Spring search algorithm for simultaneous placement of distributed generation and capacitors

Purpose. In this paper, for simultaneous placement of distributed generation (DG) and capacitors, a new approach based on Spring Search Algorithm (SSA), is presented. This method is contained two stages using two sensitive index Sv and Ss. Sv and Ss are calculated according to nominal voltageand network losses. In the first stage, candidate buses are determined for installation DG and capacitors according to Sv and Ss. Then in the second stage, placement and sizing of distributed generation and capacitors are specified using SSA. The spring search algorithm is among the optimization algorithms developed by the idea of laws of nature and the search factors are a set of objects. The proposed algorithm is tested on 33-bus and 69-bus radial distribution networks. The test results indicate good performance of the proposed methodЦель. В статье для одновременного размещения распределенной генерации и конденсаторов представлен новый подход, основанный на "пружинном" алгоритме поиска (Spring Search Algorithm, SSA). Данный метод состоит из двух этапов с использованием двух показателей чувствительности Sv и Ss. Показатели чувствительности Sv и Ss рассчитываются в соответствии с номинальным напряжением и потерями в сети. На первом этапе определяются шины-кандидаты для установки распределенной генерации и конденсаторов согласно Sv и Ss. Затем, на втором этапе размещение и калибровка распределенной генерации и конденсаторов выполняются с использованием алгоритма SSA. "Пружинный" алгоритм поиска входит в число алгоритмов оптимизации, разработанных на основе идей законов природы, а факторы поиска представляют собой набор объектов. Предлагаемый алгоритм тестируется на радиальных распределительных сетях с 33 и 69 шинами. Результаты тестирования показывают хорошую эффективность предложенного метода

PLANNING OF ENERGY CARRIERS BASED ON FINAL ENERGY CONSUMPTION USING DYNAMIC PROGRAMMING AND PARTICLE SWARM OPTIMIZATION

Purpose. In the present article, a new approach of the energy grid studies is introduced to program energy carriers. In this view, a proper plan is designed on the use of energy carriers considering the energy optimum use. Indeed, the proper energy grid is designed by applying Iran energy balance sheet information. It is proper to mention that, the energy grid modelling is done in a matrix form. The electrical energy distribution among power stations is achieved by using the particle swarm optimization algorithm. In the present paper, concerning the dynamic programming method, it is tried to determine a suitable combination of energy carriers

Learning and memory disorders related to hippocampal inflammation following exposure to air pollution

It has been demonstrated that sub-chronic exposure to air pollution containing nanoscale (�100 nm) diesel exhaust particles (DEPs) may lead to excessive oxidative stress and neuro-inflammation in adult male mice. Hereby, we investigated the effects of DEPs on hippocampus-dependent spatial learning and neuro-inflammation and memory-related gene expression in male mice. In this study, we divided 48 adult NMRI male mice into control group VS. three exposure groups. Mice were exposed to 300-350 μg/m3 DEPs for 2, 5, and 7 h daily for 12 weeks. The Morris Water Maze (MWM) and Elevated Plus Maze device were used to examine anxiety, spatial memory and learning, respectively. The mRNAs expression of pro-inflammatory cytokines, N-methyl-D-aspartate (NMDA) receptor subunits, and glutaminase were studied in hippocampus (HI) by real-time RT-PCR. Besides, malondialdehyde (MDA) tests were used to determine the state of oxidative stress. After 5 and 7 h. of DEPs exposure, mRNA expression of NR2A and NR3B IL1α, IL1β, TNFα, NMDA receptor subunits and MDA levels increased significantly (P < 0.05). Also, DEPs exposed mice for 2, 5, and 7 h. showed diminished entrance into open arms with short time spent there. Indeed, 5 and 7 h/day exposed mice required a longer time to reach the hidden platform. Sub-chronic exposure to DEPs increased oxidative stress markers, neuroinflammation, anxiety, impaired spatial learning and memory. © 2021, Springer Nature Switzerland AG

Learning and memory disorders related to hippocampal inflammation following exposure to air pollution

