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.

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For health monitoring of bridges, wireless acceleration sensor nodes (WASNs) are normally used. In bridge environment, several forms of energy are available for operating WASNs that include wind, solar, acoustic, and vibration energy. However, only bridge vibration has the tendency to be utilized for embedded WASNs application in bridge structures. This paper reports on the recent advancements in the area of vibration energy harvesters (VEHs) utilizing bridge oscillations. The bridge vibration is narrowband (1 to 40 Hz) with low acceleration levels (0.01 to 3.8 g). For utilization of bridge vibration, electromagnetic based vibration energy harvesters (EM-VEHs) and piezoelectric based vibration energy harvesters (PE-VEHs) have been developed. The power generation of the reported EM-VEHs is in the range from 0.7 to 1450000 μW. However, the power production by the developed PE-VEHs ranges from 0.6 to 7700 μW. The overall size of most of the bridge VEHs is quite comparable and is in mesoscale. The resonant frequencies of EM-VEHs are on the lower side (0.13 to 27 Hz) in comparison to PE-VEHs (1 to 120 Hz). The power densities reported for these bridge VEHs range from 0.01 to 9539.5 μW/cm3and are quite enough to operate most of the commercial WASNs.

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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.

This article describes the current state-of-the-art technique of percutaneous transplant renal biopsy. A brief overview of the history of transplant renal biopsy is given. The indications and contraindications are discussed, including pre- and postprocedure patient management. The technique of the procedure and the devices that are available in the market are described.

Underwater wireless sensor networks (UWSNs) is an emerging technology for exploration of underwater resources. Security plays an important role in the UWSNs environment because the environment of UWSNs is prone to different security attacks. This research proposes SEECR: Secure Energy Efficient and Cooperative Routing protocol for UWSNs. SEECR comprised of energy efficient and strong defense mechanism for combatting attacks in underwater environment. SEECR exploits cooperative routing for enhancing the performance of network. Considering the resource constrained UWSNs environment minimum computation is employed for implementing security so that SEECR remains suitable for underwater environment. In order to evaluate the performance of SEECR, this research compares the performance of SEECR with AMCTD: Adaptive Mobility of Courier Nodes in Threshold-optimized DBR-a wellknown routing protocol for UWSNs environment. The performance of SEECR and AMCTD protocols are evaluated using different performance evaluation parameters such as number of alive nodes, transmission loss, throughput, energy tax and end-to-end delay. The results suggest an improved performance of SEECR over AMCTD. SEECR shows an improvement of 9% in terms of number of alive nodes, over 50% reduction in terms of transmission loss, up to 9% increase in throughput, up to 23% reduction in energy tax, and 25% reduction in end-to-end delay. Further, we observe that attack significantly degrades the performance of AMCTD whereas due to the embedded defense mechanism in SEECR the impact of attack is negligible.