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In vitro antihistamine-releasing activity of a peptide derived from wasp venom of Vespa orientalis

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Asian Pacific Journal of Tropical Biomedicine 2016年第3期6卷 259-264页

作者： Jafar Jalaei Mehdi Fazeli Hamid Rajaian Somayeh Layeghi Ghalehsoukhteh alireza dehghani Dominic Winter Department of Pharmacology and Toxicology School of Veterinary Medicine Shiraz University Institute of Biochemistry and Molecular Biology University of Bonn

Objective: To investigate the antihistamine-releasing effect of a peptide isolated from wasp venom of Vespa ***: This peptide was separated from crude venom by chromatography methods and mass spectrometry. Then various concentrations(2, 4, 8, 16, 32, 64, 128 and256 mmol/L) of the peptide were incubated with mast cells and lactate dehydrogenase assay was ***: No significant effect was observed in lactate dehydrogenase absorbance under128 mmol/L concentration. This implied that the peptide did not cause cell death in mast cells and consequently, histamine release did not happen. Moreover, the results showed the IC50 of mast cells degranulation at 126 mmol/L, which was approximately high implying that this peptide had high selectivity for normal cells and did not cause histamine release from these ***: This would be a great aim in new drug development, in which an agent acts potentially on its target tissue without activating the immune system.

关键词： Vespa orientalis Antihistamine release Lactate dehydrogenase assay Peptide

A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 1-21页

作者： Mina Haghighat Mehdi Niroomand Hossein dehghani Tafti Christopher D.Townsend Tyrone Fernando the Department of Electrical Engineering University of IsfahanIsfahanIran the Department of Electrical Electronic and Computer EngineeringUniversity of Western AustraliaCrawley WA 6009Australia

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)***,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power ***,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid ***,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing *** purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage *** paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var *** of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT *** three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also *** paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

关键词： Maximum power point tracking(MPPT) flexi ble power point tracking(FPPT) power reserve control(PRC) power ramp rate control(PRRC) low voltage ride-through(LVRT) constant power generation(CPG)

Frilled Lizard Optimization: A Novel Bio-Inspired Optimizer for Solving Engineering Applications

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Computers, Materials & Continua 2024年第6期79卷 3631-3678页

作者： Ibraheem Abu Falahah Osama Al-Baik Saleh Alomari Gulnara Bektemyssova Saikat Gochhait Irina Leonova OmParkash Malik Frank Werner Mohammad dehghani Department of Mathematics Faculty of ScienceThe Hashemite UniversityP.O.Box 330127Zarqa13133Jordan Department of Software Engineering Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Science and Information Technology Software EngineeringJadara UniversityIrbid21110Jordan Department of Computer Engineering International Information Technology UniversityAlmaty050000Kazakhstan Symbiosis Institute of Digital and Telecom Management Constituent of Symbiosis International Deemed UniversityPune412115India Neuroscience Research Institute Samara State Medical UniversitySamara443001Russia Faculty of Social Sciences Lobachevsky UniversityNizhny Novgorod603950Russia Department of Electrical and Software Engineering University of CalgaryCalgaryAB T2N 1N4Canada Faculty of Mathematics Otto-von-Guericke UniversityP.O.Box 4120Magdeburg39016Germany Department of Electrical and Electronics Engineering Shiraz University of TechnologyShiraz***Iran

This research presents a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization(FLO),which emulates the unique hunting behavior of frilled lizards in their natural *** draws its inspiration from the sit-and-wait hunting strategy of these *** algorithm’s core principles are meticulously detailed and mathematically structured into two distinct phases:(i)an exploration phase,which mimics the lizard’s sudden attack on its prey,and(ii)an exploitation phase,which simulates the lizard’s retreat to the treetops after *** assess FLO’s efficacy in addressing optimization problems,its performance is rigorously tested on fifty-two standard benchmark *** functions include unimodal,high-dimensional multimodal,and fixed-dimensional multimodal functions,as well as the challenging CEC 2017 test ***’s performance is benchmarked against twelve established metaheuristic algorithms,providing a comprehensive comparative *** simulation results demonstrate that FLO excels in both exploration and exploitation,effectively balancing these two critical aspects throughout the search *** balanced approach enables FLO to outperform several competing algorithms in numerous test ***,FLO is applied to twenty-two constrained optimization problems from the CEC 2011 test suite and four complex engineering design problems,further validating its robustness and versatility in solving real-world optimization ***,the study highlights FLO’s superior performance and its potential as a powerful tool for tackling a wide range of optimization problems.

