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Computer Modeling in Engineering & Sciences 2024年第9期140卷 2795-2823页

作者： naif alotaibi a.S.a.-Moisheer Ibra.im Elba.a. Moha.med Elga.hy Eha. M.a.metwa.ly Depa.tment of Ma.hema.ics a.d Sta.istics Faculty of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Depa.tment of Ma.hema.ics College of ScienceJouf UniversityP.O.Box 848Sakaka72351Saudi Arabia Ma.hema.ics a.d Computer Science Depa.tment Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt Depa.tment of Ba.ic Sciences Higher Institute of Administrative SciencesBelbeisEgypt Fa.ulty of Business a.ministra.ion Delta University for Science and TechnologyGamasa11152Egypt

This a.ticle introduces a.novel va.ia.t of the genera.ized linea. exponentia.(GLE)distribution,known a. the sine genera.ized linea. exponentia.(SGLE)*** SGLE distribution utilizes the sine tra.sforma.ion to enha.ce its *** upda.ed distribution is very a.a.ta.le a.d ma. be efficiently used in the modeling of surviva. da.a.a.d dependa.ility *** suggested model incorpora.es a.ha.a.d ra.e function(HRF)tha. ma. displa. a.rising,J-sha.ed,or ba.htub form,depending on its unique *** model includes ma.y well-known lifespa. distributions a. sepa.a.e *** suggested model is a.compa.ied with a.ra.ge of sta.istica. *** model pa.a.eters a.e exa.ined using the techniques of ma.imum likelihood a.d Ba.esia. estima.ion using progressively censored *** order to eva.ua.e the effectiveness of these techniques,we provide a.set of simula.ed da.a.for testing *** releva.ce of the newly presented model is shown via.two rea.-world da.a.et a.plica.ions,highlighting its superiority over other respected simila. models.

关键词： Sine G fa.ily genera.ized linea. fa.lure ra.e progressively censored da.a moments ma.imum likelihood estima.ion Ba.esia. estima.ion simula.ion

Rea.tive Power Problem a.d Solutions: a. Overview

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Journa. of Power a.d Energy Engineering 2017年第5期5卷 40-54页

作者： a.med a. a.dElha.ez Sa.d H. a.ruwa.s Ya.eed a. a.sa.f Mutla. F. a.thoba.ti a.dulmohsen B. alotaibi naif a. alotaibi Electrica. Engineering Depa.tment College of Engineering Shaqra University Shaqra KSA Electrica. Engineering Depa.tment Faculty of Engineering Assiut University Assiut Egypt

This a.ticle presents a.comprehensive review for the dilemma.of rea.tive power flow, while a.dressing different proposed remedy stra.egies: conventiona. a.d most upda.e solutions. Robust a.a.ytica. expressions were utilized to exploit the functiona.ity of the proposed solutions a.d to show clea.ly the rela.ion between the rea.tive power a.d control va.ia.les. The a.ticle, moreover, proposes a.simple, innova.ive a.d robust a.a.ysis for sta.ic performa.ce of the STa.COM. This a.proa.h shows clea.ly the a.va.ta.es of the STa.TCOM in regula.ing rea.tive power a.d ma.nta.ning loa. volta.e level within presuma.le limits. The a.proa.h, furthermore, revea.s explicitly via.a.a.ytica. expressions the impa.t of the STa.COM opera.ion on different a.pects of the power system under concern.

关键词： Compensa.ion TCR TSC STa.COM Rea.tive Power

Developing a.Model for Pa.kinson’s Disea.e Detection Using Ma.hine Lea.ning a.gorithms

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Computers, Ma.eria.s & Continua 2024年第6期79卷 4945-4962页

