Smart Substation Network Fault Classification Based on a Hybrid Optimization Algorithm

Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods

mRNA vaccine in cancer therapy: Current advance and future outlook

Abstract Messenger ribonucleic acid (mRNA) vaccines are a relatively new class of vaccines that have shown great promise in the immunotherapy of a wide variety of infectious diseases and cancer. In the past 2 years, SARS‐CoV‐2 mRNA vaccines have contributed tremendously against SARS‐CoV2, which has prompted the arrival of the mRNA vaccine research boom, especially in the research of cancer vaccines. Compared with conventional cancer vaccines, mRNA vaccines have significant advantages, including efficient production of protective immune responses, relatively low side effects and lower cost of acquisition. In this review, we elaborated on the development of cancer vaccines and mRNA cancer vaccines, as well as the potential biological mechanisms of mRNA cancer vaccines and the latest progress in various tumour treatments, and discussed the challenges and future directions for the field