Host use and crop impacts of Oribius Marshall species (Coleoptera: Curculionidae) in Eastern Highlands Province, Papua New Guinea

Oribius species are small flightless weevils endemic to the island of New Guinea and far northern Cape York, Australia. The adults feed externally on leaves, developing fruit and green bark, but their impact as pests and general host use patterns are poorly known. Working in Eastern Highlands Province, Papua New Guinea, we carried out structured host use surveys, farmer surveys, shade-house growth trials, and on-farm and on-station impact trials to: (i) estimate the host range of the local Oribius species; (ii) understand adult daily activity patterns; (iii) elucidate feeding habits of the soil dwelling larvae; and (iv) quantify the impacts of adult feeding damage. Oribius inimicus and O. destructor accounted for nearly all the Oribius species encountered locally: of these two O. inimicus was the most abundant. Weevils were collected from 31 of 33 plants surveyed in the Aiyura Valley and a combination of farmer interviews and literature records provided evidence for the beetles being pestiferous on 43 crops currently or previously grown in the Highlands. Adult weevils had a distinct diurnal pattern of being in the upper plant canopy early in the morning and, to a lesser extent, again late in the afternoon. For the remainder of the day beetles resided within the canopy, or possibly off the plant. Movement of adults between plants appeared frequent. Pot trials confirmed the larvae are root feeders. Quantified impact studies showed that the weevils are damaging to a range of vegetable and orchard crops (broccoli, capsicum, celery, French bean, Irish potato, lettuce, orange and strawberry), causing average yield losses of around 30-40%, but up to 100% on citrus. Oribius weevils pose a significant and apparently growing problem for Highland’s agriculture.

Can hybridization cause local extinction : the case for demographic swamping of the Australian native, Senecio pinnatifolius, by the invasive, S. madagascariensis?

The outcome of interspecific hybridization between native and invasive species depends on the relative frequencies of parental taxa and viability of hybrid progeny. We investigated individual and population level consequences of hybridization between the Australian native, Senecio pinnatifolius, and the exotic S. madagascariensis, with AFLP markers and used this information to simulate the expected outcome of hybridization.A high frequency (range 8.3-75.6 %) of hybrids was detected in open pollinated seeds of both species, but mature hybrids were absent from sympatric populations indicating that sympatric populations represent tension zones. A hybridization advantage was observed for S. madagascariensis,where significantly more progeny than expected were sired based on proportional representation of the two species in sympatric populations. Simulations indicated S. pinnatifolius could be replaced in sympatric populations if hybridization was density dependent.For this native-exotic pair, prezygotic isolating barriers are weak, but low hybrid viability maintains a strong postzygotic barrier to introgression. Due to asymmetric hybridization, S. pinnatifolius appears under threat from demographic swamping, and local extinction is possible where it occurs in sympatry with S. madagascariensis.

Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia

Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

A Modified inverse integer Cholesky decorrelation method and the performance on ambiguity resolution

One of the research focuses in the integer least squares problem is the decorrelation technique to reduce the number of integer parameter search candidates and improve the efficiency of the integer parameter search method. It remains as a challenging issue for determining carrier phase ambiguities and plays a critical role in the future of GNSS high precise positioning area. Currently, there are three main decorrelation techniques being employed: the integer Gaussian decorrelation, the Lenstra–Lenstra–Lovász (LLL) algorithm and the inverse integer Cholesky decorrelation (IICD) method. Although the performance of these three state-of-the-art methods have been proved and demonstrated, there is still a potential for further improvements. To measure the performance of decorrelation techniques, the condition number is usually used as the criterion. Additionally, the number of grid points in the search space can be directly utilized as a performance measure as it denotes the size of search space. However, a smaller initial volume of the search ellipsoid does not always represent a smaller number of candidates. This research has proposed a modified inverse integer Cholesky decorrelation (MIICD) method which improves the decorrelation performance over the other three techniques. The decorrelation performance of these methods was evaluated based on the condition number of the decorrelation matrix, the number of search candidates and the initial volume of search space. Additionally, the success rate of decorrelated ambiguities was calculated for all different methods to investigate the performance of ambiguity validation. The performance of different decorrelation methods was tested and compared using both simulation and real data. The simulation experiment scenarios employ the isotropic probabilistic model using a predetermined eigenvalue and without any geometry or weighting system constraints. MIICD method outperformed other three methods with conditioning improvements over LAMBDA method by 78.33% and 81.67% without and with eigenvalue constraint respectively. The real data experiment scenarios involve both the single constellation system case and dual constellations system case. Experimental results demonstrate that by comparing with LAMBDA, MIICD method can significantly improve the efficiency of reducing the condition number by 78.65% and 97.78% in the case of single constellation and dual constellations respectively. It also shows improvements in the number of search candidate points by 98.92% and 100% in single constellation case and dual constellations case.