作者： naif a. Muda.i Depa.tment of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Pa.kinson’s disea.e(PD)is a.chronic neurologica. condition tha. progresses over *** sta.t to ha.e trouble spea.ing,writing,wa.king,or performing other ba.ic skills a. dopa.ine-genera.ing neurons in some bra.n regions a.e injured or *** pa.ient’s symptoms become more severe due to the worsening of their signs over *** this study,we a.plied sta.e-of-the-a.t ma.hine lea.ning a.gorithms to dia.nose Pa.kinson’s disea.e a.d identify rela.ed risk *** resea.ch worked on the publicly a.a.la.le da.a.et on PD,a.d the da.a.et consists of a.set of significa.t cha.a.teristics of *** a.m to a.ply soft computing techniques a.d provide a. effective solution for medica. professiona.s to dia.nose PD *** resea.ch methodology involves developing a.model using a.ma.hine lea.ning *** the model selection,eight different ma.hine lea.ning techniques were a.opted:Na.ely,Ra.dom Forest(RF),Decision Tree(DT),Support Vector Ma.hine(SVM),Na.ve Ba.es(NB),Light Gra.ient Boosting Ma.hine(LightGBM),K-Nea.est Neighbours(KNN),Extreme Gra.ient Boosting(XGBoost),a.d Logistic Regression(LR).Subsequently,the concentra.ed models were va.ida.ed through 10-fold Cross-Va.ida.ion a.d Receiver Opera.ing Cha.a.teristic(ROC)—a.ea.Under the Curve(a.C).In a.dition,GridSea.chCV wa. utilised to mea.ure ea.h a.gorithm’s best pa.a.eter;eventua.ly,the models were tra.ned through the hyperpa.a.eter tuning *** 98%a.cura.y,LightGBM ha. the highest a.cura.y in this ***,KNN,a.d SVM ca.e in second with 96%***,the performa.ce scores of NB a.d LR were recorded to be 76%a.d 83%,*** is to be mentioned tha. a.ter a.plying 10-fold cross-va.ida.ion,the a.era.e performa.ce score of LightGBM a.counted for 93%.a. the sa.e time,the percenta.e of ROC-a.C a.pea.ed a. 0.92,which indica.es tha. this LightGBM model rea.hed a.sa.isfa.tory ***,we extra.ted mea.ingful insights a.d figured out potentia. ga.s on top of *** extra.ting mea.ingful in

关键词： Light GBM cross-va.ida.ion ROC-a.C Pa.kinson’s disea.e(PD) SVM a.d XGBoost

Roa. Tra.fic Monitoring from a.ria. Ima.es Using Templa.e Ma.ching a.d Inva.ia.t Fea.ures

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Computers, Ma.eria.s & Continua 2024年第3期78卷 3683-3701页

作者： a.ifa.Mehmood Qureshi naif a. Muda.i Moha.med a.ona.i Sa.ia.a.la.ua.Chelloug Jeongmin Pa.k Depa.tment of Crea.ive Technologies Air UniversityIslamabad46000Pakistan Depa.tment of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Depa.tment of Informa.ion Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Depa.tment of Informa.ion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Roa. tra.fic monitoring is a. impera.ive topic widely discussed a.ong *** used to monitor tra.fic frequently rely on ca.era. mounted on bridges or ***,a.ria. ima.es provide the flexibility to use mobile pla.forms to detect the loca.ion a.d motion of the vehicle over a.la.ger *** this end,different models ha.e shown the a.ility to recognize a.d tra.k ***,these methods a.e not ma.ure enough to produce a.cura.e results in complex roa. ***,this pa.er presents a. a.gorithm tha. combines sta.e-of-the-a.t techniques for identifying a.d tra.king vehicles in conjunction with ima.e *** extra.ted fra.es were converted to gra.sca.e,followed by the a.plica.ion of a.georeferencing a.gorithm to embed coordina.e informa.ion into the *** ma.king technique elimina.ed irreleva.t da.a.a.d reduced the computa.iona. cost of the overa.l monitoring ***,Sobel edge detection combined with Ca.ny edge detection a.d Hough line tra.sform ha. been a.plied for noise *** preprocessing,the blob detection a.gorithm helped detect the *** of va.ying sizes ha.e been detected by implementing a.dyna.ic thresholding *** wa. done on the first ima.e of every ***,to tra.k vehicles,the model of ea.h vehicle wa. ma.e to find its ma.ches in the succeeding ima.es using the templa.e ma.ching *** further improve the tra.king a.cura.y by incorpora.ing motion informa.ion,Sca.e Inva.ia.t Fea.ure Tra.sform(SIFT)fea.ures ha.e been used to find the best possible ma.ch a.ong multiple *** a.cura.y ra.e of 87%for detection a.d 80%a.cura.y for tra.king in the a. Motorwa. Netherla.d da.a.et ha. been *** the Vehicle a.ria. Ima.ing from Drone(Va.D)da.a.et,a. a.cura.y ra.e of 86%for detection a.d 78%a.cura.y for tra.king ha. been a.hieved.

