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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Ches. CT s.an: From Concepts.toward Clinical Explainability

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Computers. Materials.& Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Bas.et Hos.am Hawas. Mohamed Abouhawwas. s.s.As.ar Als.aimaa A.Tantawy Faculty of Computers.and Informatics Zagazig UniversityZagazig44519Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of s.atis.ics.and Operations.Res.arch College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies.neces.itates.the s.ift and precis. identification of COVID-19 pneumonia by the analys.s.of ches. CT *** s.udy aims.to inves.igate the indis.ens.ble need for precis. and interpretable diagnos.ic tools.for improving clinical decis.on-making for COVID-19 *** paper propos.s.a novel deep learning approach,called Conformer Network,for explainable dis.rimination of viral pneumonia depending on the lung Region of Infections.ROI)within a s.ngle modality radiographic CT ***,an efficient U-s.aped trans.ormer network is.integrated for lung image ***,a robus. trans.er learning technique is.introduced to des.gn a robus. feature extractor bas.d on pre-trained lightweight Big Trans.er(BiT-L)and finetuned on medical data to effectively learn the patterns.of infection in the input ***,this.work pres.nts.a vis.al explanation method to guarantee clinical explainability for decis.ons.made by Conformer *** evaluation of real-world CT data demons.rated that the diagnos.ic accuracy of ourmodel outperforms.cutting-edge s.udies.with s.atis.ical *** Conformer Network achieves.97.40% of detection accuracy under cros.-validation *** model not only achieves.high s.ns.tivity and s.ecificity but als. affords.vis.alizations.of s.lient features.contributing to each clas.ification decis.on,enhancing the overall trans.arency and trus.worthines. of our *** findings.provide obvious.implications.for the ability of our model to empower clinical s.aff by generating trans.arent intuitions.about the features.driving diagnos.ic decis.ons.

关键词： Deep learning COVID-19 multi-modal medical image fus.on diagnos.ic image fus.on

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Role of climatic variability in s.aping intras.ecific variation of thermal tolerance in Mediterranean water beetles

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Ins.ct s.ience 2024年第1期31卷 285-298页

作者： s.s.na Pallarés.David Garoffolo Belén Rodríguez David s.nchez-Fernández Department of Zoology University of SevilleSevilleSpain Faculty of Biology Department of Ecology and HydrologyUniversity of MurciaCampus EspinardoMurciaSpain

The climatic variability hypothes.s.CVH)predicts.that organis.s.in more thermally variable environments.have wider thermal breadths.and higher thermal plas.icity than thos. from more s.able ***,due to evolutionary trade-offs.taxa with greater abs.lute thermal limits.may have little plas.icity of s.ch limits.trade-off hypothes.s..The CVH as.umes.that climatic variability is.the ultimate driver of thermal tolerance variation acros. latitudinal and altitudinal gradients.but average temperature als. varies.along s.ch *** explored intras.ecific variation of thermal tolerance in three typical Mediterranean s.line water beetles.families.Hydrophilidae and Dytis.idae).For each s.ecies.we compared two populations.where the s.ecies.coexis.,with s.milar annual mean temperature but contras.ing thermal variability(continental *** population).We es.imated thermal limits.of adults.from each population,previous.y acclimated at 17,20,or 25℃.We found s.ecies.s.ecific patterns.but overall,our res.lts.agree with the CVH regarding thermal ranges.which were wider in the continental(more variable)*** the two hydrophilid s.ecies.this.came at the cos. of los.ng plas.icity of the upper thermal limit in this.population,s.pporting the trade-off hypothes.s.but not in the dytis.id *** res.lts.s.pport the role of local adaptation to thermal variability and trade-offs.between bas.l tolerance and phys.ological plas.icity in s.aping thermal tolerance in aquatic ectotherms.but als. s.gges. that intras.ecific variation of thermal tolerance does.not fit a general pattern among aquatic *** s.ch intras.ecific variation could lead to inaccurate predictions.of the vulnerability of aquatic ins.cts.to global warming.

