Bacterial infection in association with snakebite: A 10-year experience in a northern Taiwan medical center

BackgroundMicrobiological data of secondary wound infections following snakebites is rarely reported in Taiwan. The objective of this study was to assess the secondary wound infection after venomous snakebites.MethodsWe conducted a 10-year retrospective survey on patients admitted for venomous snakebites and microbiological data of wound cultures at a medical center in northern Taiwan.ResultsBetween April 2001 and April 2010, 231 patients who experienced snakebites were included. Male predominated, accounting for 62.3% (144). The age range of patients was 4–95 years. Ninety-five (41.1%) people were bitten by Trimeresurus mucrosquamatus, followed by Tstejnegeri, and cobra. A total of 61 pathogens were obtained from 21 patients. Thirty-nine (63.9%) isolates were gram-negative bacteria, 14 (23%) gram-positive pathogens, and 8 (13.1%) anaerobic pathogens. There were 17 patients bitten by cobra in these 21 patients. Morganella morganii and Enterococcus species were the most common pathogens identified in the wound cultures.ConclusionCobra bite causes more severe bacterial infection than other kinds of snakebites. Oral amoxicillin/clavulanate plus ciprofloxacin or parenteral piperacillin/tazobactam alone can be the choices for empirical or definitive treatment, and surgical intervention should be considered for established invasive soft tissue infections

Teachers' recognition of school bullying according to background variables and type of bullying

How teachers identify and judge school bullying may affect their willingness to intervene in bullying situations and influence their strategies for doing so. This study aimed to investigate whether there were significant differences in teachers' identification of bullying incidents according to background variables (gender, teaching experience, and education level). The participants of this study were 150 primary school and middle school teachers in Taiwan, A 24-item Recognition of Bullying incidents Questionnaire (RBIQ) was used in this study to explore whether teachers can identify physical, verbal, and relational scenarios as bullying or non-bullying incidents. A mixed-model two way ANOVA was used to analyze this data. Results revealed that teachers' teaching experiences significantly interacted with behavioral types, and teachers' education levels also sigm candy interacted with behavioral types. In addition, no gender differences in the identification of bullying were observed. Overall, teachers were more likely to identifi physical bullying incidents than relational ones. The results of this study suggest that teachers should participate in training to help them identify bullying incidents, particularly when these involve relational bullying

Container Number Recognition Method Based on SSD_MobileNet and SVM

Aiming at how to realize the recognition of the container number on the container surface at the entrance and exit of the port, a method based on image affine transformation and SVM classifier is proposed. The main process includes truck target detection, box number area detection, text correction stage, image preprocessing stage and segmentation detection and recognition stage. Firstly, a kind of container truck detection program based on frame difference method and decreasing sequence of connected domain is proposed; secondly, a method of container number area detection based on SSD_MobileNet is proposed; in the case number recognition stage, a text correction method based on image affine transformation is proposed, and different processing methods are proposed for vertical sequence box number and horizontal sequence box number in image preprocessing stage In the stage of segmentation detection and recognition, a character segmentation algorithm based on connected domain segmentation and a segmentation detection and recognition algorithm based on SVM classifier are proposed. Through the detection and recognition of container images in the field monitoring video, the accuracy rate of regional detection can reach 97%, and the accuracy rate of character recognition can reach 95%, and it can achieve good real-time performance