关键词： Unma.ned a.ria. Vehicles(Ua.) a.ria. ima.es da.a.et object detection object tra.king da.a.elimina.ion templa.e ma.ching blob detection SIFT Va.D

Fine-Tuning Cyber Security Defenses: Eva.ua.ing Supervised Ma.hine Lea.ning Cla.sifiers for Windows Ma.wa.e Detection

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Computers, Ma.eria.s & Continua 2024年第8期80卷 2917-2939页

作者： Isla. Za.a.Moha.med naif a.a.a.i Syed Muha.ma. Sa.la.n a.dulla. a.sha.ra.i a.el a.sha.ra. Ka.wa. Imra. Hessa.a.fra.hi Depa.tment of Softwa.e Engineering International Islamic UniversityIslamabad25000Pakistan Informa.ion Technology Depa.tment Faculty of Computers and Information TechnologyUniversity of TabukTabuk71491Saudi Arabia Depa.tment of Computer Science a.d a.tificia. Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Depa.tment of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Depa.tment of Computer Science University of PeshawarPeshawar25121Pakistan Depa.tment of Informa.ion Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Ma.wa.e a.ta.ks on Windows ma.hines pose significa.t cybersecurity threa.s,necessita.ing effective detection a.d prevention *** ma.hine lea.ning cla.sifiers ha.e emerged a. promising tools for ma.wa.e ***,there rema.ns a.need for comprehensive studies tha. compa.e the performa.ce of different cla.sifiers specifica.ly for Windows ma.wa.e *** this ga. ca. provide va.ua.le insights for enha.cing cybersecurity *** numerous studies ha.e explored ma.wa.e detection using ma.hine lea.ning techniques,there is a.la.k of systema.ic compa.ison of supervised cla.sifiers for Windows ma.wa.e *** the rela.ive effectiveness of these cla.sifiers ca. inform the selection of optima. detection methods a.d improve overa.l security *** study a.ms to bridge the resea.ch ga. by conducting a.compa.a.ive a.a.ysis of supervised ma.hine lea.ning cla.sifiers for detecting ma.wa.e on Windows *** objectives include Investiga.ing the performa.ce of va.ious cla.sifiers,such a. Ga.ssia. Na.ve Ba.es,K Nea.est Neighbors(KNN),Stocha.tic Gra.ient Descent Cla.sifier(SGDC),a.d Decision Tree,in detecting Windows *** the a.cura.y,efficiency,a.d suita.ility of ea.h cla.sifier for rea.-world ma.wa.e detection *** the strengths a.d limita.ions of different cla.sifiers to provide insights for cybersecurity pra.titioners a.d *** recommenda.ions for selecting the most effective cla.sifier for Windows ma.wa.e detection ba.ed on empirica. *** study employs a.structured methodology consisting of severa. pha.es:explora.ory da.a.a.a.ysis,da.a.preprocessing,model tra.ning,a.d *** da.a.a.a.ysis involves understa.ding the da.a.et’s cha.a.teristics a.d identifying preprocessing *** preprocessing includes clea.ing,fea.ure encoding,dimensiona.ity reduction,a.d optimiza.ion to prepa.e the da.a.for *** tra.ning utilizes va.ious

关键词： Security a.d priva.y cha.lenges in the context of requirements engineering supervisedma.hine lea.ning ma.wa.e detection windows systems compa.a.ive a.a.ysis Ga.ssia. Na.ve Ba.es K Nea.est Neighbors Stocha.tic Gra.ient Descent Cla.sifier Decision Tree

UNet Ba.ed onMulti-Object Segmenta.ion a.d Convolution Neura. Network for Object Recognition

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Computers, Ma.eria.s & Continua 2024年第7期80卷 1563-1580页

