简介:TheperformanceofalinearresuspensionmodeldevelopedintheBalticSeawasstudiedintheconditionsofaeutrophicLakeKirkkoj(a|¨)rvi(southernFinland).Themodelpredictssedimentresuspensionrateusingdataonvegetationcover,windandsedimentqualityasaninput.Whentheoriginalmodelcoefficientswereused,themodelresultedonaverage1.8foldoverestimationoftheresuspensionrateinKirkkoj(a|¨)rvi.Thiswasduetolowerfetchandwaterdepth,andlessconsolidatedsedimentofKirkkoj(a|¨)rvicomparedwiththeBalticSeastudysite.WhencoefficientswereadjustedforKirkkoj(a|¨)rvi,themodelpredictionswere1.1timesthemeasuredvalues.Duetothecontinuousresuspension,theeffectofthewindterminthemodelwassolowthatitcouldbeexcludedwithoutaffectingtheaccuracyofmodelpredictions.Thestudydemonstratedthatinashalloweutrophiclakeaccuratepredictionsonresuspensionratecanbemadeusingonlydataonsedimentqualityandonfactorsinhibitingresuspension(macrophytes).Themodelresidualsincreasedwithincreasingresuspensionrateandhighratesofresuspensionwereunderestimatedbythemodel.DuetothefluffysedimentinKirkkoj(a|¨)rvi,erosionofsedimentincreasesmorethanlinearwithincreasingshearstress.Thusinsuchconditions,evenbetterpredictionscouldbeachievedbyanon-linearresuspensionmodel.
简介:Inthispaperwedevelopanelasto-dynamicmodelofthehumanarmforuseinneuro-muscularcontrolanddynamicinteractionstudies.Themotivationforthisworkistopresentacasefordevelopingandusingnon-quasistaticmodelsofhumanmusculo-skeletalbiomechanics.Themodelisbasedonhybridparametermultiplebodysystem(HPMBS)variationalprojectionprinciples.Inthispaper,wepresentanoverviewoftheHPMBSvariationalprincipleappliedtothefullelasto-dynamicmodelofthearm.Thegeneralityofthemodelallowsonetoincorporatemuscleeffectsaseitherloadstransmittedthroughthetendonatpointsoforiginandinsertionorasaneffectivetorqueatajoint.Thoughthetechniqueissuitablefordetailedboneandjointmodeling,wepresentinthisinitialeffortonlysimplegeometrywiththebonesdiscretizedasRayleighbeamswithelongation,whileallowingforlargedeflections.Simulationsdemonstratetheviabilityofthemcthodforuseinthecompanionpaperandinfuturestudies.
简介:Amulti-loopadaptiveinternalmodelcontrol(IMC)strategybasedonadynamicpartialleastsquares(PLS)frame-workisproposedtoaccountforplantmodelerrorscausedbyslowaging,driftinoperationalconditions,orenvironmentalchanges.SincePLSdecompositionstructureenablesmulti-loopcontrollerdesignwithinlatentspaces,amultivariableadaptivecontrolschemecanbeconvertedeasilyintoseveralindependentunivariablecontrolloopsinthePLSspace.Ineachlatentsubspace,oncethemodelerrorexceedsaspecificthreshold,onlineadaptationrulesareimplementedseparatelytocorrecttheplantmodelmismatchviaarecursiveleastsquares(RLS)algorithm.BecausetheIMCextractstheinverseoftheminimumpartoftheinternalmodelasitsstructure,theIMCcontrollerisself-tunedbyexplicitlyupdatingtheparameters,whicharepartsoftheinternalmodel.Bothparameterconvergenceandsystemstabilityarebrieflyanalyzed,andprovedtobeeffective.Finally,theproposedcontrolschemeistestedandevaluatedusingawidely-usedbenchmarkofamulti-inputmulti-output(MIMO)systemwithpuredelay.
简介:A2-Dslab-symmetricmodelofmixedconvective-stratiformcloudisdevelopedbysuperimposingconvectivecloud-sizefieldontheconvergencefield,inordertosimulateandstudythemixedcloudsconsistingofstratiformcloudandconvectivecloud.Adeepconvective,anelasticandconservativesystemofequationswithbasicvariables(V,θ,π’)issolvedbyanewmethodtocalculatedynamicfield.Thewatersubstanceinthecloudisdividedinto6categoriesandthemicrophysicalprocessesaredescribedinspectrumwithtwovariableparametersandmorereasonableparticlenumber/sizedistributions.Tocomparewithmeasuredradarechointensityandstructure,themodelmaycalculateechointensityofthemodelcloudobservedbyradar.
简介:Basedonthefirstlawofthermodynamicsandthethermaldiffusionequation,thededucedtheoreticalmodelofmitochondrialthermogenesissatisfiestheLaplaceequationandisaspecialcaseofthethermaldiffusionequation.Themodelsettlesthelong-standingquestionoftheabilitytoincreasecellulartemperaturebyendogenousthermogenesisandexplainsthethermogeniccharacteristicsofbrownadipocytes.Themodelandcalculationsalsosuggestthatthenumberoffreeavailableprotonsisthemajorlimitingfactorforendogenousthermogenesisanditsspeed.
