This study aimed to find bacterial profile of urinary tract infection (UTI) in children between 2 months to 15 years of age. This is a hospital based retrospective study conducted at Gandaki medical college and teaching hospital, Pokhara over a period of 18 months. Among the total 575 children enrolled for the study, 110 children (19.1%) were found to be culture positive. Most common age group having culture positivity is 1-5 years (40%). Present study showed that UTI is more common in girls (69.1%) than in boys (30.9%). E. coli was still the most commonly isolated bacteria (70.9%) followed by Proteus (20%), Klebsiella (5.4%) and Pseudomonas sp. in (1.8%). E. coli was sensitive to Nitrofurantoin (84.6 %), Amikacin (80.7%), Gentamicin (73%) and Ofloxacin in (53.8%). Most commonly used drugs for the treatment of UTI like Cefixime and Ceftriaxone was sensitive only in 15% and 10% respectively. Similarly, Klebsiella was sensitive to Amikacin and Gentamicin (100%) but sensitive to Nitrofurantoin in only 66% of cases. Proteus was sensitive to Nitrofurantoin (95.4%), Amikacin (86%) and to Gentamicin (59%). High resistance rate was observed to Cefixime and Ceftriaxone, the commonly used drugs for its treatment in OPD basis. DOI: http://dx.doi.org/10.3126/jcmc.v3i3.8633 Journal of Chitwan Medical College 2013; 3(3): 22-25

Plagiarism is the main problem in the digital world, as people use others’ content without giving prior credit to the creator. Therefore, there should be proper and efficient algorithms to find plagiarized content on the Internet. This research proposes two algorithms: the winnowing algorithm and the extended winnowing algorithm. The winnowing algorithm can only calculate the similarity rate between documents, whereas the extended algorithm can mark the plagiarized text segment in the compared records along with their similarity rates. The similarity rate in both algorithms has been calculated using the Jaccard Coefficient. Although the extended algorithm is beneficial as it provides a text marking feature, it consumes more computation power, which is discussed in this study. There are research works done previously using this approach, but none has compared the algorithms’ performance on small texts. Thus, this research utilizes the Twitter form of data to test these algorithms’ performance, as it contains a maximum of 280 characters. The application proposed to detect plagiarism in tweets has been developed using Python as the backend and React as the front-end technology.

Plagiarism refers to using other ideas or works as their own without giving proper acknowledgment. The act of plagiarism is inappropriate and untrue for many reasons, especially in the academic world. Academicians are aware of this and try to avoid the act of plagiarism by any means necessary. In the present context, the digital way of teaching and learning is in practice which has more chance of plagiarized content. This research provides plagiarism detection features due to the lack of such features in digital-based teaching-learning activities. This proposed system handles the document in text format and uses Winnowing Algorithm for fingerprinting the assignment documents, and the hashing technique chosen for this algorithm is the Rolling Hash function. The similarity value is calculated using Jaccard coefficient. The test results show the combinations of parameters (n-gram, window length, and the base prime number) for the successful implementation of the system. The system successfully detects plagiarism on student assignments. The overall system is developed by using Python Web Framework Django and MySQL as a database.

Acute respiratory infections (ARI) are the commonest infections in children under the age of five years inNepal. An under five child will have 4-6 episodes of ARI per year in Nepal. ARI episode does not differmuch between developed and developing countries. Pneumonia is the commonest single cause that causesdeath in a child with respiratory infections in developing countries. Treating pneumonia is still confusing.This article re-visits the basic concept in the treatment of pneumonia.Key Words: Pneumonia, persistent, pneumonia, antibiotics, treatment.