As a high-risk occupation, coal mining has many accidents, primarily due to the unsafe behavior of coal miners. Based on the research of analysis of unsafe behavior and pan-scenario data of miners, a theoretical framework for the analysis of unsafe behavior characteristics was proposed in this paper. The collected data were divided into realistic scenes and abstract scenes according to different manifestations; the pan-scene data were described from the eight dimensions of time, behavioral trace, location, behavioral property, behavioral individual, degree, unsafe action, and specialty using a quantitative method for the structure conversion; and the rules were discovered through cluster analysis and association analysis. A total of 225 coal mine gas explosion accidents were used for analysis, and the pan-scene data description and structure conversion of unsafe behavior that caused these accidents were realized. In a certain cluster, the distribution rules of dimensions and the interaction between different dimensions of unsafe behavior were explored after analysis. The results show that the proposed eight dimensions can fully explain the basic characteristics and attributes of the unsafe behavior of coal miners. The structure conversion can reduce the workload of managers and effectively improve the safety data processing capabilities, and the result of data analysis can provide data support and a management basis for safety management. A new method and thought for the data analysis of miners’ unsafe behavior is provided.
The emerging threat of multi-drug resistance (MDR) in a wide range of diseases is a major public health problem, which prolongs treatment, imposes disabilities and reduces the expected life span. MDR is common in urinary tract infections (UTI). Due to recent dramatic change in antimicrobial activity spectrum, we evaluated the current spectrum of antimicrobials activity in UTIs. We observed 33% infection rate in cultures and positive cultures were followed by the Kirby-Bauer technique for sensitivity testing. We evaluated that females are 3.71 folds more infected than males. We observed Escherichia coli (E. coli) as the most frequent and Pseudomonas aeruginosa (P. aeruginosa) as the least (9.1%). Further, we noted that E. coli infection in males is 4.75 times of males. Moreover, Klebsiella pneumoniae (K. pneumoniae) and E. coli are 2.33 and 7.67 times more prevalent than P. aeruginosa respectively. Our sensitivity results indicate that E. coli and K. pneumoniae are resistant to the most tested antimicrobials. However, P. aeruginosa is susceptible to only few of the tested drugs which include Amikacin, Piperacillin+Tazobactam (in combination), and Ceftriaxone. We conclude, due to MDR strains we need to imitate the current strategies and propose neoadjuvant and other therapies like applied in cancer.
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