Under the background of the development of the network information age, the current Internet industry has obtained more development opportunities, but it has also brought corresponding challenges in the process of wide application. In the development and construction of modernization, society pays more attention to the supervision and determination of the characteristics of online public opinion. From the perspective of the current characteristics of network public opinion, because social information is more extensive and involves many fields, network public opinion has a high degree of complexity and diffusion. Therefore, it is necessary to strengthen the analysis and application of relevant data mining systems in order to achieve efficient management of network public opinion. The key to the disadvantage of the traditional excavation of public opinion communication characteristics lies in the lag of the excavation process, and it is difficult to deal with malignant public opinion in a timely and effective manner. Therefore, in order to truly solve the lagging problem of public opinion data dissemination feature mining technology, it is necessary to strengthen the application of artificial intelligence technology in it.

With the continuous development of social economy and science and technology, the world has entered the era of artificial intelligence. my country is also working hard on the cultivation of talents in the field of artificial intelligence, and paying more and more attention to technology research and development. This puts forward higher requirements for cultivating higher education talents. It is not only necessary to work hard on the cultivation of “people”, implement the concept of mass entrepreneurship and innovation, adapt to the development of the times, update educational concepts, and improve students’ thinking ability and logic ability. We must also work hard on “talent”, innovate teaching methods, integrate education with science and technology, and provide talent guarantee and intellectual support for social development.

With the development of the times, the political party system with Chinese characteristics has shown a strong vitality, promoted the development of the world's political party system, and made important contributions to human political civilization. At present, the political party system with Chinese characteristics has far-reaching influence and its discourse is of greater significance. Strengthening the construction of its discourse system can enhance the self-confidence and confidence of the Chinese people, highlight the superiority of China's political party system, and also effectively curb the discourse hegemony of Western political party systems, so that China has a strong discourse in the international arena, promoting the development and growth of China and achieving long-term stable development. This paper is mainly based on the study of the construction of the theoretical discourse system of the political party system with Chinese characteristics in the new era to develop the discussion.

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

According to the World Health Organization (WHO), breast cancer is among the most common cancers worldwide. Most of the anticancer agents have been showing a variety of side effects. Recently, bacterial proteins have been investigated as promising anticancer agents. Azurin is a bacterial cupredoxin protein secreted from Pseudomonas aeruginosa and has been reported as a potent multi-targeting anticancer agent, which makes it an appropriate candidate for drug delivery. Azurin may be delivered to cancer cells using different carriers like polymeric micro and nanoparticles. In the present study, azurin was extracted from the bacterial host and loaded into chitosan particles. Then its effect on MCF-7 cell line was investigated. Chitosan-azurin particles were made using the ion gelation method. Results showed that chitosan-azurin particles are about 200 nm, and the loading of the protein in particles did not affect its integrity. The MTT assay showed a significant reduction in cell viability in azurin and chitosan-azurin-treated cells. The toxicity level after 5 days was 63.78% and 82.53% for free azurin and chitosan-azurin-treated cells, respectively. It seems using an appropriate carrier system for anticancer proteins like azurin is a promising tool for developing low side effect anticancer agents.