Dielectric studies of molecular and intramolecular motions in polystryrene matrices

Dielectric absorption studies of a variety of polar solutes containing rotatable groups and of some analogous rigid molecules dispersed in atactic polystyrene have been carried out. Preparation of the solutions as solid disks, and the dielectric measurements using a General Radio 1615-A capacitance bridge and a Hewlett-Packard Q-meter with appropriate temperature-controllable cells have been described. The experimental data as a function of frequency at different temperatures were subjected to analysis by a series of computer programmes written in the API language. The activation energy barriers opposing the dielectric relaxation processes were obtained by the application of the Eyring rate equation. Different types of polar rigid molecules have been studied mainly to provide sources of relaxation data and activation parameters for comparisons with those of flexible molecules of analogous size. Attempts have also been made to correlate the activation parameters with size, shape, and rotating volume of the rigid molecules. Studies of some nitrogen-containing heterocyclic rigid molecules and the comparison of their Eyring analysis results with those of the analogous non-heterocycles showed no significant molecular interaction with the polymer matrix. Of the flexible molecules, a wide variety of compounds containing the carbonyl group have been studied. Intramolecular processes involving the rotation of the polar carbonyl group with one or more segments from the alkyl substituents have been observed for phenyl alkyl (aryl-alkyl) and dialkyl ketones. Significantly higher energy barriers to acetyl group rotation around the C — N bond have been found in N-acetylimidazole in which the N atom is involved in ring conjugation. However, this barrier appeared to have been reduced considerably due to the effect of saturation as in N-acetyl-4-piperidone..

Interaction of palmitic acid with losartan potassium at the binding sites of bovine serum albumin

The binding of losartan potassium, an angiotensin II receptor antagonist, to bovine serum albumin was studied by equilibrium dialysis method (ED) in presence or absence of palmitic acid. The study was carried out using ranitidine and diazepam as site-1 and site-2 specific probe, respectively. Different analysis of binding of losartan to bovine serum albumin suggested two sets of association constants: high affinity association constant (k1 = 11.2 x 105 M-1) with low capacity (n1 = 2) and low affinity association (k2 = 2. 63 x 105 M-1) constant with high capacity (n2 = 10) at pH 7.4 and 27°C. During concurrent administration of palmitic acid and losartan potassium in presence or absence of ranitidine or diazepam, it was that found that palmitic acid causes the release of losartan potassium from its binding site on BSA resulting reduced binding of losartan potassium to BSA. The increment in free fraction of losartan potassium was from 13.1% to 47.2 % upon the addition of increased concentration of only palmitic acid at a concentration of 0 x 10-5 M to 16 x 10-5 M. In presence of ranitidine or diazepam as site specific probes, palmitic acid further increases the free fraction of losartan potassium were from 22.8% to 53.4% and 35.3 to 65.5%, respectively. This data provided the evidence of interaction of higher concentration of palmitic acid at the binding sites on BSA changing the pharmacokinetics properties of losartan potassium

PERFORMANCE OF YIELD AND YIELD CONTRIBUTING CHARACTERISTICS OF BC2F3 POPULATION WITH ADDITION OF BLAST RESISTANT GENE

ABSTRACTThe study was carried out in the University Putra Malaysia (UPM) Rice Research Centre to evaluate the yield performance of newly developed selected blast resistant plants of BC2F3 generations derived from a cross between MR263, a high yielding rice variety but blast susceptible and Pongsu Seribu 1, donor with blast resistant (Pi-7(t)and Pi-d (t)1, Pir2-3(t)genes and qLN2 QTL), Malaysian local variety. On the basis of assessed traits, the plants 12, 6, 7, 5, 21, 22, 5, 26, 11, 8, 10, 13 and 15 had the higher yield, blast resistant and good morphological traits. More than 70% heritability was found in days to maturity, plant height, tiller numbers per hill, and panicle per hill, 80% heritability was found in filled grain and yield per hill and more than 90% heritability was found in grain length, grain width and seed weight. Cluster analysis based on the traits grouped 30 plants along with MR263 into seven clusters. According to PCA, the first four principal components account for about 69.3% total variation for all measured traits and exhibited high correlation among the characteristics analyzed

