Health Workforce Governance: Improved Access, Good Regulatory Practice, Safer Patients

With increasing recognition of the international market in health professionals and the impact of globalism on regulation, the governance of the health workforce is moving towards greater public engagement and increased transparency. This book discusses the challenges posed by these processes, such as improved access to health services and how structures can be reformed so that good practice is upheld and quality of service and patient safety are ensured.

Dual-band Decoupling and Matching Network Design for very Closely Spaced Antennas

A practical method for the design of dual-band decoupling and matching networks (DMN) for two closely spaced antennas using discrete components is presented. The DMN reduces the port-to-port coupling and enhances the diversity of the antennas. By applying the DMN, the radiation efficiency can also be improved when one port is fed and the other port is match terminated. The proposed DMN works at two frequencies simultaneously without the need for any switch. As a proof of concept, a dual-band DMN for a pair of monopoles spaced 0.05λ apart is designed. The measured return loss and port isolation exceed 10 dB from 1.71 GHz to 1.76 GHz and from 2.27 GHz to 2.32 GHz.

Efficient preconditioning of the method of lines for solving nonlinear two-sided space-fractional diffusion equations

A standard method for the numerical solution of partial differential equations (PDEs) is the method of lines. In this approach the PDE is discretised in space using �finite di�fferences or similar techniques, and the resulting semidiscrete problem in time is integrated using an initial value problem solver. A significant challenge when applying the method of lines to fractional PDEs is that the non-local nature of the fractional derivatives results in a discretised system where each equation involves contributions from many (possibly every) spatial node(s). This has important consequences for the effi�ciency of the numerical solver. First, since the cost of evaluating the discrete equations is high, it is essential to minimise the number of evaluations required to advance the solution in time. Second, since the Jacobian matrix of the system is dense (partially or fully), methods that avoid the need to form and factorise this matrix are preferred. In this paper, we consider a nonlinear two-sided space-fractional di�ffusion equation in one spatial dimension. A key contribution of this paper is to demonstrate how an eff�ective preconditioner is crucial for improving the effi�ciency of the method of lines for solving this equation. In particular, we show how to construct suitable banded approximations to the system Jacobian for preconditioning purposes that permit high orders and large stepsizes to be used in the temporal integration, without requiring dense matrices to be formed. The results of numerical experiments are presented that demonstrate the effectiveness of this approach.

Damage quantification techniques in acoustic emission monitoring

Acoustic emission (AE) analysis is one of the several diagnostic techniques available nowadays for structural health monitoring (SHM) of engineering structures. Some of its advantages over other techniques include high sensitivity to crack growth and capability of monitoring a structure in real time. The phenomenon of rapid release of energy within a material by crack initiation or growth in form of stress waves is known as acoustic emission (AE). In AE technique, these stress waves are recorded by means of suitable sensors placed on the surface of a structure. Recorded signals are subsequently analysed to gather information about the nature of the source. By enabling early detection of crack growth, AE technique helps in planning timely retrofitting or other maintenance jobs or even replacement of the structure if required. In spite of being a promising tool, some challenges do still exist behind the successful application of AE technique. Large amount of data is generated during AE testing, hence effective data analysis is necessary, especially for long term monitoring uses. Appropriate analysis of AE data for quantification of damage level is an area that has received considerable attention. Various approaches available for damage quantification for severity assessment are discussed in this paper, with special focus on civil infrastructure such as bridges. One method called improved b-value analysis is used to analyse data collected from laboratory testing.

Low temperature synthesis of carbon nanotubes on indium tin oxide electrodes for organic solar cells

The electrical performance of indium tin oxide (ITO) coated glass was improved by including a controlled layer of carbon nanotubes directly on top of the ITO film. Multi-wall carbon nanotubes (MWCNTs) were synthesized by chemical vapor deposition, using ultra-thin Fe layers as catalyst. The process parameters (temperature, gas flow and duration) were carefully refined to obtain the appropriate size and density of MWCNTs with a minimum decrease of the light harvesting in the cell. When used as anodes for organic solar cells based on poly(3-hexylthiophene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM), the MWCNT-enhanced electrodes are found to improve the charge carrier extraction from the photoactive blend, thanks to the additional percolation paths provided by the CNTs. The work function of as-modified ITO surfaces was measured by the Kelvin probe method to be 4.95 eV, resulting in an improved matching to the highest occupied molecular orbital level of the P3HT. This is in turn expected to increase the hole transport and collection at the anode, contributing to the significant increase of current density and open circuit voltage observed in test cells created with such MWCNT-enhanced electrodes.

