Fouling of tubular ceramic membranes during processing of cane sugar juice

This paper examines the fouling characteristics of four tubular ceramic membranes with pore sizes 300 kDa, 0.1 μm and 0.45 μm installed in a pilot plant at a sugar factory for processing clarified cane sugar juices. All the membranes, except the one with a pore size of 0.45 μm, generally gave reproducible results through the trials, were easy to clean and could handle operation at high volumetric concentration factors. Analysis of fouled and cleaned ceramic membranes revealed that polysaccharides, lipids and to a lesser extent, polyphenols, as well as other colloidal particles cause fouling of the membranes. Electrostatic and hydrophobic forces cause strong aggregation of the polymeric components with one another and with colloidal particles. To combat irreversible fouling of the membranes, treatment options that result in the removal of particles having a size range of 0.2–0.5 μm and in addition remove polymeric impurities, need to be identified. Chemical and microscopic evaluations of the juices and the structural characterisation of individual particles and aggregates identified options to mitigate the fouling of membranes. These include conditioning the feed prior to membrane filtration to break up the network structure formed between the polymers and particles in the feed and the use of surfactants to prevent the aggregation of polymers and particles.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Comparison of human alveolar osteoblasts cultured on polymer-ceramic composite scaffolds and tissue culture plates

The effects of medical grade polycaprolactone–tricalcium phosphate (mPCL–TCP) (80:20) scaffolds on primary human alveolar osteoblasts (AOs) were compared with standard tissue-culture plates. Of the seeded AOs, 70% adhered to and proliferated on the scaffold surface and within open and interconnected pores; they formed multi-layered sheets and collagen fibers with uniform distribution within 28 days. Elevation of alkaline phosphatase activity occurred in scaffold–cell constructs independent of osteogenic induction. AO proliferation rate increased and significant decrease in calcium concentration of the medium for both scaffolds and plates under induction conditions were seen. mPCL–TCP scaffolds significantly influenced the AO expression pattern of osterix and osteocalcin (OCN). Osteogenic induction down-regulated OCN at both RNA and protein level on scaffolds (3D) by day 7, and up-regulated OCN in cell-culture plates (2D) by day 14, but OCN levels on scaffolds were higher than on cell-culture plates. Immunocytochemical signals for type I collagen, osteopontin and osteocalcin were detected at the outer parts of scaffold–cell constructs. More mineral nodules were found in induced than in non-induced constructs. Only induced 2D cultures showed nodule formation. mPCL–TCP scaffolds appear to stimulate osteogenesis in vitro by activating a cellular response in AO's to form mineralized tissue. There is a fundamental difference between culturing AOs on 2D and 3D environments that should be considered when studying osteogenesis in vitro.

Toothless tiger, sleeping dragon : implied freedoms, internet filters and the growing culture of internet censorship in Australia

The internet by its very nature challenges an individual’s notions of propriety, moral acuity and social correctness. A tension will always exist between the censorship of obscene and sensitive information and the freedom to publish and/or access such information. Freedom of expression and communication on the internet is not a static concept: ‘Its continual regeneration is the product of particular combinations of political, legal, cultural and philosophical conditions’.

Accurate urban road model reconstruction from high resolution remotely sensed imagery based on Support Vector Machine and Gabor filters

In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

Preparation of porous calcium phosphate ceramic scaffold in bone tissue engineering

Calcium Phosphate ceramic has been widely used in bone tissue engineering due to its excellent biocompatibility and biodegradability. However, low mechanical properties and biodegradability limit their potential applications. In this project, hydroxyapatite (HA) and calcium phosphate bioglass were used to produce porous tri-calcium phosphate (TCP) bio-ceramic scaffolds. It was found that porous TCP bioceramic could be obtained when 20wt percent bioglass addition and sintered in 1400 degrees celsius for 3 h. Significantly higher compressive strength (9.98 MPa) was achieved in the scaffolds as compared to those produced from tCP power (<3 MPa). The biocompatibility of the scaffold was also estimated.

Practical stability of approximating discrete-time filters with respect to model mismatch using relative entropy concepts

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Using local consistency assumption, the practical stability established is in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Significantly, these practical stability results do not require the approximating model to be of the same model type as the true system. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.