Tactile sensor based intelligent grasping system

Mazid, AM ORCiD: 0000-0003-0854-7652This paper offers the design and prototype technology of a tactile sensor, based on the principle of surface texture recognition, capable of monitoring slip in robotic grasping. The sensor has been mounted onto a parallel gripper jaw of a robot. The integrated system of tactile sensor, gripper, robot and the system control, in real life experiments, has proven itself capable of slip detection and adjusting adequate grasping force preventing objects from falling down. Several experiments have been carried out with the newly developed system for grasping a number of various object-samples. Success rate of the system for testing in slip detection and adjusting adequate grasping force in experiments was about 85% in average

Grasping Force Estimation Recognizing Object Slippage by Tactile Data Using Neural Network

Abstract -Hierarchical and wider applications of robots, manipulators, and pick and place machines are facing challenges in industrial environments due to their insufficient intelligence for appropriately recognizing objects for grasping and handling purposes. Since robots do not posses self-consciousness, estimation of adequate grasping force for individual objects by robots or manipulators is another challenge for wider applications of robots and manipulators. This article suggests a mathematical model, recently developed, for computation of scattered energy of vibrations sensed by the stylus during an object slippage in robot grippers. The model includes in it dynamic parameters like trial grasping force, object falling velocity, and geometry of object surface irregularities. It is envisaged that using the said mathematical model, with the help of robust decision making capabilities of artificial neural network (NN), a robot memory could be able to estimate appropriate/optimal grasping force for an object considering its physiomechanical properties. On the basis of above mentioned mathematical model, this article demonstrates an experimental methodology of estimating adequate grasping forces of an object by robot grippers using Backpropagation (BP) neural networks. Four different algorithms have been explored to experiment the optimal grasping force estimation

Grasping force estimation recognizing object slippage by tactile data using neural network

Abstract - Hierarchical and wider applications of robots, manipulators, and pick and place machines are facing challenges in industrial environments due to their insufficient intelligence for appropriately recognizing objects for grasping and handling purposes. Since robots do not posses self-consciousness, estimation of adequate grasping force for individual objects by robots or manipulators is another challenge for wider applications of robots and manipulators. This article suggests a mathematical model, recently developed, for computation of scattered energy of vibrations sensed by the stylus during an object slippage in robot grippers. The model includes in it dynamic parameters like trial grasping force, object falling velocity, and geometry of object surface irregularities. It is envisaged that using the said mathematical model, with the help of robust decision making capabilities of artificial neural network (NN), a robot memory could be able to estimate appropriate/optimal grasping force for an object considering its physiomechanical properties. On the basis of above mentioned mathematical model, this article demonstrates an experimental methodology of estimating adequate grasping forces of an object by robot grippers using Backpropagation (BP) neural networks. Four different algorithms have been explored to experiment the optimal grasping force estimation

Opto-tactile sensor for surface texture pattern identification using support vector machine

Experimental application of a recently developed opto-tactile sensor in object surface texture pattern recognition using soft computational techniques has been successfully demonstrated in this article. Design and working principles of a number of optical type sensors have been illustrated and explained. Using the opto-tactile sensor multiple surface texture patterns of a number of objects like a carpet, stone, rough sheet metal, paper carton and a table surface have been captured and saved in MATLAB environment. The captured data have been adopted to soft computational techniques like Support Vector Machine (SVM) technique, Decision Tree (DT) C4.5 algorithm, and Naive Bayes (NB) algorithm for their learning. Testing with unknown surfaces using these techniques shows promising results at this stage and demonstrates its potential industrial use with further development. Results suggest that the methodology and procedures presented here are well suited for applications in intelligent robotic grasping