关键词： Optimization engineering bio-inspired metaheuristic frilled lizard exploration exploitation

Investigating of Correlation between MODIS Satellite Data and Ground Data Related to Aerosols and Modeling Aerosols Using Neural Networks over Shiraz

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Investigating of Correlation between MODIS Satellite Data an...

Migration Algorithm:A New Human-BasedMetaheuristic Approach for Solving Optimization Problems

2012 Asian Pacific Conference on Energy,Environment and Sustainable Development(APEESD 2012)

作者： alireza dehghani Ali Akbar Safavi Mohammad Jafar Nazemossadat Seyed Mohammad Hessam Mohammadi School of E.Learning instrumentation and automation Shiraz University School of Electrical and Computer Engineering Shiraz University School of Agriculture Shiraz University School of E. Learning instrumentation and automation Shiraz University

This paper presents an investigation of satellite data and ground data about aerosols and then modelsthe mentioned data over Shiraz using artificial neural networks. MODIS satellite data are available on 36 various frequency bands. In this study, a good correlation between ground data and the 10 first satellite image bands is being shown. Specially, the best correlation was found in band number 8. Therefore, using neural networks and ground data along with satellite information, a model of aerosols is constructed. In the mentioned model, satellite data of band 8 and ground data are used as network input and output, respectively. The results show the effectiveness of the proposed model.

关键词： Aerosols Pollution Monitoring Modeling Neural Network Shiraz MODIS

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Computer Modeling in Engineering & Sciences 2023年第11期137卷 1695-1730页

作者： Pavel Trojovsky Mohammad dehghani Department of Mathematics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic

This paper introduces a newmetaheuristic algorithmcalledMigration Algorithm(MA),which is helpful in solving optimization *** fundamental inspiration of MA is the process of human migration,which aims to improve job,educational,economic,and living conditions,and so *** of the proposed MAis presented in two phases to empower the proposed approach in exploration and exploitation during the search *** the exploration phase,the algorithm population is updated based on the simulation of choosing the migration destination among the available *** the exploitation phase,the algorithm population is updated based on the efforts of individuals in the migration destination to adapt to the new environment and improve their ***’s performance is evaluated on fifty-two standard benchmark functions consisting of unimodal and multimodal types and the CEC 2017 test *** addition,MA’s results are compared with the performance of twelve well-known metaheuristic *** optimization results show the proposed MA approach’s high ability to balance exploration and exploitation to achieve suitable solutions for optimization *** analysis and comparison of the simulation results show that MA has provided superior performance against competitor algorithms in most benchmark ***,the implementation of MA on four engineering design problems indicates the effective capability of the proposed approach in handling optimization tasks in real-world applications.

关键词： Optimization metaheuristic migration human-based algorithm exploration exploitation

SSABA:Search Step Adjustment Based Algorithm

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Computers, Materials & Continua 2022年第6期71卷 4237-4256页

作者： Fatemeh Ahmadi Zeidabadi Ali dehghani Mohammad dehghani Zeinab Montazeri Stepán Hubálovsky Pavel Trojovsky Gaurav Dhiman Department of Mathematics and Computer Sciences Sirjan University of TechnologySirjanIran Department of Civil Engineering Islamic Azad UniversityEstahban BranchEstahbanIran Department of Mathematics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science Government Bikram College of CommercePatialaPunjabIndia

Finding the suitable solution to optimization problems is a fundamental challenge in various *** algorithms are one of the effective stochastic methods in solving optimization *** this paper,a new stochastic optimization algorithm called Search StepAdjustment Based Algorithm(SSABA)is presented to provide quasi-optimal solutions to various optimization *** the initial iterations of the algorithm,the step index is set to the highest value for a comprehensive search of the search ***,with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer to the global optimal,the step index is reduced to reach the minimum value at the end of the algorithm *** is mathematically modeled and its performance in optimization is evaluated on twenty-three different standard objective functions of unimodal and multimodal *** results of optimization of unimodal functions show that the proposed algorithm SSABA has high exploitation power and the results of optimization of multimodal functions show the appropriate exploration power of the proposed *** addition,the performance of the proposed SSABA is compared with the performance of eight well-known algorithms,including Particle Swarm Optimization(PSO),Genetic Algorithm(GA),Teaching-Learning Based Optimization(TLBO),Gravitational Search Algorithm(GSA),Grey Wolf Optimization(GWO),Whale Optimization Algorithm(WOA),Marine Predators Algorithm(MPA),and Tunicate Swarm Algorithm(TSA).The simulation results show that the proposed SSABA is better and more competitive than the eight compared algorithms with better performance.

