Prevalence and Antimicrobial Susceptibility of Escherichia Coli O157 Isolated From Raw Milk Marketed in Chittagong, Bangladesh

Escherichia coli is an emerging public health concern in most countries of the world. It is an important cause of food-borne human disease. The present study assessed the prevalence and determined the antibiotic resistance patterns of E. coli from raw milk marketed in Chittagong, Bangladesh. Of the raw milk marketed in Chittagong ~33(18%) of the 186 raw milk samples of it contains E. coli, indicator bacteria for any enteric pathogens. The mean viable count of total bacteria was 4.04×108 cfu/ml and the mean viable count of E. coli in the contaminated raw milk was 1.88×106 cfu/ml. E. coli from only six (18.2%) of the 33 positive samples yielded colourless colonies across the CT-SMAC, suggesting the probable presence of populations belonging to the serotype O157 and rest of the isolates 27 (81.82%) produced coloured colony on CT-SMAC considering the probable presence of populations belonging to the serotype non-O157. Growth of probable E. coli O157, as evidenced by the colourless colonies on CT-SMAC compared to coloured colonies from other bacteria. Confirmed isolates were further subjected to antimicrobial susceptibility test using the Agar disc diffusion technique. Antibiotics susceptibility profile showed that all the isolates in case of E. coli O157, penicillin (100%), tetracycline (100%), amoxicillin (83.33%) and erythromycin (83.33%) were the most resistant whereas ciprofloxacin (66.67%), gentamicin (50.0%), and streptomycin (50.0%) were the most sensitive antibiotics. In case of E.coli non-O157 susceptibility profile showed that chloramphenicol (40.74%), erythromycin (40.74%) and oxacillin (37.04%) were the most resistant whereas ciprofloxacin (70.37%), sulphamethoxazole/trimethoprim (S/T) (59.26%) and gentamycin (55.55%) were the most sensitive antibiotics. The antimicrobial resistance exhibited by E. coli O157and non-O157 strains in this study is an indication of possible antibiotic abuse

An effective hotel recommendation system through processing heterogeneous data

Recommendation systems have recently gained a lot of popularity in various industries such as entertainment and tourism. They can act as filters of information by providing relevant suggestions to the users through processing heterogeneous data from different networks. Many travelers and tourists routinely rely on textual reviews, numerical ratings, and points of interest to select hotels in cities worldwide. To attract more customers, online hotel booking systems typically rank their hotels based on the recommendations from their customers. In this paper, we present a framework that can rank hotels by analyzing hotels’ customer reviews and nearby amenities. In addition, a framework is presented that combines the scores generated from user reviews and surrounding facilities. We perform experiments using datasets from online hotel booking platforms such as TripAdvisor and Booking to evaluate the effectiveness and applicability of the proposed framework. We first store the keywords extracted from reviews and assign weights to each considered unigram and bigram keywords and, then, we give a numerical score to each considered keyword. Finally, our proposed system aggregates the scores generated from the reviews and surrounding environments from different categories of the facilities. Experimental results confirm the effectiveness of the proposed recommendation framework

出芽酵母TORC1不活性化後のESCRT介在性ミクロオートファジー誘導の解析

博士（理学）doctoral創造科学技術大学院静岡大学甲第1138号non

Smart RFID reader protocol for malware detection

Radio frequency identification (RFID) is a remote identification technique promises to revolutionize the way a specific object use to identify in our industry. However, large scale implementation of RFID sought for protection, against Malware threat, information privacy and un-traceability, for low cost RFID tag. In this paper, we propose a framework to provide privacy for tag data and to provide protection for RFID system from malware. In the proposed framework, malware infected tag is detected by analysing individual component of the RFID tag. It uses sanitization technique for analysing individual component. Here authentication based shared unique parameters is used as a method to protect privacy. This authentication protocol will be capable of handling forward and backward security and identifying rogue reader better than existing protocols. Using this framework, the RFID system will be protected from malware and the privacy of the tag will be ensured as well.<br /

An approach for Ewing test selection to support the clinical assessment of cardiac autonomic neuropathy

Objective: This article addresses the problem of determining optimal sequences of tests for the clinical assessment of cardiac autonomic neuropathy (CAN) We investigate the accuracy of using only one of the recommended Ewing tests to classify CAN and the additional accuracy obtained by adding the remaining tests of the Ewing battery This is important as not all five Ewing tests can always be applied in each situation in practice Methods and material: We used new and unique database of the diabetes screening research initiative project, which is more than ten times larger than the data set used by Ewing in his original investigation of CAN We utilized decision trees and the optimal decision path finder (ODPF) procedure for identifying optimal sequences of tests Results: We present experimental results on the accuracy of using each one of the recommended Ewing tests to classify CAN and the additional accuracy that can be achieved by adding the remaining tests of the Ewing battery We found the best sequences of tests for cost-function equal to the number of tests The accuracies achieved by the initial segments of the optimal sequences for 2, 3 and 4 categories of CAN are 80.80, 91.33, 93.97 and 94.14, and respectively, 79.86, 89.29, 91.16 and 91.76, and 78.90, 86.21, 88.15 and 88.93 They show significant improvement compared to the sequence considered previously in the literature and the mathematical expectations of the accuracies of a random sequence of tests The complete outcomes obtained for all subsets of the Ewing features are required for determining optimal sequences of tests for any cost-function with the use of the ODPF procedure We have also found two most significant additional features that can increase the accuracy when some of the Ewing attributes cannot be obtained Conclusions: The outcomes obtained can be used to determine the optimal sequences of tests for each individual cost-function by following the ODPF procedure The results show that the best single Ewing test for diagnosing CAN is the deep breathing heart rate variation test Optimal sequences found for the cost-function equal to the number of tests guarantee that the best accuracy is achieved after any number of tests and provide an improvement in comparison with the previous ordering of tests or a random sequence © 2013 Elsevier B.V

Governance based on partnership with NGOs: Implications for development and empowerment in rural Bangladesh

10.1177/0020852304044255International Review of Administrative Sciences702271-29