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Background: Chronic Suppurative Otitis Media (CSOM) has received considerable attention, not only because of its high incidence and chronicity, but also because of issues such as the changes in the microbiological flora following the indiscriminate use of antibiotics resulting in emergence of antibiotic ressistance. Aim: This study was done to find the microbiological profile of Chronic Suppurative Otitis Media (CSOM), susceptibility pattern of antibiotics and to provide data to formulate prescription policies in treatment of CSOM Material and Method: A total of 100 clinically diagnosed patients of CSOM were enrolled in the study and the samples were obtained from each patient using sterile cotton swabs and cultured for microbial flora. Drug susceptibility testing for aerobic isolates was conducted using modified Kirby-Bauer disc diffusion method and zone diameter was interpreted in accordance to CLSI guidelines 2014. Results: Out of 95 culture positive samples, Pseudomonas aeruginosa was the commonest organism to be isolated with the rate of 54.73%. Total Fungal isolates were found in 13% of cases where Candida species was most common where it was isolated in 10% of cases. Among commonly used antibiotics, Amikacin(75%) and Gentamicin(71.87%) were found to be most effective against Gram negative bacteria. Gentamicin(100%) & Tetracycline(100%) were found to be most effective against Gram positive bacteria. [ABSTRACT FROM AUTHOR]

Aim: The purpose of this article is to determine the racial predilection of C-shaped canal configuration in a mandibular second molar. Background: Unusual root canal anatomy always poses a diagnostic and treatment challenge. Identification of such variation is important for the success of root canal treatment outcome. C-shaped canal configuration is such an aberrant morphology of molar teeth that vary in different population and is commonly seen in a mandibular second molar. Thus, knowledge of racial predilection of C-shaped canal configuration in different population for early diagnosis is obligatory. Materials and Methods: An exhaustive search was undertaken to identify published research articles related to C-shaped canal configuration in mandibular second molars. Forty-three research articles were analyzed which included 12,481 mandibular second molars. Chi-square test using value of P < 0.05 was performed to assess the statistical significance of this anomalous anatomic variation among the different population. Results: Statistical test revealed a significant variation between the Asian and nonAsian population. The highest incidence of racial predilection was observed in China (Asia) with 93.1%, and the minimum was observed in America with 2.7%. Conclusion: This research reported that racial predilection of C-shaped canal configuration in mandibular second molar varies significantly. [ABSTRACT FROM AUTHOR]

The article focuses on the international law developments in patents, copyright and trademarks in 2012. It informs that the European Court of Justice has held that member state courts can issue crossborder interim injunctions in patent infringement cases in other European Union countries and mentions the Federal Code of Civil Procedure Law (CCP) Article 158. It also discusses proposed amendments to the Patent Law.

In this paper, a total variation (TV) based approach is proposed for pixel-level fusion to fuse images acquired using multiple sensors. In this approach, fusion is posed as an inverse problem and a locally affine model is used as the forward model. A TV seminorm based approach in conjunction with principal component analysis is used iteratively to estimate the fused image. The feasibility of the proposed algorithm is demonstrated on images from computed tomography (CT) and magnetic resonance imaging (MRI) as well as visible-band and infrared sensors. The results clearly indicate the feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

Typical consumer digital cameras sense only one out of three color components per image pixel. The problem of demosaicing deals with interpolating those missing color components. In this paper, we present compressive demosaicing (CD), a framework for demosaicing natural images based on the theory of compressed sensing (CS). Given sensed samples of an image, CD employs a CS solver to find the sparse representation of that image under a fixed sparsifying dictionary Ψ. As opposed to state of the art CS-based demosaicing approaches, we consider a clear distinction between the interchannel (color) and interpixel correlations of natural images. Utilizing some well-known facts about the human visual system, those two types of correlations are utilized in a nonseparable format to construct the sparsifying transform Ψ. Our simulation results verify that CD performs better (both visually and in terms of PSNR) than leading demosaicing approaches when applied to the majority of standard test images.