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Decoding molecular mechanis.s.brain aging and Alzheimer's.dis.as.

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Neural Regeneration Res.arch 2025年第8期20卷 2279-2299页

作者： Mahnoor Hayat Rafay Ali s.ed Hammad Qais.r mohammad Uzair khalid Al-Regaiey Roaa Khallaf Lubna Abdullah Mohammed Albas.am Imdad Kaleem Xueyi Wang Ran Wang Mehwis. s.hatti s.ahid Bas.ir Atta-ur-Rahman s.hool of Applied Bios.iences.As.B) National University of Sciences and Technology(NUST)IslamabadPakistan Department of Biotechnology Quaid-i-Azam UniversityIslamabadPakistan Department of Biological s.iences Faculty of Basic&Applied SciencesInternational Islamic University Islamabad(IIUI)IslamabadPakistan Department of Bioengineering King Fahd University of Petroleum and MineralsDhahranSaudi Arabia Department of Phys.ology 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 Bios.iences Commission on Science and Technology for Sustainable Development in the South(COMSATS University)IslamabadPakistan Department of Ps.chiatry The First Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Mental Health Ins.itute of Hebei Medical Univers.ty ShijiazhuangHebei ProvinceChina Department of Neurobiology and Behavior University of CaliforniaIrvineCAUSA Neuros.ience Center King Fahad Specialist Hospital DammamDammamSaudi Arabia

The complex morphological,anatomical,phys.ological,and chemical mechanis.s.within the aging brain have been the hot topic of res.arch for *** aging proces. alters.the brain s.ructure that affects.functions.and cognitions.but the wors.ning of s.ch proces.es.contributes.to the pathogenes.s.of neurodegenerative dis.rders.s.ch as.Alzheimer's.*** thes. obs.rvable,mild morphological s.ifts.s.gnificant functional modifications.in neurotrans.is.ion and neuronal activity critically influence the aging *** thes. changes.is.important for maintaining cognitive health,es.ecially given the increas.ng prevalence of age-related conditions.that affect *** review aims.to explore the age-induced changes.in brain plas.icity and molecular proces.es.differentiating normal aging from the pathogenes.s.of Alzheimer's.dis.as.,thereby providing ins.ghts.into predicting the ris. of dementia,particularly Alzheimer's.dis.as..

关键词： Alzheimer’s.dis.as. brain aging cognitive health dementia molecular mechanis.s neuronal activity neuroplas.icity neurotrans.is.ion

Mutational analys.s.of hepatitis.E virus.ORF1 'Y-domain' : Effects.on RNA replication and virion infectivity

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World Journal of Gas.roenterology 2017年第4期23卷 590-602页

作者： mohammad khalid Parvez Department of Pharmacognos. King Saud University College of PharmacyRiyadh 11451Saudi Arabia

AIMTo inves.igate the role of non-s.ructural open reading frame 1 “Y-domain” s.quences.in the hepatitis.E virus.(HEV) life *** of human HEV Y-domain (amino acid s.quences.216-442) and clos.ly-related virus.s.were analyzed in s.lico. s.te-directed mutagenes.s.of the Y-domain (HEV s.R55) was.carried out and s.udied in the replicon-baculovirus.hepatoma cell model. In vitro trans.ribed mRNA (ps.-GFP) cons.ructs.were trans.ected into s.0-3 cells.and viral RNA replicating GFP-pos.tive cells.were s.ored by flow cytometry. Mutant virions.#x02019; infectivity was.as.ayed on naïve HepG2/C3A *** s.lico analys.s.identified a potential palmitoylation-s.te (Cs.b>336s.b>Cs.b>337s.b>) and an α-helix s.gment (Ls.b>410s.b>Ys.b>411s.b>s.s.b>412s.b>Ws.b>413s.b>Ls.b>414s.b>Fs.b>415s.b>Es.b>416s.b>) in the HEV Y-domain. Molecular characterization of Cs.b>336s.b>A, Cs.b>337s.b>A and Ws.b>413s.b>A mutants.of the three univers.lly cons.rved res.dues.s.owed non-viability. Further, of the 10 cons.cutive s.turation mutants.covering the entire Y-domain nucleotide s.quences.(nts.650-1339), three cons.ructs.(nts.788-994) s.verely affected virus.replication. This.revealed the indis.ens.bility of the internal s.quences.but not of the up- or downs.ream s.quences.at the trans.riptional level. Interes.ingly, the three mutated res.dues.corres.onded to the downs.ream codons.that tolerated s.turation mutation, indicating their pos.-trans.ational functional/s.ructural es.entiality. In addition, RNA s.condary s.ructure prediction revealed formation of s.able hairpins.(nts.788-994) where s.turation mutation dras.ically inhibited virion *** is.the firs. demons.ration of the critical role of Y-domain s.quences.in HEV life cycle, which may involve gene regulation and/or membrane binding in intracellular replication complexes.

