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Decoding molecular mechanisms:brain aging and alzheimer's disease

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Neural Regeneration Research 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay ali syed Hammad Qaiser Mohammad Uzair Khalid al-Regaiey Roaa Khallaf Lubna Abdullah mohammed albassam Imdad Kaleem Xueyi Wang Ran Wang Mehwish sBhatti shahid Bashir Atta-ur-Rahman school of Applied Biosciences(AsAB) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological sciences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Physiology College of MedicineKing Saud UniversityRiyadhSaudi Arabia Department of Neurology Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Mental Health Neuroscience CenterKing Fahad Specialist HospitalDammamSaudi Arabia Department of Biosciences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Psychiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Institute of Hebei Medical University ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuroscience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for *** aging process.alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as.alzheimer's *** these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging *** these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect *** review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly alzheimer's disease.

关键词： alzheimer’s disease brain aging cognitive health dementia molecular mechanisms neuronal activity neuroplasticity neurotransmission

Intrusion Detection in the Internet of Things Using Fusion of GRU-LsTM Deep Learning Model

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Intelligent Automation & soft Computing 2023年第8期37卷 2279-2290页

作者： Mohammad s.al-kahtani Zahid Mehmood Tariq sadad Islam Zada Gauhar ali mohammed ElAffendi Department of Computer Engineering Prince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan The FAMLIR Group The University of LahoreLahore54000Pakistan Department of Computer science University of Engineering&TechnologyMardan23200Pakistan Faculty of Computing International Islamic UniversityIslamabad44000Pakistan EIAs Data science and Blockchain Lab College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia

Cybersecurity threats are increasing rapidly as hackers use advanced *** a result,cybersecurity has now a significant factor in protecting organizational *** detection systems(IDss)are used in networks to flag serious issues during network management,including identifying malicious traffic,which is a *** remains an open contest over how to learn features in IDs since current approaches use deep learning *** learning,which combines swarm intelligence and evolution,is gaining attention for further improvement against cyber *** this study,we employed a PsO-GA(fusion of particle swarm optimization(PsO)and genetic algorithm(GA))for feature selection on the CICIDs-2017 *** achieve better accuracy,we proposed a hybrid model called LsTM-GRU of deep learning that fused the GRU(gated recurrent unit)and LsTM(long short-term memory).The results show considerable improvement,detecting several network attacks with 98.86%accuracy.A comparative study with other current methods confirms the efficacy of our proposed IDs scheme.

关键词： Cyber security deep learning intrusion detection PsO-GA CICIDs-2017 intelligent system security and privacy IoT

Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

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Computer Modeling in Engineering & sciences 2024年第3期138卷 2103-2127页

作者： Othman s.al-Heety Zahriladha Zakaria Ahmed Abu-Khadrah Mahamod Ismail sarmad Nozad Mahmood mohammed Mudhafar shakir Hussein alsariera Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka(UTeM)Durian TunggalMalaysia College of Computing&Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Department of Electrical Electronic and System EngineeringUniversiti Kebangsaan MalaysiaUKM BangiSelangorMalaysia Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityKirkukIraq Faculty of Engineering and Electronic Engineering Universiti Tun Hussein Onn Malaysia(UTHM)Batu PahatMalaysia 6Research Center DepartmentThe University of MashreqBaghdadIraq

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the *** this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things *** framework integrates Kalman filtering and *** smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction *** traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction *** evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art ***,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

关键词： Q-learning intelligent transportation system(ITs) traffic control vehicular communication kalman filtering smart city Internet of Things

Pomegranate peel extract lessens histopathologic changes and restores antioxidant homeostasis in the hippocampus of rats with aluminium chloride-induced alzheimer’s disease

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Asian Pacific Journal of Tropical Medicine 2020年第10期13卷 456-463页

作者： steve Harakeh Wafaa s.Ramadan mohammed s.al Muhayawi soad al Jaouni shaker Mousa Khalid Rehman Hakeem special Infectious Agent Unit King Fahd Medical Research CenterKing Abdulaziz UniversityKingdom of Saudi Arabia Department of Anatomy Faculty of MedicineKing Abdulaziz UniversityKingdom of Saudi Arabia Department of Anatomy Faculty of MedicineAin Shams UniversityCairoEgypt Department of Medical Microbiology/Parasitology and Molecular Microbiology Laboratory KAUHKing Abdulaziz UniversityKingdom of Saudi Arabia Department of Hematology/Pediatric Oncology King Abdulaziz University Hospital(KAUH)Faculty of MedicineKing Abdulaziz UniversityKingdom of Saudi Arabia Yousef Abdul Latif Jameel scientific Chair of Prophetic Medicine Application Faculty of MedicineKing Abdulaziz UniversityKingdom of Saudi Arabia Pharmaceutical Research Institute Albany College of Pharmacy and Health SciencesRensselaerNYUSA Department of Biological sciences Faculty of SciencesKing Abdulaziz UniversityJeddahSaudi Arabia

