Dissolution Rates of Commercial Phenylbutazone Tablets: Inter-And Intra-Brand Effects

A study has been carried out to investigate the dissolution rate profiles of twelve batches of sugar-coated phenylbutazone tablets belonging to four commercial brands. Using the rotating basket method, significant inter-brand and inter-batch variations in dissolution rates were found. Only two batches of one brand passed the B.P. dissolution limit whilst other batches had percentages dissolution between 0.3 and 58 after 45 min. Batches with poor dissolution characteristics exhibited significant tablet-to-tablet variations in dissolution rates; a finding which was not observed in the relatively fast-dissolving batches. When the paddle method was substituted for the B.P. basket method, the dissolution rates were relatively faster but similar dissolution failure was found. However, the tablet-to-tablet dissolution variability was decreased in some of the batches. The observed differences in dissolution rates of the batches examined were unrelated to their disintegration times. Inspite of the poor dissolution characteristics of most of the batches studied, no apparent chemical degradation was found. It is recommended that when evaluating the dissolution rates of brands of phenylbutazone tablets, a number of batches from each brand should be tested.     

Fractionation of Bolti fish tissue lipids into classes and within the triglyceride class with TLC

By utilising TLC with a developing system of petroleum ether-diethylether-acetic acid (70:30:2 v/v) and allowing the front to travel 18 cm, the best conditions for the fractionation of Bolti tissue lipids were achieved. Four distinct classes—triglycerides, free fatty acids, sterols and phospholipids—were detected. In addition, two other faint classes—hydrocarbons and diglycerides—were identified.Silica gel impregnated with silver nitrate has been employed for the fractionation of the triglycerides into groups. Seven groups were found when 1·5% of ethanol was added to the developing system of chloroform-acetic acid (99·5:0·5 v/v). Raising the ethanol content to 2% resulted in the detection of eight groups.     

Application of Response Surface Methodology to the Selection of Machining Variables

This paper presents the use of Response Surface Methodology for analysis of material removal processes. Mathematical models of tool life, surface finish and cutting force are developed in terms of cutting speed, feed, and depth of cut. The models were then used to select the levels of the machining variables such that certain criteria could be achieved. Specific examples include increasing the rate of metal removal without sacrificing surface finish and with a minimum loss in tool life.     

HYDROMAGNETIC NATURAL CONVECTION FROM AN INCLINED POROUS SQUARE ENCLOSURE WITH HEAT GENERATION

The problem of unsteady, laminar, two-dimensional hydromagnetic natural convection heat transfer in an inclined square enclosure filled with a fluid-saturated porous medium in the presence of a transverse magnetic field and fluid heat generation effects is studied numerically. The walls of the enclosure are maintained at constant temperatures. The flow in the porous region is modeled using the Brinkman-extended Darcy's law to account for the no-slip conditions at the walls. The control volume method is used to solve the governing balance equations for different values of the Darcy number, Hartmann number, and the inclination angle. Favorable comparisons with previously published work are performed. These comparisons confirmed the correctness of the numerical results. The obtained numerical results are presented graphically in terms of streamlines and isotherms as well as velocity and temperature profiles at midsections of the cavity to illustrate interesting features of the solution.     

Impregnated active layer combustion synthesis of nano MgFe2O4 using green template

Nano-Magnesium ferrite (MgFe₂O₄) powders have been prepared by a modified combustion synthesis method named impregnated active layer combustion (IALC). The effects of five important parameters such as main fuel to oxidizer ratio (F/O), main fuel type, added fuel type, template type and main fuel (Added F/MF) to the added fuel ratio have been studied using Taguchi design. Xylitol, D-mannitol, ethylene diamine tetra acetic acid (EDTA) and diethylene triamine penta acetic acid (DTPA) were used as fuels. Besides, waste newspaper and Platanus orientalis leaf (POL) were used as new green templates. Samples were characterized by XRD, XRF, SEM, TEM, BET and VSM analyses. Results showed that the average crystallite size of the sample prepared under optimized condition (mixture of Xylitol and DTPA as fuel, POL as template, and Added F/MF ratio of 0.75) was 17.66?nm. The result was confirmed by TEM. The saturated magnetization of the optimum sample was 21?emu/g and the specific surface area was 15.377?m²/g.     

A computer-based goal-oriented productivity index

This paper presents a Weighted Multi-Factor Productivity Index. This index monitors the performance of an organization and identifies productivity problems. Key resource factors are defined and a weighting technique, with both subjective and objective attributes, is presented. This productivity index is dynamic and responsive to the changing needs of an organization and is a goal oriented measuring tool.     

THE EFFECTS OF STRESS RATIO, COMPRESSIVE PEAK STRESS AND MAXIMUM STRESS LEVEL ON FATIGUE BEHAVIOUR OF 2024-T3 ALUMINIUM ALLOY

Abstract— Fatigue crack growth behaviour of 2024-T3 aluminium alloy is investigated as a function of stress ratio, compressive peak stress and maximum stress level. It is found that as the stress ratio and the magnitude of the compressive peak stress are increased, the threshold stress intensity range decreased linearly. Intermediate and near threshold growth rate data are analysed with different formulae for effective stress intensity range. The data covered different values of stress ratio, compressive peak stress and maximum stress level. A formula for the crack opening stress level is introduced as a function of stress ratio, compressive peak stress and maximum stress level. The formula permitted a good correlation between crack growth data for both positive stress ratio and negative compressive peak stress values. Using the new formula, intermediate and near threshold crack growth data for the 2024-T3 aluminium alloy yielded a unique crack growth rate vs effective stress intensity range curve for all stress ratio and compressive peak stress values investigated. This suggests that for the 2024-T3 aluminium alloy the crack growth rate vs effective stress intensity range curve does not depend on stress ratio, compressive peak stress, or maximum stress level. The significance of the new equation and the crack growth rate versus effective stress intensity range curve is that they allow a designer to find crack growth rate vs stress intensity range data for the 2024-T3 aluminium alloy in both intermediate and near threshold regions for the particular stress ratio, compressive peak stress and maximum stress level conditions of the component under investigation.     

A novel composite model approach to improve software quality prediction

Context:How can quality of software systems be predicted before deployment? In attempting to answer this question, prediction models are advocated in several studies. The performance of such models drops dramatically, with very low accuracy, when they are used in new software development environments or in new circumstances.ObjectiveThe main objective of this work is to circumvent the model generalizability problem. We propose a new approach that substitutes traditional ways of building prediction models which use historical data and machine learning techniques.MethodIn this paper, existing models are decision trees built to predict module fault-proneness within the NASA Critical Mission Software. A genetic algorithm is developed to combine and adapt expertise extracted from existing models in order to derive a “composite” model that performs accurately in a given context of software development. Experimental evaluation of the approach is carried out in three different software development circumstances.ResultsThe results show that derived prediction models work more accurately not only for a particular state of a software organization but also for evolving and modified ones.ConclusionOur approach is considered suitable for software data nature and at the same time superior to model selection and data combination approaches. It is then concluded that learning from existing software models (i.e., software expertise) has two immediate advantages; circumventing model generalizability and alleviating the lack of data in software-engineering.