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Quranic Verse No. 8 of Surat Al-Jumu’ah Describes Cancer as a Complete and Accurate Description and Leads Us to Determine the True Cause of Cancer. “Part-1”

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CellBio 2018年第1期7卷 1-11页

作者： mahmoud saad mohamed el-khodary Department of Veterinary Medicine Zagazig University Zagazig Egypt Department of Fish Diseases Suez Canal University Ismailia Egypt General Organization for Export and Import Control Suez Egypt

Cancer is the cell fleeing from death by blocking the pathways of the intrinsic and the extrinsic program of cell death (Apoptosis). The success depends on making the programs of cell death run again.

关键词： Cancer Description Intrinsic Apoptosis Extrinsic Apoptosis

Quranic Verse No. 8 of Surat Al-Jumu’ah Leads us to Describe Cancer and Determine Its True Cause (Part-III)

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CellBio 2018年第2期7卷 35-49页

Therapeutic strategies for destroying cancer cells by making its death programs run again. The normal cell passes through several stages (Accumulation stage, Detoxification stage, Formation of free radical stage and Activation of nuclear factor kappa B stage and the shutting down of programs of cell death stage) to become a cancerous cell. The success of the therapeutic strategy to treat cancer depends on making either one or both programs of cell death run again. Shutting down one stage completely will be sufficient to stop the transformation of the natural cell into a cancerous cell, which eliminates the production of hydrogen peroxide, thus the activity of the NF-Kb will be inhibited. However, shutting down all stages is the most comprehensive therapeutic strategy and guarantees treatment success.

关键词： Cancer Therapeutic Strategy Accumulation Detoxification Enzymes Free Radicals Antioxidants H2O2 Glutathione NF-Kb Sulforaphane Flavonoid Cur Cumin

How to Return the Death Programs of Cancer Cells to Work again and Cure Cancer within a Short Time?

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CellBio 2019年第2期8卷 17-39页

作者： mahmoud saad mohamed el-khodary Sahar Ezeldien Hasan Wael A. Hassan Maather M. el-Lamie Ismail A. M. Eissa Waleed F. Khalil Salah M. Aly Suez Canal University Ismailia Egypt General Organization for Export and Import Control Suez Egypt Pharmacology Department Faculty of Vet. Medicine Suez Canal University Ismailia Egypt Pathology Department Faculty of Medicine Suez Canal University Ismailia Egypt Department of Basic Sciences Suliman Al-Rajhi Collage of Medicine Al Bukayriyah KSA Department of Fish Diseases & Management Faculty of Vet. Medicine Suez Canal Univ. Ismailia Egypt Pathology Department Faculty of Vet. Medicine Suez Canal University Ismailia Egypt

Cancer is cell fleeing from death by blocking the intrinsic and extrinsic pathways of cell death programs. In the present work, the experimental formula was designed to remove these blockers. It was applied on 120 Swiss albino mice which were inoculated intraperitoneally and subcutaneously with Ehrlich Ascites Carcinoma cells;1 × (106) cell/mouse. The activity of the cell death programs of the tumor was detected by measuring the volume of Ascites fluid, counting the number of dead cancer cells, measuring the size of the tumor, detecting the positive reaction of caspase enzyme in cancer cells and presence of macrophages and apoptotic bodies in tumor tissue. The experimental formula succeeded in removing the blockers of the cell death program in cancer cells returning the cell death program to work again.

关键词： Cancer Therapeutic Strategy Accumulation Detoxification Enzymes Free Radicals Antioxidants H2O2 Glutathione NF-kB Sulforaphane Flavonoid Cur Cumin

Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

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Computers, Materials & Continua 2024年第7期80卷 819-841页

作者： saad Abdalla Agaili mohamed Sefer Kurnaz Department of electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey

VPNs are vital for safeguarding communication routes in the continually changing cybersecurity ***,increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorizeVPNnetwork *** present a novelVPNnetwork traffic flowclassificationmethod utilizing Artificial Neural Networks(ANN).This paper aims to provide a reliable system that can identify a virtual private network(VPN)traffic fromintrusion attempts,data exfiltration,and denial-of-service *** compile a broad dataset of labeled VPN traffic flows from various apps and usage ***,we create an ANN architecture that can handle encrypted communication and distinguish benign from dangerous *** effectively process and categorize encrypted packets,the neural network model has input,hidden,and output *** use advanced feature extraction approaches to improve the ANN’s classification accuracy by leveraging network traffic’s statistical and behavioral *** also use cutting-edge optimizationmethods to optimize network characteristics and *** suggested ANN-based categorization method is extensively tested and *** show the model effectively classifies VPN traffic *** also show that our ANN-based technique outperforms other approaches in precision,recall,and F1-score with 98.79%*** study improves VPN security and protects against new *** VPNtraffic flows effectively helps enterprises protect sensitive data,maintain network integrity,and respond quickly to security *** study advances network security and lays the groundwork for ANN-based cybersecurity solutions.