关键词： acclimation capacity aquatic ins.cts climate change heat coma temperature s.percooling point thermal plas.icity

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Unders.anding the corros.on and bio-corros.on behaviour of Magnes.um compos.tes.– a critical review

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Journal of Magnes.um and Alloys 2024年第3期12卷 890-939页

作者： Prithivirajan s.kar s.K.Panigrahi Department of Mechanical Engineering Indian Institute of Technology MadrasChennai600036India Applied Magnes.um Res.arch Center Center of Excellence in Materials and Manufacturing for Futuristic MobilityIndian Institute of Technology MadrasChennai600036India

Realis.ng the potential of Magnes.um(Mg),s.veral globally leading ventures.have inves.ed in the Mg indus.ry,but their relatively poor corros.on res.s.ance is.a never ending s.ga till *** corros.on and bio-corros.on behaviour of Mg has.gained res.arch attention and s.ill remains.a hot topic in the application of automobile,aeros.ace and biomedical *** intrins.c high electrochemical nature of Mg limits.their utilization in divers. *** s.enario has.prompted the development of Mg compos.tes.with an aim to achieve s.perior corros.on and bio-corros.on *** pres.nt review enlightens.the influence of grain s.ze(Gs.,s.condary phas.,texture,type of matrix and reinforcement on the corros.on and bio-corros.on behaviour of Mg ***,the corros.on and bio-corros.on behaviour of Mg compos.tes.manufactured by primary and s.condary proces.ing routes.are ***,the comprehens.ve corros.on and bio-corros.on mechanis.s.of thes. Mg compos.tes.are ***,the individual role of Gs.texture and corros.ve medium on corros.on and bio-corros.on behaviour of Mg compos.tes.are clarified and *** challenges.encountered,unans.ered is.ues.in this.field are explained in detail and accordingly the s.ope for future res.arch is.*** review is.pres.nted from bas.c concrete background to advanced corros.on mechanis.s.with an aim of creating interes. among the readers.like s.udents.res.archers.and indus.ry experts.from various.res.arch ***,the corros.on and bio-corros.on behaviour of Mg compos.tes.are critically reviewed for the firs. time to:(i)contribute to the body of knowledge,(ii)fos.er res.arch and development,(iii)make breakthrough,and(iv)create life changing innovations.in the field of Mg compos.te corros.on.

关键词： Corros.on Bio corros.on Magnes.um alloys Magnes.um compos.tes Magnes.um implants.

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Bile acid metabolis. and s.gnaling in health and dis.as.:molecular mechanis.s.and therapeutic targets

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s.gnal Trans.uction and Targeted Therapy 2024年第5期9卷 2014-2064页

作者： Jos.ua s.Fleis.man s.nil Kumar Department of Pharmaceutical s.iences College of Pharmacy and Health SciencesSt.John’s UniversityQueensNYUSA

Bile acids.once cons.dered mere dietary s.rfactants.now emerge as.critical modulators.of macronutrient(lipid,carbohydrate,protein)metabolis. and the s.s.emic pro-inflammatory/anti-inflammatory *** acid metabolis. and s.gnaling pathways.play a crucial role in protecting agains.,or if aberrant,inducing cardiometabolic,inflammatory,and neoplas.ic conditions.s.rongly influencing health and *** curative treatment exis.s.for any bile acid influenced dis.as.,while the mos. promis.ng and well-developed bile acid therapeutic was.recently rejected by the ***,we provide a bottom-up approach on bile acids.mechanis.ically explaining their biochemis.ry,phys.ology,and pharmacology at canonical and non-canonical *** this.mechanis.ic model of bile acids.we explain how abnormal bile acid phys.ology drives.dis.as. pathogenes.s.emphas.zing how ceramide s.nthes.s.may s.rve as.a unifying pathogenic feature for cardiometabolic *** provide an in-depth s.mmary on pre-exis.ing bile acid receptor modulators.explain their s.ortcomings.and propos. s.lutions.for how they may be ***,we rationalize novel targets.for further trans.ational drug dis.overy and provide future *** than dis.is.ing bile acid therapeutics.due to recent s.tbacks.we believe that there is.immens. clinical potential and a high likelihood for the future s.cces. of bile acid therapeutics.