Improved Subject Identification in Surveillance Video using Super Resolution

The time consuming and labour intensive task of identifying individuals in surveillance video is often challenged by poor resolution and the sheer volume of stored video. Faces or identifying marks such as tattoos are often too coarse for direct matching by machine or human vision. Object tracking and super-resolution can then be combined to facilitate the automated detection and enhancement of areas of interest. The object tracking process enables the automatic detection of people of interest, greatly reducing the amount of data for super-resolution. Smaller regions such as faces can also be tracked. A number of instances of such regions can then be utilized to obtain a super-resolved version for matching. Performance improvement from super-resolution is demonstrated using a face verification task. It is shown that there is a consistent improvement of approximately 7% in verification accuracy, using both Eigenface and Elastic Bunch Graph Matching approaches for automatic face verification, starting from faces with an eye to eye distance of 14 pixels. Visual improvement in image fidelity from super-resolved images over low-resolution and interpolated images is demonstrated on a small database. Current research and future directions in this area are also summarized.

Developing a framework for planning healthy communities : the Logan Beaudesert health decision support system

In the last few decades, the focus on building healthy communities has grown significantly (Ashton, 2009). There is growing evidence that new approaches to planning are required to address the challenges faced by contemporary communities. These approaches need to be based on timely access to local information and collaborative planning processes (Murray, 2006; Scotch & Parmanto, 2006; Ashton, 2009; Kazda et al., 2009). However, there is little research to inform the methods that can support this type of responsive, local, collaborative and consultative health planning (Northridge et al., 2003). Some research justifies the use of decision support systems (DSS) as a tool to support planning for healthy communities. DSS have been found to increase collaboration between stakeholders and communities, improve the accuracy and quality of the decision-making process, and improve the availability of data and information for health decision-makers (Nobre et al., 1997; Cromley & McLafferty, 2002; Waring et al., 2005). Geographic information systems (GIS) have been suggested as an innovative method by which to implement DSS because they promote new ways of thinking about evidence and facilitate a broader understanding of communities. Furthermore, literature has indicated that online environments can have a positive impact on decision-making by enabling access to information by a broader audience (Kingston et al., 2001). However, only limited research has examined the implementation and impact of online DSS in the health planning field. Previous studies have emphasised the lack of effective information management systems and an absence of frameworks to guide the way in which information is used to promote informed decisions in health planning. It has become imperative to develop innovative approaches, frameworks and methods to support health planning. Thus, to address these identified gaps in the knowledge, this study aims to develop a conceptual planning framework for creating healthy communities and examine the impact of DSS in the Logan Beaudesert area. Specifically, the study aims to identify the key elements and domains of information that are needed to develop healthy communities, to develop a conceptual planning framework for creating healthy communities, to collaboratively develop and implement an online GIS-based Health DSS (i.e., HDSS), and to examine the impact of the HDSS on local decision-making processes. The study is based on a real-world case study of a community-based initiative that was established to improve public health outcomes and promote new ways of addressing chronic disease. The study involved the development of an online GIS-based health decision support system (HDSS), which was applied in the Logan Beaudesert region of Queensland, Australia. A planning framework was developed to account for the way in which information could be organised to contribute to a healthy community. The decision support system was developed within a unique settings-based initiative Logan Beaudesert Health Coalition (LBHC) designed to plan and improve the health capacity of Logan Beaudesert area in Queensland, Australia. This setting provided a suitable platform to apply a participatory research design to the development and implementation of the HDSS. Therefore, the HDSS was a pilot study examined the impact of this collaborative process, and the subsequent implementation of the HDSS on the way decision-making was perceived across the LBHC. As for the method, based on a systematic literature review, a comprehensive planning framework for creating healthy communities has been developed. This was followed by using a mixed method design, data were collected through both qualitative and quantitative methods. Specifically, data were collected by adopting a participatory action research (PAR) approach (i.e., PAR intervention) that informed the development and conceptualisation of the HDSS. A pre- and post-design was then used to determine the impact of the HDSS on decision-making. The findings of this study revealed a meaningful framework for organising information to guide planning for healthy communities. This conceptual framework provided a comprehensive system within which to organise existing data. The PAR process was useful in engaging stakeholders and decision-making in the development and implementation of the online GIS-based DSS. Through three PAR cycles, this study resulted in heightened awareness of online GIS-based DSS and openness to its implementation. It resulted in the development of a tailored system (i.e., HDSS) that addressed the local information and planning needs of the LBHC. In addition, the implementation of the DSS resulted in improved decision- making and greater satisfaction with decisions within the LBHC. For example, the study illustrated the culture in which decisions were made before and after the PAR intervention and what improvements have been observed after the application of the HDSS. In general, the findings indicated that decision-making processes are not merely informed (consequent of using the HDSS tool), but they also enhance the overall sense of ‗collaboration‘ in the health planning practice. For example, it was found that PAR intervention had a positive impact on the way decisions were made. The study revealed important features of the HDSS development and implementation process that will contribute to future research. Thus, the overall findings suggest that the HDSS is an effective tool, which would play an important role in the future for significantly improving the health planning practice.

