Social Learning of Employee Engagement

The influence of coworkers on workplace attitudes and behaviors is a well-researched and established occurrence in organizational psychology. Given that many of these relationships may be bi-directional, Social Learning theory is a fitting lens to examine these connections. One construct that consistently surfaces as a prominent topic in organizational research is employee engagement. The aim of this research was to investigate how social learning theory may be applied to the relationship between engagement levels of role models and observing employees. Results revealed some truly validating insights, primarily confirming the influence of coworkers on employee engagement. Model type (i.e., manager vs. non-manager) as well as relationship satisfaction were explored and added some contextually mixed evidence to what was postulated. Additionally, the interactions of energy, enablement and self-efficacy within the model-observer engagement relationship were corroborated – albeit, in a condition contrary to the hypothesis, but with significant implications nonetheless

Modelling the Flow of Aqueous Humor in Schlemm’s Canal in the Eye

A simple mathematical model for the transient flow of aqueous humor in the canal of Schlemm is developed to investigate the acceleration effects of a sudden elevation in the intraocular pressure on the flow characteristics of the aqueous humor in the canal. The model treats a canal segment as a tube of elliptic cross-section. Exact analytical solution to the model is obtained using separation of variables method. The effects of some important model parameters on the maximum and minimum shear stresses exerted on the Schlemm’s canal epithelial cells (wall) by flowing aqueous humor are investigated for the steady-state flow

Geometric and strain analyses in folds of the area around Gankot, district Pithoragarh, Uttarakhand, India

The study area around Gankot in Pithoragarh district of Uttarakhand belongs to the Thalkedar Limestone unit of Mandhali Formation, Tejam Group in Inner Sedimentary Zone of Lesser Himalaya, which exposes complexly folded and refolded structures. Geometric analysis carried out on the profile section of the fold tracing using dip isogon and orthogonal thickness parameters revealed presence of all the fold geometry suggested by Ramsay (1967) however the class 3 followed by class 1B are the most dominant classes in the study area when individual layers of the fold were studied. The study of folds as multilayered unit reveals that folds in study area belong to strongly non-analogous fold class of anisodeviatoric folds. In fold, the strain analysis has been done by drawing strain ellipse obtained by Inverse Thickness Method which is useful in estimating flattening strain even when the flattening is imposed obliquely to the fold’s axial trace. The finite two-dimensional flattening strain ratio (Rs) value ranged between 1 and 3.14 with an average Rs value of 1.60. The method of Srivastava and Gairola (2003) has also been used to obtain shear strain and flattening strain for the multilayered folds of study area. The results reveal that the multilayered folds around Gankot area are moderately flattened with mean flatting strain varying between 1.06 and 2.28. A very high degree of variation in shearing ranging about 70o in both clockwise and anticlockwise directions has been noticed. The shear strains (γ) in folds have been found to vary between -2.75 to + 3.27 with an average of +0.33. The shearing and strain patterns are suggestive that the most dominant folding mechanism has been the flexure-shear for the folds of the study area which are overprinted by the fold flattening and other subsequent deformations

Determination of protein-protein interaction through Artificial Neural Network and Support Vector Machine: A Comparative study

Protein-protein interactions (PPI) plays considerable role in most of the cellular processes and study of PPI enhances understanding of molecular mechanism of the cells. After emergence of proteomics, huge amount of protein sequences were generated but there interaction patterns are still unrevealed. Traditionally various techniques were used to predict PPI but are deficient in terms of accuracy. To overcome the limitations of experimental approaches numerous computational approaches were developed to find PPI. However previous computational approaches were based on descriptors, various external factors and protein sequences. In this article, a sequence based prediction model is proposed by using various machine learning approaches. A comparative study was done to understand efficiency of various machine learning approaches. Large amount of yeast PPI data have been analyzed. Same data has been incorporated for different classification approach like Artificial Neural Network (ANN) and Support Vector Machine (SVM), and compared their results. Existing methods with additional features were implemented to enhance the accuracy of the result. Thus it was concluded that efficiency of this model was more admirable than those existing sequence-based methods; therefore it can be effective for future proteomics research work

Impact of ICT on LIS jobs in university libraries: a study based on job announcements

268-274The paper examines the employment opportunities trend in the library and information science profession based on job advertisements published in Employment News. Data for the analysis pertained to the years 1980, 1990, 2000, 2010 and 2019. The study reflects the impact of ICT on various aspects of vacancies advertised in libraries such as designation, required qualifications, experience, skills and competencies. It is found that there have been significant changes over the years in the required ICT related qualifications and skills. In most of the job vacancies, the recruiters are looking for candidates who have sound knowledge of information technology. It is also found that with the ICT implementation, more vacancies are published in Employment News in the field of library and information science

Impact of ICT on LIS jobs in university libraries: a study based on job announcements

The paper examines the employment opportunities trend in the library and information science profession based on job advertisements published in Employment News. Data for the analysis pertained to the years 1980, 1990, 2000, 2010 and 2019. The study reflects the impact of ICT on various aspects of vacancies advertised in libraries such as designation, required qualifications, experience, skills and competencies. It is found that there have been significant changes over the years in the required ICT related qualifications and skills. In most of the job vacancies, the recruiters are looking for candidates who have sound knowledge of information technology. It is also found that with the ICT implementation, more vacancies are published in Employment News in the field of library and information science

DPAAR: a Database of Perfect Amino Acid Repeat

Repeat of amino acids in a protein sequence has clinical and functional importance. Perfect Amino Acid Repeat (PAAR) is a kind of relational as well as flat file database which is created by the comprehensive analysis of  5,42,782 protein sequences of Swiss-Prot database (released on 19th March,2014) to know the association between repeated sequence and disease. It provides the search engine for rapid access of a particular repeated amino acid, or particular swissprot ID, or particular length of repeated amino acids in a protein sequence. It also provides the flat files for single, oligo, and tandem repeated sequence information to get the complete informaton about concerned amino acids repeat. It consists of the tables of repeated sequence and its associated disease in human being