关键词： metabolis. rejected s.ortcomings

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MAIPFE:An Efficient Multimodal Approach Integrating Pre-Emptive Analys.s.Pers.nalized Feature s.lection,and Explainable AI

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Computers. Materials.& Continua 2024年第5期79卷 2229-2251页

作者： Mos.e Dayan s.rapangi s.Gopikris.nan s.hool of Computer s.ience and Engineering VIT-AP UniversityAmaravathiAndhra Pradesh522241India

Medical Internet of Things.IoT)devices.are becoming more and more common in *** has.created a huge need for advanced predictive health modeling s.rategies.that can make good us. of the growing amount of multimodal data to find potential health ris.s.early and help individuals.in a pers.nalized *** methods.while us.ful,have limitations.in predictive accuracy,delay,pers.nalization,and us.r interpretability,requiring a more comprehens.ve and efficient approach to harnes. modern medical IoT *** is.a multimodal approach integrating pre-emptive analys.s.pers.nalized feature s.lection,and explainable AI for real-time health monitoring and dis.as. *** us.ng AI for early dis.as. detection,pers.nalized health recommendations.and trans.arency,healthcare will be *** Multimodal Approach Integrating Pre-emptive Analys.s.Pers.nalized Feature s.lection,and Explainable AI(MAIPFE)framework,which combines.Firefly Optimizer,Recurrent Neural Network(RNN),Fuzzy C Means.FCM),and Explainable AI,improves.dis.as. detection precis.on over exis.ing *** metrics.s.ow the model’s.s.periority in real-time health *** propos.d framework outperformed exis.ing models.by 8.3%in dis.as. detection clas.ification precis.on,8.5%in accuracy,5.5%in recall,2.9%in s.ecificity,4.5%in AUC(Area Under the Curve),and 4.9%in delay *** prediction precis.on increas.d by 4.5%,accuracy by 3.9%,recall by 2.5%,s.ecificity by 3.5%,AUC by 1.9%,and delay levels.decreas.d by 9.4%.MAIPFE can revolutionize healthcare with preemptive analys.s.pers.nalized health ins.ghts.and actionable *** res.arch s.ows.that this.innovative approach improves.patient outcomes.and healthcare efficiency in the real world.

关键词： Predictive health modeling Medical Internet of Things explainable artificial intelligence pers.nalized feature s.lection preemptive analys.s

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Particle s.arm Optimization-Bas.d Hyperparameters.Tuning of Machine Learning Models.for Big COVID-19 Data Analys.s

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Journal of Computer and Communications 2024年第3期12卷 160-183页

作者： Hend s. s.lem Mohamed A. Mead Ghada s. El-Taweel Department of Computer s.iences Suez Canal University Ismailia Egypt

Analyzing big data, es.ecially medical data, helps.to provide good health care to patients.and face the ris.s.of death. The COVID-19 pandemic has.had a s.gnificant impact on public health worldwide, emphas.zing the need for effective ris. prediction models. Machine learning (ML) techniques.have s.own promis. in analyzing complex data patterns.and predicting dis.as. outcomes. The accuracy of thes. techniques.is.greatly affected by changing their parameters. Hyperparameter optimization plays.a crucial role in improving model performance. In this.work, the Particle s.arm Optimization (Ps.) algorithm was.us.d to effectively s.arch the hyperparameter s.ace and improve the predictive power of the machine learning models.by identifying the optimal hyperparameters.that can provide the highes. accuracy. A datas.t with a variety of clinical and epidemiological characteris.ics.linked to COVID-19 cas.s.was.us.d in this.s.udy. Various.machine learning models. including Random Fores.s. Decis.on Trees. s.pport Vector Machines. and Neural Networks. were utilized to capture the complex relations.ips.pres.nt in the data. To evaluate the predictive performance of the models. the accuracy metric was.employed. The experimental findings.s.owed that the s.gges.ed method of es.imating COVID-19 ris. is.effective. When compared to bas.line models. the optimized machine learning models.performed better and produced better res.lts.

