The present study is designed to compare two different types of meditations, Mindfulness Based Stress Reduction Programme (MBSRP; Zinn, 2003) and Sufi Meditation (SM) in the treatment of neurotic anxiety and enhancement of mental health in female population. The study is comprised of a total of 200 participants upon whom Hamilton Anxiety Scale (HAS; Hamilton, 1959) was administered and two groups of subjects each comprising of 50 (n = 50) subjects with high anxiety and 50 (n = 50) with low anxiety scores (n = 100) derived, further bifurcated into four subgroups wherein 25 (n = 25) subjects with low anxiety randomly assigned to both groups and remaining 25 (n = 25) with high anxiety assigned randomly to each groups. Pre- and post-test measures on HAS and Psychological Well-Being Scale (Ryff, 1989) for both groups was obtained and analyzed. The overall results of study showed that Mindfulness meditation group showed significantly higher score on HAS as compared to Sufi meditation group. According to the results, Sufi meditation was more effective in lowering anxiety and enhancing mental health, since it matches the belief system of the population. Hence results provide a base for future research to combine both types of meditations developing a new healing dimension.

Let G n , m represent the family of square power graphs of order n and size m , obtained from the family of graphs F n , k of order n and size k , with m ≥ k . In this paper, we discussed the least eigenvalue of graph G in the family G n , m c . All graphs considered here are undirected, simple, connected, and not a complete K n for positive integer n .

Change is inevitable, software undergoes continuous change during its life cycle. A small change can trigger high evolution because of the ripple effect identified during the activity of impact analysis. However, it depends on the traceability information, which is the connection between software development artifacts. The current traceability techniques lack the breadth and depth to carryout informative impact analysis. We have performed a detailed literature survey of traceability techniques from the year 2008-2018. These techniques are evaluated on the criteria for effective impact analysis present in the literature. The results highlight that no single technique fulfills the criteria for effective impact analysis alone, they can be combined together to achieve promising results. We have presented a hybrid approach that combines four traceability techniques to achieve the entire criteria for an effective impact analysis after careful evaluation. The techniques combined are: Information Retrieval, Pre-Requirement Specification Traceability, Value based Requirements Traceability Technique and Goal Centric Traceability Technique. Our proposed hybrid approach is empirically validated via a field experiment. Results are analyzed for time and effort utilized in maintaining and retrieving the traceability information. The results are promising as the hybrid approach achieves effective impact analysis within minimal time and effort. We plan to extend the validation to real world impact analysis situation via case study.

Hypergraph is a generalization of graph in which an edge can join any number of vertices. Hypergraph is used for combinatorial structures which generalize graphs. In this research work, the notion of hypergraphical metric spaces is introduced, which generalizes many existing spaces. Some fixed point theorems are studied in the corresponding spaces. To show the authenticity of the established work, nontrivial examples and applications are also provided.

Background: Coronavirus disease (COVID-19) was declared as pandemic by World Health Organization (WHO) on 30th January 2020. Cancer patients are a vulnerable population with increased risk for mortality associated with COVID-19 infection. In this study, we report the impact of education for acceptance of COVID-19 vaccination in our cancer patients. Methods: This was a cross-sectional study between 1st August 2021 and 31st October 2021. All patients with diagnosis of cancer who presented to the oncology clinic were asked whether they received COVID-19 vaccine or planning to get vaccinated. Patients, who had refused the vaccine, were educated to get vaccinated. Post counseling, they were again asked if they would agree to get vaccinated. Results: Out of 512 cancer patients, 274 (53.5%) were male. Of total, 456 (89.1%) were diagnosed cases of solid malignancy. Patients who were on active oncological treatment were 406 (79.3%). Of total 512, 396 (77.3%) patients agreed for the COVID-19 vaccine while 116 (22.7%) had refused to get vaccinated. Of those 116, 75 (64.7%) patients accepted to get vaccinated post counseling. Conclusion: COVID-19 vaccine acceptance is higher among cancer patients at our institute compared to reported data. Oncologists should play a key role in encouraging their patients to get vaccine in order to reduce COVID-19 related mortality.