Precipitation In Small Systems--II. Mean Field Equations More Effective Than Population Balance

Part I (Manjunath et al., 1994, Chem. Engng Sci. 49, 1451-1463) of this paper showed that the random particle numbers and size distributions in precipitation processes in very small drops obtained by stochastic simulation techniques deviate substantially from the predictions of conventional population balance. The foregoing problem is considered in this paper in terms of a mean field approximation obtained by applying a first-order closure to an unclosed set of mean field equations presented in Part I. The mean field approximation consists of two mutually coupled partial differential equations featuring (i) the probability distribution for residual supersaturation and (ii) the mean number density of particles for each size and supersaturation from which all average properties and fluctuations can be calculated. The mean field equations have been solved by finite difference methods for (i) crystallization and (ii) precipitation of a metal hydroxide both occurring in a single drop of specified initial supersaturation. The results for the average number of particles, average residual supersaturation, the average size distribution, and fluctuations about the average values have been compared with those obtained by stochastic simulation techniques and by population balance. This comparison shows that the mean field predictions are substantially superior to those of population balance as judged by the close proximity of results from the former to those from stochastic simulations. The agreement is excellent for broad initial supersaturations at short times but deteriorates progressively at larger times. For steep initial supersaturation distributions, predictions of the mean field theory are not satisfactory thus calling for higher-order approximations. The merit of the mean field approximation over stochastic simulation lies in its potential to reduce expensive computation times involved in simulation. More effective computational techniques could not only enhance this advantage of the mean field approximation but also make it possible to use higher-order approximations eliminating the constraints under which the stochastic dynamics of the process can be predicted accurately.

Defect-selective photothermal imaging: a sensitive tool for damage mapping in optical coatings

A defect-selective photothermal imaging system for the diagnostics of optical coatings is demonstrated. The instrument has been optimized for pump and probe parameters, detector performance, and signal processing algorithm. The imager is capable of mapping purely optical or thermal defects efficiently in coatings of low damage threshold and low absorbance. Detailed mapping of minor inhomogeneities at low pump power has been achieved through the simultaneous action of a low-noise fiber optic photothermal beam defection sensor and a common-mode-rejection demodulation (CMRD) technique. The linearity and sensitivity of the sensor have been examined theoretically and experimentally, and the signal to noise ratio improvement factor is found to be about 110 compared to a conventional bicell photodiode. The scanner is so designed that mapping of static or shock sensitive samples is possible. In the case of a sample with absolute absorptance of 3.8 x 10(-4), a change in absorptance of about 0.005 x 10(-4) has been detected without ambiguity, ensuring a contrast parameter of 760. This is about 1085% improvement over the conventional approach containing a bicell photodiode, at the same pump power. The merits of the system have been demonstrated by mapping two intentionally created damage sites in a MgF2 coating on fused silica at different excitation powers. Amplitude and phase maps were recorded for thermally thin and thick cases, and the results are compared to demonstrate a case which, in conventional imaging, would lead to a deceptive conclusion regarding the type and location of the damage. Also, a residual damage profile created by long term irradiation with high pump power density has been depicted.

Magnetization, magnetotransport and electron magnetic resonance studies of nanoparticles and nanowires of Pr0.5Sr0.5MnO3

In this paper, we present the preparation and characterization of nanoparticles and nanowires of Pr0.5Sr0.5MnO3 (PSMO). The main results of this investigation are as follows: (a) a comparison with the properties of the bulk material shows that the ferromagnetic (FM) transition at 270 K remains unaffected but the anti-ferromagnetic (AFM) transition at TN = 150 K disappears in the nanoparticles, (b) the size induced ground state magnetic phase (below 150 K) is predominantly FM, coexisting with a residual AFM phase, and (c) the temperature dependence of magnetic anisotropy shows complex behaviour, being higher in the nanoparticles at high temperatures and lower at moderately lower temperatures in comparison with the bulk. The results obtained from the extensive magnetization, magnetotransport and electron magnetic resonance studies made on various samples are presented and discussed in detail.

Influence of surface stress on elastic constants of nanohoneycombs

Surface effect on the four independent elastic constants of nanohoneycombs is investigated in this paper. The axial deformation of the horizontal cell wall is included, comparing to the Gibson's method, and the contributions of the two components of surface stress (i.e. surface residual stress and surface elasticity) are discussed. The result shows that the regular hexagonal honeycomb is not isotropic but orthotropic. An increase in the cell-wall thickness t leads to an increase in the discrepancy of the Young's moduli in both directions. Furthermore, the surface residual stress dominates the surface effect on the elastic constants when t < 15 nm (or the relative density <0.17), which is in contrast to that the surface elasticity does when t > 15 nm (or the relative density > 0.17) for metal Al. The present structure and theory may be useful in the design of future nanodevices.

