Stable parallel algorithms for solving the inverse gravimetry and magnetometry problems

The three-dimensional inverse problems of gravimetry and magnetometry for finding the interfaces between mediums from the gravitational and magnetic data are investigated. We assume that a model of the lower halfspace consists of three mediums with constant densities which are separated by the surfaces S1 and S2 to be determined. The inverse problems are reduced to nonlinear integral equations of the first kind, hence these problems are illposed. After discretization of the integral equation we obtain a system of nonlinear equations of large dimension. To solve this system, we use the iteratively regularized Gauss-Newton method. To realize one step of this method, we have to solve a system of linear algebraic equations with full matrix. For this aim, parallel variants of the Gauss, Gauss-Jordan and the conjugate gradient method are applied. Their realization has been implemented on the Massively Parallel Computing System MVS-1000. The analysis of the efficiency of parallelization of the iterative algorithms with different numbers of processors is carried out. Parallelization of the algorithms decreases significantly the time of solving the problems. The interfaces S1 and S2 obtained by the Gauss-Newton method correspond to the real geological perceptions about the Ural region under investigation

An Efficient Numerical Technique for Solving the Inverse Gravity Problem of Finding a Lateral Density

The main goal of our paper is to construct a technique for the gravity inversion problem of finding a variable density in a horizontal layer on the basis of gravitational data. This technique consists of two steps: extracting the gravitational field and solving the linear integral equation of the density. After discretization and approximation of integral operator, this problem is reduced to solving large systems of linear algebraic equations. To solve these systems, we proposed a memory-efficient algorithm based on the iterative method of minimal residuals. The idea of memory optimization is based on exploiting the block-Toeplitz structure of coefficients matrix. The algorithms were parallelized and implemented using the Uran and UrFU supercomputers. A model problem with synthetic gravitational data was solved

The Discourse Personality of Politician Sergey Mikheyev with Regards to his Speech Behaviour

This paper presents the results of research into the linguistic personality of politician Sergey Mikheyev when viewed as a discourse personality. Special consideration has been given to the speech behaviour characteristic of a discourse personality. The paper presents the results of the cognitive-discursive and linguo-rhetorical description of a discourse personality.The relevance of this research is based on the growing interest for linguistic personality typology with regards to discourse (K. F. Sedov, V. I. Karasik, N. D. Golev, A. V. Bolotnov, et al.). A mixed type of political discourse that actualises both the personal and status factors of its formation was chosen as the object of analysis. The research focuses on semantic dominants and semantic constructs of the discourse behaviour of the Russian politician Sergey Mikheyev, as well as on the cognitive and linguo-rhetorical mechanisms of the interpretation of speech acts when viewed as elements of individual discourse behaviour. We define the linguo-rhetorical competence of the politician’s personality. The study is novel in that it identifies semantic dominants and semantic constructs found in Mikheyev’s discourse and uses an integrative approach to analysis (cognitive-discursive and linguo-rhetorical). It is proven that semantic dominants, constructs, and presuppositions manifest inventive mechanisms of individual discourse activity. We suggest defining the status of Mikheyev’s discourse personality as a mixed type of elitist linguistic personality that is pragmatically oriented. We prove that the discourse personality of Sergey Mikheyev is a prototype of a future successful politician’s linguistic personality. The paper presents the author’s original communicative competence system of S. Mikheyev’s discourse personality

Effect of bacterization with Aeromonas media GS4 and Pseudomonas extremorientalis PhS1 on wheat seedlings under different abiotic conditions

