A study to Evaluate the Effectiveness of Progressive Muscle Relaxation Therapy on stress among patients with Coronary Artery Disease in Rahav Hospital, Appakudal, Erode District

STATEMENT OF THE PROBLEM: A study to evaluate the effectiveness of progressive muscle relaxation therapy on stress among patient with coronary artery disease in Raghav Hospital, Appakudal, Erode District. OBJECTIVES: 1. To assess the level of stress among patients with coronary artery disease of experimental and control group in Raghav hospital, Appakudal, erode district. 2. To evaluate the effectiveness of progressive muscle relaxation therapy on stress among patients with coronary artery disease in experimental group. 3. To compare the posttest level of stress among patients with coronary artery disease of experimental and control group. 4. To find out the association between pretest level of stress among patients with coronary artery disease with their selected demographic variables and clinical variables. METHODS: The research approach used for this study was evaluative approach and the research design was quasi experimental design, 60 patients with coronary artery disease, among that 30 in experimental group 30 in control group were selected for this study by using convenient sampling technique. Descriptive statistics (frequency, percentage, mean and standard deviation) and inferential statistics (chi-square, paired ‘t’ test & unpaired ‘t’ test) were used to analyze the data and to test hypothesis. MAJOR FINDINGS: The result of the study showed that the pretest level of stress. The mean score in experimental group is Mild 2 (7%), Moderate 6 (20%) and Severe 22 (73%) whereas, it was reduced in the post test with means score mild 18 (60%), moderate 10 (33.3%) and severe 2 (6.6%). It states that Progressive muscle relaxation therapy has an impact on stress among CAD patients in experimental group. The computed ‘t’ value 11.353 was higher than the calculated value at 0.05 level of significance. Hence, H1 (there is significant difference between pre test and post test level of stress among CAD patients in experimental group) was accepted. The post test overall stress score in experimental group. The mild 18 (60%), moderate 10 (33.3%) and severe 2 (6.6%) and where as in control group mild 2 (6.6%), moderate 9 (20%) and severe 22 (73.3%). The comparison between post test level of stress score in experimental group and control group. showing the value are significant which was observed from unpaired ‘t’ test value of 9.833 at 0.05 level of significance, which is evident for the effect of Progressive muscle relaxation therapy in reducing stress level among CAD patients. Hence, H2 (There is significant difference in post test level of stress among CAD patients in experimental group and control group) was accepted. The findings of the study showed that there is significant association between pretest level of stress and demographic variables such as living area and clinical variables such as pulse rate, blood pressure in experimental group and control group. CONCLUSION: The study assessed the level of stress among patients with coronary artery disease and found that after progressive muscle relaxation therapy and their level of stress was significantly reduced in experimental group. The study concluded that the progressive muscle relaxation therapy is effective in reducing the level of stress among patient with coronary artery disease

An Adaptive Firefly Optimization (AFO) with Multi-Kernel SVM (MKSVM) Classification for Big Data Dimensionality Reduction

The data's dimensionality had already risen sharply in the last several decades. The "Dimensionality Curse" (DC) is a problem for conventional learning techniques when dealing with "Big Data (BD)" with a higher level of dimensionality. A learning model's performance degrades when there is a numerous range of features present. "Dimensionality Reduction (DR)" approaches are used to solve the DC issue, and the field of "Machine Learning (ML)" research is significant in this regard. It is a prominent procedure to use "Feature Selection (FS)" to reduce dimensions. Improved learning effectiveness such as greater classification precision, cheaper processing costs, and improved model comprehensibility are all typical outcomes of this approach that selects an optimal portion of the original features based on some relevant assessment criteria. An "Adaptive Firefly Optimization (AFO)" technique based on the "Map Reduce (MR)" platform is developed in this research. During the initial phase (mapping stage) the whole large "DataSet (DS)" is first subdivided into blocks of contexts. The AFO technique is then used to choose features from its large DS. In the final phase (reduction stage), every one of the fragmentary findings is combined into a single feature vector. Then the "Multi Kernel Support Vector Machine (MKSVM)" classifier is used as classification in this research to classify the data for appropriate class from the optimal features obtained from AFO for DR purposes. We found that the suggested algorithm AFO combined with MKSVM (AFO-MKSVM) scales very well to high-dimensional DSs which outperforms the existing approach "Linear Discriminant Analysis-Support Vector Machine (LDA-SVM)" in terms of performance. The evaluation metrics such as Information-Ratio for Dimension-Reduction, Accuracy, and Recall, indicate that the AFO-MKSVM method established a better outcome than the LDA-SVM method

