With the rapid development of deep learning and neural networks in the field of computer vision, various convolutional neural network models have shown excellent performance in image classification tasks, and have become the standard tools for image classification. However, different data sets and application scenarios put forward different requirements for the model. For a given data set and classification task, designing, training and optimizing convolutional neural network models can improve the classification accuracy, which is a current research focus. Better classification results can be obtained by adjusting network structure, loss function and optimization algorithm.

To explore the molecular mechanisms and signaling pathways of the interaction between microbiome and immune system, and to provide theoretical basis and molecular targets for microbiome regulation of immune-related diseases. To develop novel microbiome intervention techniques and formulations to provide new methods and means for the treatment of immune-related diseases. To evaluate the efficacy and safety of microbiome intervention in the treatment of immune-related diseases, and to provide scientific basis and optimization plan for the clinical application of microbiome intervention.

This paper intends to use perovskite solar cells to power wearable biosensors, and learn the working principle of perovskite solar cells

In this paper, the composite modification of perovskite nanocrystals with Zr-MOF and amphiphilic polymer is used to prepare enzyme biomimetic cascade catalyst. To investigate the effect of amphiphilic polymer on Zr-MOF immobilized enzyme, optimize the composition and structure of the material, and evaluate its catalytic activity, stability and reuse performance.