作者： Nouf a.dulla. a.muja.ly Bisma.Ria. Chughta. naif a. Muda.i a.dulwa.a. a.a.eb a.a.d a.ga.ni Ha.da. a.a.za.ra.i Jeongmin Pa.k Depa.tment of Informa.ion Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Depa.tment of Computer Science Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Depa.tment of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Informa.ion Technology Depa.tment College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia Depa.tment of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent a.va.cements in vision technology ha.e ha. a.significa.t impa.t on our a.ility to identify multiple objects a.d understa.d complex *** technologies,such a. a.gmented rea.ity-driven scene integra.ion,robotic na.iga.ion,a.tonomous driving,a.d guided tour systems,hea.ily rely on this type of scene *** pa.er presents a.novel segmenta.ion a.proa.h ba.ed on the UNet network model,a.med a. recognizing multiple objects within a. *** methodology begins with the a.quisition a.d preprocessing of the ima.e,followed by segmenta.ion using the fine-tuned UNet ***,we use a. a.nota.ion tool to a.cura.ely la.el the segmented *** la.eling,significa.t fea.ures a.e extra.ted from these segmented objects,encompa.sing Ka.E(a.celera.ed Segmenta.ion a.d Extra.tion)fea.ures,energy-ba.ed edge detection,frequency-ba.ed,a.d blob *** the cla.sifica.ion sta.e,a.convolution neura. network(CNN)is *** comprehensive methodology demonstra.es a.robust fra.ework for a.hieving a.cura.e a.d efficient recognition of multiple objects in *** experimenta. results,which include complex object da.a.ets like MSRC-v2 a.d Pa.Ca.-VOC12,ha.e been *** a.a.yzing the experimenta. results,it wa. found tha. the Pa.Ca.-VOC12 da.a.et a.hieved a. a.cura.y ra.e of 95%,while the MSRC-v2 da.a.et a.hieved a. a.cura.y of 89%.The eva.ua.ion performed on these diverse da.a.ets highlights a.nota.ly impressive level of performa.ce.

关键词： UNet segmenta.ion blob fourier tra.sform convolution neura. network

Vision ba.ed intelligent tra.fic light ma.a.ement system using Fa.ter R‐CNN

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Ca.I Tra.sa.tions on Intelligence Technology 2024年第4期9卷 932-947页

作者： Syed Kona.n a.ba. Muha.ma. Usma. Gha.i Kha. Jia.Zhu Ra.eem Sa.wa. naif R.a.joha.i Ibra.im a.Ha.eed Muha.ma. Uma.r Ha.sa. Depa.tment of Computer Science a.d Engineering University of Engineering and TechnologyLahorePakistan Zhejia.g Key La.ora.ory of Intelligent Educa.ion Technology a.d a.plica.ion Zhejiang Normal UniversityJinhuaChina OTHEM Manchester Metropolitan UniversityManchesterUK Fa.ulty of Computing a.d Informa.ion Technology King Abdulaziz UniversityJeddahSaudi Arabia Depa.tment of ICT a.d Na.ura. Sciences Norwegian University of Science and Technology(NTNU)ÅlesundNorway

Tra.sporta.ion systems prima.ily depend on vehicula. flow on roa.s. Developed coun-tries ha.e shifted towa.ds a.toma.ed signa. control, which ma.a.es a.d upda.es signa. synchronisa.ion a.toma.ica.ly. In contra.t, tra.fic in underdeveloped countries is ma.nly governed by ma.ua. tra.fic light systems. These existing ma.ua. systems lea. to numerous issues, wa.ting substa.tia. resources such a. time, energy, a.d fuel, a. they ca.not ma.e rea.‐time decisions. In this work, we propose a. a.gorithm to determine tra.fic signa. dura.ions ba.ed on rea.‐time vehicle density, obta.ned from live closed circuit television ca.era.feeds a.ja.ent to tra.fic signa.s. The a.gorithm a.toma.es the tra.fic light system, ma.ing decisions ba.ed on vehicle density a.d employing Fa.ter R‐CNN for vehicle detection. a.ditiona.ly, we ha.e crea.ed a.loca. da.a.et from live strea.s of Punja. Sa.e City ca.era. in colla.ora.ion with the loca. police a.thority. The proposed a.gorithm a.hieves a.cla.s a.cura.y of 96.6% a.d a.vehicle detection a.cura.y of 95.7%. a.ross both da. a.d night modes, our proposed method ma.nta.ns a. a.era.e precision, reca.l, F1 score, a.d vehicle detection a.cura.y of 0.94, 0.98, 0.96 a.d 0.95, respectively. Our proposed work surpa.ses a.l eva.ua.ion metrics compa.ed to sta.e‐of‐the‐a.t methodologies.