Multi-method, multi-theoretical, multi-level research in the learning sciences

We examine methodologies and methods that apply to multi-level research in the learning sciences. In so doing we describe how multiple theoretical frameworks informs the use of different methods that apply to social levels involving space-time relationships that are not accessible consciously as social life is enacted. Most of the methods involve analyses of video and audio files. Within a framework of interpretive research we present a methodology of event-oriented social science, which employs video ethnography, narrative, conversation analysis, prosody analysis, and facial expression analysis. We illustrate multi-method research in an examination of the role of emotions in teaching and learning. Conversation and prosody analyses augment facial expression analysis and ethnography. We conclude with an exploration of ways in which multi-level studies can be complemented with neural level analyses.

Experimental studies of wireless communication and GNSS kinematic positioning performance in high-mobility vehicle environments

In order to support intelligent transportation system (ITS) road safety applications such as collision avoidance, lane departure warnings and lane keeping, Global Navigation Satellite Systems (GNSS) based vehicle positioning system has to provide lane-level (0.5 to 1 m) or even in-lane-level (0.1 to 0.3 m) accurate and reliable positioning information to vehicle users. However, current vehicle navigation systems equipped with a single frequency GPS receiver can only provide road-level accuracy at 5-10 meters. The positioning accuracy can be improved to sub-meter or higher with the augmented GNSS techniques such as Real Time Kinematic (RTK) and Precise Point Positioning (PPP) which have been traditionally used in land surveying and or in slowly moving environment. In these techniques, GNSS corrections data generated from a local or regional or global network of GNSS ground stations are broadcast to the users via various communication data links, mostly 3G cellular networks and communication satellites. This research aimed to investigate the precise positioning system performances when operating in the high mobility environments. This involves evaluation of the performances of both RTK and PPP techniques using: i) the state-of-art dual frequency GPS receiver; and ii) low-cost single frequency GNSS receiver. Additionally, this research evaluates the effectiveness of several operational strategies in reducing the load on data communication networks due to correction data transmission, which may be problematic for the future wide-area ITS services deployment. These strategies include the use of different data transmission protocols, different correction data format standards, and correction data transmission at the less-frequent interval. A series of field experiments were designed and conducted for each research task. Firstly, the performances of RTK and PPP techniques were evaluated in both static and kinematic (highway with speed exceed 80km) experiments. RTK solutions achieved the RMS precision of 0.09 to 0.2 meter accuracy in static and 0.2 to 0.3 meter in kinematic tests, while PPP reported 0.5 to 1.5 meters in static and 1 to 1.8 meter in kinematic tests by using the RTKlib software. These RMS precision values could be further improved if the better RTK and PPP algorithms are adopted. The tests results also showed that RTK may be more suitable in the lane-level accuracy vehicle positioning. The professional grade (dual frequency) and mass-market grade (single frequency) GNSS receivers were tested for their performance using RTK in static and kinematic modes. The analysis has shown that mass-market grade receivers provide the good solution continuity, although the overall positioning accuracy is worse than the professional grade receivers. In an attempt to reduce the load on data communication network, we firstly evaluate the use of different correction data format standards, namely RTCM version 2.x and RTCM version 3.0 format. A 24 hours transmission test was conducted to compare the network throughput. The results have shown that 66% of network throughput reduction can be achieved by using the newer RTCM version 3.0, comparing to the older RTCM version 2.x format. Secondly, experiments were conducted to examine the use of two data transmission protocols, TCP and UDP, for correction data transmission through the Telstra 3G cellular network. The performance of each transmission method was analysed in terms of packet transmission latency, packet dropout, packet throughput, packet retransmission rate etc. The overall network throughput and latency of UDP data transmission are 76.5% and 83.6% of TCP data transmission, while the overall accuracy of positioning solutions remains in the same level. Additionally, due to the nature of UDP transmission, it is also found that 0.17% of UDP packets were lost during the kinematic tests, but this loss doesn't lead to significant reduction of the quality of positioning results. The experimental results from the static and the kinematic field tests have also shown that the mobile network communication may be blocked for a couple of seconds, but the positioning solutions can be kept at the required accuracy level by setting of the Age of Differential. Finally, we investigate the effects of using less-frequent correction data (transmitted at 1, 5, 10, 15, 20, 30 and 60 seconds interval) on the precise positioning system. As the time interval increasing, the percentage of ambiguity fixed solutions gradually decreases, while the positioning error increases from 0.1 to 0.5 meter. The results showed the position accuracy could still be kept at the in-lane-level (0.1 to 0.3 m) when using up to 20 seconds interval correction data transmission.

