Cognitive Information Processing

Contains reports on one research project.National Institutes of Health (Grant 5 P01 GM14940-06

A Computational Study of Toxicity of Nitrobenzenes Using QSPR and DFT-Based Molecular Surface Electrostatic Potential

In the present study, the density functional B3LYP/6-311G** level of theory was used to compute and map the molecular surface electrostatic potentials of a group of substituted nitrobenzenes to identify common features related to their subsequent toxicities. Several statistical properties including potentials’ extrema (Vmin, Vmax), molecular volume, surface area, polar surface area, along with different energies were computed. A little linear correlation was revealed between Vmin and surface area, and systems’ toxicities. Another computations employed quantitative structure–property relationships model in CODESSA package to correlate toxicities with calculated descriptors. Statistically, the most significant correlation is a five-parameter equation with correlation coefficient, R2 values of 0.962, and the cross-validated correlation coefficient, R2 CV= 0.950. The obtained models allowed us to reveal toxic activity of nitrobenzenes

Measuring Push, Pull And Personal Factors Affecting Turnover Intention: A Case Of University Teachers In Pakistan

It has been observed that professional and qualified teacher’s retention become a challenge for Higher Education Institutions (HEIs) in Pakistan as the turnover rate has been significantly increased in recent years. The main objective of this paper is to access personal, push and pull factors and to find out that which factors contribute more to turnover intention. Primary data were collected from 100 teachers of 5 HEIs using questionnaire methods. The results indicate that all factors (personal, pull and push) have contributed in the employees’ turnover intentions. However, some facets of personal factor have significantly contributed in turnover intentions.Turnover, Higher Education Institution, Job Quit, Personal Factors, Push Factors, Pull Factors

A Density Functional Based Molecular Surface Electrostatic Potentials of Histamine H1-Agonists

A computational analysis of the electrostatic potentials of nine histamine H1 agonists of various structural modifications has been carried out at the density functional B3P86/6-31G** level of theory. It focuses upon the relationships between these potentials and the H1-agonistic activities of the molecules through identifying any common features. Analysis of several statistically based properties of the surface potentials has revealed that H1-Agonism is a linear function with of the potential’s maxima, max,

Experimental investigation of nano-alumina effect on the filling time in VARTM process

In this research, by producing composite samples made of glass fibers and epoxy resin with different percentages of nanoparticles (Nano-alumina), the adding effect of nanoparticles of alumina Alpha and Gamma grade on filling time in the vacuum assistant resin transfer molding process (VARTM) is investigated. The grade Alpha and Gamma of Nano alumina were added to the epoxy system with the weight percentage of 1, 2, 3, 4, 5 and 6. The experimental results show that increasing nanoparticles lead to increase the filling time which is caused by increased fluid viscosity and consequently more resistant to vacuum pressure applied to flow fluid in porous media of preforms. By adding of nanoparticles, an optimal limit exists to prevent a significant increase in the filling time which is 3% for Nano-composite samples of alumina with grade of Alpha and Gamma. Also, in the first, the movement speed of the resin into the preform is about one centimeter per second, and by increasing flow this speed gradually decreases (close to zero).Keywords: Nano-composite, VARTM, Nano-Alumina, displacement-time curve, die filling tim

Variation of parameters in Becke‐3 hybrid exchange‐correlation functional

We have investigated the consequences of varying the three parameters in Becke's hybrid exchange‐correlation functional, which includes five contributions: Hartree–Fock exchange, local exchange, Becke's gradient exchange correction, local correlation, and some form of gradient correlation correction. Our primary focus was upon obtaining orbital energies with magnitudes that are reasonable approximations to the electronic ionization potentials; however, we also looked at the effects on molecular geometries and atomization enthalpies. A total of 12 parameter combinations was considered for each of three different gradient correlation corrections: the Lee–Yang–Parr, the Perdew‐86, and the Perdew–Wang 91. Five molecules were included in the study: HCN, N2, N2O, F2O, and H2O. For comparison, a Hartree–Fock calculation was also carried out for each of these. The 6‐31+G** basis set was used

Stability and Antimicrobial Activity of Transition Metal (II) Complexes with SNO and ONO Functionalized Ligand: A Computational Study

In this work, the structural, surface potential, and antimicrobial aspects of a set of recently synthesized and published complexes of five transition metals (II) are investigated using the semiempirical PM6 and B3LYP/6-31G* methods. The complexes ML2 [M= Ni, Cu, and Zn] are mainly composed of 2-thiophenecarbaldehyde isonicotinoyl hydrazone containing a trifunctional SNO-donor system. Experimentally, the complexes were synthesized and characterized using their conductivity, IR, and partially using 1H NMR, and MS spectra, where they show similar properties to those in their analogous NNO functionalized ligand and ONO donor ligand. The attained wavefunction for each of the complexes was subsequently used to compute six molecular descriptors which were then investigated in light of their reported antimicrobial activities against Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa

Tautomerism of 5-methyl imidazolidine thio derivatives in the gas phase: a density functional study

Relative tautomerisation energies, enthalpies, entropies, Gibbs free energies, and dipole moments for 5-methyl-2,4-dioxo-imidazolidine and its thio analogous have been studied in the gas phase using hybrid density functional at the B3LYP level of theory using 6-31(d) and 6-31

A Comparative Study on Critical Thinking Skills of Bachelor and Master�s Degree Students in Critical Care Nursing

Background: Promoting critical thinking skills is an essential outcome of undergraduate and postgraduate nursing education. Objectives: The current study aims at comparing critical thinking skills of bachelor students of nursing (BSc) and master’s students of critical care nursing (MSc) in the academic year 2014 - 2015. Methods: The current cross-sectional study was conducted on 79 BSc students of nursing and 44 MSc students of critical care nursing in 3 universities of medical sciences including Semnan, Tehran, and Kashan. The California critical thinking test, form B, was used for data collection. Analysis of variance Mann-Whitney, and Kruskal-Wallis tests were used for statistical analyses. Results: Themeanscores of BS and MSc nursing students were 11.14�3.01 and 10.05�3.33, respectively, which were not significantly different. The mean scores of students in Semnan, Tehran, and Kashan universities of medical sciences were 9.84 � 3.13, 9.66 � 3.32, and 11.79 � 2.92, respectively, and the total mean score was 10.46 � 3.24. The scores of critical thinking domains showed that students in Kashan University gained higher scores in interference, and deductive and inductive reasoning domains compared with the students in other universities. Conclusions: The level of critical thinking in BSc students was higher. The overall level of critical thinking skills was low in nursing students. It is suggested that appropriate and effective methods should be employed to create and improve critical thinking in nursing education

Automatic Face and Hijab Segmentation Using Convolutional Network

Taking pictures and Selfies are now very common and frequent between people. People are also interested in enhancing pictures using different image processing techniques and sharing them on social media. Accurate image segmentation plays an important role in portrait editing, face beautification, human identification, hairstyle identification, airport Surveillance system and many other computer vision problems. One specific functionality of interest is automatic face and veil segmentation as this allows processing each separately. Manual segmentation can be difficult and annoying especially on smartphones small screen. In this paper, the proposed model uses fully convolutional network (FCN) to make semantic segmentation into skin, veil and background. The proposed model achieved an outperforming result on the dataset which consists of 250 images with global accuracy 92% and mean accuracy 92.69