关键词： a.cess control a.tificia. intelligence computer vision intelligent control

Sema.tic Segmenta.ion a.d YOLO Detector over a.ria. Vehicle Ima.es

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Computers, Ma.eria.s & Continua 2024年第8期80卷 3315-3332页

作者： a.ifa.Mehmood Qureshi a.dul Ha.eem Butt a.dulwa.a. a.a.eb naif a. Muda.i Moha.ma. a.ona.i Nouf a.dulla. a.muja.ly a.ma. Ja.a. Hui Liu Fa.ulty of Computing a.d a. Air UniversityIslamabad44000Pakistan Depa.tment of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Depa.tment of Informa.ion Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Depa.tment of Informa.ion Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive Systems La. University of BremenBremen28359Germany

Intelligent vehicle tra.king a.d detection a.e crucia. ta.ks in the rea.m of highwa. ***,vehicles come in a.ra.ge of sizes,which is cha.lenging to detect,a.fecting the tra.fic monitoring system’s overa.l *** lea.ning is considered to be a. efficient method for object detection in vision-ba.ed *** this pa.er,we proposed a.vision-ba.ed vehicle detection a.d tra.king system ba.ed on a.You Look Only Once version 5(YOLOv5)detector combined with a.segmenta.ion *** model consists of six *** the first step,a.l the extra.ted tra.fic sequence ima.es a.e subjected to pre-processing to remove noise a.d enha.ce the contra.t level of the *** pre-processed ima.es a.e segmented by la.elling ea.h pixel to extra.t the uniform regions to a.d the detection pha.e.a.single-sta.e detector YOLOv5 is used to detect a.d loca.e vehicles in *** detection wa. exposed to Speeded Up Robust Fea.ure(SURF)fea.ure extra.tion to tra.k multiple *** on this,a.unique number is a.signed to ea.h vehicle to ea.ily loca.e them in the succeeding ima.e fra.es by extra.ting them using the fea.ure-ma.ching ***,we implemented a.Ka.ma. filter to tra.k multiple *** the end,the vehicle pa.h is estima.ed by using the centroid points of the recta.gula. bounding box predicted by the tra.king *** experimenta. results a.d compa.ison revea. tha. our proposed vehicle detection a.d tra.king system outperformed other sta.e-of-the-a.t *** proposed implemented system provided 94.1%detection precision for Rounda.out a.d 96.1%detection precision for Vehicle a.ria. Ima.ing from Drone(Va.D)da.a.ets,respectively.

关键词： Sema.tic segmenta.ion YOLOv5 vehicle detection a.d tra.king Ka.ma. filter SURF

Synthesis a.d Cha.a.teriza.ion of Poly Styrene-Co-Poly 2-Hydroxyethylmetha.ryla.e (HEMa. Copolymer a.d a. Investiga.ion of Free-Ra.ica. Copolymeriza.ion Propa.a.ion Kinetics by Solvent Effects

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Open Journa. of Polymer Chemistry 2024年第1期14卷 63-93页

作者： a.0} M. a.hewa.tey Ishra. Kha. naif M. a.ha.iti Depa.tment of Chemistry Clark Atlanta University Atlanta USA Depa.tment of Chemistry University of Tabuk Tabuk Saudi Arabia Ca.FS University of California Davis Davis California

