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Because of the global spread of COVID-19 in 2020, the analysis of activities and travel behavior of urban residents is the key for the prevention and control of epidemic situation. Based on this, the research on track data mining and semantic location perception is conducted. The analysis of travel behavior characteristics of urban residents is helpful to carry out epidemic prevention activities scientifically. However, the traditional manual survey and statistical analysis cannot meet the needs of the rapid development of urbanization. On the other hand, with the application and development of information technology such as communication, location and storage, a large number of mobile trajectory data of urban residents can be collected and stored. These trajectory data contain rich spatiotemporal semantic information. Through mining and analysis, a lot of valuable travel information can be get and then the daily behavior of individual users and the spatial distribution characteristics of group users’ movement can be found. The results can effectively serve the current epidemic prevention work and can be applied to the infection tracking in the process of epidemic prevention.

Cell-like P systems with channel states, which are a variant of tissue P systems in membrane computing, can be viewed as highly parallel computing devices based on the nested structure of cells, where communication rules are classified as symport rules and antiport rules. In this work, we remove the antiport rules and construct a novel variant, namely, cell-like P systems with channel states and symport rules, where one rule is only allowed to be nondeterministically applied once per channel. To explore the computational efficiency of the variant, we solve the S A T problem and obtain a uniform solution in polynomial time with the maximal length of rules 1. The results of our work are reflected in the following two aspects: first, communication rules are restricted to only one type, namely, symport rules; second, the maximal length of rules is decreased from 2 to 1. Our work indicates that the constructed variant with fewer rule types can still solve the S A T problem and obtain better results in terms of computational complexity. Hence, in terms of computational efficiency, our work is a notable improvement.

Flip-flop P systems with proteins are a bio-inspired variant of cell-like P systems in membrane computing, where proteins can control the execution of rules. In this work, firstly, in order to simulate the fact that the execution time of biochemical reactions is uncertain, considering time-freeness, we therefore construct a novel variant, namely timed flip-flop P systems with proteins, where the protein on each membrane only has two types of working states, and such a system runs under the time-freeness mode; secondly, we study the computation power of this variant, and it is shown that a system with only one membrane and a maximum rule length of 4 is Turing universal; moreover, based on the variant, a solution to the SAT problem is obtained by the constructed system in polynomial time. Our work indicates that the constructed variant with time-freeness can still solve the SAT problem in feasible time. Because timefreeness of rules is employed, the variant may be more suitable for particular applications. INDEX TERMS P system, protein, university, SAT , time-freeness.