Realizing the 'hindered charge ordered phase' in nanoscale charge ordered manganites: magnetization, magneto-transport and EPR investigations

We report three prominent observations made on the nanoscale charge ordered ( CO) manganites RE(1-x)AE(x)MnO(3) (RE = Nd, Pr; AE = Ca; x = 0.5) probed by temperature dependent magnetization and magneto-transport, coupled with electron magnetic/paramagnetic resonance spectroscopy (EMR/EPR). First, evidence is presented to show that the predominant ground state magnetic phase in nanoscale CO manganites is ferromagnetic and it coexists with a residual anti-ferromagnetic phase. Secondly, the shallow minimum in the temperature dependence of the EPR linewidth shows the presence of a charge ordered phase in nanoscale manganites which was shown to be absent from the DC static magnetization and transport measurements. Thirdly, the EPR linewidth, reflective of spin dynamics, increases significantly with a decrease of particle size in CO manganites. We discuss the interesting observations made on various samples of different particle sizes and give possible explanations. We have shown that EMR spectroscopy is a highly useful technique to probe the 'hindered charge ordered phase' in nanoscale CO manganites, which is not possible by static DC magnetization and transport measurements.

Codoping Effect of Zn and Pr in YBa2Cu3O7-delta

In this paper we present the resistivity data for Pr and Zn codoped compound Y1-xPrxBa2[Cu1-yZny](3)O7-delta with 0 < y < 0.1 and x = 0.0, 0.1 and 0.2. The data is analysed in terms of the superconducting critical temperature T-c, residual resistivity rho(0) and the resistivity slope d rho/dT corresponding to the linear rho-T region. It is found that for x = 0.1 Pr has a minimal influence on the in-plane processes for Zn impurity alone affecting slightly T-c and rho(0). The slope dp/dT becomes larger for 0.03 < y < 0.06 leading to larger depining effect and hence slower fall of T, as a function of y. For x = 0.2 there is a drastic change, rho(0) becomes abnormally large, d rho/dT becomes negative implying absence of depinning and a totally pinned charge stripes. Superconductivity vanishes at y = 0.03. It is concluded that for x = 0.2 Pr converts the system from overdoped to underdoped region leading to the universal superconductor-insulator transition.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Smooth bootstrap methods for analysis of longitudinal data

In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the 'sandwich' method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain 'bootstrapped' realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.

Reduced complexity two stage vector quantization

We address the issue of complexity for vector quantization (VQ) of wide-band speech LSF (line spectrum frequency) parameters. The recently proposed switched split VQ (SSVQ) method provides better rate-distortion (R/D) performance than the traditional split VQ (SVQ) method, even at the requirement of lower computational complexity. but at the expense of much higher memory. We develop the two stage SVQ (TsSVQ) method, by which we gain both the memory and computational advantages and still retain good R/D performance. The proposed TsSVQ method uses a full dimensional quantizer in its first stage for exploiting all the higher dimensional coding advantages and then, uses an SVQ method for quantizing the residual vector in the second stage so as to reduce the complexity. We also develop a transform domain residual coding method in this two stage architecture such that it further reduces the computational complexity. To design an effective residual codebook in the second stage, variance normalization of Voronoi regions is carried out which leads to the design of two new methods, referred to as normalized two stage SVQ (NTsSVQ) and normalized two stage transform domain SVQ (NTsTrSVQ). These two new methods have complimentary strengths and hence, they are combined in a switched VQ mode which leads to the further improvement in R/D performance, but retaining the low complexity requirement. We evaluate the performances of new methods for wide-band speech LSF parameter quantization and show their advantages over established SVQ and SSVQ methods.

Enzymatic activity other than lipase

In this chapter, enzymes (other than lipase) which are present in cream are discussed. The effects of heat treatments on the activities of these enzymes are described. The influence of residual enzyme activiv, remaining after heating, on cream quality is also discussed.

Calciothermic reduction of TiO2: A diagrammatic assessment of the thermodynamic limit of deoxidation

Calciothermic reduction of TiO2 provides a potentially low-cost route to titanium production. Presented in this article is a suitably designed diagram, useful for assessing the degree of reduction of TiO2 and residual oxygen contamination in metal as a function of reduction temperature and other process parameters. The oxygen chemical potential diagram à la Ellingham-Richardson-Jeffes is useful for visualization of the thermodynamics of reduction reactions at high temperatures. Although traditionally the diagram depicts oxygen potentials corresponding to the oxidation of different metals to their corresponding oxides or of lower oxides to higher oxides, oxygen potentials associated with solution phases at constant composition can be readily superimposed. The usefulness of the diagram for an insightful analysis of calciothermic reduction, either direct or through an electrochemical process, is discussed. Identified are possible process variations, modeling and optimization strategies.

Low-density koala (Phascolarctos cinereus) populations in the mulgalands of south-west Queensland. II. Distribution and diet

This study used faecal pellets to investigate the broadscale distribution and diet of koalas in the mulgalands biogeographic region of south-west Queensland. Koala distribution was determined by conducting faecal pellet searches within a 30-cm radius of the base of eucalypts on 149 belt transects, located using a multi-scaled stratified sampling design. Cuticular analysis of pellets collected ffom 22 of these sites was conducted to identify the dietary composition of koalas within the region. Our data suggest that koala distribution is concentrated in the northern and more easterly regions of the study area, and appears to be strongly linked with annual rainfall. Over 50% of our koala records were obtained from non-riverine communities, indicating that koalas in the study area are not primarily restricted to riverine communities, as bas frequently been suggested. Cuticular analysis indicates that more than 90% of koala diet within the region consists of five eucalypt species. Our data highlights the importance of residual Tertiary landforms to koala conservation in the region.

