Straightforward biodegradable nanoparticle generation through megahertz-order ultrasonic atomization

Simple and reliable formation of biodegradable nanoparticles formed from poly-ε-caprolactone was achieved using 1.645 MHz piston atomization of a source fluid of 0.5% w/v of the polymer dissolved in acetone; the particles were allowed to descend under gravity in air 8 cm into a 1 mM solution of sodium dodecyl sulfate. After centrifugation to remove surface agglomerations, a symmetric monodisperse distribution of particles φ 186 nm (SD=5.7, n=6) was obtained with a yield of 65.2%. © 2006 American Institute of Physics.

A Fixed Order Model Matching Approach for the Design of Robust Power System Oscillation Damper

This book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems.

Not just what they want, but why they want it: Traditional market research to deep customer insights

Purpose This paper explores advantages and disadvantages of both traditional market research and deep customer insight methods in order to lay the platform for revealing how a relationship between these two domains could be optimised during firm-based innovation. Design/methodology/approach The paper reports on an empirical research study conducted with thirteen Australian based firms engaged in a design-led approach to innovation. Firms were facilitated through a design-led approach where the process of gathering deep customer insights was isolated and investigated further in comparison to traditional market research methods. Findings Results show that deep customer insight methods are able to provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. Findings concluded that deep customer insights methods provide the critical layer to understand why customers do and don’t engage with businesses. Revealing why was not accessible in traditional market research methods. Research limitations/implications The theoretical outcome of this study is a complementary methods matrix, providing guidance on appropriate implementation of research methods in accordance with a project’s timeline to optimise the complementation of traditional market research methods with design-led customer engagement methods. Practical implications Deep customer insight methods provide fresh, non-obvious ways of understanding customer needs, problems and behaviours that can become the foundation of new business opportunities. It is hoped that those in a position of data collection are encouraged to experiment and use deep customer insight methods to connect with their customers on a meaningful level and translate these insights into value. Originality/value This paper provides original value to a new understanding how design techniques can be applied to compliment and strengthen existing market research strategies. This is crucial in an era where business competition hinges on a subtle and often intimate understanding of customer needs and behaviours.

Second-order quantile methods for experts and combinatorial games

We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.

Numerical algorithms for time-fractional subdiffusion equation with second-order accuracy

This article aims to fill in the gap of the second-order accurate schemes for the time-fractional subdiffusion equation with unconditional stability. Two fully discrete schemes are first proposed for the time-fractional subdiffusion equation with space discretized by finite element and time discretized by the fractional linear multistep methods. These two methods are unconditionally stable with maximum global convergence order of $O(\tau+h^{r+1})$ in the $L^2$ norm, where $\tau$ and $h$ are the step sizes in time and space, respectively, and $r$ is the degree of the piecewise polynomial space. The average convergence rates for the two methods in time are also investigated, which shows that the average convergence rates of the two methods are $O(\tau^{1.5}+h^{r+1})$. Furthermore, two improved algorithms are constrcted, they are also unconditionally stable and convergent of order $O(\tau^2+h^{r+1})$. Numerical examples are provided to verify the theoretical analysis. The comparisons between the present algorithms and the existing ones are included, which show that our numerical algorithms exhibit better performances than the known ones.

High order unconditionally stable difference schemes for the Riesz space-fractional telegraph equation

In this paper, a class of unconditionally stable difference schemes based on the Pad´e approximation is presented for the Riesz space-fractional telegraph equation. Firstly, we introduce a new variable to transform the original dfferential equation to an equivalent differential equation system. Then, we apply a second order fractional central difference scheme to discretise the Riesz space-fractional operator. Finally, we use (1, 1), (2, 2) and (3, 3) Pad´e approximations to give a fully discrete difference scheme for the resulting linear system of ordinary differential equations. Matrix analysis is used to show the unconditional stability of the proposed algorithms. Two examples with known exact solutions are chosen to assess the proposed difference schemes. Numerical results demonstrate that these schemes provide accurate and efficient methods for solving a space-fractional hyperbolic equation.

Numerical analysis for the time distributed-order and Riesz space fractional diffusions on bounded domains

Subdiffusion equations with distributed-order fractional derivatives describe some important physical phenomena. In this paper, we consider the time distributed-order and Riesz space fractional diffusions on bounded domains with Dirichlet boundary conditions. Here, the time derivative is defined as the distributed-order fractional derivative in the Caputo sense, and the space derivative is defined as the Riesz fractional derivative. First, we discretize the integral term in the time distributed-order and Riesz space fractional diffusions using numerical approximation. Then the given equation can be written as a multi-term time–space fractional diffusion. Secondly, we propose an implicit difference method for the multi-term time–space fractional diffusion. Thirdly, using mathematical induction, we prove the implicit difference method is unconditionally stable and convergent. Also, the solvability for our method is discussed. Finally, two numerical examples are given to show that the numerical results are in good agreement with our theoretical analysis.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.