Integrating Digital Literacy Skills and Technological Intelligence in the Higher Education Curriculum of India: A New Paradigm

Background: The twenty-first-century learners can be termed as digital natives and therefore, any discussion on the pedagogies and curriculum must concentrate on integrating digital literacy skills and the teaching and learning materials must focus on the development of the technological intelligence of the learners. The principal appre-hension for all the educationists and curriculum planners is how to transform and modify higher education for preparing the learners of this century to more effectively cope with the challenges of today’s labor market. Purpose: The paper aims to answer two key questions facing higher educational educators are those of: (i) what is the present status of higher education in preparing the graduates with the necessary skills and competencies for 21st-century skills, and (ii) how can the present education system integrate the digital and technological intelligence in the curriculum? Methods: Exploration of the current Indian higher education cur-riculum and critically analyzing the results of various studies con-ducted in a similar area and by analyzing newspapers, educational policies, public survey results, and literature regarding the trends and developments in the higher education academia. Results: This disposition visualized the possible challenges and suggests practical measures to solve the problems and demand for a new paradigm where there is symbiotic integration of digital literacy skills and technological intelligence is highlighted. Conclusion: There is a great need for updating and transforming the curriculum and pedagogic approaches in tune with the learning styles and demands of the learners

Investigating 21st Century Skills Level among Youth : An Empirical Study

Twenty-first century skills are a set of capabilities and competencies that students need to cultivate and develop to succeed in the age of information and technology. The success and growth of today's youth in the labour market and the knowledge economy depend on the level of 21st century skills they possess. Hence the key objective of this study was to answer the questions: to what extent do the youth possess 21st century skills? Is there a difference between levels of 21st century skills on account of various demographic variables? The researchers used the descriptive survey method and selected 160 college students randomly from various higher education institutions of Kerala, the southern part of India, for the study. The significant findings of this study revealed that 15.6% have a Low level, 68.1% have an Average level, 16.3% have a high level of 21st-century skills. No significant difference exists between males and females and stream of subjects of college students with respect to the level of 21st century skills, but there is a substantial difference between the youth who belong to the urban and rural locality

Influence of biliary stents on the diagnostic outcome of endoscopic ultrasound–guided tissue acquisition from solid pancreatic lesions: a systematic review and meta-analysis

Background/Aims This meta-analysis analyzed the effect of an indwelling biliary stent on endoscopic ultrasound (EUS)–guided tissue acquisition from pancreatic lesions. Methods A literature search was performed to identify studies published between 2000 and July 2022 comparing the diagnostic outcomes of EUS-tissue acquisition (TA) in patients with or without biliary stents. For non-strict criteria, samples reported as malignant or suspicious for malignancy were included, whereas for strict criteria, only samples reported as malignant were included in the analysis. Results Nine studies were included in this analysis. The odds of an accurate diagnosis were significantly lower in patients with indwelling stents using both non-strict (odds ratio [OR], 0.68; 95% confidence interval [CI], 0.52–0.90) and strict criteria (OR, 0.58; 95% CI, 0.46–0.74). The pooled sensitivity with and without stents were similar (87% vs. 91%) using non-strict criteria. However, patients with stents had a lower pooled sensitivity (79% vs. 88%) when using strict criteria. The sample inadequacy rate was comparable between groups (OR, 1.12; 95% CI, 0.76–1.65). The diagnostic accuracy and sample inadequacy were comparable between plastic and metal biliary stents. Conclusions The presence of a biliary stent may negatively affect the diagnostic outcome of EUS-TA for pancreatic lesions

Characterisation of PolyVinyl Alcohol (PVA) as a water-soluble sacrificial layer for affordable surface micromachining