Objective:To investigate the neuroprotective efficacy of pomegranate and ellagic acid on the histopathological changes in the hippocampus of an aluminium chloride(alCl3)induced rat model of alzheimer’s ***:sprague Da... 详细信息

Objective:To investigate the neuroprotective efficacy of pomegranate and ellagic acid on the histopathological changes in the hippocampus of an aluminium chloride(alClsub>3)induced rat model of alzheimer’s ***:sprague Dawley rats were divided into 4 groups(n=10each):GroupⅠ:serving as negative control;GroupⅡ,alzheimer model,induced by administration of 17 mg/kg bw alCl3;GroupⅢ,administered the same dose of alCl3 with 50 mg/kg of pomegranate peel extract and GroupⅣ:administered ellagic acid(50 mg/kg)in addition to the same dose of *** medication given to all groups continued for 28 *** were given the compounds by gastric *** arm maze test,hippocampus antioxidant markers,histopathology of the dentate gyrus,and CA3 of the hippocampus were ***:Rats treated with pomegranate peel extract exposed to radial arm maze test showed less number of errors and reduced time needed to reach the *** was an increase in the levels of glutathione,catalase,and total antioxidant capacity and decreased lipid peroxidation *** features in dentate gyrus and CA3 as apoptosis and chromatolysis of pyramidal cells and granular layer,respectively,were *** characteristic neurofibrillary tangles and senile plaques were *** with ellagic acid ameliorated the pathological results but to a statistically lower ***:Pomegranate peel extract alleviates memory deficit and restores antioxidant homeostasis following degenerative changes in the hippocampus induced by aluminium chloride in rats.

关键词： Pomegranate Peel extract Ellagic acid Antioxidants Hippocampus Behavioural test

A Comprehensive Investigation of Machine Learning Feature Extraction and ClassificationMethods for Automated Diagnosis of COVID-19 Based on X-ray Images

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Computers, Materials & Continua 2021年第3期66卷 3289-3310页

作者： Mazin Abed mohammed Karrar Hameed Abdulkareem Begonya Garcia-Zapirain salama A.Mostafa Mashael s.Maashi alaa s.al-Waisy mohammed Ahmed subhi Ammar Awad Mutlag Dac-Nhuong Le College of Computer science and Information Technology University of AnbarRamadi31001Iraq College of Agriculture Al-Muthanna UniversitySamawah66001Iraq eVIDA Lab University of DeustoBilbao48007Spain Faculty of Computer science and Information Technology Universiti Tun Hussein Onn MalaysiaJohor86400Malaysia software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11451Saudi Arabia Faculty of Engineering and Built Environment Universiti Kebangsaan MalaysiaBangi43600Malaysia Pure science Department Ministry of EducationGeneral Directorate of CurriculaBaghdad10Iraq Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam

The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global *** biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 *** this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(sVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 ***(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection *** on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 *** comparison,in traditional machine learning techniques, the sVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.

关键词： Coronavirus disease COVID-19 diagnosis machine learning convolutional neural networks resnet50 artificial neural network support vector machine X-ray images feature transfer learning

Practical Fast Computation of Zernike Moments

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Journal of Computer science & Technology 2002年第2期17卷 181-188页

作者： al-Rawi mohammed 杨杰 Image Processing and Pattern Recognition Institute Shanghai Jiaotong University Shanghai 200030 P.R. China

The fast computation of Zernike moments from normalized geometric moments has been developed in this paper. The computation is multiplication free and only additions are needed to generate Zernike moments. Geometric moments are generated using Hatamian's filter up to high orders by a very simple and straightforward computation scheme. Other kinds of moments (e.g., Legendre, pseudo Zernike) can be computed using the same algorithm after giving the proper transformations that state their relations to geometric moments. Proper normalizations of geometric moments are necessary so that the method can be used in the efficient computation of Zernike moments. To ensure fair comparisons, recursive algorithms are used to generate Zernike polynomials and other coefficients. The computational complexity model and test programs show that the speed-up factor of the proposed algorithm is superior with respect to other fast and/or direct computations. It perhaps is the first time that Zernike moments can be computed in real time rates, which encourages the use of Zernike momentfeatures in different image retrieval systems that support huge databases such as the XM experimental model stated for the MPEG-7 experimental core. It is concluded that choosing direct computation would be impractical.

