Roche tomography of cataclysmic variables - V. A high-latitude star-spot on RU Pegasi

We present Roche tomograms of the secondary star in the dwarf nova system RU Pegasi derived from blue and red arm ISIS data taken on the 4.2-m William Herschel Telescope. We have applied the entropy landscape technique to determine the system parameters and obtained component masses of M1 = 1.06 Msun, M2 = 0.96 Msun, an orbital inclination angle of i = 43 degrees, and an optimal systemic velocity of gamma = 7 km/s. These are in good agreement with previously published values. Our Roche tomograms of the secondary star show prominent irradiation of the inner Lagrangian point due to illumination by the disc and/or bright spot, which may have been enhanced as RU Peg was in outburst at the time of our observations.We find that this irradiation pattern is axi-symmetric and confined to regions of the star which have a direct view of the accretion regions. This is in contrast to previous attempts to map RU Peg which suggested that the irradiation pattern was non-symmetric and extended beyond the terminator. We also detect additional inhomogeneities in the surface distribution of stellar atomic absorption that we ascribe to the presence of a large star-spot. This spot is centred at a latitude of about 82 degrees and covers approximately 4 per cent of the total surface area of the secondary. In keeping with the high latitude spots mapped on the cataclysmic variables AE Aqr and BV Cen, the spot on RU Peg also appears slightly shifted towards the trailing hemisphere of the star. Finally, we speculate that early mapping attempts which indicated non-symmetric irradiation patterns which extended beyond the terminator of CV donors could possibly be explained by a superposition of symmetric heating and a large spot.

Contribution of process variables to the entrapment efficiency of propranolol hydrochloride within ethylcellulose microspheres prepared by the solvent evaporation method as evaluated using a factorial design

The effects of the process variables, pH of aqueous phase, rate of addition of organic, polymeric, drug-containing phase to aqueous phase, organic:aqueous phase volume ratio and aqueous phase temperature on the entrapment of propranolol hydrochloride in ethylcellulose (N4) microspheres prepared by the solvent evaporation method were examined using a factorial design. The observed range of drug entrapment was 1.43 +/- 0.02%w/w (pH 6, 25 degrees C, phase volume ratio 1:10, fast rate of addition) to 16.63 +/- 0.92%w/w (pH 9, 33 degrees C, phase volume ratio 1:10, slow rate of addition) which corresponded to mean entrapment efficiencies of 2.86 and 33.26, respectively. Increased pH, increased temperature and decreased rate of addition significantly enhanced entrapment efficiency. However, organic:aqueous phase volume ratio did not significantly affect drug entrapment. Statistical interactions were observed between pH and rate of addition, pH and temperature, and temperature and rate of addition. The observed interactions involving pH are suggested to be due to the abilities of increased temperature and slow rate of addition to sufficiently enhance the solubility of dichloromethane in the aqueous phase, which at pH 9, but not pH 6, allows partial polymer precipitation prior to drug partitioning into the aqueous phase. The interaction between temperature and rate of addition is due to the relative lack of effect of increased temperature on drug entrapment following slow rate of addition of the organic phase. In comparison to the effects of pH on drug entrapment, the contributions of the other physical factors examined were limited.

AN INVESTIGATION OF THE EFFECTS OF SOME PROCESS VARIABLES ON THE MICROENCAPSULATION OF PROPRANOLOL HYDROCHLORIDE BY THE SOLVENT EVAPORATION METHOD

The effects of four process factors: pH, emulsifier (gelatin) concentration, mixing and batch, on the % w/w entrapment of propranolol hydrochloride in ethylcellulose microcapsules prepared by the solvent evaporation process were examined using a factorial design. In this design the minimum % w/w entrapments of propranolol hydrochloride were observed whenever the external aqueous phase contained 1.5% w/v gelatin at pH 6.0 (0.71-0.91% w/w) whereas maximum entrapments occurred whenever the external aqueous phase was composed of 0.5% w/v gelatin at pH 9.0,(8.9-9.1% w/w). The theoretical maximum loading was 50% w/w. Statistical evaluation of the results by analysis of variance showed that emulsifer (gelatin) concentration and pH, but not mixing and batch significantly affected entrapment. An interaction between pH and gelatin concentration was observed in the factorial design which was accredited to the greater effect of gelatin concentration on % w/w entrapment at pH 9.0 than at pH 6.0. Maximum theoretical entrapment was achieved by increasing the pH of the external phase to 12.0. Marked increases in drug entrapment were observed whenever the pH of the external phase exceeded the pK(2) of propranolol hydrochloride. It was concluded that pH, and hence ionisation, was the greatest determinant of entrapment of propranolol hydrochloride into microcapsules prepared by the solvent evaporation process.

Design optimization of cold-formed steel portal frames taking into account the effect of building topology

Cold-formed steel portal frames are a popular form of construction for low-rise commercial, light industrial and agricultural buildings with spans of up to 20 m. In this article, a real-coded genetic algorithm is described that is used to minimize the cost of the main frame of such buildings. The key decision variables considered in this proposed algorithm consist of both the spacing and pitch of the frame as continuous variables, as well as the discrete section sizes.A routine taking the structural analysis and frame design for cold-formed steel sections is embedded into a genetic algorithm. The results show that the real-coded genetic algorithm handles effectively the mixture of design variables, with high robustness and consistency in achieving the optimum solution. All wind load combinations according to Australian code are considered in this research. Results for frames with knee braces are also included, for which the optimization achieved even larger savings in cost.

An investigation of the influence of process and formulation variables on mechanical properties of high shear granules using design of experiment

Being able to predict the properties of granules from the knowledge of the process and formulation variables is what most industries are striving for. This research uses experimental design to investigate the effect of process variables and formulation variables on mechanical properties of pharmaceutical granules manufactured from a classical blend of lactose and starch using hydroxypropyl cellulose (HPC) as the binder. The process parameters investigated were granulation time and impeller speed whilst the formulation variables were starch-to-lactose ratio and HPC concentration. The granule properties investigated include granule packing coefficient and granule strength. The effect of some components of the formulation on mechanical properties would also depend on the process variables used in granulation process. This implies that by subjecting the same formulation to different process conditions results in products with different properties. © 2012 Elsevier B.V. All rights reserved.

The Conditional Phase-type distribution: Graphical Models for Continuous Non-Normal Data:The Conditional Phase-type (C-Ph) distribution:

Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.

Are richness patterns of common and rare species equally well explained by environmental variables?

We investigated relationships between richness patterns of rare and common grassland species and environmental factors, focussing on comparing the degree to which the richness patterns of rare and common species are determined by simple environmental variables. Using data collected in the Machair grassland of the Outer Hebrides of Scotland, we fitted spatial regression models using a suite of grazing, soil physicochemical and microtopographic covariates, to nested sub-assemblages of vascular and non-vascular species ranked according to rarity. As expected, we found that common species drive richness patterns, but rare vascular species had significantly stronger affinity for high richness areas. After correcting for the prevalence of individual species distributions, we found differences between common and rare species in 1) the amount of variation explained: richness patterns of common species were better summarised by simple environmental variables, 2) the associations of environmental variables with richness showed systematic trends between common and rare species with coefficient sign reversal for several factors, and 3) richness associations with rare environments: richness patterns of rare vascular species significantly matched rare environments but those of non-vascular species did not. Richness patterns of rare species, at least in this system, may be intrinsically less predictable than those of common species.