Strontium-containing mesoporous bioactive glass scaffolds with improved osteogenic/cementogenic differentiation of periodontal ligament cells for periodontal tissue engineering

To achieve the ultimate goal of periodontal tissue engineering, it is of great importance to develop bioactive scaffolds which could stimulate the osteogenic/cementogenic differentiation of periodontal ligament cells (PDLCs) for the favorable regeneration of alveolar bone, root cementum, and periodontal ligament. Strontium (Sr) and Sr-containing biomaterials have been found to induce osteoblast activity. However, there is no systematic report about the interaction between Sr or Sr-containing biomaterials and PDLCs for periodontal tissue engineering. The aims of this study were to prepare Sr-containing mesoporous bioactive glass (Sr-MBG) scaffolds and investigate whether the addition of Sr could stimulate the osteogenic/cementogenic differentiation of PDLCs in tissue engineering scaffold system. The composition, microstructure and mesopore properties (specific surface area, nano-pore volume and nano-pore distribution) of Sr-MBG scaffolds were characterized. The proliferation, alkaline phosphatase (ALP) activity and osteogenesis/cementogenesis-related gene expression (ALP, Runx2, Col I, OPN and CEMP1) of PDLCs on different kinds of Sr-MBG scaffolds were systematically investigated. The results show that Sr plays an important role in influencing the mesoporous structure of MBG scaffolds in which high contents of Sr decreased the well-ordered mesopores as well as their surface area/pore volume. Sr2+ ions could be released from Sr-MBG scaffolds in a controlled way. The incorporation of Sr into MBG scaffolds has significantly stimulated ALP activity and osteogenesis/cementogenesis-related gene expression of PDLCs. Furthermore, Sr-MBG scaffolds in simulated body fluids environment still maintained excellent apatite-mineralization ability. The study suggests that the incorporation of Sr into MBG scaffolds is a viable way to stimulate the biological response of PDLCs. Sr-MBG scaffolds are a promising bioactive material for periodontal tissue engineering application.

Non-invasive method for detecting changes in soil moisture using wireless sensor networks

There are several popular soil moisture measurement methods today such as time domain reflectometry, electromagnetic (EM) wave, electrical and acoustic methods. Significant studies have been dedicated in developing method of measurements using those concepts, especially to achieve the characteristics of noninvasiveness. EM wave method provides an advantage because it is non-invasive to the soil and does not need to utilise probes to penetrate or bury in the soil. But some EM methods are also too complex, expensive, and not portable for the application of Wireless Sensor Networks; for example satellites or UAV (Unmanned Aerial Vehicle) based sensors. This research proposes a method in detecting changes in soil moisture using soil-reflected electromagnetic (SREM) wave from Wireless Sensor Networks (WSNs). Studies have shown that different levels of soil moisture will affects soil’s dielectric properties, such as relative permittivity and conductivity, and in turns change its reflection coefficients. The SREM wave method uses a transmitter adjacent to a WSNs node with purpose exclusively to transmit wireless signals that will be reflected by the soil. The strength from the reflected signal that is determined by the soil’s reflection coefficients is used to differentiate the level of soil moisture. The novel nature of this method comes from using WSNs communication signals to perform soil moisture estimation without the need of external sensors or invasive equipment. This innovative method is non-invasive, low cost and simple to set up. There are three locations at Brisbane, Australia chosen as the experiment’s location. The soil type in these locations contains 10–20% clay according to the Australian Soil Resource Information System. Six approximate levels of soil moisture (8, 10, 13, 15, 18 and 20%) are measured at each location; with each measurement consisting of 200 data. In total 3600 measurements are completed in this research, which is sufficient to achieve the research objective, assessing and proving the concept of SREM wave method. These results are compared with reference data from similar soil type to prove the concept. A fourth degree polynomial analysis is used to generate an equation to estimate soil moisture from received signal strength as recorded by using the SREM wave method.