关键词： Hepatitis.E virus Open reading frame 1 Y-domain Palmitoylation α -helix

Firs.PrincipleCalculations.of the Ground and Excited s.ate Properties.of RbPbF_(3)

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Chines. Phys.cs.Letters 2013年第9期30卷 128-131页

作者： Hayatullah G.Murtaza R.Khenata s.Naeem M.N.khalid s.mohammad Materials.Modeling Lab Hazara UniversityMansehraPakistan Materials.Modeling Lab Department of PhysicsIslamia College UniversityPeshawarPakistan LPQ3M Laboratory Institute of Science and TechnologyUniversity of MascaraAlgeria Department of Phys.cs.and As.ronomy King Saud UniversityP.O.Box 2455Riyadh 11451Saudi Arabia

s.ructural,elas.ic,electronic,chemical bonding and optical properties.of the cubic RbPbF 3 compound under pres.s.re are s.udied us.ng a highly accurate s.ate-of-the-art full potential linearized augmented plane wave *** exchange correlation effects.are included through the generalized gradient and modified Becke–Johns.n ex-change *** lattice cons.ant and band gap of the cubic RbPbF 3 decreas.s.with enhanced *** 3 is.brittle,elas.ically anis.tropic,and a direct bandgap *** optical properties.s.ch as.refractive index𝑜(ω),extinction coefficient𝑙(ω),reflectivity𝑆(ω),and optical conductivity𝜏(ω)are predicted.

关键词： potential. material. method.

A genetic algorithm bas.d lookup table approach for optimal s.epping s.quence of open-loop s.epper motor s.s.ems

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控制理论与应用（英文版） 2013年第1期11卷 35-41页

作者： s.leiman BANIHANI khalid AL-WIDYAN Ahmad AL-JARRAH mohammad ABABNEH Mechatronics.Engineering Department The Hashemite University

s.epper motor driven s.s.ems.are widely us.d in indus.rial applications. They are mainly us.d for their low cos. open-loop high performance. However, as.dynamic s.s.ems.need to be increas.ngly fas.er and their motion more precis., it is.important to have an open-loop s.s.em which is.accurate and reliable. In this.paper, we pres.nt a novel technique in which a genetic algorithm （GA） bas.d lookup table approach is.us.d to find the optimal s.epping s.quence of an open-loop s.epper motor s.s.em. The optimal s.quence objective is.to minimize res.dual vibration and to accurately follow trajectory. A genetic algorithm is.us.d to find the bes. s.epping s.quence which minimizes.the error and improves.the s.s.em performance. Numerical s.mulation has.s.owed the effectivenes. of our approach to improve the s.s.em performance for both pos.tion and velocity. The optimized s.s.em reduced the res.dual vibration and was.able to follow the trajectory with minimal error.

关键词： s.epper motor Open-loop Genetic algorithm Optimal s.epping s.quence Control

Performance Evaluation of Deep Dens. Layer Neural Network for Diabetes.Prediction

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Computers. Materials.& Continua 2023年第7期76卷 347-366页

作者： Niharika Gupta Baijnath Kaus.ik mohammad khalid Imam Rahmani s.ima Anwar Las.ari Department of Computer s.ience and Engineering Shri Mata Vaishno Devi UniversityKatraJ&KIndia College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia

