Application of Weighted Cross-Entropy Loss Function in Intrusion Detection

The deep learning model is overfitted and the accuracy of the test set is reduced when the deep learning model is trained in the network intrusion detection parameters, due to the traditional loss function convergence problem. Firstly, we utilize a network model architecture combining Gelu activation function and deep neural network;Secondly, the cross-entropy loss function is improved to a weighted cross entropy loss function, and at last it is applied to intrusion detection to improve the accuracy of intrusion detection. In order to compare the effect of the experiment, the KDDcup99 data set, which is commonly used in intrusion detection, is selected as the experimental data and use accuracy, precision, recall and F1-score as evaluation parameters. The experimental results show that the model using the weighted cross-entropy loss function combined with the Gelu activation function under the deep neural network architecture improves the evaluation parameters by about 2% compared with the ordinary cross-entropy loss function model. Experiments prove that the weighted cross-entropy loss function can enhance the model’s ability to discriminate samples.

Study on the Teaching Reform of Plant Physiology in the Context of Modern Education

The Plant Physiology is characterized by wide coverage,strong theories and practicality,and limited class hour.In view of these characteristics,this paper introduced the reform of teaching methods,including reform of teaching content,reform of teaching methods and means,reform of experimental teaching and examination methods.It is expected to achieve the objective of improving the teaching effect of Plant Physiology.

New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine

Over the past thirty years,the importance of chemokines and their seven-transmembrane G protein-coupled receptors(GPCRs)has been increasingly recognized.Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes,including host homeostasis and responses to disease.Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity.Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases,including cancer,immune and inflammatory diseases,and metabolic and neurological disorders,which render the system a focus of studies aiming to discover therapies and important biomarkers.The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states,including,among others,coronavirus disease 2019(COVID-19).In this review,by reporting the latest advances in chemokine biology and results fromanalyses of a plethora of sequencing-based datasets,we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network,focusing on chemokine-mediated inflammation and cancer.Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Identification of lipid droplets in gut bacteria

Dear Editor,The field of gut microbiota is progressing rapidly and thus,appellations like the last human organ,a separate organ,a forgotten organ,and a new organ have been applied to gut microbiota to emphasize its vital functions in our body(Chang and Kao,2019).Gut microbiota has been shown to play a central role in the regulation of human lipid metabolism and be associated with lipid metabolism disorders when aberrant,through composition and microbial metabolites.