A New Algorithm for Exploratory Projection Pursuit

In this paper, we propose a new algorithm for exploratory projection pursuit. The basis of the algorithm is the insight that previous approaches used fairly narrow definitions of interestingness / non interestingness. We argue that allowing these definitions to depend on the problem / data at hand is a more natural approach in an exploratory technique. This also allows our technique much greater applicability than the approaches extant in the literature. Complementing this insight, we propose a class of projection indices based on the spatial distribution function that can make use of such information. Finally, with the help of real datasets, we demonstrate how a range of multivariate exploratory tasks can be addressed with our algorithm. The examples further demonstrate that the proposed indices are quite capable of focussing on the interesting structure in the data, even when this structure is otherwise hard to detect or arises from very subtle patterns.Comment: 29 pages, 8 figure

U wave: an Important Noninvasive Electrocardiographic Diagnostic Marker

Study of U waves exemplifies important clinical role of noninvasive electrocardiography in modern cardiology. Present article highlights significance of U waves with a clinical case and also summarizes in brief the history of the same

NSL-BP: A Meta Classifier Model Based Prediction of Amazon Product Reviews

In machine learning, the product rating prediction based on the semantic analysis of the consumers' reviews is a relevant topic. Amazon is one of the most popular online retailers, with millions of customers purchasing and reviewing products. In the literature, many research projects work on the rating prediction of a given review. In this research project, we introduce a novel approach to enhance the accuracy of rating prediction by machine learning methods by processing the reviewed text. We trained our model by using many methods, so we propose a combined model to predict the ratings of products corresponding to a given review content. First, using k-means and LDA, we cluster the products and topics so that it will be easy to predict the ratings having the same kind of products and reviews together. We trained low, neutral, and high models based on clusters and topics of products. Then, by adopting a stacking ensemble model, we combine Naïve Bayes, Logistic Regression, and SVM to predict the ratings. We will combine these models into a two-level stack. We called this newly introduced model, NSL model, and compared the prediction performance with other methods at state of the art

Racing heart and pounding neck: Classic clinical sign revisited

The present report describes “Frog sign” due to prominent jugular pulsations in the neck. This is seen in case of paroxysmal atrioventricular nodal reentrant tachycardia

Evaluation of a training workshop on tobacco cessation: capacity building initiative in India

Background The World Health Organization's (WHO) Tobacco Free Initiative highlights the role of health care professionals such as nurses, pharmacists, counselors and related support staff, in implementing smoking-cessation services. However, to be competent in providing smoking-cessation interventions, they need to establish and demonstrate knowledge, skills, and confidence in this field. Methods Pre-Post quasi-experimental design was used in this study to test the effectiveness of the educational training program. A total of 90 healthcare professionals, including nurses, nursing trainees, psychology trainees, social workers and trainees attended the workshop. Seventy six completed the pre-post assessment as a part of the one day workshop at All India Institute of Medical Sciences, New Delhi. The tool developed by the researchers included twenty questions evaluating the knowledge, attitude and skills related to Tobacco cessation activities. Each item in the questionnaire had a score of one for correct and zero for incorrect responses. Paired sample t-test was performed to compare the scores on above parameters. Ethical approval was obtained from Institute Ethics Committee. Results The participants were predominantly females (80.26%) with professional experience of up to 3 years (Mean = 1.68; SD ± 0.84) in various healthcare related activities. There was a statistically significant improvement in total scores after the workshop as compared to before (Mean change: 2.86; t = 8.71, p< 0.001). The improvement was statistically significant in both knowledge related (t = 7.46, p< 0.001) and attitude/ skills related scores (t = 2.94, p=0.004). The level of professional experience and previous attending workshops could not statistically predict change in scores. Conclusions The workshop proved to be an effective approach in enhancing knowledge and imparting attitudinal changes in the healthcare professionals. Continued educational programs should be organized for capacity building in Tobacco cessation activities

Tumor necrosis factor-alpha −308G/A gene polymorphism and novel biomarker profiles in patients with Takayasu arteritis

Background: Takayasu arteritis (TA) is an idiopathic chronic inflammatory disease of the aorta and its branches, leading to stenosis, occlusion, and aneurysmal dilatation. Tumor necrosis factor-alpha (TNF-α) is a cytokine with pleomorphic actions and plays a pivotal role in inflammation; the serum level of TNF-α is genetically determined. However, the literature lacks adequate information on the association of TNF-α polymorphisms with TA. Hence, the present study investigates the contribution of TNF-α polymorphism toward the complex etiology of TA. Methods: A cross-sectional study was performed in 87 patients with TA and 90 controls. A promoter region polymorphism of TNF-α, rs1800629 G/A, or −308G/A was genotyped in all the study subjects followed by a case–control association study. Furthermore, to understand the biomarker profile, levels of specific markers such as erythrocyte sedimentation rate, serum high-sensitivity C-reactive protein, interleukin-18, interleukin-6, and TNF-α were measured in all the study subjects. Results: All the inflammatory markers were significantly higher in the TA patients than in the controls. The genetic study (available for 57 TA patients and 36 controls) revealed that the TNF-α −308A allele was overrepresented in the TA patients (12% vs 7%). The TNF-α −308A allele correlated with the increased TNF-α levels, but it could not attain significance because of a small sample size. Conclusion: The TNF-α −308G/A polymorphism is associated with TNF-α levels in Indian population, which might have implications for clinical risk stratification and treatment. The different TNF-α gene promoter polymorphism might contribute to the molecular pathogenesis of TA. However, further study of the underlying mechanism is warranted. Keywords: Takayasu arteritis, Biomarkers, Tumor necrosis factor-alpha, Gene polymorphis