It has been demonstrated that sub-chronic exposure to air pollution containing nanoscale (�100 nm) diesel exhaust particles (DEPs) may lead to excessive oxidative stress and neuro-inflammation in adult male mice. Hereby, we investigated the effects of DEPs on hippocampus-dependent spatial learning and neuro-inflammation and memory-related gene expression in male mice. In this study, we divided 48 adult NMRI male mice into control group VS. three exposure groups. Mice were exposed to 300-350 μg/m3 DEPs for 2, 5, and 7 h daily for 12 weeks. The Morris Water Maze (MWM) and Elevated Plus Maze device were used to examine anxiety, spatial memory and learning, respectively. The mRNAs expression of pro-inflammatory cytokines, N-methyl-D-aspartate (NMDA) receptor subunits, and glutaminase were studied in hippocampus (HI) by real-time RT-PCR. Besides, malondialdehyde (MDA) tests were used to determine the state of oxidative stress. After 5 and 7 h. of DEPs exposure, mRNA expression of NR2A and NR3B IL1α, IL1β, TNFα, NMDA receptor subunits and MDA levels increased significantly (P < 0.05). Also, DEPs exposed mice for 2, 5, and 7 h. showed diminished entrance into open arms with short time spent there. Indeed, 5 and 7 h/day exposed mice required a longer time to reach the hidden platform. Sub-chronic exposure to DEPs increased oxidative stress markers, neuroinflammation, anxiety, impaired spatial learning and memory. © 2021, Springer Nature Switzerland AG

Binary spring search algorithm for solving various optimization problems

One of the most powerful tools for solving optimization problems is optimization algorithms (inspired by nature) based on populations. These algorithms provide a solution to a problem by randomly searching in the search space. The design’s central idea is derived from various natural phenomena, the behavior and living conditions of living organisms, laws of physics, etc. A new population-based optimization algorithm called the Binary Spring Search Algorithm (BSSA) is introduced to solve optimization problems. BSSA is an algorithm based on a simulation of the famous Hooke’s law (physics) for the traditional weights and springs system. In this proposal, the population comprises weights that are connected by unique springs. The mathematical modeling of the proposed algorithm is presented to be used to achieve solutions to optimization problems. The results were thoroughly validated in different unimodal and multimodal functions; additionally, the BSSA was compared with high-performance algorithms: binary grasshopper optimization algorithm, binary dragonfly algorithm, binary bat algorithm, binary gravitational search algorithm, binary particle swarm optimization, and binary genetic algorithm. The results show the superiority of the BSSA. The results of the Friedman test corroborate that the BSSA is more competitive

Investigation of metabolic kinetics in different brain regions of awake rats using the 1H-13C-NMR technique

Energy metabolism and neurotransmission are necessary for sustaining normal life activities. Hence, neurological or psychiatric disorders are always associated with changes in neurotransmitters and energy metabolic states in the brain. Most studies have only focused on the most important neurotransmitters, particularly GABA and Glu, however, other metabolites such as NAA and aspartate which are also very important for cerebral function are rarely investigated. In this study, most of the metabolic kinetics information of different brain regions was investigated in awake rats using the 1H-13C-NMR technique. Briefly, rats (n = 8) were infused 1-13C glucose through the tail vein for two minutes. After 20 min of glucose metabolism, the animals were sacrificed and the brain tissue was extracted and treated. Utilizing the 1H observed/13C-edited nuclear magnetic resonance (POCE-NMR), the enrichment of neurochemicals was detected which reflected the metabolic changes in different brain regions and the metabolic connections between neurons and glial cells in the brain. The results suggest that the distribution of every metabolite differed from every brain region and the metabolic rate of NAA was relatively low at 8.64 ± 2.37 μmol/g/h. In addition, there were some correlations between several 13C enriched metabolites, such as Glu4-Gln4 (p = 0.062), Glu4-GABA2 (p < 0.01), Glx2-Glx3 (p < 0.001), Asp3-NAA3 (p < 0.001). This correlativity reflects the signal transmission between astrocytes and neurons, as well as the potential interaction between energy metabolism and neurotransmission. In conclusion, the current study systematically demonstrated the metabolic kinetics in the brain which shed light on brain functions and the mechanisms of various pathophysiological states. © 2021 Elsevier B.V