Micro-Electro Mechanical Systems (MEMS) play a significant role in many industries today. These include aerospace, automotive, biomedical, optical display and wireless communication. MEMS are very small devices that can sense, think, communicate and even act. This makes them the backbone of many industries. As the sizes of these devices gets smaller and smaller to the micro- or nano-scale, the fabrication process becomes a challenge. There are numerous methods of creating such devices. One such method is the use of sacrificial layers in surface micromachining. Currently the common sacrificial layers that are used require acids, that are highly corrosive and toxic, to dissolve them. This is harmful not just to the people handling it but also to the environment. Thus a safer means of creating such devices is essential. Imagine being able to form such devices with solvents that are extremely safe and environmentally friendly. Water is one such solvent, and that is why it important to obtain a sacrificial layer that can be dissolved using water and still be able to function just as well as other sacrificial layers. PolyVinyl Alcohol (PVA) is a polymer that is soluble in water. Therefore this study focused on the possibility of using PVA as a water-soluble sacrificial layer. Experiments were carried out to form PVA film from solid PVA and then structural layers were deposited on top of the PVA. The structural layers used were Norland Optical Adhesive (NOA), epoxy resin and cyanoacrylate. The PVA was then dissolved away using water to form channels. This process resembles the basic steps required to create micro-devices using a sacrificial layer. It was found that PVA can be used as a water-soluble sacrificial layer for surface micromachining. However, success in using PVA depends heavily on the choice of structural layer, because certain materials such as NOA and epoxy resin alter the solubility of PVA. Nevertheless, with further process development, the use of PVA as a sacrificial layer could result in the elimination of toxic solvents from MEMS fabrication.Bachelor of Engineering (Mechanical Engineering

A feature reduction based LDA with SVM classification on dimensionality reduction for Big Data

Analytics of Big data research has been entering the latest processes of "fast-data", in which every second many Giga Bytes of data arriving towards a massive structure of data. Based on the number, speed, importance, variation, uncertainty and veracity of the collected data, current Big data applications gather dynamic data sources and thus create massive unstructured Big Data. Data sources that are decreased and significant are deemed more valuable than raw, repetitive, unreliable, and noisy data set. A further prospect for reducing the big data whereas the thousands of attributes in large data sets are the cause of the dimensionality which takes infinite computing resources to expose working patterns of information. Not each feature in the generated datasets is essential for the training of computer algorithms. Any characteristics do not influence the effects of the forecast and some may be negligible. The ignorance of this trivial or less important characteristics lowers the pressure on the algorithms of Machine Learning (ML). The MapReduce technology in existing has also been used to decrease dimensionality, but without decreasing irrelevant features it takes all data for a direct reduction, which contributes to lower classification precision.&nbsp

CRAB score for prediction of colectomy within 2 years following admission for acute severe ulcerative colitis

Background: The Oxford and Swedish indexes were developed to predict in-hospital colectomy in acute severe ulcerative colitis (ASUC), but not long-term prediction, and all these indexes were based on Western data. Our study aimed to analyze the predictors of colectomy within 3 years of ASUC in an Indian cohort and derive a simple predictive score. Methods: A prospective observational study was conducted in a tertiary health care center in South India over a period of 5 years. All patients admitted with ASUC were followed up for a period of 24 months after the index admission, to look for progression to colectomy. Results: A total of 81 (47 male) patients were included in the derivation cohort. Fifteen (18.5%) patients required colectomy during a follow-up period of 24 months. On regression analysis, C-reactive protein (CRP) and serum albumin were independent predictors of 24-month colectomy. The CRAB (CRP + AlBumin) score was obtained by multiplying coefficient of beta to albumin and CRP (CRAB score = CRP x 0.2 – Albumin x 0.26). The CRAB score demonstrated an AUROC of 0.923 and a score of >0.4 with a sensitivity of 82% and specificity of 92% for the prediction of 2-year colectomy following ASUC. The score was validated in a validation cohort of 31 patients, and at >0.4, the score had a sensitivity of 83% and a specificity of 96% in predicting colectomy. Conclusion: CRAB score is a simple prognostic score that can predict 2-year colectomy in ASUC patients with high sensitivity and specificity

A rare cause for recurrent cystitis

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