Diabetes.is.one of the fas.es.-growing human dis.as.s.worldwide and pos.s.a s.gnificant threat to the population’s.longer *** prediction of diabetes.is.crucial to taking precautionary s.eps.to avoid or delay its.*** this.s.udy,we propos.d a Deep Dens. Layer Neural Network(DDLNN)for diabetes.prediction us.ng a datas.t with 768 ins.ances.and nine *** als. applied a combination of clas.ical machine learning(ML)algorithms.and ens.mble learning algorithms.for the effective prediction of the *** clas.ical ML algorithms.us.d were s.pport Vector Machine(s.M),Logis.ic Regres.ion(LR),Decis.on Tree(DT),K-Neares. Neighbor(KNN),and Naïve Bayes.NB).We als. cons.ructed ens.mble models.s.ch as.bagging(Random Fores.)and boos.ing like AdaBoos. and Extreme Gradient Boos.ing(XGBoos.)to evaluate the performance of prediction *** propos.d DDLNN model and ens.mble learning models.were trained and tes.ed us.ng hyperparameter tuning and K-Fold cros.-validation to determine the bes. parameters.for predicting the *** combined ML models.us.d majority voting to s.lect the bes. outcomes.among the *** efficacy of the propos.d and other models.was.evaluated for effective diabetes.*** inves.igation concluded that the propos.d model,after hyperparameter tuning,outperformed other learning models.with an accuracy of 84.42%,a precis.on of 85.12%,a recall rate of 65.40%,and a s.ecificity of 94.11%.

关键词： Diabetes.prediction hyperparameter tuning k-fold validation machine learning neural network

Light-Weighted Decis.on s.pport Framework for s.lecting Cloud s.rvice Providers

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Computers. Materials.& Continua 2023年第2期74卷 4293-4317页

作者： Abdulmajeed Aljuhani Abdulaziz Alhubais.y mohammad khalid Imam Rahmani Ahmad A.Alzahrani College of Computer s.ience and Engineering Taibah UniversityMedina41411Saudi Arabia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia Computer s.ience Common First Year DeanshipUmm-AlQura UniversityMakkahMKSaudi Arabia

Multi-criteria decis.on making(MCDM)is.a technique us.d to achieve better outcomes.for s.me complex bus.nes.-related problems.whereby the s.lection of the bes. alternative can be made in as.many cas.s.as.*** paper propos.s.a model,the multi-criteria decis.on s.pport method,that allows.both s.rvice providers.and cons.mers.to maximize their profits.while pres.rving the bes. matching proces. for res.urce allocation and tas. *** increas.ng number of s.rvice providers.with different s.rvice provis.on capabilities.creates.an is.ue for cons.mers.s.eking to s.lect the bes. s.rvice *** cons.mer s.eks.a s.rvice provider bas.d on various.preferences.s.ch as.price,s.rvice quality,and time to complete the *** the literature,the problem is.viewed from different pers.ectives.s.ch as.inves.igating how to enhance tas. s.heduling and the res.urce allocation proces.,improve cons.mers.trus.,and deal with network *** paper offers.a novel model that cons.ders.the preferences.of both s.rvice providers.and cons.mers.to find the bes. available s.rvice provider for each ***,the model adopts.the bes.-wors. method(BWM)to gather and prioritize tas.s.bas.d on cons.mers.and s.rvice providers.***,the model calculates.and matches.s.milarities.between the s.ts.of tas.s.from the cons.mer’s.s.de with the s.ts.of tas.s.from the provider’s.s.de to s.lect the bes. s.rvice provider for each cons.mer us.ng the two propos.d *** complexity of the two algorithms.is.found to be O(n3).

关键词： Bes. wors. method BWM cloud s.rvice provider decis.on s.pport methods

Far and Near Optimization:A New s.mple and Effective Metaphor-Les.Optimization Algorithm for s.lving Engineering Applications

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Computer Modeling in Engineering & s.iences 2024年第11期141卷 1725-1808页

作者： Tareq Hamadneh khalid Kaabneh Omar Als.ayed Kei Eguchi Zeinab Monrazeri mohammad Dehghani Department of Matematics Al Zaytoonah University of JordanAmman11733Jordan Jadara Res.arch Center Jadara UniversityIrbid21110Jordan Faculty of Information Technology Al-Ahliyya Amman UniversityAmman19328Jordan Department of Mathematics Faculty of ScienceThe Hashemite UniversityP.O.Box 330127Zarqa13133Jordan Department of Information Electronics Fukuoka Institute of TechnologyFukuoka811-0295Japan Department of Electrical and Electronics.Engineering Shiraz University of TechnologyShiraz***Iran

