Maryam Mousavi

Evaluating and ranking the learning components of entrepreneurial skills based on a hybrid approach of the M-learning technology and TOPSIS method

M-learning, a new type of e-learning, is created through the use of mobile phones connected to the internet. The present study aims to create a tool to investigate the learning of entrepreneurial skills via m-learning. An educational system to evaluate and enhance the learning of entrepreneurial skills and the creativity and innovations of the learners has to analyze the involved components. The effectiveness and importance of the components have to be determined to prioritize the components. In this research to create a tool, first a questionnaire that contained eighty-three questions was used to collect data. The statistical population included three hundred and thirty six BA students from the Faculty of Economics and Administrative Sciences at the University of Isfahan. Analyses were carried out by means of descriptive statistics and inferential statistical methods, including one-variable t-test and TOPSIS technique. This survey evaluates the effects of the m-learning on the learning components of the entrepreneurial skills and identifies the most effective components as well. The results revealed that there is a positive and significant relationship between the m-learning, the motivation, the degree of learners participation, the variety of educational methods, the satisfaction and the increase in self confidence in learners of entrepreneurial skills. It also revealed that motivation, self-confidence and participation have the highest effect on learning of entrepreneurial skills.

Nanobiological studies on drug design using molecular mechanic method

Background: Influenza H1N1 is very important worldwide and point mutations that occur in the virus gene are a threat for the World Health Organization (WHO) and druggists, since they could make this virus resistant to the existing antibiotics. Influenza epidemics cause severe respiratory illness in 30 to 50 million people and kill 250,000 to 500,000 people worldwide every year. Nowadays, drug design is not done through trial and error because of its cost and waste of time; therefore bioinformatics studies is essential for designing drugs. Materials and Methods: This paper, infolds a study on binding site of Neuraminidase (NA) enzyme, (that is very important in drug design) in 310K temperature and different dielectrics, for the best drug design. Information of NA enzyme was extracted from Protein Data Bank (PDB) and National Center for Biotechnology Information (NCBI) websites. The new sequences of N1 were downloaded from the NCBI influenza virus sequence database. Drug binding sites were assimilated and homologized modeling using Argus lab 4.0, HyperChem 6.0 and Chem. D3 softwares. Their stability was assessed in different dielectrics and temperatures. Result: Measurements of potential energy (Kcal/mol) of binding sites of NA in different dielectrics and 310K temperature revealed that at time step size = 0 pSec drug binding sites have maximum energy level and at time step size = 100 pSec have maximum stability and minimum energy. Conclusions: Drug binding sites are more dependent on dielectric constants rather than on temperature and the optimum dielectric constant is 39/78.