关键词： Optimization population-based optimization problem search step optimization algorithm minimization maximization

Language Education Optimization: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems

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Computer Modeling in Engineering & Sciences 2023年第8期136卷 1527-1573页

作者： Pavel Trojovsky Mohammad dehghani Eva Trojovská Eva Milkova Department of Mathematics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic

In this paper,based on the concept of the NFL theorem,that there is no unique algorithm that has the best performance for all optimization problems,a new human-based metaheuristic algorithm called Language Education Optimization(LEO)is introduced,which is used to solve optimization *** is inspired by the foreign language education process in which a language teacher trains the students of language schools in the desired language skills and *** is mathematically modeled in three phases:(i)students selecting their teacher,(ii)students learning from each other,and(iii)individual practice,considering exploration in local search and exploitation in local *** performance of LEO in optimization tasks has been challenged against fifty-two benchmark functions of a variety of unimodal,multimodal types and the CEC 2017 test *** optimization results show that LEO,with its acceptable ability in exploration,exploitation,and maintaining a balance between them,has efficient performance in optimization applications and solution *** efficiency in optimization tasks is compared with ten well-known metaheuristic *** of the simulation results show that LEO has effective performance in dealing with optimization tasks and is significantly superior andmore competitive in combating the compared *** implementation results of the proposed approach to four engineering design problems show the effectiveness of LEO in solving real-world optimization applications.

关键词： Optimization language education exploration exploitation metaheuristic algorithm

Cluster decay half-lives using asymmetry dependent densities

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Chinese Physics C 2022年第4期46卷 131-140页

作者： V.dehghani S.A.Alavi R.Razavi A.Soylu F.Koyuncu Department of Physics University of Sistan and BaluchestanZahedanIran Physics Department Faculty of ScienceImam Hossein Comprehensive UniversityTehranIran Department of Physics Nigdeomer Halisdemir UniversityNigde 51240Turkey Program of Opticianry Golhisar Vocational School of Health ServicesBurdur Mehmet Akif Ersoy University15400GolhisarBurdurTurkey

By adopting different neutron and proton density distributions,cluster decay half-lives were investigated using double-folding potentials with constant and nuclear asymmetry dependent sets of nuclear density *** adopted asymmetry dependent sets of parameters were fitted based on microscopic calculations,and they were calculated based on the neutron skin/halo-type nuclei assumption and by employing experimental rms charge radii.A bulk agreement between theory and experiment was obtained for all sets of parameters using a calculated cluster preformation *** differences were observed between the skin and halo-type ***,the notable role of the asymmetry parameter was observed in the relatively large differences between the skin and skintype with zero thickness.

关键词： cluster decay double-folding charge radii density

MLA:A New Mutated Leader Algorithm for Solving Optimization Problems

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Computers, Materials & Continua 2022年第3期70卷 5631-5649页

作者： Fatemeh Ahmadi Zeidabadi Sajjad Amiri Doumari Mohammad dehghani Zeinab Montazeri Pavel Trojovsky Gaurav Dhiman Department of Mathematics and Computer Sciences Sirjan University of TechnologySirjanIran Graduate of Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Electrical and Electronics Engineering Shiraz University of TechnologyShirazIran Department of Mathematics Faculty of ScienceUniversity of Hradec Králové50003Hradec KrálovéCzech Republic Department of Computer Science Government Bikram College of CommercePatialaPunjabIndia

Optimization plays an effective role in various disciplines of science and *** problems should either be optimized using the appropriate method(i.e.,minimization or maximization).Optimization algorithms are one of the efficient and effective methods in providing quasioptimal solutions for these type of *** this study,a new algorithm called the Mutated Leader Algorithm(MLA)is *** main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated *** addition to information about the best member of the population,themutated leader also contains information about the worst member of the population,as well as other normal members of the *** proposed MLA is mathematically modeled for implementation on optimization problems.A standard set consisting of twenty-three objective functions of different types of unimodal,fixed-dimensional multimodal,and high-dimensional multimodal is used to evaluate the ability of the proposed algorithm in ***,the results obtained from theMLA are compared with eight well-known *** results of optimization of objective functions show that the proposed MLA has a high ability to solve various optimization ***,the analysis and comparison of the performance of the proposed MLA against the eight compared algorithms indicates the superiority of the proposed algorithm and ability to provide more suitable quasi-optimal solutions.

关键词： Optimization metaheuristics leader benchmark objective function