Generalized element load method for first- and second-order element solutions with element load effect

The finite element method in principle adaptively divides the continuous domain with complex geometry into discrete simple subdomain by using an approximate element function, and the continuous element loads are also converted into the nodal load by means of the traditional lumping and consistent load methods, which can standardise a plethora of element loads into a typical numerical procedure, but element load effect is restricted to the nodal solution. It in turn means the accurate continuous element solutions with the element load effects are merely restricted to element nodes discretely, and further limited to either displacement or force field depending on which type of approximate function is derived. On the other hand, the analytical stability functions can give the accurate continuous element solutions due to element loads. Unfortunately, the expressions of stability functions are very diverse and distinct when subjected to different element loads that deter the numerical routine for practical applications. To this end, this paper presents a displacement-based finite element function (generalised element load method) with a plethora of element load effects in the similar fashion that never be achieved by the stability function, as well as it can generate the continuous first- and second-order elastic displacement and force solutions along an element without loss of accuracy considerably as the analytical approach that never be achieved by neither the lumping nor consistent load methods. Hence, the salient and unique features of this paper (generalised element load method) embody its robustness, versatility and accuracy in continuous element solutions when subjected to the great diversity of transverse element loads.

Protecting Australia's children: A cross-jurisdictional review of domestic violence protection order legislation

Increasingly, domestic violence is being treated as a child protection issue, and children affected by domestic violence are recognised as experiencing a form of child abuse. Domestic violence protection order legislation – as a key legal response to domestic violence – may offer an important legal option for the protection of children affected by domestic violence. In this article, we consider the research that establishes domestic violence as a form of child abuse, and review the provisions of State and Territory domestic violence protection order legislation to assess whether they demonstrate an adequate focus on the protection of children.

Numerical simulation of railway track supporting system using finite-infinite and thin layer elements under impulsive loads

The present study deals with two dimensional, numerical simulation of railway track supporting system subjected to dynamic excitation force. Under plane strain condition, the coupled finite-infinite elements to represent the near and far field stress distribution and thin layer interface element was employed to model the interfacial behavior between sleepers and ballast. To account for the relative debonding, slipping and crushing that could take place in the contact area between the sleepers and ballast, modified Mohr-Coulomb criterion was adopted. Furthermore an attempt has been made to consider the elasto-plastic material non-linearity of the railway track supporting media by employing different constitutive models to represent steel, concrete and supporting materials. Based on the proposed physical and constitutive modeling a code has been developed for dynamic loads. The applicability of the developed F.E code has been demonstrated by analyzing a real railway supporting structure.

Numerical modeling of railway track supporting system using finite–infinite and thin layer elements

The present contribution deals with the numerical modelling of railway track-supporting systems-using coupled finite-infinite elements-to represent the near and distant field stress distribution, and also employing a thin layer interface element to account for the interfacial behaviour between sleepers and ballast. To simulate the relative debonding, slipping and crushing at the contact area between sleepers and ballast, a modified Mohr-Coulomb criterion was adopted. Further more an attempt was made to consider the elasto plastic materials’ non-linearity of the railway track supporting media by employing different constitutive models to represent steel, concrete and other supporting materials. It is seen that during an incremental-iterative mode of load application, the yielding initially started from the edge of the sleepers and then flowed vertically downwards and spread towards the centre of the railway supporting system.

Thermal behavior of kaolinite–urea intercalation complex and molecular dynamics simulation for urea molecule orientation

The thermal behavior of kaolinite–urea intercalation complex was investigated by thermogravimetry–differential scanning calorimetry (TG–DSC), X-ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR). In addition, the interaction mode of urea molecules intercalated into the kaolinite gallery was studied by means of molecular dynamics simulation. Three main mass losses were observed at 136 °C, in the range of 210–270 °C, and at 500 °C in the TG–DSC curves, which were, respectively, attributed to (1) melting of the surface-adsorbed urea, (2) removal of the intercalated urea, and (3) dehydroxylation of the deintercalated kaolinite. The three DSC endothermic peaks at 218, 250, and 261 °C were related to the successive removals of intercalated urea with three different distribution structures. Based on the angle between the dipole moment vector of urea and the basal surface of kaolinite, the three urea models could be described as follows: (1) Type A, the dipole moment vector is nearly parallel to the basal surface of kaolinite; (2) Type B, the dipole moment vector points to the silica tetrahedron with the angle between it and the basal surface of kaolinite ranging from 20°to 40°; and (3) Type C, the dipole moment vector is nearly perpendicular to the basal surface of kaolinite. The three distribution structures of urea molecules were validated by the results of the molecular dynamics simulation. Furthermore, the thermal behavior of the kaolinite–urea intercalation complex investigated by TG–DSC was also supported by FTIR and XRD analyses.

Characterisation of thin layer polymer cement mortared concrete masonry bond

Masonry bond is affected by many parameters such as the type of mortar used, the techniques of dispersion of mortar and the surface texture of the concrete blocks. Additionally it is understood from the studies on conventional masonry that the bond characteristics are also influenced by the curing methods as well as the age of the bond at the time of testing. These effects on thin layer mortared masonry employing polymer cement mortars are not well understood. Therefore, the effect of curing methods and age to the bond strength and deformation of masonry containing thin layered polymer cement mortar was investigated as part of an ongoing research program at the Queensland University of Technology. This paper presents an experimental investigation of the flexural and shear bond characteristics of the thin layer mortared concrete masonry. The parameters examined include the effects curing and ageing to the bond development over a period from 14 days to 56 days after fabrication. The results exhibit that dry cured thin layer mortared masonry exhibits higher bond strength and Young’s and shear moduli compared to the wet cured specimens.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.