Liaoning Planning and Design Institute of Post and Telecommunication

Background: Toxoplasma gondii is a foodborne zoonotic parasite that can infect humans and a variety of warm-blooded animals. Wild rodents play an important role as intermediate hosts of T. gondii, and the survey data of T. gondii in wild rodents in China are limited. Methods: Therefore, from August 2023 to May 2024, a total of 510 brain tissue samples were collected from nine species of wild rodents, and T. gondii was detected using a nested PCR targeting the B1 gene. All positive samples were genotyped at 11 PCR-RFLP markers (i.e., SAG1, 5'-and 3'-SAG2, alternative SAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1, and Apico) to determine their genotype. Results: In the present study, out of a total of 510 samples analyzed by nested PCR, three (0.59%) tested positive for T. gondii. It is noteworthy that all three positive samples were derived from female Rattus flavipectus rodents captured in Yunnan Province, where the detection rate was 3.41% (3/88; 95% confidence interval: 0-6.96). Complete genotyping was successfully performed on these three samples, revealing two to be of the ToxoDB #9, which is a common and widely distributed strain in China. The third sample presented a novel genotype. Conclusion: This finding suggests that wild rodents could be harboring a variety of T. gondii genotypes, including new genotypes, which may have significant implications for understanding the epidemiology of the parasite and its potential to cause disease in humans and animals.

This paper investigates the potential disconnections and reconnection issues that may arise during the roaming process in the wireless local area network (WLAN) authentication and privacy infrastructure (WAPI). The tripartite peer-to-peer security authentication architecture employed by WAPI, which includes the station (STA), access point (AP), and authentication server (AS), results in significantly longer authentication times during roaming compared to Wi-Fi. Hence, optimizing WAPI's security authentication methods and reducing the authentication duration are crucial to addressing these roaming issues. Based on the existing WAPI security authentication mechanisms, this paper proposes two innovative security authentication improvement schemes: pre-authentication and decentralization of the AS. These solutions aim to enhance WAPI's roaming performance significantly by employing smarter, more flexible, and adaptive authentication strategies, providing valuable insights for practitioners seeking to achieve fast and seamless roaming.

With the rapid development of Smart Grid, modern power communication networks need to support more complex and dynamic functions, such as real-time monitoring, fault detection, demand response and distributed generation management. These functions put forward higher requirements on the structure of power communication networks and reasonable resource allocation. In view of the fact that existing algorithms cannot adapt well to the optimization of power communication network structure and reasonable resource allocation, this paper proposes an improved hybrid algorithm EAGO (Enhanced Ant Genetic Optimization) based on ACO (Ant Colony Optimization) algorithm and GA (Genetic Algorithm). Through simulation in the topology diagram of power communication network, relevant evaluation indicators are selected and compared with existing algorithms. The experimental results show that the EAGO algorithm in this paper is better than the comparison algorithm in reliability, packet loss rate, robustness and other indicators. Because it is a hybrid algorithm, the network load at different scales increases slightly.

Building the dual prevention mechanism is a new way to solve traffic safety problems. At present, in the field of highways, the dual prevention mechanism of operational safety risk graded control and accident hazard investigation and management has not been perfected. The deep-seated contradictions and problems that restrict highway operation safety have not changed. Based on the dual prevention model of highway operation safety, this paper studied and established basic databases such as "safety risk and accident hazard map", "safety risk and accident hazard database", and "responsibility list" for highway operation safety. Using modern information technologies such as the Internet of Things, cloud computing, and big data, a dual prevention intelligent control system for highway operation safety was developed. The system includes eight modules such as highway operation safety risk control, accident hazard investigation and management, emergency management, and safety education, which realizes the accurate identification, intelligent classification, real-time analysis, and dynamic control of highway operation safety risks and hazards. The results of the application of nearly 1,000 kilometers of highway projects in Guangdong Province, Hebei Province, etc. show that the system has improved the safety of highway operations and the efficiency of hazard detection. A large amount of labor, transportation and other highway safety management costs can be saved every year. This system effectively promoted the systematization, standardization and refinement of highway operation safety management.

With the development of communication technology in the power system, there are higher demands for comprehensive support and assurance capabilities in communication specialties. Different application scenarios in power communication have varied requirements, such as ultra-large bandwidth, ultra-low latency, and massive device access. To allocate resources reasonably and adapt to the differentiated demands of various services, this paper proposes the use of SPN (Slicing Packet Network) technology to slice the resources of power communication networks. Four types of service slices are designed, and the resource allocation problem is modeled as a MDP (Markov Decision Process). Deep reinforcement learning is introduced to solve for the optimal strategy. Simulation results show that compared to other algorithms, the ADQNS (Adaptive DQN Slicing) algorithm, which is framed by DQN (Deep Q-Network) technology, meets the quality of experience requirements for multiple services, demonstrating better performance in terms of end-to-end throughput, end-to-end latency, resource utilization, and fairness metrics.

A polydimethylsilosane/multiwalled carbon nanotube (PDMS/MWCNT) nanocomposite, as a tensile-strain-sensing material, was manufactured using a simple solution casting method. The percolation threshold, the relationship between the temperature and resistance, the tensile sensitivity, and the mechanism of the tensile sensitivity of the PDMS/MWCNT nanocomposite were studied, along with its application in concrete crack monitoring. The results show that the PDMS/MWCNT nanocomposite demonstrated a significant percolation phenomenon. The resistance change ratio of the PDMS/MWCNT nanocomposite changed linearly with the environmental temperature, gradually decreasing with an increasing environmental temperature. The PDMS/MWCNT nanocomposite had a higher tensile sensitivity, and the sensing factor was 6.65 when the volume fraction of carbon nanotubes was 1.26 v/v% near the percolation threshold, and the sensing factor of the PDMS/MWCNT nanocomposite decreased with an increase in the volume fraction of carbon nanotubes. The relationship between the relative electrical conductivity of the PDMS/MWCNT nanocomposite and the tensile strain can be expressed as ln(σ/σ0) = Aε. In addition, the quantitative relationship between the electrical conductivity of the PDMS/MWCNT nanocomposite and the volume fraction of carbon nanotubes was obtained based on the tunneling effect theory and the effective medium model. PDMS/MWCNT nanocomposites can be used as a sensing material to monitor the propagation of concrete cracks under the impact of a free-falling ball.