We studied the effect of soft wheat seed treatment (Triticum aestivum L.) with two bacterial strains (Aeromonas media GS4 and Pseudomonas extremorientalis PhS1) isolated from earthworm coprolites on the growth and development of wheat seedlings in a 12-day laboratory experiment, as well as on root rot disease and the activity of guaiacol-dependant peroxidase under optimal conditions and abiotic stress (elevated and low temperatures and moisture content). We established that growing nonbacterized wheat plants under stress abiotic conditions reduced the height of plants compared to growing under optimal abiotic conditions, and seed bacterization with P. extremorientalis PhS1 strain increased wheat plant height (by 9-15%) under stress abiotic conditions compared to the nonbacterized plants. Bacterization with both strains decreased infestation of wheat seedlings (2.5-4 times) by root rots under unfavorable abiotic conditions compared to nonbacterized plants. In addition, under optimal and arid conditions, bacterization with P. extremorientalis PhS1 strain was the most effective, and under humid conditions it was bacterization with A. media GS4 strain. We showed that the activity of guaiacol-dependant peroxidase correlates with the development of plant resistance to abiotic stress. In our experiments, plant bacterization resulted in a 2-fold increase in peroxidase activity both in leaves and roots of wheat plants compared to the nonbacterized plants. As the result, the ability of bacteria to activate peroxidase can serve as an information indicator of strengthening protective mechanisms of plants during bacterization

Optimal Scheduling for the Linear Section of a Single-Track Railway with Independent Edges Orientations

The paper is devoted to the problem of organizing the flow in both directions, in the most efficient way, for the linear section of a single-track railway. The authors propose an algorithm for scheduling with independent orientations of edges, investigate the properties of this algorithm and perform computational experiments. The authors also present some estimates for the track capacity of the section

Design and implementation of adaptive technology for teaching mathematics to school children based on integrated diagnostic approach to subject preparation and competence development

The development of school teaching  systems to enable effective adaptive communication of information requires specific pedagogical solutions to several important theoretical and methodological problems .These include 1) the discernment of basic characteristics needed to diagnose and improve the quality of subject preparation for schoolchildren, 2) clarifying the role of the teacher in the structure of adaptive learning  process, and  3) finding ways to integrate adaptive content into the framework of courses on mathematics. The purpose of our study was to determine theoretical and methodological foundations of teaching mathematics to schoolchildren taking into account their level of ability with the consequent development of appropriate adaptive content. The basic characteristics that underpin the concept of adaptive learning which contributes to both individual profiles of student ability to learn and subsequent success outcomes are: proficiency, motivation to learn and level of mathematical knowledge. The evaluation of individual profile structure of schoolchildren determines the choice of methodologies for presentation of adaptive content in ways allowing development and motivation. The system of educational process management developed in this way includes both content-methodical and procedural-technological components. This makes it possible to automatically evaluate the level of each students' mathematical training (knowledge, motivation, development) and to ensure continuous improvement. This system can also be used by secondary teachers of mathematics as a part of extracurricular activities, or as a distance learning support. In addition, the recommendations for structuring multi-level problem material can be used by mathematics teachers to self-construct adaptive sets tasks at various stages of teaching mathematics. As a result, students have the opportunity to improve their own profile of learning success, particularly by solving a chain of tasks

Review of deep learning approaches in solving rock fragmentation problems

One of the most significant challenges of the mining industry is resource yield estimation from visual data. An example would be identification of the rock chunk distribution parameters in an open pit. Solution of this task allows one to estimate blasting quality and other parameters of open-pit mining. This task is of the utmost importance, as it is critical to achieving optimal operational efficiency, reducing costs and maximizing profits in the mining industry. The mentioned task is known as rock fragmentation estimation and is typically tackled using computer vision techniques like instance segmentation or semantic segmentation. These problems are often solved using deep learning convolutional neural networks. One of the key requirements for an industrial application is often the need for real-time operation. Fast computation and accurate results are required for practical tasks. Thus, the efficient utilization of computing power to process high-resolution images and large datasets is essential. Our survey is focused on the recent advancements in rock fragmentation, blast quality estimation, particle size distribution estimation and other related tasks. We consider most of the recent results in this field applied to open-pit, conveyor belts and other types of work conditions. Most of the reviewed papers cover the period of 2018-2023. However, the most significant of the older publications are also considered. A review of publications reveals their specificity, promising trends and best practices in this field. To place the rock fragmentation problems in a broader context and propose future research topics, we also discuss state-of-the-art achievements in real-time computer vision and parallel implementations of neural networks

Prospects for the peat using as the basis of the soil-like substrate in mini-ecosystems modelling