Low-density koala (Phascolarctos cinereus) populations in the mulgalands of south-west Queensland. IV. Abundance and conservation status

Urban encroachment on dense, coastal koala populations has ensured that their management has received increasing government and public attention. The recently developed National Koala Conservation Strategy calls for maintenance of viable populations in the wild. Yet the success of this, and other, conservation initiatives is hampered by lack of reliable and generally accepted national and regional population estimates. In this paper we address this problem in a potentially large, but poorly studied, regional population in the State that is likely to have the largest wild populations. We draw on findings from previous reports in this series and apply the faecal standing-crop method (FSCM) to derive a regional estimate of more than 59 000 individuals. Validation trials in riverine communities showed that estimates of animal density obtained from the FSCM and direct observation were in close agreement. Bootstrapping and Monte Carlo simulations were used to obtain variance estimates for our population estimates in different vegetation associations across the region. The most favoured habitat was riverine vegetation, which covered only 0.9% of the region but supported 45% of the koalas. We also estimated that between 1969 and 1995 -30% of the native vegetation associations that are considered as potential koala habitat were cleared, leading to a decline of perhaps 10% in koala numbers. Management of this large regional population has significant implications for the national conservation of the species: the continued viability of this population is critically dependent on the retention and management of riverine and residual vegetation communities, and future vegetation-management guidelines should be cognisant of the potential impacts of clearing even small areas of critical habitat. We also highlight eight management implications.

Phosphorus concentrations in the leaves of cotton in tropical Australia are determined by temperature.

Previous research on P leaf analysis for detecting deficiencies in cotton (Gossypium hirsutum L.) has not considered temperature as a determining factor. This is despite correlations between leaf P content and temperature being observed in other crops. As part of research into a new cotton farming system for the semi-arid tropics of Australia, we conducted two P fertiliser rate experiments on recently cleared un-cropped (bicarbonate P < 5 mg kg- 1) and previously cropped (bicarbonate P 26 mg kg- 1) soil. They aimed to develop P requirements and more importantly to determine if temperature affects the leaf P concentrations used to diagnose P deficiencies. In 2002, optimal yield on un-cropped, low P soil was achieved with a 60 kg P ha- 1 rate. In 2003, residual P from the 40 kg P ha- 1 treatment produced optimal yield. On cropped, high P soil there was no yield response to treatments up to 100 kg P ha- 1. On low P soil, a positive correlation was observed between P concentration in the youngest fully-unfurled leaf (YFUL), fertiliser rate, and mean diurnal temperature in the seven days prior to sampling. On high P soil, a positive correlation was observed between the YFUL and mean diurnal temperature however there was no correlation with fertiliser rate. These results show that YFUL analysis can be used to diagnose P deficiencies in cotton, provided the temperature prior to sampling is considered.

CBCT image guidance in head and neck irradiation: The impact of daily and weekly imaging protocols

Purpose This study evaluated the impact of a daily and weekly image-guided radiotherapy protocols in reducing setup errors and setting of appropriate margins in head and neck cancer patients. Materials and methods Interfraction and systematic shifts for the hypothetical day 1–3 plus weekly imaging were extrapolated from daily imaging data from 31 patients (964 cone beam computed tomography (CBCT) scans). In addition, residual setup errors were calculated by taking the average shifts in each direction for each patient based on the first three shifts and were presumed to represent systematic setup error. The clinical target volume (CTV) to planning target volume (PTV) margins were calculated using van Herk formula and analysed for each protocol. Results The mean interfraction shifts for daily imaging were 0·8, 0·3 and 0·5 mm in the S-I (superior-inferior), L-R (left-right) and A-P (anterior-posterior) direction, respectively. On the other hand the mean shifts for day 1–3 plus weekly imaging were 0·9, 1·8 and 0·5 mm in the S-I, L-R and A-P direction, respectively. The mean day 1–3 residual shifts were 1·5, 2·1 and 0·7 mm in the S-I, L-R and A-P direction, respectively. No significant difference was found in the mean setup error for the daily and hypothetical day 1–3 plus weekly protocol. However, the calculated CTV to PTV margins for the daily interfraction imaging data were 1·6, 3·8 and 1·4 mm in the S-I, L-R and A-P directions, respectively. Hypothetical day 1–3 plus weekly resulted in CTV–PTV margins of 5, 4·2 and 5 mm in the S-I, L-R and A-P direction. Conclusions The results of this study show that a daily CBCT protocol reduces setup errors and allows setup margin reduction in head and neck radiotherapy compared to a weekly imaging protocol.