简介:GivenanewDouble-MarkovriskmodelDM=(μ,Q,ν,H;Y,Z)andDouble-MarkovriskprocessU={U(t),t≥0}.Theruinorsurvivalproblemisaddressed.Equationswhichthesurvivalprobabilitysatisfiedandtheformulasofcalculatingsurvivalprobabilityareobtained.Recursionformulasofcalculatingthesurvivalprobabilityandanalyticexpressionofrecursionitemsareobtained.TheconclusionsareexpressedbyQmatrixforaMarkovchainandtransitionprobabilitiesforanotherMarkovChain.
简介:Thecurrentapplicablerelease&dispersionmodelsarereviewed.AtypicalmodelisdevelopedonthebasisofLPGstorageconditionsinChinaandtheauthors'research.ThestudyisfocusedontherelationshipbetweenLPGcompositionandreleaserate,andontheinfluenceofbuildingsorstructureslocatedinthesurroundingareaonthedispersionofgasplume.Theestablishedmodeliscomparedwithexistingmodelsbytheuseofpublishedfieldtestdata.
简介:HavingvisitedTilanqiaoPrison,Ibegantofeelmuchbetter,withalltheuneasinessandfearswith"imnates"and"prisons"gone.OnthewaytoQingpuPrisonIhadlearnedthatitisofanewmodel,quitecivilized.Theprisonisacomplexofwhitebuildingssurroundedbyawidestretchofgarden,IfnotforthefourChinesecharacters"QingPuJianYu"onthegates,noonecouldguessthatitisaprison.Itismorelikeauniversity.Fromtheproductionareatothelivingarea,fromtheteachingbuildingtothemedical
简介:一个适当小动物模型的缺乏仍然是一个主要障碍因为学习immunotolerance和immunopathogenesis由肝炎B病毒(HBV)导致了感染。在这研究,我们与recombinant在感染以后与持续HBVviremia报导一个老鼠模型带一个可复制的HBV染色体(AAV/HBV)的联系adeno的病毒(AAV)。类似于临床的HBV搬运人,感染AAV/HBV的老鼠为对HBV表面抗原(HBsAg)的抗体是sero否定的。有面对铝助手疫苗的常规HBV的免疫没能在这些老鼠对HBV得到有免疫力的回答。为了识别一支疫苗,那能潜在地围绕这忍耐,TLR9收缩筋CpG作为一个助手被加到HBsAg。有HBsAg/CpG的老鼠的种痘导致了viremia,而且强壮的抗体生产和T房间回答的不仅清理。而且,DNA复制和HBV的蛋白质表示显著地在AAV/HBV-infected鼠标的肝被减少。因此,AAV/HBV-infected老鼠可以作为一个柔韧的模型被使用调查HBVimmunotolerance并且为开发新奇免疫疗法根除的内在的机制HBV感染。
简介:Inthispaper,thej,υcorrectedformulaeoftheamplitudesandthephasesof58astronomicalconstituentsaregiven,andthemodelsfortheanalysisandpredictionof169constituentsarepresented.ThenewCartwright’scalculatedresultsofthetidalpotentialareused,andthequadraticanalysisismade.Ithasbeenprovedbyanumberoftrialsthattheharmonicconstantsofconstituentsaremorestableandtheaccuracyofthepredictedresultreliable.
简介:ThetraditionalGaussianMixtureModel(GMM)forpatternrecognitionisanunsupervisedlearningmethod.Theparametersinthemodelarederivedonlybythetrainingsamplesinoneclasswithouttakingintoaccounttheeffectofsampledistributionsofotherclasses,hence,itsrecognitionaccuracyisnotidealsometimes.ThispaperintroducesanapproachforestimatingtheparametersinGMMinasupervisingway.TheSupervisedLearningGaussianMixtureModel(SLGMM)improvestherecognitionaccuracyoftheGMM.Anexperimentalexamplehasshownitseffectiveness.TheexperimentalresultshaveshownthattherecognitionaccuracyderivedbytheapproachishigherthanthoseobtainedbytheVectorQuantization(VQ)approach,theRadialBasisFunction(RBF)networkmodel,theLearningVectorQuantization(LVQ)approachandtheGMM.Inaddition,thetrainingtimeoftheapproachislessthanthatofMultilayerPerceptrom(MLP).
简介:Traditionalportfoliotheoryassumesthatthereturnrateofportfoliofollowsnormality.However,thisassumptionisnottruewhenderivativeassetsareincorporated.Inthispaperaportfolioselectionmodelisdevelopedbasedonutilityfunctionwhichcancaptureasymmetriesinrandomvariabledistributions.Otherrealisticconditionsarealsoconsidered,suchasliabilitiesandintegerdecisionvariables.Sincetheresultingmodelisacomplexmixed-integernonlinearprogrammingproblem,simulatedannealingalgorithmisappliedforitssolution.Anumericalexampleisgivenandsensitivityanalysisisconductedforthemodel.