Формирование опорной транспортной сети региона с учетом размещения альтернативных источников энергии на основе методов искусственного интеллекта

In the modern world the alternative energy sources, which considerably depend on a region, play more and more significant role. However, the transition of regions to new energy sources lead to the change of transport and logistic network configuration. The formation of optimal core transport network today is a guarantee of the successful economic development of a region tomorrow. The present article studies the issue of advanced core transport network development in a region based on the experience of European and Asian countries and the opportunity to adapt the best foreign experience to Russian conditions. On the basis of artificial intelligence methods for forest industry complex of Sverdlovskaya Oblast the algorithm of problem solution of an optimal logistic infrastructure allocation is offered and some results of a regional transport network are presented. These methods allowed to solve the set task in the conditions of information uncertainty. There are suggestions on the improvement of transport and logistic network in the territory of Sverdlovskaya Oblast. Traditionally the logistics of mineral fuel plays main role in regions development. Actually it is required to develop logistic strategic plans to be able to provide different possibilities of power-supply, flexible enough to change with the population density, transport infrastructure and demographics of different regions. The problem of logistic centers allocation was studied by many authors. The approach, offered by the authors of this paper is to solve the set of tasks by applying artificial intelligence methods, such as fuzzy set theory and genetic algorithms.В современном мире альтернативные источники энергии, которые в значительной степени зависят от региона, играют все более значимую роль. Однако переход регионов к новым источникам энергии приведет к изменению транспортно- логистического конфигурации сети. Формирование оптимальной опорной транспортной сети сегодня является залогом успешного экономического развития региона завтра. Настоящая статья изучает вопрос опережающего развития опорной транспортной сети региона на основе опыта стран Европы и Азии, а также возможность адаптировать лучший зарубежный опыт к российским условиям. На основе методов искусственного интеллекта для лесопромышленного комплекса Свердловской области предлагается алгоритм решения задачи оптимального логистического распределения инфраструктуры и представлены некоторые результаты моделирования региональной транспортной сети. Эти методы позволили решить поставленную задачу в условиях информационной неопределенности. Дать предложения по совершенствованию транспортной и логистической сети на территории Свердловской области. Зависимость логистики от минерального топлива, является устойчивой тенденцией развития регионов, однако при составлении стратегических планов необходимо на ряду, с плотностью населения, особенностями транспортной инфраструктуры и прогнозом демографических изменений, также предусмотреть альтернативные возможности смены источников энергоресурсов. К проблеме размещения логистических центров обращались многие авторы. Особенностью подхода, предлагаемого авторами этой статьи является применение методов искусственного интеллекта, в частности, теории нечетких множеств и генетических алгоритмов

Application of the hybrid controller for isothermal extrusion process control

Nowadays most of critical machine elements are manufactured by means of extrusion method. Such workpieces are widely applicable in aeronautical and rocket engineering as well as transport mechanical engineering. One of the methods allowing workpiece quality improvement is isothermal extrusion which provides constant temperature on the surface of the workpiece by changing extrusion velocity. To control over isothermal extrusion process was designed hybrid intelligent controller. This controller was realized as neuro-fuzzy system

Complete genome sequences of T5-related Escherichia coli bacteriophages DT57C and DT571/2 isolated from horse feces

We report the complete genome sequencing of two Escherichia coli T5-related bacteriophages, DT57C and DT571/2, isolated from the same specimen of horse feces. These two isolates share 96 % nucleotide sequence identity and can thus be considered representatives of the same novel species within the genus T5likevirus. The observed variation in the ltfA gene of these phages, resulting from a recent recombination event, may explain the observed host-range differences, suggesting that a modular mechanism makes a significant contribution to the short-term evolution (or adaptation) of T5-like phage genomes in the intestinal ecosystem. Comparison of our isolates to their closest relative, coliphage T5, revealed high overall synteny of the genomes and high conservation of the sequences of almost all structural proteins as well as of the other proteins with identified functions. At the same time, numerous alterations and non-orthologous replacements of non-structural protein genes (mostly of those with unknown functions) as well as substantial differences in tail fiber locus organization support the conclusion that DT57C and DT571/2 form a species-level group clearly distinct from bacteriophage T5

Branched Lateral Tail Fiber Organization in T5-Like Bacteriophages DT57C and DT571/2 is Revealed by Genetic and Functional Analysis

The T5-like siphoviruses DT57C and DT571/2, isolated from horse feces, are very closely related to each other, and most of their structural proteins are also nearly identical to T5 phage. Their LTFs (L-shaped tail fibers), however, are composed of two proteins, LtfA and LtfB, instead of the single Ltf of bacteriophage T5. In silico and mutant analysis suggests a possible branched structure of DT57C and DT571/2 LTFs, where the LtfB protein is connected to the phage tail via the LtfA protein and with both proteins carrying receptor recognition domains. Such adhesin arrangement has not been previously recognized in siphoviruses. The LtfA proteins of our phages are found to recognize different host O-antigen types: E. coli O22-like for DT57C phage and E. coli O87 for DT571/2. LtfB proteins are identical in both phages and recognize another host receptor, most probably lipopolysaccharide (LPS) of E. coli O81 type. In these two bacteriophages, LTF function is essential to penetrate the shield of the host's O-antigens. We also demonstrate that LTF-mediated adsorption becomes superfluous when the non-specific cell protection by O-antigen is missing, allowing the phages to bind directly to their common secondary receptor, the outer membrane protein BtuB. The LTF independent adsorption was also demonstrated on an O22-like host mutant missing O-antigen O-acetylation, thus showing the biological value of this O-antigen modification for cell protection against phages