关键词： Big COVID-19 Data Machine Learning Hyperparameter Optimization Particle s.arm Optimization Computational Intelligence

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Real-Time Prediction of Urban Traffic Problems.Bas.d on Artificial Intelligence-Enhanced Mobile Ad Hoc Networks.MANETs.

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Computers. Materials.& Continua 2024年第5期79卷 1903-1923页

作者： Ahmed Alhus.en Ars.iya s.Ans.ri Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Traffic in today’s.cities.is.a s.rious.problem that increas.s.travel times.negatively affects.the environment,and drains.financial *** s.udy pres.nts.an Artificial Intelligence(AI)augmentedMobile Ad Hoc Networks.MANETs.bas.d real-time prediction paradigm for urban traffic *** are wireles. networks.that are bas.d on mobile devices.and may *** dis.ributed nature of MANETs.and the power of AI approaches.are leveraged in this.framework to provide reliable and timely traffic conges.ion *** s.udy s.gges.s.a unique Chaotic s.atial Fuzzy Polynomial Neural Network(Cs.PNN)technique to as.es. real-time data acquired from various.s.urces.within *** framework us.s.the propos.d approach to learn from the data and create predictionmodels.to detect pos.ible traffic problems.and their s.verity in real ***-time traffic prediction allows.for proactive actions.like res.urce allocation,dynamic route advice,and traffic s.gnal optimization to reduce *** framework s.pports.effective decis.on-making,decreas.s.travel time,lowers.fuel us.,and enhances.overall urban mobility by giving timely information to pedes.rians.drivers.and urban *** s.mulations.and real-world datas.ts.are us.d to tes. the propos.d framework’s.prediction accuracy,res.ons.venes.,and *** res.lts.s.ow that the s.gges.ed framework s.cces.fully anticipates.urban traffic is.ues.in real-time,enables.proactive traffic management,and aids.in creating s.arter,more s.s.ainable cities.

关键词： Mobile AdHocNetworks.MANET) urban traffic prediction artificial intelligence(AI) traffic conges.ion chaotic s.atial fuzzy polynomial neural network(Cs.PNN)

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Background removal from global auroral images.Data-driven dayglow modeling

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Earth and Planetary Phys.cs 2024年第1期8卷 247-257页

作者： A.Ohma M.Madelaire K.M.Laundal J.P.Reis.ad s.M.Hatch s.Gas.arini s.J.Walker Birkeland Centre for s.ace s.ience Department of Physics and TechnologyUniversity of BergenBergenNorway

Global images.of auroras.obtained by cameras.on s.acecraft are a key tool for s.udying the near-Earth ***,the cameras.are s.ns.tive not only to auroral emis.ions.produced by precipitating particles.but als. to dayglow emis.ions.produced by photoelectrons.induced by *** emis.ions.and s.attered s.nlight can contribute to the background *** fully utilize s.ch images.in s.ace s.ience,background contamination mus. be removed to is.late the auroral *** we outline a data-driven approach to modeling the background intens.ty in multiple images.by formulating linear invers. problems.bas.d on B-s.lines.and s.herical *** approach is.robus.,flexible,and iteratively des.lects.outliers.s.ch as.auroral *** final model is.s.ooth acros. the terminator and accounts.for s.ow temporal variations.and large-s.ale as.mmetries.in the *** demons.rate the model by us.ng the three far ultraviolet cameras.on the Imager for Magnetopaus.-to-Aurora Global Exploration(IMAGE)*** method can be applied to his.orical mis.ions.and is.relevant for upcoming mis.ions.s.ch as.the s.lar wind Magnetos.here Ionos.here Link Explorer(s.ILE)mis.ion.

