Polymerization of Diphenylcarbodiimide Catalysed by Fullerene-60

In the presence of fullerene-60 as a catalyst, the formation of diphenylcarbodiimide (DPCD) from phenylisocyanate followed by its polymerization into a hexamer in xylene at refluxing temperature was carried out. The product was analysed by FAB-Mass spectrometry, FT-IR, UV-Vis and HPLC techniques.     

Prediction of Heat of Vapourization of Moisture from Cereal Grains - A Modelling Approach

The Henderson's EMC model in modified form was used to fit the EMC data given by Engels et al (1987) for brown, parboiled rice. The constants in the model were related to temperature. A method to find an expression for heat of vapourization of moisture from grain was developed and demonstrated using the EMC data of brown, parboiled rice. The heat of vapourization of moisture from rice was high at low moisture contents. For moisture contents above 25% (db), the moisture inside the grain behaved almost like free water.     

Automated classification of patients with coronary artery disease using grayscale features from left ventricle echocardiographic images

Coronary Artery Disease (CAD), caused by the buildup of plaque on the inside of the coronary arteries, has a high mortality rate. To efficiently detect this condition from echocardiography images, with lesser inter-observer variability and visual interpretation errors, computer based data mining techniques may be exploited. We have developed and presented one such technique in this paper for the classification of normal and CAD affected cases. A multitude of grayscale features (fractal dimension, entropies based on the higher order spectra, features based on image texture and local binary patterns, and wavelet based features) were extracted from echocardiography images belonging to a huge database of 400 normal cases and 400 CAD patients. Only the features that had good discriminating capability were selected using t-test. Several combinations of the resultant significant features were used to evaluate many supervised classifiers to find the combination that presents a good accuracy. We observed that the Gaussian Mixture Model (GMM) classifier trained with a feature subset made up of nine significant features presented the highest accuracy, sensitivity, specificity, and positive predictive value of 100%. We have also developed a novel, highly discriminative HeartIndex, which is a single number that is calculated from the combination of the features, in order to objectively classify the images from either of the two classes. Such an index allows for an easier implementation of the technique for automated CAD detection in the computers in hospitals and clinics.     

Fischer–Tropsch synthesis: Effect of CO2 containing syngas over Pt promoted Co/γ-Al2O3 and K-promoted Fe catalysts

The effect of CO₂ was studied for cobalt and iron Fischer–Tropsch (FT) synthesis. CO₂ behaves differently in the presence of CO over cobalt and iron catalysts in terms of hydrogenation. A systematic increase of the CO₂ mole fraction of carbon in the feed gas mixture alters the product distribution dramatically for cobalt FT synthesis with CO₂ behaving like an inert gas at higher partial pressure of CO. With cobalt, CO appears to compete with CO₂ for adsorption. Using an iron FT catalyst, hydrogenation of CO₂ was effected due to the presence of the reverse water–gas shift activity of the catalyst which converts CO₂ to hydrocarbons through the formation of CO. Unlike the cobalt catalyst, the product distribution was only slightly altered with increasing CO₂ content in the feed gas mixture to the iron catalyst. This difference in behavior of CO₂ over cobalt and iron could be attributed to the absence of reverse water–gas shift activity on cobalt and hydrogenation of CO₂ to hydrocarbons—other than methane—will be derived through the formation of CO.     

Double‐wall carbon nanotube‐reinforced polyester nanocomposites: Improved dispersion and mechanical properties

Double‐walled carbon nanotube (DWCNT)‐reinforced polyester nanocomposites were prepared and tested to characterize their mechanical properties. The DWCNTs were functionalized to improve their dispersion within the polyester matrix. The improvement in the mechanical properties shows that the functionalized DWCNTs have better distribution within, and good adhesion with, the polyester matrix. A comparison of the mechanical properties of nanocomposites reinforced by functionalized and nonfunctionalized DWCNTs confirms that the functionalization leads to substantially improved composites. POLYM. COMPOS., 2012. © 2012 Society of Plastics Engineers     

2-[(E)-{(1S,2R)-1-Hydroxy-1-phenylpropan-2-ylimino}methyl]phenol for Inhibition of Acid Corrosion of Mild Steel

2-[(E)-{(1S,2R)-1-hydroxy-1-phenylpropan-2-ylimino}methyl]phenol has been synthesized and its influence on corrosion of mild steel in 1?M HCl solution has been studied by means of weight loss and electrochemical measurements under various circumstances. The inhibitor showed a maximum of 91?% of inhibition efficiency at 100?ppm. Interestingly, the inhibition efficiency has decreased on increasing the inhibitor concentration. This abnormal behavior is attributed to the release of phenolic hydrogen from the molecule. The mechanism of corrosion inhibition follows Langmuir adsorption isotherm. The negative ?G _ads indicates the spontaneous adsorption of the inhibitor on mild steel surface. Potentiodynamic polarization studies show that it is a mixed type inhibitor with predominant cathodic inhibition. UV?CVisible spectroscopy of the inhibitor and inhibitor adsorbed on the mild steel confirmed the chemical interaction of the inhibitor with the metal surface.     

Classification analysis of burnout people's brain images using ontology-based speculative sense model

Burnout is a state of exhaustion that results from prolonged, excessive workplace stress. This can be examined with the biological explications of burnout and physical consequences and classified against prolonged vigorous activities. The research aims to classify burnout people's brain images against prolonged emotional activities using ontology analysis of treatment and prevention and intermediate layers formation based on a speculative sense model. In this segment, the Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model is employed for burnout people's classification analysis. The methodology is performed in the platform of ontology creation and performs the classification analysis. The calculation analysis found the result, and the brain images were classified. The classification analysis of burnout people's brain images, separation of prolonged vigorous activities, and the ontology creation for treatment and prevention against burnout people's brain images were obtained. The analysis received the result, and the results of the precision, recall, storage, computation time, specificity, and classification of burnout people's brain images were obtained. Furthermore, all these Ontology analysis of Treatment and prevention and intermediate layers formation based on a hypothetical sense model had the prediction sensitivity (SN) over 50% and specificity (SP) over 90%. The Classification of Burnout People's Brain performance comparison shows that the proposed system is much more successful than existing methods, especially on a scoring accuracy of 98%.