Modelling urban public transit users' route choice behaviour: review and outlook

This paper reviews the main development of approaches to modelling urban public transit users’ route choice behaviour from 1960s to the present. The approaches reviewed include the early heuristic studies on finding the least cost transit route and all-or-nothing transit assignment, the bus common line problem and corresponding network representation methods, the disaggregate discrete choice models which are based on random utility maximization assumptions, the deterministic use equilibrium and stochastic user equilibrium transit assignment models, and the recent dynamic transit assignment models using either frequency or schedule based network formulation. In addition to reviewing past outcomes, this paper also gives an outlook into the possible future directions of modelling transit users’ route choice behaviour. Based on the comparison with the development of models for motorists’ route choice and traffic assignment problems in an urban road area, this paper points out that it is rewarding for transit route choice research to draw inspiration from the intellectual outcomes out of the road area. Particularly, in light of the recent advancement of modelling motorists’ complex road route choice behaviour, this paper advocates that the modelling practice of transit users’ route choice should further explore the complexities of the problem.

High-performance ceramic membranes with a separation layer of metal oxide nanofibers

In conventional fabrication of ceramic separation membranes, the particulate sols are applied onto porous supports. Major structural deficiencies under this approach are pin-holes and cracks, and the dramatic losses of flux when pore sizes are reduced to enhance selectivity. We have overcome these structural deficiencies by constructing hierarchically structured separation layer on a porous substrate using lager titanate nanofibers and smaller boehmite nanofibers. This yields a radical change in membrane texture. The resulting membranes effectively filter out species larger than 60 nm at flow rates orders of magnitude greater than conventional membranes. This reveals a new direction in membrane fabrication.

Stem cell regulatory gene expression in human adult dental pulp and periodontal ligament cells undergoing odontogenic/osteogenic differentiation

Introduction During development and regeneration, odontogenesis and osteogenesis are initiated by a cascade of signals driven by several master regulatory genes. Methods In this study, we investigated the differential expression of 84 stem cell–related genes in dental pulp cells (DPCs) and periodontal ligament cells (PDLCs) undergoing odontogenic/osteogenic differentiation. Results Our results showed that, although there was considerable overlap, certain genes had more differential expression in PDLCs than in DPCs. CCND2, DLL1, and MME were the major upregulated genes in both PDLCs and DPCs, whereas KRT15 was the only gene significantly downregulated in PDLCs and DPCs in both odontogenic and osteogenic differentiation. Interestingly, a large number of regulatory genes in odontogenic and osteogenic differentiation interact or crosstalk via Notch, Wnt, transforming growth factor β (TGF-β)/bone morphogenic protein (BMP), and cadherin signaling pathways, such as the regulation of APC, DLL1, CCND2, BMP2, and CDH1. Using a rat dental pulp and periodontal defect model, the expression and distribution of both BMP2 and CDH1 have been verified for their spatial localization in dental pulp and periodontal tissue regeneration. Conclusions This study has generated an overview of stem cell–related gene expression in DPCs and PDLCs during odontogenic/osteogenic differentiation and revealed that these genes may interact through the Notch, Wnt, TGF-β/BMP, and cadherin signalling pathways to play a crucial role in determining the fate of dental derived cell and dental tissue regeneration. These findings provided a new insight into the molecular mechanisms of the dental tissue mineralization and regeneration

Privacy and security in open and trusted health information systems

The Open and Trusted Health Information Systems (OTHIS) Research Group has formed in response to the health sector’s privacy and security requirements for contemporary Health Information Systems (HIS). Due to recent research developments in trusted computing concepts, it is now both timely and desirable to move electronic HIS towards privacy-aware and security-aware applications. We introduce the OTHIS architecture in this paper. This scheme proposes a feasible and sustainable solution to meeting real-world application security demands using commercial off-the-shelf systems and commodity hardware and software products.

Open and trusted information systems/health informatics access control (OTHIS/HIAC)

Information and Communications Technologies globally are moving towards Service Oriented Architectures and Web Services. The healthcare environment is rapidly moving to the use of Service Oriented Architecture/Web Services systems interconnected via this global open Internet. Such moves present major challenges where these structures are not based on highly trusted operating systems. This paper argues the need of a radical re-think of access control in the contemporary healthcare environment in light of modern information system structures, legislative and regulatory requirements, and security operation demands in Health Information Systems. This paper proposes the Open and Trusted Health Information Systems (OTHIS), a viable solution including override capability to the provision of appropriate levels of secure access control for the protection of sensitive health data.

Automating human thought processes for a UAV forced landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system

