Degradation prediction of proton exchange membrane fuel cell stack using semi-empirical and data-driven methods

Degradation prediction of proton exchange membrane fuel cell(PEMFC)stack is of great significance for improving the rest useful life.In this study,a PEMFC system including a stack of 300 cells and subsystems has been tested under semi-steady operations for about 931 h.Then,two different models are respectively established based on semi-empirical method and data-driven method to investigate the degradation of stack performance.It is found that the root mean square error(RMSE)of the semi-empirical model in predicting the stack voltage is around 1.0 V,while the predicted voltage has no local dynamic characteristics,which can only reflect the overall degradation trend of stack performance.The RMSE of short-term voltage degradation predicted by the DDM can be less than 1.0 V,and the predicted voltage has accurate local variation characteristics.However,for the long-term prediction,the error will accumulate with the iterations and the deviation of the predicted voltage begins to fluctuate gradually,and the RMSE for the long-term predictions can increase to 1.63 V.Based on the above characteristics of the two models,a hybrid prediction model is further developed.The prediction results of the semi-empirical model are used to modify the input of the data-driven model,which can effectively improve the oscillation of prediction results of the data-driven model during the long-term degradation.It is found that the hybrid model has good error distribution(RSEM=0.8144 V,R2=0.8258)and local performance dynamic characteristics which can be used to predict the process of long-term stack performance degradation.

Suppression of Jasmonic Acid-Mediated Defense by Viral-Inducible MicroRNA319 Facilitates Virus Infection in Rice

MicroRNAs （miRNAs） are pivotal modulators of plant development and host-virus interactions. However, the roles and action modes of specific miRNAs involved in viral infection and host susceptibility remain largely unclear. In this study, we show that Rice ragged stunt virus （RRSV） infection caused increased accumulation of miR319 but decreased expression of miR319-regulated TCP （TEOSINTE BRANCHED/ CYCLOIDEA/PCF） genes, especially TCP21, in rice plants. Transgenic rice plants overexpressing miP,319 or downregulating TCP21 exhibited disease-like phenotypes and showed significantly higher susceptibility to RRSV in comparison with the wild-type plants. In contrast, only mild disease symptoms were observed in RRSV-infected lines overexpressing TCP21 and especially in the transgenic plants overexpressing miR319- resistant TCP21. Both RRSV infection and overexpression of miR319 caused the decreased endogenous jasmonic acid （JA） levels along with downregulated expression of JA biosynthesis and signaling-related genes in rice. However, treatment of rice plants with methyl jasmonate alleviated disease symptoms caused by RRSV and reduced virus accumulation. Taken together, our results suggest that the induction of miR319 by RRSV infection in rice suppresses JA-mediated defense to facilitate virus infection and symp- tom development.