简介：ThisstudyexaminestheseasonalvariationsoftropicalcyclogenesisovertheSouthChinaSea(SCS)usingagenesispotential(GP)indexdevelopedbyEmanuelandNolan.Howdifferentenvironmentalfactors(includinglow-levelvorticity,mid-levelrelativehumidity,verticalwindshear,andpotentialintensity)contributetothesevariationsisinvestigated.CompositeanomaliesoftheGPindexareproducedforthesummerandwintermonsoonsseparately.ThesecompositesreplicatetheobservedseasonalvariationsoftheobservedfrequencyandlocationoftropicalcyclogenesisovertheSCS.Thedegreeofcontributionbyeachfactorindifferentregionsisdeterminedquantitativelybyproducingcompositesofmodifiedindicesinwhichonlyoneofthecontributingfactorsvaries,withtheotherssettoclimatology.OverthenorthernSCS,potentialintensitymakesthelargestcontributionstotheseasonalvariationsintropicalcyclogenesis.OverthesouthernSCS,thelow-levelrelativevorticityplaystheprimaryroleintheseasonalmodulationoftropicalcyclone(TC)genesisfrequency,andtheverticalwindshearplaysthesecondaryrole.ThermodynamicfactorsplaymoreimportantrolesfortheseasonalvariationsintropicalcyclogenesisoverthenorthernSCS,whiledynamicfactorsaremoreimportantintheseasonalmodulationofTCgenesisfrequencyoverthesouthernSCS.

简介：Thispaperaddressesthemulti-faultdiagnosisproblemofthrustersandsensorsforautonomousunderwatervehicles（AUVs）.Traditionalsupportvectordomaindescription（SVDD）haslowclassificationaccuracyintheprocessofAUVmulti-faultpatternclassificationbecauseoftheeffectofsamplesparsedensityandtheunevendistributionofsamples,andsoon.Thus,afuzzyweightedsupportvectordomaindescription（FWSVDD）methodbasedonpositiveandnegativeclasssamplesisproposed.Inthismethod,thenegativeclasssampleisintroducedduringclassifiertraining,andthelocaldensityandtheclassweightareintroducedforeachsample.Toimprovethemulti-faultpatternclassifiertrainingspeedandfaultdiagnosisaccuracyofFWSVDD,amulti-faultmodeclassificationmethodbasedonahierarchicalstrategyisproposed.Thismethodaddsfaultcontaindetectionsurfaceforeachthrusterandsensortoisolatefaultcomponentsduringfaultdiagnosis.Byconsideringtheproblemofpatternclassificationforafuzzysample,whichmaybelocatedintheoverlappingareaofhyper-spheresormaynotbelongtoanyhyper-sphereintheprocessofmulti-faultclassificationbasedonFWSVDD,arelativedistancejudgmentmethodisgiven.Theeffectivenessoftheproposedmulti-faultdiagnosisapproachisdemonstratedthroughwatertankexperimentswithanexperimentalAUVprototype.

简介：病毒的紧张的坏死(VNN)在海洋的鱼引起高死亡，特别在grouper，全球并且在中国。因为没有有效疫苗或药处理VNN，早察觉和预防是重要的堵住它的爆发。在这研究，反向的抄写聚合酶链反应(RT-PCR)为VNN病原体的快速、方便、敏感的察觉被开发，紧张的坏死病毒(NNV)，在grouper。整个过程从RNA抽取在3.5h以内被完成到PCR产品可视化。这个方法的察觉限制是NNVRNA标准的200个拷贝，它对应于病毒粒子的200个拷贝。这个RT-PCR方法对NNV察觉没有特定对另外的鱼跨反应病毒的疾病病原体例如传染胰腺的坏死病毒(IPNV)，传染造血的坏死病毒(IHNV)，鲤鱼病毒(SVCV)的春天viraemia，流行于家畜的造血的坏死病毒(EHNV)，并且大黄croakeriridovirus(LYCIV)。与这个方法，看到橘子的grouper(Epinepheluscoioides)从育种站与或没有在福建省的VNN流行病的发生的油炸食品被检测。结果都显示出那或当从没有VNN的二个育种站的40%油炸食品或25%流行病也作为NNV被检测时，从有流行病的发生的二个育种站的93%油炸食品作为积极被诊断积极，显示这个RT-PCR方法能被用于快速，NNV感染的敏感察觉并且在VNN流行警戒适用。