3D-printing of highly uniform CaSiO3 ceramic scaffolds : preparation, characterization and in vivo osteogenesis

Calcium silicate (CaSiO3, CS) ceramics have received significant attention for application in bone regeneration due to their excellent in vitro apatite-mineralization ability; however, how to prepare porous CS scaffolds with a controllable pore structure for bone tissue engineering still remains a challenge. Conventional methods could not efficiently control the pore structure and mechanical strength of CS scaffolds, resulting in unstable in vivo osteogenesis. The aim of this study is to set out to solve these problems by applying a modified 3D-printing method to prepare highly uniform CS scaffolds with controllable pore structure and improved mechanical strength. The in vivo osteogenesis of the prepared 3D-printed CS scaffolds was further investigated by implanting them in the femur defects of rats. The results show that the CS scaffolds prepared by the modified 3D-printing method have uniform scaffold morphology. The pore size and pore structure of CS scaffolds can be efficiently adjusted. The compressive strength of 3D-printed CS scaffolds is around 120 times that of conventional polyurethane templated CS scaffolds. 3D-Printed CS scaffolds possess excellent apatite-mineralization ability in simulated body fluids. Micro-CT analysis has shown that 3D-printed CS scaffolds play an important role in assisting the regeneration of bone defects in vivo. The healing level of bone defects implanted by 3D-printed CS scaffolds is obviously higher than that of 3D-printed b-tricalcium phosphate (b-TCP) scaffolds at both 4 and 8 weeks. Hematoxylin and eosin (H&E) staining shows that 3D-printed CS scaffolds induce higher quality of the newly formed bone than 3D-printed b-TCP scaffolds. Immunohistochemical analyses have further shown that stronger expression of human type I collagen (COL1) and alkaline phosphate (ALP) in the bone matrix occurs in the 3D-printed CS scaffolds than in the 3D-printed b-TCP scaffolds. Considering these important advantages, such as controllable structure architecture, significant improvement in mechanical strength, excellent in vivo osteogenesis and since there is no need for second-time sintering, it is indicated that the prepared 3D-printed CS scaffolds are a promising material for application in bone regeneration.

Anomalous subdiffusion equations by the meshless collocation method

This paper aims to develop an implicit meshless collocation technique based on the moving least squares approximation for numerical simulation of the anomalous subdiffusion equation(ASDE). The discrete system of equations is obtained by using the MLS meshless shape functions and the meshless collocation formulation. The stability and convergence of this meshless approach related to the time discretization are investigated theoretically and numerically. The numerical examples with regular and irregular nodal distributions are used to the newly developed meshless formulation. It is concluded that the present meshless formulation is very effective for the modeling of ASDEs.

Beef carcasses with larger eye muscle areas, lower ossification scores and improved nutrition have a lower incidence of dark cutting

This study evaluated the effect of eye muscle area (EMA), ossification, carcass weight, marbling and rib fat depth on the incidence of dark cutting (pH u > 5.7) using routinely collected Meat Standards Australia (MSA) data. Data was obtained from 204,072 carcasses at a Western Australian processor between 2002 and 2008. Binomial data of pH u compliance was analysed using a logit model in a Bayesian framework. Increasing eye muscle area from 40 to 80 cm 2, increased pH u compliance by around 14% (P < 0.001) in carcasses less than 350 kg. As carcass weight increased from 150 kg to 220 kg, compliance increased by 13% (P < 0.001) and younger cattle with lower ossification were also 7% more compliant (P < 0.001). As rib fat depth increased from 0 to 20 mm, pH u compliance increased by around 10% (P < 0.001) yet marbling had no effect on dark cutting. Increasing musculature and growth combined with good nutrition will minimise dark cutting beef in Australia.