关键词： VPN network traffic flow ANN classification intrusion detection data exfiltration encrypted traffic feature extraction network security

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in electrical Networks

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi mohamed A.Zohdy saad Aldoihi Department of electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

Improved combustion stability of biogas at different CO_(2) concentrations using inhomogeneous partially premixed stratified flames

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Global Energy Interconnection 2024年第4期7卷 486-502页

作者： Mohy saad Mansour Maged Kiriakos Lili Hao mohamed Amr Serag-eldin Mechanical Power Engineering Department Cairo University1 Gamaa StreetCairo Governorate 12613Egypt Mechanical Engineering Department The American University in CairoAUC AveCairo Governorate 11835Egypt College of electrical Engineering and Control Science Nanjing Tech UniversityNanjing 211816P.R.China

Biogas is a renewable and clean energy source that plays an important role in the current environment of lowcarbon *** high-content CO_(2) in biogas can be separated,transformed,and utilized,it not only realizes high-value utilization of biogas but also promotes carbon reduction in the biogas *** improve the combustion stability of biogas,an inhomogeneous,partially premixed stratified(IPPS)combustion model was adopted in this *** thermal flame structure and stability were investigated for a wide range of mixture inhomogeneities,turbulence levels,CO_(2) concentrations,air-to-fuel velocity ratios,and combustion energies in a concentric flow slot burner(CFSB).A fine-wire thermocouple is used to resolve the thermal flame *** flame size was reduced by increasing the CO_(2) concentration and the flames became lighter *** flame temperature also decreased with increase in CO_(2) *** stability was reduced by increasing the CO_(2) ***,at a certain level of mixture inhomogeneity,the concentration of CO_(2) in the IPPS mode did not affect the ***,the IPPS mode of combustion should be suitable for the combustion and stabilization of *** should support the design of highly stabilized biogas turbulent flames independent of CO_(2) *** data show that the lower stability conditions are partially due to the change in fuel combustion energy,which is characterized by the Wobbe index(WI).In addition,at a certain level of mixture inhomogeneity,the effect of the WI on flame stability becomes dominant.

关键词： Biogas Renewable energy Effect of CO_(2) Combustion stability Burner design Renewable fuels Partial premixed

BHJO: A Novel Hybrid Metaheuristic Algorithm Combining the Beluga Whale, Honey Badger, and Jellyfish Search Optimizers for Solving Engineering Design Problems

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 219-265页

作者： Farouq Zitouni saad Harous Abdulaziz S.Almazyad Ali Wagdy mohamed Guojiang Xiong Fatima Zohra Khechiba Khadidja Â Kherchouche Department of Computer Science and Information Technology Kasdi Merbah UniversityP.O.Box 30000OuarglaAlgeria Department of Computer Science College of Computing and InformaticsUniversity of SharjahP.O.Box 27272SharjahUnited Arab Emirates Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11937Jordan Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China

Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization *** approach aims to leverage the strengths of multiple algorithms,enhancing solution quality,convergence speed,and robustness,thereby offering a more versatile and efficient means of solving intricate real-world optimization *** this paper,we introduce a hybrid algorithm that amalgamates three distinct metaheuristics:the Beluga Whale Optimization(BWO),the Honey Badger Algorithm(HBA),and the Jellyfish Search(JS)*** proposed hybrid algorithm will be referred to as *** this fusion,the BHJO algorithm aims to leverage the strengths of each *** this hybridization,we thoroughly examined the exploration and exploitation capabilities of the BWO,HBA,and JS metaheuristics,as well as their ability to strike a balance between exploration and *** meticulous analysis allowed us to identify the pros and cons of each algorithm,enabling us to combine them in a novel hybrid approach that capitalizes on their respective strengths for enhanced optimization *** addition,the BHJO algorithm incorporates Opposition-Based Learning(OBL)to harness the advantages offered by this technique,leveraging its diverse exploration,accelerated convergence,and improved solution quality to enhance the overall performance and effectiveness of the hybrid ***,the performance of the BHJO algorithm was evaluated across a range of both unconstrained and constrained optimization problems,providing a comprehensive assessment of its efficacy and applicability in diverse problem ***,the BHJO algorithm was subjected to a comparative analysis with several renowned algorithms,where mean and standard deviation values were utilized as evaluation *** rigorous comparison aimed to assess the performance of the BHJOalgorithmabout its counterparts,shedd