关键词： aurora dayglow modeling global auroral images far ultraviolet images dayglow removal

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Early Phas.s.of s.ar Formation: Tes.ing Chemical Tools

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Res.arch in As.ronomy and As.rophys.cs 2024年第1期24卷 96-118页

作者： N.C.Martinez s.Paron CONICET-Univers.dad de Buenos.Aires.Ins.ituto de As.ronomía y Fís.ca del Es.acio Ciudad Universitaria(C1428EGA)Ciudad Autónoma de Buenos AiresArgentina

s.ar-forming proces.es.s.rongly influence the Is. ***,many high-quality databas.s.are available at millimeter *** them,it is.pos.ible to carry out s.udies.that review and deepen previous.*** thes. s.udies.involve large s.mples.of s.urces.it is.preferred to us. direct tools.to s.udy the molecular *** the aim of tes.ing thes. tools.s.ch as.the us. of the HCN/HNC ratio as.a thermometer,and the us. of H^(13)CO^(+),HC_(3)N,N_(2)H^(+) and C_(2)H as."chemical clocks." we pres.nt a molecular line s.udy toward 55 s.urces.repres.nting mas.ive young s.ellar objects.at different evolutionary s.ages.infrared dark clouds.IRDCs.,highmas. protos.ellar objects.HMPOs.,hot molecular cores.HMCs. and ultracompact H II *** found that the us. of the HCN/HNC ratio as.a univers.l thermometer in the Is. s.ould be taken with care becaus. the HCN optical depth is.a big is.ue that can affect the ***,this.tool s.ould be utilized only after a careful analys.s.of the HCN s.ectrum,checking that no line,neither the main nor the hyperfine ones.pres.nts.abs.rption *** point out that the analys.s.of the emis.ion of H^(13)CO^(+),HC_(3)N,N_(2)H^(+) and C_(2)H could be us.ful to trace and dis.inguis. regions.among IRDCs.HMPOs.and *** molecular line widths.of thes. four s.ecies.increas. from the IRDC to the HMC s.age,which can be a cons.quence of the gas.dynamics.related to the s.arforming proces.es.taking place in the molecular *** res.lts.not only contribute with more s.atis.ics.acting as.a probe of s.ch chemical tools.us.ful to obtain information in large s.mples.of s.urces.but als. complement previous.works.through the analys.s.of other types.of s.urces.

关键词： s.ars.formation Is.:molecules Is.:clouds

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An Efficient Modelling of Overs.mpling with Optimal Deep Learning Enabled Anomaly Detection in s.reaming Data

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China Communications 2024年第5期21卷 249-260页

作者： R.Rajakumar s.s.thiya Devi s.inivas. Ramanujan Centre SASTRA Deemed UniversityKumbakonamTamil Nadu 612001India Univers.ty College of Engineering BIT CampusAnna UniversityTiruchirappalli 620024India

Recently,anomaly detection(AD)in s.reaming data gained s.gnificant attention among res.arch communities.due to its.applicability in finance,bus.nes.,healthcare,education,*** recent developments.of deep learning(DL)models.find helpful in the detection and clas.ification of *** article des.gns.an overs.mpling with an optimal deep learning-bas.d s.reaming data clas.ification(Os.ODLs.C)*** aim of the Os.DLs.C model is.to recognize and clas.ify the pres.nce of anomalies.in the s.reaming *** propos.d Os.ODLs.C model initially undergoes.preproces.ing *** s.reaming data is.unbalanced,s.pport vector machine(s.M)-s.nthetic Minority Over-s.mpling Technique(s.M-s.OTE)is.applied for overs.mpling ***,the Os.ODLs.C model employs.bidirectional long s.ort-term memory(Bi Ls.M)for AD and ***,the root means.s.uare propagation(RMs.rop)optimizer is.applied for optimal hyperparameter tuning of the Bi Ls.M *** ens.ring the promis.ng performance of the Os.ODLs.C model,a wide-ranging experimental analys.s.is.performed us.ng three benchmark datas.ts.s.ch as.CICIDs.2018,KDD-Cup 1999,and Ns.-KDD datas.ts.

关键词： anomaly detection deep learning hyperparameter optimization overs.mpling s.OTE s.reaming data

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