Strategic Analysis of Circular Economy on "Integration of Two Networks": Take the Tobacco Industry in C City as an Example

Objectives: Reducing garbage sorting and renewable resources recovery increment is an important content of promoting circulation economy development of China, based on the C city tobacco industry as an example, first the present situation of "two network convergence" in C city tobacco industry and results were analyzed, and then using accident tree analysis it is concluded that the tobacco industry "two nets fusion" are faced with the problem, and then establish orthogonalization discrete Hopfield neural network capability evaluation model, "two network convergence" By using Matlab to conduct network learning and training, simulation experiments and data analysis, the quantitative evaluation of the tobacco industry "two-network integration" ability of five cities including C city is objectively obtained. On this basis, the countermeasures for improving the tobacco industry "two-network integration" ability of China are given.

Design of electric power emergency communication system based on multi-network integration

Natural disasters and emergencies generally pose serious threats to power facilities. Therefore, it is necessary to establish an efficient electric power emergency communication (EPEC) system. Existing systems based on a single network carrier (for example,4G, satellite, and Wi-Fi) may not meet the requirements of complex environments. We design a new EPEC system based on multi-network convergence technology by integrating the above three network carriers. It overcomes the limitations of single network carrier and improves the efficiency of power emergency communication. The test results show that the system can improve the transmission line bandwidth, automatically switch to the optimal signal network, and guarantee the security and stability of data transmission.

Analysis of Nanotoxicity with Integrated Omics and Mechanobiology

Nanoparticles (NPs) in biomedical applications have benefits owing to their small size. However, their intricate and sensitive nature makes an evaluation of the adverse effects of NPs on health necessary and challenging. Since there are limitations to conventional toxicological methods and omics analyses provide a more comprehensive molecular profiling of multifactorial biological systems, omics approaches are necessary to evaluate nanotoxicity. Compared to a single omics layer, integrated omics across multiple omics layers provides more sensitive and comprehensive details on NP-induced toxicity based on network integration analysis. As multi-omics data are heterogeneous and massive, computational methods such as machine learning (ML) have been applied for investigating correlation among each omics. This integration of omics and ML approaches will be helpful for analyzing nanotoxicity. To that end, mechanobiology has been applied for evaluating the biophysical changes in NPs by measuring the traction force and rigidity sensing in NP-treated cells using a sub-elastomeric pillar. Therefore, integrated omics approaches are suitable for elucidating mechanobiological effects exerted by NPs. These technologies will be valuable for expanding the safety evaluations of NPs. Here, we review the integration of omics, ML, and mechanobiology for evaluating nanotoxicity.