关键词： Global optimization hybridization of metaheuristics beluga whale optimization honey badger algorithm jellyfish search optimizer chaotic maps opposition-based learning

Climate change impact and adaptation on wheat yield, water use and water use efficiency at North Nile Delta

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Frontiers of Earth Science 2020年第3期14卷 522-536页

作者： Marwa Gamal mohamed Ali mahmoud mohamed Ibrahim Ahmed el Baroudy Michael Fullen el-Said Hamad Omar Zheli Ding Ahmed Mohammed saad Kheir Soil and Water Department Faculty of AgricultureTanta UniversityTanta33516Egypt Soils Water and Environment Research InstituteAgricultural Research CenterGiza12411Egypt Faculty of Science and Engineering The University of WolverhamptonWolverhamptonWV11LYUK Haikou Experimental Station Chinese Academy of Tropical Agricultural Sciences(CATAS)Haikou570000China

Investigation of climate change impacts on food security has become a global hot *** so,efforts to mitigate these issues in arid regions have been ***,in this paper,further research is discussed based on data obtained from various crop and climate *** DSSATcrop models(CMs)(CERESWheat and N-Wheat)were calibrated with two wheat cultivars(Gemiza9 and Misr1).A baseline simulation(1981-2010)was compared with different scenarios of simulations using three Global Climate Models(GCMs)for the 2030s,2050s and *** impacts of climate change were assessed using the GCMs and CMs under the high emission Representative Concentration Pathway(RCP8.5).Results predicted decreased wheat grain yields by a mean of 8.7%,11.4%and 13.2%in the 2030s,2050s and 2080s,respectively,relative to the baseline *** impacts of climatic change are probable,despite some uncertainties within the GCMs(i.e.,2.1%,5.0%and 8.0%)and CMs(i.e.,2.2%,6.0%and 9.2%).Changing the planting date with a scenario of plus or minus 5 or 10 days from the common practice was assessed as a potentially effective adaptation option,which may partially offset the negative impacts of climate *** the sowing date by 10 days(from 20 November to 30 November)proved the optimum scenario and decreased further reduction in wheat yields resulting from climate change to 5.2%,6.8%and 8.5%in the 2030s,2050s and 2080s,respectively,compared with the 20 November *** planting 5-days earlier scenario showed a decreased impact on climate change ***,the 10-days early planting scenario increased yield reduction under projected climate *** cultivar Misr1 was more resistant to rising temperature than *** the negative impacts of projected climate change on wheat production,water use efficiency would slightly *** ensemble of multi-model estimated impacts and adaptation uncertainties of climate change can assist decision-makers in planning clima

关键词： DSSAT models scenarios adaptation water use efficiency climate change

Wireless Sensor Networks Routing Attacks Prevention with Blockchain and Deep Neural Network

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Computers, Materials & Continua 2022年第3期70卷 6127-6140页

作者： mohamed Ali Ibrahim A.Abd el-Moghith mohamed N.el-Derini saad M.Darwish Higher Institute for Tourism Hotels and ComputerAl-SeyoufAlexandria21533Egypt Department of Information Technology Institute of Graduate Studies and ResearchAlexandria University21526Egypt Department of Computer and Systems Engineering Faculty of EngineeringAlexandria UniversityAlexandria21544Egypt

Routing is a key function inWireless Sensor Networks(WSNs)since it facilitates data transfer to base *** attacks have the potential to destroy and degrade the functionality ofWSNs.A trustworthy routing system is essential for routing security andWSN *** methods have been implemented to build trust between routing nodes,including the use of cryptographic methods and centralized ***,the majority of routing techniques are unworkable in reality due to the difficulty of properly identifying untrusted routing node *** the moment,there is no effective way to avoid malicious node *** a consequence of these concerns,this paper proposes a trusted routing technique that combines blockchain infrastructure,deep neural networks,and Markov Decision Processes(MDPs)to improve the security and efficiency of WSN *** authenticate the transmission process,the suggested methodology makes use of a Proof of Authority(PoA)mechanism inside the blockchain *** validation group required for proofing is chosen using a deep learning approach that prioritizes each node’s *** are then utilized to determine the suitable next-hop as a forwarding node capable of securely transmitting *** to testing data,our routing system outperforms current routing algorithms in a 50%malicious node routing scenario.

关键词： Wireless sensor networks trusted routing deep neural network blockchain markov decision