The advent of the World Wide Web and the rapid adoption of social media platforms (such as Facebook and Twitter) paved the way for information dissemination that has never been witnessed in the human history before. With the current usage of social media platforms, consumers are creating and sharing more information than ever before, some of which are misleading with no relevance to reality. Automated classification of a text article as misinformation or disinformation is a challenging task. Even an expert in a particular domain has to explore multiple aspects before giving a verdict on the truthfulness of an article. In this work, we propose to use machine learning ensemble approach for automated classification of news articles. Our study explores different textual properties that can be used to distinguish fake contents from real. By using those properties, we train a combination of different machine learning algorithms using various ensemble methods and evaluate their performance on 4 real world datasets. Experimental evaluation confirms the superior performance of our proposed ensemble learner approach in comparison to individual learners.

Objective: To compare the complications rate of percutaneous nephrostomy and double J ureteral stenting in the management of obstructive uropathy. Methodology: Total number of 300 patients of age 20-80 years who underwent JJ stenting or percutaneous nephrostomy for obstructive uropathy were included in this study. Patients were divided in two groups i.e. A & B. In group A, 100 patients who underwent double J ureteral stenting while in group B, 200 patients who underwent percutaneous nephrostomy tube insertion were included. The stent was inserted retrograde by using cystoscope, under mild sedation or local anesthesia. While the percutaneous nephrostomy was done under ultrasound guidance by using local anesthetic agent. Complications were noted in immediate post-operative period and on follow up. Results: Majority of the patients were between 36 to 50 years of age with male to female ratio was 2.6:1. The most common cause of obstructive uropathy was stone disease i.e. renal, ureteric or both. Post DJ stent, complications like painful trigon irritation, septicemia, haematuria and stent encrustation were seen in 12.0%, 7.0%, 10.0% and 5.0% patients respectively. On the other hand, post-PCN septicemia, bleeding and tube dislodgment or blockage was seen in 3.5%, 4.5% and 4.5% respectively. In this study, overall success rate for double J stenting was up to 83.0% and for percutaneous nephrostomy (PCN) was 92.0% (p<0.0001). Conclusion: Percutaneous nephrostomy is a safe and better method of temporary urinary diversion than double J stenting for management of obstructive uropathy with lower incidence of complications.

Real world complex networks are indirect representation of complex systems. they grow over time. these networks are fragmented and raucous in practice. An important concern about complex network is link prediction. Link prediction aims to determine the possibility of probable edges. the link prediction demand is often spotted in social networks for recommending new friends, and, in recommender systems for recommending new items (movies, gadgets etc) based on earlier shopping history. in this work, we propose a new link prediction algorithm namely "common neighbor and centrality based parameterized Algorithm" (ccpA) to suggest the formation of new links in complex networks. Using AUC (Area Under the receiver operating characteristic curve) as evaluation criterion, we perform an extensive experimental evaluation of our proposed algorithm on eight real world data sets, and against eight benchmark algorithms. the results validate the improved performance of our proposed algorithm.