A New Species of the Genus Achalinus from Huangshan, Anhui, China(Squamata: Xenodermidae)

A new species of the genus Achalinus is described based on five specimens collected from the villages of Huangjialing and Fuxi, Huangshan, Anhui, China. It can be morphologically differentia ted from all the other species in Achalinus except for A. spinalis and A. werneri by the presence of a dotted black streak in the middle of the subcaudal. It can be distinguished from A. spinalis in that its two anterior temporals are in contact with eye, and A. werneri by its light brown flanks. The phylogenetic rela tionship of Achalinus was reconstructed using the mitochondrial locus of cytochrome coxidase subunit 1(CO1). The five new specimens form a monophyletic clade with strong support. The uncorrected p-dista nces between the new species and other representatives of Achalinus range from 13.6% to 21.7%. The recognition of the new species increases the number of described Achalinus species to 14.

Compound Fault Diagnosis for Rotating Machinery:State-of-the-Art,Challenges,and Opportunities

Compound fault,as a primary failure leading to unexpected downtime of rotating machinery,dramatically increases the difficulty in fault diagnosis.To deal with the difficulty encountered in implementing compound fault diagnosis(CFD),researchers and engineers from industry and academia have made numerous significant breakthroughs in recent years.Admittedly,many systematic surveys focused on fault diagnosis have been conducted by reputable researchers.Nevertheless,previous review articles paid more attention to fault diagnosis with several single or independent faults,resulting in that there is still lacking a comprehensive survey on CFD.Therefore,to fulfill the above requirements,it is necessary to provide an in-depth overview of fault diagnosis methods or algorithms for compound faults of rotating machinery and uncover potential challenges or opportunities that would guide and inspire readers to devote their efforts to promoting fault diagnosis technology more effective and practical.Specifically,the backgrounds,including the related definitions and a new taxonomy of CFD methods,are detailed according to the way of implementing compound fault recognition.Then,the stateof-the-art applications of CFD are overviewed based on relevant publications in the past decades.Finally,the challenges and opportunities associated with implementing CFD are concluded and followed by a conclusion for ending this survey.We believe that this review article can provide a systematic guideline of CFD from different aspects for potential readers and seasoned researchers.

Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis

In machinery fault diagnosis,labeled data are always difficult or even impossible to obtain.Transfer learning can leverage related fault diagnosis knowledge from fully labeled source domain to enhance the fault diagnosis performance in sparsely labeled or unlabeled target domain,which has been widely used for cross domain fault diagnosis.However,existing methods focus on either marginal distribution adaptation(MDA)or conditional distribution adaptation(CDA).In practice,marginal and conditional distributions discrepancies both have significant but different influences on the domain divergence.In this paper,a dynamic distribution adaptation based transfer network(DDATN)is proposed for cross domain bearing fault diagnosis.DDATN utilizes the proposed instance-weighted dynamic maximum mean discrepancy(IDMMD)for dynamic distribution adaptation(DDA),which can dynamically estimate the influences of marginal and conditional distribution and adapt target domain with source domain.The experimental evaluation on cross domain bearing fault diagnosis demonstrates that DDATN can outperformance the state-of-the-art cross domain fault diagnosis methods.

A New Species of the Genus Sinomicrurus Slowinski,Boundy and Lawson,2001 (Squamata:Elapidae) from Hainan Province,China

A new species of the coral snake genus Sinomicrurus is described based on four specimens from southern Hainan Island （three specimens from Tianchi, Jianfengling National Nature Reserve, one specimen from Diaoluoshan National Nature Reserve）, Hainan Province, China. Morphologically, the new species is rather similar to Sinomicrurus kelloggi. However, it is distinct from S. kelloggi by the pattern on the head, the head length, head length/width, the number of infralabial scales, number of bands on dorsal body, and number of blotches on the belly.

The Research on Optimization of the Multiphase Flow Field of Biogas Plant by Using CFD Software

The inner flow field of a biogas plant can be optimized by agitating the feedstock to be evenly distributed for a rising biogas production rate. A hydraulic agitator can be installed in the digester with outlets far above the bottom. Hydraulic mixing is essential in a solid-liquid two-phase flow process, in which large solid particles can be found at the initial stage and turn to being high-concentration viscous liquid （non-Newtonian fluid）. A 0.75 m3 digester was taken as a case study with CFD （computational fluid dynamics） software. The basic pattern was simulated by using water as the medium and the pattern of pseudo plastic fluid state was simulated by the Euler-Euler Model, then the effect of optimized design with bottom inflow and high dispersed outlets could be verified. Viewed from the mixing effects, the velocity of 0.6 m/s is better than l m/s for water medium, while 1 m/s better than 0.6 m/s for pseudo plastic fluid medium.

大规模集成的高性能本征可拉伸电子

Skin-like electronics exhibit soft and stretchable mechanical properties,enabling seamless conformal contact with the human skin and organ surfaces[1].Consequently,skin-like electronics facilitate high-fidelity bio-signal monitoring and imperceptible interaction with the human body[2],thereby empowering future telemedicine[3],soft robotics[4],and augmented reality applications[5].

Digital twin-assisted gearbox dynamic model updating toward fault diagnosis

One of the core challenges of intelligent fault diagnosis is that the diagnosis model requires numerous labeled training datasets to achieve satisfactory performance.Generating training data using a virtual model is a potential solution for addressing such a problem,and the construction of a high-fidelity virtual model is fundamental and critical for data generation.In this study,a digital twin-assisted dynamic model updating method for fault diagnosis is thus proposed to improve the fidelity and reliability of a virtual model,which can enhance the generated data quality.First,a virtual model is established to mirror the vibration response of a physical entity using a dynamic modeling method.Second,the modeling method is validated through a frequency analysis of the generated signal.Then,based on the signal similarity indicator,a physical–virtual signal interaction method is proposed to dynamically update the virtual model in which parameter sensitivity analysis,surrogate technique,and optimization algorithm are applied to increase the efficiency during the model updating.Finally,the proposed method is successfully applied to the dynamic model updating of a single-stage helical gearbox;the virtual data generated by this model can be used for gear fault diagnosis.