Objective This study aims to better understand lightning deaths and their distribution law in Liaoning Province and provide a reliable basis for the forensic analysis and identification of lightning deaths and the related research. Methods A retrospective review of related data of lightning deaths from Forensic Science Division of Liaoning Provincial Public Security Department was performed between 2010 and 2015 .Results One hundred and twelve decedents were identified, ages 6–72 years old (mean 37.4 years old), 85 males and 27 females. Physical findings were often related to the superthermal effect carried by the electrical current including the damage of clothing and the metal items(55.4%) , burning of skin(54.5%), lightning mark(19.6%). Most deaths occurred from June to August of each year between 14:00 and 20:00 at weekends, associated with the location, work and activity environment. The number of deaths in rural areas is higher than that in urban areas. Conclusion The occurrence of lightning death cases has certain regularity,systematic and comprehensive examination of lightning deaths are required. Through the statistics of the lightning deaths in Liaoning Province and the analysis of related influencing factors , it is conducive to improving the level of scene investigation and forensic identification of the lightning deaths.

Objective To investigate the relationship between changes in the liver computed tomography (CT) images and the postmortem interval (PMI) of rabbits 129 h after their death due to hemorrhagic shock. Methods CT scanning was used to investigate the hemorrhagic shock death model in 23 rabbits to identify the postmortem cerebral changes from 0 h to 129 h after death. Results The liver or lumbar area in the liver window showed the following characteristic changes: from unchanged, to rapid shrinkage, to slow shrinkage; the mean CT values of the liver initially increased and subsequently decreased. The regression equations for the relationship between the two indices and PMI were established by surgery, and they all had statistical significance (P ＜ 0. 01). Conclusion CT scanning can accurately show changes in the rabbit liver after death. The mean CT value of the liver tissue is more sensitive for inferring early PMI. Furthermore, the liver area/lumbar area ratio parameters are more sensitive for inferring mid-late PMI.

Objective:To design a visual allocation system of emergency medical equipment based on the Internet of Things technology,and to realize the coordinated allocation of emergency medical equipment in hospitals.Methods:The client and server(C/S)architecture was adopted,and the design of emergency medical equipment visual allocation system was mainly based on Bluetooth 5.1 technology,with automatic acquisition and automatic analysis of Bluetooth positioning tag,low power consumption sensor and signal communication of Bluetooth Internet of Things base station.The sample data of 150 pieces of equipment managed by the traditional allocation center mode of The 900th Hospital of People's Liberation Army Joint Logistics Support Force from January to December 2021 were selected,and the sample data of 150 pieces of equipment allocation during the application of the visual allocation system from June 2022 to June 2023 were randomly selected,and the allocation response time and the allocation warehousing in and out time were compared.A total of 40 ventilator devices were randomly selected during the traditional allocation center mode and the visual allocation period,with 20 ventilators in each mode,the start-up rate,utilization rate and profitability of medical equipment during the service period were compared.Results:The visual allocation system can realize the functions of automatic equipment positioning,emergency deployment,ledger management,remote repair report and benefit analysis.The allocation response time,allocation outbound time and allocation inbound time of the visual allocation system were(19.61±3.119)min,(11.73±2.104)min,(10.21±2.165)min,respectively,which were shorter than(54.98±3.999)min,(21.54±2.811)min,(16.80±2.000)min of the traditional allocation center mode,the difference was statistically significant(t=85.407,34.229,27.395,P<0.05).The start-up rate,utilization rate and profitability of ventilator equipment using visual allocation mode were 78.24%,51.23%and 82.76%,respectively,which were higher than 43.52%,36.26%and 47.83%of the traditional allocation center mode,the difference was statistically significant(x2=8.792,7.813,12.216,P<0.05).Conclusion:The visual allocation system of emergency medical equipment based on the Internet of Things technology can realize the functions of emergency medical equipment allocation and storage,equipment positioning and use status analysis,provide a theoretical basis for the allocation of hospital emergency medical equipment,and maximize the role of emergency medical equipment.