Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Authentic Leadership Fostering Creativity in Start-ups: Mediating Role of Work Engagement and Employee Task Proactivity:

Abstract: This study investigates the effect of authentic leadership (AL) on employee creativity and the mediating role of work engagement (WE) and employee task proactivity (ETP) in the context of start-ups...

A Unique Computational Method for Constructing Intervals in Fuzzy Time Series Forecasting

Abstract: Abstract This research article suggests a computational method for constructing fuzzy sets in absence of expert knowledge. This method uses concepts of central tendencies mean and variance. This study gives a solution to the critical issue in designing of fuzzy systems, number of fuzzy sets. Proposed computational method helps in finding intervals and thereby fuzzy sets for fuzzy time series forecasting. Proposed computational method is implemented on the authentic data for the enrolments of University of Alabama, which is considered as benchmark problem in the field of fuzzy time series. The forecasted values are compared with the results of other methods to state its supremacy. Projected computational method along with Gaussian membership function gave promising results over other methods for fuzzy time series for the above said benchmark data.

A Novel Approach to Generate Test Cases Using Class and Sequence Diagrams

Abstract: It is very important in today’s highly dynamic environment with changing requirements to develop test plan at each stage of the Software Development Life Cycle Owing to the ever changing requirements, adequate updation in the requirement specifications is unavoidable Due to lack of proper updation in the requirements, inconsistencies creep up Research shows that number of software fail on account of these inconsistencies because proper testing is not possible on archaic requirements Further, the increasing complexity of the projects make manual testing impossible This calls for automatic testing of specifications to keep a check on the inconsistencies Most of the earlier approaches to testing specifications use intermediate forms that makes automation difficult In this paper, we will present a novel approach to automatic test case generation that integrates information from UML class and sequence diagrams and at the same time does not use any intermediate form Users input the diagram information in the form of XMI files These files are processed to extract the environment variables from the class diagrams and test sequences from sequence diagram and finally generate the test cases by applying Robustness Testing on the test sequence generated Thus we avoid the intermediate forms as well as make automation an easier task

Self-Efficacy, Work Passion and Wellbeing: A Theoretical Framework

Abstract: Passion has captivated researchers of different disciplines for centuries. While the concept of passion for work has received a good deal of attention in the popular press, theoretical and empirical researches have lagged behind. The purpose of this review is to analyze the concept of passion from different perspectives and offer a cohesive definition of passion for work with its underlying dimensions. Further, the authors have tried to propose a theoretical framework, where, self-efficacy is hypothesized to facilitate passion for work, which in turn will enhance employee well being. Directions for future research and implications for management practice are discussed as well.

Comparative Genomics and Integrated Network Approach Unveiled Undirected Phylogeny Patterns, Co-mutational Hot Spots, Functional Cross Talk, and Regulatory Interactions in SARS-CoV-2

Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in 92 million cases in a span of 1 year. The study focuses on understanding population-specific variations attributing its high rate of infections in specific geographical regions particularly in the United States. Rigorous phylogenomic network analysis of complete SARS-CoV-2 genomes (245) inferred five central clades named a (ancestral), b, c, d, and e (subtypes e1 and e2). Clade d and subclade e2 were found exclusively comprised of U.S. strains. Clades were distinguished by 10 co-mutational combinations in Nsp3, ORF8, Nsp13, S, Nsp12, Nsp2, and Nsp6. Our analysis revealed that only 67.46% of single nucleotide polymorphism (SNP) mutations were at the amino acid level. T1103P mutation in Nsp3 was predicted to increase protein stability in 238 strains except for 6 strains which were marked as ancestral type, whereas co-mutation (P409L and Y446C) in Nsp13 were found in 64 genomes from the United States highlighting its 100% co-occurrence. Docking highlighted mutation (D614G) caused reduction in binding of spike proteins with angiotensin-converting enzyme 2 (ACE2), but it also showed better interaction with the TMPRSS2 receptor contributing to high transmissibility among U.S. strains. We also found host proteins, MYO5A, MYO5B, and MYO5C, that had maximum interaction with viral proteins (nucleocapsid [N], spike [S], and membrane [M] proteins). Thus, blocking the internalization pathway by inhibiting MYO5 proteins which could be an effective target for coronavirus disease 2019 (COVID-19) treatment. The functional annotations of the host-pathogen interaction (HPI) network were found to be closely associated with hypoxia and thrombotic conditions, confirming the vulnerability and severity of infection. We also screened CpG islands in Nsp1 and N conferring the ability of SARS-CoV-2 to enter and trigger zinc antiviral protein (ZAP) activity inside the host cell.IMPORTANCE In the current study, we presented a global view of mutational pattern observed in SARS-CoV-2 virus transmission. This provided a who-infect-whom geographical model since the early pandemic. This is hitherto the most comprehensive comparative genomics analysis of full-length genomes for co-mutations at different geographical regions especially in U.S. strains. Compositional structural biology results suggested that mutations have a balance of opposing forces affecting pathogenicity suggesting that only a few mutations are effective at the translation level. Novel HPI analysis and CpG predictions elucidate the proof of concept of hypoxia and thrombotic conditions in several patients. Thus, the current study focuses the understanding of population-specific variations attributing a high rate of SARS-CoV-2 infections in specific geographical regions which may eventually be vital for the most severely affected countries and regions for sharp development of custom-made vindication strategies.