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Fluid-structural coupling occurs when microcantilever sensors vibrate in a fluid. Due to the complexity of the mechanical characteristics of microcantilevers and lack of high-precision microscopic mechanical testing instruments, effective methods for studying the fluid-structural coupling of microcantilevers are lacking, especially for non-rectangular microcantilevers. Here, we report fluid-structure interactions (FSI) of the cable-membrane structure via a macroscopic study. The simplified aeroelastic model was introduced into the microscopic field to establish a fluid-structure coupling vibration model for microcantilever sensors. We used the finite element method to solve the coupled FSI system. Based on the simplified aeroelastic model, simulation analysis of the effects of the air environment on the vibration of the commonly used rectangular microcantilever was also performed. The obtained results are consistent with the literature. The proposed model can also be applied to the auxiliary design of rectangular and non-rectangular sensors used in fluid environments. 相似文献
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Bayesian nonparametric inference for panel count data with an informative observation process 下载免费PDF全文
In this paper, the panel count data analysis for recurrent events is considered. Such analysis is useful for studying tumor or infection recurrences in both clinical trial and observational studies. A bivariate Gaussian Cox process model is proposed to jointly model the observation process and the recurrent event process. Bayesian nonparametric inference is proposed for simultaneously estimating regression parameters, bivariate frailty effects, and baseline intensity functions. Inference is done through Markov chain Monte Carlo, with fully developed computational techniques. Predictive inference is also discussed under the Bayesian setting. The proposed method is shown to be efficient via simulation studies. A clinical trial dataset on skin cancer patients is analyzed to illustrate the proposed approach. 相似文献
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Janne Alahuhta Sarian Kosten Munemitsu Akasaka Dominique Auderset Mattia M. Azzella Rossano Bolpagni Claudia P. Bove Patricia A. Chambers Eglantine Chappuis John Clayton Mary de Winton Frauke Ecke Esperança Gacia Gana Gecheva Patrick Grillas Jennifer Hauxwell Seppo Hellsten Jan Hjort Mark V. Hoyer Christiane Ilg Agnieszka Kolada Minna Kuoppala Torben Lauridsen En Hua Li Balázs A. Lukács Marit Mjelde Alison Mikulyuk Roger P. Mormul Jun Nishihiro Beat Oertli Laila Rhazi Mouhssine Rhazi Laura Sass Christine Schranz Martin Søndergaard Takashi Yamanouchi Qing Yu Haijun Wang Nigel Willby Xiao Ke Zhang Jani Heino 《Journal of Biogeography》2017,44(8):1758-1769
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Jiefeng He Haichao Zhao Dongfeng Deng Yadong Wang Xiao Zhang Haoliang Zhao Zongquan Xu 《Journal of cellular physiology》2020,235(3):2464-2477
This study aimed to identify significant biomarkers related to the prognosis of liver cancer using long noncoding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) analysis. Differentially expressed mRNA and lncRNAs between liver cancer and paracancerous tissues were screened, and the functions of these mRNAs were predicted by gene ontology and pathway enrichment analyses. A ceRNA network consisting of differentially expressed mRNAs and lncRNAs was constructed. LncRNA FENDRR and lncRNA HAND2-AS1 were hub nodes in the ceRNA network. A risk score assessment model consisting of eight genes (PDE2A, ESR1, FBLN5, ALDH8A1, AKR1D1, EHHADH, ADRA1A, and GNE) associated with prognosis were developed. Multivariate Cox regression suggested that both pathologic_T and risk group could be regarded as independent prognostic factors. Furthermore, a nomogram model consisting of pathologic_T and risk group showed a good prediction ability for predicting the survival rate of liver cancer patients. The nomogram model consisting of pathologic_T and a risk score assessment model could be regarded as an independent factor for predicting prognosis of liver cancer. 相似文献