关键词： Zernike moment fast algorithm digital filter invariant patternrecognition

The PCDD/PCDF Dioxin Releases in the Climate of Environment of Jordan in the Period (2000-2008)

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Journal of Thermal science 2010年第2期19卷 182-192页

作者： mohammed Awwad al-Dabbas Mechanical Engineering department Mutah University

Many environment problems of the full using of several categories of processing include mining,heat generators,direct combustion of forest fires,cement production,power plant,transport,medical ***/furan releases from these categories are one of these environment *** lines of reducing the PCDD/PCDF (Polychlorinated dibenzo-para-dioxins/Polychlorinated dibenzofurans) releases from these categories are *** contribution of this paper is present the identification and estimation of the latest figure of dioxin/furan releases in the climate of environment of Jordan in the period 2000-2008 from the following categories (cement,aluminum,ceramic,medical waste,power plant,land fill,ferrous and non-ferrous metals,uncontrolled combustion process (biomass burning,waste burning,accidental fires in house,transport).These finding shows the sign of growth of estimated PCDD/PCDF releases from categories which did not calculated and followed after *** result shows the highest PCDD/PCDF release from landfill fires (62.75 g TEQ/year),medical waste (8.8264 g TEQ/year),and transport (3.0145 g TEQ/year).Jordan seeks by next years,a reduction in total releases of dioxins and furans from sources resulting from human *** challenge will apply to the aggregate of releases to the air nationwide and of releases to the water within the Jordan *** should conduct air monitoring for dioxin in order to track fluctuations in atmospheric deposition levels.

关键词： Jordan transport sector PCB dioxin & furan POP PCDD/PCDF power plant biogas

Effect evaluation of s.ale types on hydrocarbon potential using well logs and crossplot approach,Halewah oilfield,sab'atayn Basin,Yemen

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Energy Geoscience 2022年第2期3卷 202-210页

作者： Nabeel A.s.al al-Azazi A.s.A.E.alsrory mohammed albaroot Oil and Gas Engineering Department Faculty of Oil and MineralsShabwah UniversityShabwaYemen Geophysics Administration Yemen Company for Investment in Oil&MineralsSana'aYemen Applied Geology Department Faculty of SciencesSaba University RegionMaribYemen

Log-analysts typically distinguish three types of s.ale distribution in clastic reservoirs,that is,laminated,dispersed and structural distribution,which tend to influence the effective porosity and permeability of *** alif Member is made up of sandstone interbedded with some s.ale,with s.ale dominating on top and at the *** sedimentary formations,the gamma ray log normally reflects the s.ale *** gamma ray log and neutron-density porosity crossplot is used to estimate a reservoir's s.ale volume(Vsh),according to which the alif Member is divided into three *** addition,s.ale types are recognized by neutron-density porosity crossplot,and the correlation coefficients of gamma ray log-based Vsh and neutron-density porosity-based Vsh are suggested to be *** Vsh and s.ale types of the three zones are compared against the reservoir's potential to yield *** major oil intervals mainly concentrate in s.aly sand and sandstone zones of dispersed and laminated s.ale *** third zone,the lowermost interval,contains pure s.ale of laminated type and is considered out of reservoir standards in hydrocarbon production due to its excessive s.ale *** assessment of s.ale type distribution and Vsh by crossplot approach could not furnish correct information to evaluate massive s.ale intervals.

关键词： s.ale type distribution s.ale volume(Vsh) s.aly sandstone reservoir alif member sab'atayn Basin Yemen

Detection of Gain Enhancement in Laser-Induced Fluorescence of Rhodamine B Lasing Dye by silicon Dioxide Nanostructures-Coated Cavity

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Photonic sensors 2018年第1期8卷 80-87页

作者： mohammed N. A. al-TAMEEMI Department of Physics Al-lraqia University Baghdad 12001 Iraq

In this work, nanostructured silicon dioxide films are deposited by closed-field unbalanced direct-current （DC） reactive magnetron sputterin technique on two sides of quartz cells containing rhodamine B dye dissolved in ethanol with 10-5 M concentration as a random gain medium. The preparation conditions are optimized to prepare highly pure siO2 nanostructures with a minimum particle size of about 20nm. The effect of siO2 films as external cavity for the random gain medium is determined by the laser-induced fluorescence of this medium, and an increase of about 200% in intensity is observed after the deposition of nanostructured siO2 thin films on two sides of the dye cell.

关键词： silicon dioxide nanostructures gain enhancement rhodamine B dye