Global urbanization is causing a constant decline in arable land as cities and associated industrial zones are "attacking" adjacent agricultural areas. One of the promising ways to solve the problem of increasing food production for the constantly growing population of the planet against the background of rapidly decreasing land resources is the development of fundamentally new alternative methods for the production of crop products, including in greenhouses. The fundamental basis for technological optimization of plant cultivation parameters and the output of the productive process of a particular crop to the maximum of its genetic capacities can be the development of artificial mini-ecosystems based on the reproduction of nature-like processes, implying the balance and combination in one volume of the processes of plant production and reduction of organic waste, initiated directly in the zone of the rhizosphere of plants due to the introduction of technological earthworms into the reduction zone. According to the results of model studies presented in this article, peat is an acceptable basis for the substrate of the root block of a mini-ecosystem, and the introduction of earthworms Eisenia fetida Sav. into the reduction zone does not have a negative effect on lettuce plants, provided that it is used as an energy substrate for cattle manure worms in quantities not exceeding 10 - 20% of the total volume of the substrate

Pseudomonads associated with soil lumbricides as promising agents in root rot biocontrol for spring grain crops

Currently, crop yields can be increased by high farming standards which include environmentally friendly use of chemical fertilizers and pesticides, as well as their replacement by bioformulations having similar activity. That is why both search for new promising species, strains and isolates of bacterial antagonists for their potential use as biocontrol agents, and study of antifungal activity mechanisms, particularly the relationship between the activity in model tests and in agrocenoses, are relevant. The aim of this study was to estimate bacterial isolates from redworm coprolites as potential bioactive agents to control phytopathogenic fungi causing root rot of crops. The experiments were conducted in 2013-2015. In the preliminary laboratory screening for fungistatic and growth-promoting activity we selected two strains, Pseudomonas sp. GS4 and Pseudomonas sp. PhS1, and assessed their ability to decrease the growth rate of fungal colonies in Petri dish test on nutrient agar medium and to reduce seed infestation of soft wheat (Triticum aestivum L., Irgin cultivar) in sterile paper roll test. Seeds soaked in distilled water served as control. As a standard, we used seed treatment with a chemical fungicide Dividend® Star («Syngenta AG», Switzerland) (30 g/l difenoconazole, 6.3 g/l cyproconazole) at recommended rates. In field tests, we recorded root rots in soft wheat Irgin cultivar plants and in barley (Hordeum vulgare L.) Acha cultivar plants during tillering and beginning of blooming. The laboratory tests showed a statistically significant (р < 0.05) 1.5-2.5-fold decrease in the growth rate of phytopathogenic fungi Fusarium oxysporum, Bipolaris sorokiniana and Alternaria spp. as compared to control. In all experiments with bacterization, there was a 53-76 % decrease (р < 0.05) in total seed infestation by pathogens as compared to non-bacterized plants. The effect of the bacteria in planta was assessed in small model systems. The obtained data show a statistically significant (р < 0.05) reduction in the root rot disease incidence in bacterization with Pseudomonassp. GS4 (by 33-37 %) and Pseudomonas sp. PhS1 (by 57-60 %). Root rot disease severity decreases 2.1-2.4-fold and 3.3-3.5-fold, respectively. In 2015, we revealed a tendency towards a 19-70 % increase in the total number of rhizosphere microorganisms at the beginning of plant blooming depending on the crop and type of bacterization. The number of hosphate-mobilizing bacteria in the rhizosphere under bacterization was, on average, 5.5-7.2-fold higher in wheat and 2.1-3.2-fold higher in barley than that without bacterization. Our results of root rot field study in the 2013-2015 showed the efficacy of both monocultures and complex bacterization which provided a decrease in wheat and barley root rot disease severity by 6.5-57.6 % and 18.6-50.0 %, respectively, depending on the bacterial culture and the weather conditions. The maximum biological efficacy of the isolates is noted at the beginning of blooming

Parallel algorithms for solving linear systems with block-tridiagonal matrices on multi-core CPU with GPU

For solving systems of linear algebraic equations with block-tridiagonal matrices arising in geoelectrics problems, the parallel matrix sweep algorithm, conjugate gradient method with preconditioner, and square root method are proposed and implemented numerically on multi-core CPU Intel with graphics processors NVIDIA. Investigation of efficiency and optimization of parallel algorithms for solving the problem with quasi-model data are performed. © 2012