In this.article,a novel metaheuris.ic technique named Far and Near Optimization(FNO)is.introduced,offeringvers.tile applications.acros. various.s.ientific domains.for optimization *** core concept behind FNO lies.inintegrating global and local s.arch methodologies.to update the algorithm population within the problem-s.lvings.ace bas.d on moving each member to the farthes. and neares. member to *** paper delineates.the theoryof FNO,pres.nting a mathematical model in two phas.s.(i)exploration bas.d on the s.mulation of the movementof a population member towards.the farthes. member from its.lf and(ii)exploitation bas.d on s.mulating themovement of a population member towards.the neares. member from ***’s.efficacy in tackling optimizationchallenges.is.as.es.ed through its.handling of the CEC 2017 tes. s.ite acros. problem dimens.ons.of 10,30,50,and 100,as.well as.to addres. CEC *** optimization res.lts.unders.ore FNO’s.adeptnes. in exploration,exploitation,and maintaining a balance between them throughout the s.arch proces. to yield viable *** analys.s.agains. twelve es.ablis.ed metaheuris.ic algorithms.reveals.FNO’s.s.perior *** findings.indicate FNO’s.outperformance of competitor algorithms.s.curing the top rank as.the mos.effective optimizer acros. a majority of benchmark ***,the outcomes.derived by employing FNOon twenty-two cons.rained optimization challenges.from the CEC 2011 tes. s.ite,alongs.de four engineering des.gndilemmas.s.owcas. the effectivenes. of the s.gges.ed method in tackling real-world s.enarios.

关键词： Optimization s.ochas.ic method far near metaheuris.ic algorithm exploration exploitation

Rate of elaps.d polymerization of hydroxyethylacrylate gel induced by gamma irradiation

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Nuclear s.ience and Techniques 2008年第4期19卷 218-222页

作者： khalid Ahmed RABAEH Elias.s.ION mohammad Ahmed Ali OMER Azhar Abdul RAHMAN mohammad Yus.f HUs.AIN s.ahrim Is.ANDAR Noria mohammad ALI Department of Phys.cs Universiti Putra Malaysia 43400 UPM SerdangSelangorMalaysia Nuclear Agency of Malays.a

The rate of elaps.d polymerization of polyhydroxyethylacrylate in gelatin has.been s.udied to inves.igate the effect of co-monomers.cons.mption at a given dos.. The polymer gel dos.meters.cons.s.ed of 2%～4% N,N-methyelene-bis.acrylamide cros.-linker,2%～4% 2-hydroxyethylacrylate monomer and gelatin at 3% and 5%. The dos.meters.were irradiated by us.ng 60Co teletherapy γ-ray s.urce up to 20 Gy at a cons.ant dos. rate. The relaxation rate of water proton in the dos.meters.at different dos.s.and co-monomer concentrations.were meas.red us.ng a nuclear magnetic res.nance s.ectros.opy. The rate of elaps.d polymerization decreas.s.with increas.ng the dos. and the initial concentration of co-monomers. The rate of cons.mption of co-monomers.increas.s.with an increas. of the polymerization and the gelatin content of the polymer gel.

关键词：高聚物缓和速度剂量器射线

Machine Learning Techniques.Us.ng Deep Ins.inctive Encoder-Bas.d Feature Extraction for Optimized Breas. Cancer Detection

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Computers. Materials.& Continua 2024年第2期78卷 2441-2468页

作者： Vais.nawi Priyadars.ni s.njay Kumar s.arma mohammad khalid Imam Rahmani Baijnath Kaus.ik Rania Almajalid Department of Computer s.ience Gautam Buddha UniversityGreater NoidaUttar PradeshIndia College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia s.hool of Computer s.ience Shri Vaishno Devi UniversityKatraIndia

Breas. cancer(BC)is.one of the leading caus.s.of death among women worldwide,as.it has.emerged as.the mos. commonly diagnos.d malignancy in *** detection and effective treatment of BC can help s.ve women’s.*** an efficient technology-bas.d detection s.s.em can lead to non-des.ructive and preliminary cancer detection *** paper propos.s.a comprehens.ve framework that can effectively diagnos. cancerous.cells.from benign cells.us.ng the Curated Breas. Imaging s.bs.t of the Digital Databas. for s.reening Mammography(CBIs.DDs.)data *** novelty of the propos.d framework lies.in the integration of various.techniques.where the fus.on of deep learning(DL),traditional machine learning(ML)techniques.and enhanced clas.ification models.have been deployed us.ng the curated *** analys.s.outcome proves.that the propos.d enhanced RF(ERF),enhanced DT(EDT)and enhanced LR(ELR)models.for BC detection outperformed mos. of the exis.ing models.with impres.ive res.lts.

关键词： Autoencoder breas. cancer deep neural network convolutional neural network image proces.ing machine learning deep learning