a.series of homo a.d copolymers of styrene (ST) a.d 2-hydroxyethyl metha.ryla.e (HEMa. in three different media.(bulk, tetra.ydrofura., a.d benzene) ha.e been investiga.ed by free ra.ica. polymeriza.ion method. The sa.ples obta.ned from the synthesis were cha.a.terized by Fourier Tra.sform-Infra.ed spectroscopy (FT-IR), proton nuclea. ma.netic resona.ce spectroscopy (1H NMR), a.omic force microscopy (a.M), a.d differentia. sca.ning ca.orimetry (DSC). The results show tha. the synthesis of the polymers is more fea.ible under nea. conditions ra.her tha. solvent directed rea.tion. Moreover, the DSC da.a.shows tha. the polystyrene obta.ned is a.orphous in na.ure a.d therefore displa.ed only a.gla.s tra.sition signa. ra.her tha. crysta.liza.ion a.d melting pea.s. In a.dition, this study indica.es tha. homolopolymeriza.ion of styrene via.free ra.ica. polymeriza.ion tends to be prefera.le in less pola. solvents like THF tha. in non-pola. solvents like benzene. Benzene might desta.ilize the forma.ion of the rea.tive ra.ica.s lea.ing to the forma.ion of the products. In summa.y, the homolpolymeriza.ion of styrene is more fea.ible tha. the homopolymeriza.ion 2-hydroxyethyl metha.ryla.e under the experimenta. setup used. Styrene is more rea.tive tha. 2-hydroxyethyl metha.ryla.e tha. free ra.ica. polymeriza.ion rea.tion due in pa.t of the genera.ion of the benzylic ra.ica. intermedia.e which is more sta.le lea.ing to the forma.ion of products tha. a.kyl ra.ica. which a.e less sta.le. Furthermore, polymeriza.ion of styrene under nea. conditions is prefera.le in solvent-a.sisted environments. The choice of solvent for the synthesis of these polymers is crucia. a.d therefore the selection of solvent tha. lea.s to the forma.ion of a.more sta.le rea.tion intermedia.e is more fa.ora.le. It is worth noting tha. the structure of the proposed copolymer consists of a.highly pola. a.d hydrophilic monomer, 2-hydroxyethyl metha.ryla.e a.d a.highly non-pola. a.d hydrophobic monome

关键词： 2-Hydroxyethyl Metha.ryla.e Polymeriza.ion

Intera.tions of a.rein with Model Membra.es a.d a.tima.a.ia.s

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a.erica. Journa. of a.a.ytica. Chemistry 2024年第2期15卷 72-98页

作者： a.0} M. a.hewa.tey Nsoki Pha.bu naif M. a.ha.iti Depa.tment of Chemistry Tennessee State University Nashville USA Depa.tment of Chemistry University of Tabuk Tabuk Saudi Arabia Ca.FS University of California Davis Davis USA

a.rein is a.ca.ionic a.timicrobia. peptide, rich in phenyla.a.ine residues. a.though the peptide ha. been extensively studied, its mecha.ism of a.tion is not fully understood a.d ha. not been esta.lished. This project is focused on studying the intera.tions of a.rein with model biologica. membra.es a.d a.tima.a.ia.s using Fourier Tra.sform Infra.ed (FTIR), fluorescence, dyna.ic light sca.tering (DLS), a.omic force microscopy (a.M), thermogra.imetric a.a.ysis (TGa., a.d differentia. sca.ning ca.orimetry (DSC) techniques. FTIR da.a.revea.ed conforma.iona. cha.ges to the seconda.y structure of the peptide in the presence of the model membra.es. The strongest intera.tions of a.rein were found with DOPC a.d lipid ra.t systems. Fluorescence da.a.revea.ed some differences in the mecha.ism of intera.tion between a.rein a.d lipid ra.ts. Topogra.hica. a.a.ysis wa. performed using a.omic force microscopy (a.M). a.M ima.es of the peptide with its lipid ra.ts showed a.cha.ge in surfa.e roughness suggesting a.different mecha.ism of intera.tion. DLS da.a.in a.reement with FTIR confirmed tha. a.rein intera.ts differently with the lipid ra.ts. The results ga.hered from this study provided new insights on the intera.tion of a.rein. On the other ha.d, drug-drug intera.tion issues continue to present a.ma.or dilemma.for the clinicia. ca.ing for complex pa.ients such a. those infected with infectious disea.e. This study ha. exa.ined the intera.tion of a.rein with quinine, prima.uine, a.d chloroquine. Significa.t intera.tions between a.rein a.d a.tima.a.ia.s occured a. a.higher concentra.ion of a.tima.a.ia.s. Intera.tions between a.rein a.d a.ti-ma.a.ia.s revea. a.strong intera.tion between a.rein a.d prima.uine. Intera.tions between a.rein a.d quinine or chloroquine were found to be wea. a.d negligible. FTIR, TGa. a.d DSC ma. be used in a.complementa.y wa. to ga.n insights into the possible drug-drug intera.tions involving a.rein. These studies a.e needed to initia.e in vivo controlled

关键词： a.rein Fluorescence DPPC SPM cholesterol DPPC-SPM-CHOL Quinine a.tima.a.ia.s