High-flux ceramic membranes with a nanomesh of metal oxide nanofibers

Traditional ceramic separation membranes, which are fabricated by applying colloidal suspensions of metal hydroxides to porous supports, tend to suffer from pinholes and cracks that seriously affect their quality. Other intrinsic problems for these membranes include dramatic losses of flux when the pore sizes are reduced to enhance selectivity and dead-end pores that make no contribution to filtration. In this work, we propose a new strategy for addressing these problems by constructing a hierarchically structured separation layer on a porous substrate using large titanate nanofibers and smaller boehmite nanofibers. The nanofibers are able to divide large voids into smaller ones without forming dead-end pores and with the minimum reduction of the total void volume. The separation layer of nanofibers has a porosity of over 70% of its volume, whereas the separation layer in conventional ceramic membranes has a porosity below 36% and inevitably includes dead-end pores that make no contribution to the flux. This radical change in membrane texture greatly enhances membrane performance. The resulting membranes were able to filter out 95.3% of 60-nm particles from a 0.01 wt % latex while maintaining a relatively high flux of between 800 and 1000 L/m2·h, under a low driving pressure (20 kPa). Such flow rates are orders of magnitude greater than those of conventional membranes with equal selectivity. Moreover, the flux was stable at approximately 800 L/m2·h with a selectivity of more than 95%, even after six repeated runs of filtration and calcination. Use of different supports, either porous glass or porous alumina, had no substantial effect on the performance of the membranes; thus, it is possible to construct the membranes from a variety of supports without compromising functionality. The Darcy equation satisfactorily describes the correlation between the filtration flux and the structural parameters of the new membranes. The assembly of nanofiber meshes to combine high flux with excellent selectivity is an exciting new direction in membrane fabrication.

Fluorescence spectrometric study on the interactions of isoprocarb and sodium 2-isopropylphenate with bovine serum albumin

The binding interaction of the pesticide Isoprocarb and its degradation product, sodium 2-isopropylphenate, with bovine serum albumin (BSA) was studied by spectrofluorimetry under simulated physiological conditions. Both Isoprocarb and sodium 2-isopropylphenate quenched the intrinsic fluorescence of BSA. This quenching proceeded via a static mechanism. The thermodynamic parameters (ΔH°, ΔS° and ΔG°) obtained from the fluorescence data measured at two different temperatures showed that the binding of Isoprocarb to BSA involved hydrogen bonds and that of sodium 2-isopropylphenate to BSA involved hydrophobic and electrostatic interactions. Synchronous fluorescence spectroscopy of the interaction of BSA with either Isoprocarb or sodium 2-isopropylphenate showed that the molecular structure of the BSA was changed significantly, which is consistent with the known toxicity of the pesticide, i.e., the protein is denatured. The sodium 2-isopropylphenate, was estimated to be about 4–5 times more toxic than its parent, Isoprocarb. Synchronous fluorescence spectroscopy and the resolution of the three-way excitation–emission fluorescence spectra by the PARAFAC method extracted the relative concentration profiles of BSA, Isoprocab and sodium 2-isopropylphenate as a function of the added sodium 2-isopropylphenate. These profiles showed that the degradation product, sodium 2-isopropylphenate, displaced the pesticide in a competitive reaction with the BSA protein.

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Fast searching algorithm for candidate satellite-node set in NLMG

The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.

Synthesis and characterisation of cobalt hydroxide, cobalt oxyhydroxide and cobalt oxide nanodiscs

Cobalt hydroxide, cobalt oxyhydroxide and cobalt oxide nanomaterials were synthesized through simple soft chemistry. The cobalt hydroxide displays hexagonal morphology with clear edges 20 nm long. This morphology and nanosize is retained through to cobalt oxide Co3O4 through a topotactical relationship. Cobalt oxyhydroxide and cobalt oxide nanomaterials were synthesized through oxidation and low temperature calcination from the as-prepared cobalt hydroxide. Characterisation of these cobalt-based nanomaterials were fully developed, including X-ray diffraction, transmission electron microscopy combined with selected area electron diffraction, scanning electron microscopy, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermal gravimetric analysis. Bonding of the divalent cobalt hydroxide from the oxyhydroxide and oxides by studying their high resolution XPS spectra for Co 2p3/2 and O 1s. Raman spectroscopy of the as-prepared Co(OH)2, CoO(OH) and Co3O4 nanomaterials characterised each material. The thermal stability of the materials Co(OH)2 and CoO(OH) were established. This research has developed methodology for the synthesis of cobalt oxide and cobalt oxyhydroxide nanodiscs at low temperatures.

Implications of precursor chemistry on the alkaline hydrothermal synthesis of titania/titanate nanostructures

A systematic study of four parameters within the alkaline hydrothermal treatment of three commercial titania powders—anatase, rutile, and Degussa P25—was made. These powders were treated with 5, 7.5, 9, and 10 M NaOH between 100 and 220 °C for 20 h. The effects of alkaline concentration, hydrothermal temperature, and precursor phase and crystallite size on the resultant nanostructure formation have been studied through X-ray diffraction, Raman spectroscopy, transmission electron microscopy, and nitrogen adsorption. Through the correlation of these data, morphological phase diagrams were constructed for each commercial powder. Interpretation of the resultant morphological phase diagrams indicates that alkaline concentration and hydrothermal temperature affect nanostructure formation independently, where nanoribbon formation is significantly influenced by temperature for initial formation. The phase and crystallite size of the precursor also significantly influenced nanostructure formation, with rutile displaying a slower rate of precursor consumption compared with anatase. Small crystallite titania precursors formed nanostructures at reduced hydrothermal temperatures.

Numerical method and analytical technique of the modified anomalous subdiffusion equation with a nonlinear source term

In this paper, we consider a modified anomalous subdiffusion equation with a nonlinear source term for describing processes that become less anomalous as time progresses by the inclusion of a second fractional time derivative acting on the diffusion term. A new implicit difference method is constructed. The stability and convergence are discussed using a new energy method. Finally, some numerical examples are given. The numerical results demonstrate the effectiveness of theoretical analysis