of delivery to a warehouse. A dynamic model, which is a problem of stochastic nonlinear programming, the objective function of which is the cost of purchasing raw materials, was developed. The model makes it possible to form a plan for purchasing raw materials on the timber section of the mercantile exchange on a given planning horizon, taking into consideration uncertainties when it comes to the number of daily offers, their volumes, and prices. The risk of cancellation of the concluded contract due to the loss of the quality of raw materials during delivery and non-fulfillment of delivery terms was also taken into consideration. To find a solution to the model, a two-stage circuit, in which the first stage involves a procurement plan that is close to optimal, was proposed. At the second stage, a plan that is closest to the basic one in terms of the volume of purchased raw materials and minimizing the total costs is chosen for each day of implementation of a random flow of applications. The numerical solution at the first stage is found using the heuristic algorithm that uses the branch and bound method and the genetic algorithm at certain steps. At the second stage, the multi-criteria problem of mathematical programming is solved numerically. An example of the formation by a timber processing enterprise in the Far East of a suboptimal procurement plan that ensures an increase in the efficiency and sustainability of economic activity in the long term is considered