Continuous appearance-based trajectory SLAM

This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao-Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

The mechanical heterogeneity of the hard callus influences local tissue strains during bone healing : a finite element study based on sheep experiments

During secondary fracture healing, various tissue types including new bone are formed. The local mechanical strains play an important role in tissue proliferation and differentiation. To further our mechanobiological understanding of fracture healing, a precise assessment of local strains is mandatory. Until now, static analyses using Finite Elements (FE) have assumed homogenous material properties. With the recent quantification of both the spatial tissue patterns (Vetter et al., 2010) and the development of elastic modulus of newly formed bone during healing (Manjubala et al., 2009), it is now possible to incorporate this heterogeneity. Therefore, the aim of this study is to investigate the effect of this heterogeneity on the strain patterns at six successive healing stages. The input data of the present work stemmed from a comprehensive cross-sectional study of sheep with a tibial osteotomy (Epari et al., 2006). In our FE model, each element containing bone was described by a bulk elastic modulus, which depended on both the local area fraction and the local elastic modulus of the bone material. The obtained strains were compared with the results of hypothetical FE models assuming homogeneous material properties. The differences in the spatial distributions of the strains between the heterogeneous and homogeneous FE models were interpreted using a current mechanobiological theory (Isakson et al., 2006). This interpretation showed that considering the heterogeneity of the hard callus is most important at the intermediate stages of healing, when cartilage transforms to bone via endochondral ossification.

Expression pattern of Oct-4, Sox2, and c-Myc in the primary culture of human dental pulp derived cells

Dental pulp cells (DPCs) have shown promising potential in dental tissue repair and regeneration. However, during in vitro culture, these cells undergo replicative senescence and result in significant alteration in cell proliferation and differentiation. Recently, the transcription factors of Oct-4, Sox2, c-Myc, and Klf4 have been reported to play a regulatory role in the stem cell self-renewal process, namely cell reprogramming. Therefore, it is interesting to know whether the replicative senescence during the culture of dental pulp cells is related to the diminishing of the expression of these transcription factors. In this study, we investigated the expression of the reprogramming markers Oct-4, Sox2, and c-Myc in the in vitro explant cultured dental pulp tissues and explant cultured dental pulp cells (DPCs) at various passages by immunofluorescence staining and real-time polymerase chain reaction analysis. Our results demonstrated that Oct-4, Sox2, and c-Myc translocated from nucleus in the first 2 passages to cytoplasm after the third passage in explant cultured DPCs. The mRNA expression of Oct-4, Sox2, and c-Myc elevated significantly over the first 2 passages, peaked at second passage (P < .05), and then decreased along the number of passages afterwards (P < .05). For the first time we demonstrated that the expression of reprogramming markers Oct-4, Sox2, and c-Myc was detectable in the early passaged DPCs, and the sequential loss of these markers in the nucleus during DPC cultures might be related to the cell fate of dental pulp derived cells during the long-term in vitro cultivation under current culture conditions.

Local adjustment and global adaptation of control periods for QoC management of control systems

Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.

Network protocols and predictive control strategies for distributed real-time control applications

A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

Robust suspicious behaviour detection for smart surveillance systems

Video surveillance technology, based on Closed Circuit Television (CCTV) cameras, is one of the fastest growing markets in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. To overcome this limitation, it is necessary to have “intelligent” processes which are able to highlight the salient data and filter out normal conditions that do not pose a threat to security. In order to create such intelligent systems, an understanding of human behaviour, specifically, suspicious behaviour is required. One of the challenges in achieving this is that human behaviour can only be understood correctly in the context in which it appears. Although context has been exploited in the general computer vision domain, it has not been widely used in the automatic suspicious behaviour detection domain. So, it is essential that context has to be formulated, stored and used by the system in order to understand human behaviour. Finally, since surveillance systems could be modeled as largescale data stream systems, it is difficult to have a complete knowledge base. In this case, the systems need to not only continuously update their knowledge but also be able to retrieve the extracted information which is related to the given context. To address these issues, a context-based approach for detecting suspicious behaviour is proposed. In this approach, contextual information is exploited in order to make a better detection. The proposed approach utilises a data stream clustering algorithm in order to discover the behaviour classes and their frequency of occurrences from the incoming behaviour instances. Contextual information is then used in addition to the above information to detect suspicious behaviour. The proposed approach is able to detect observed, unobserved and contextual suspicious behaviour. Two case studies using video feeds taken from CAVIAR dataset and Z-block building, Queensland University of Technology are presented in order to test the proposed approach. From these experiments, it is shown that by using information about context, the proposed system is able to make a more accurate detection, especially those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information give critical feedback to the system designers to refine the system. Finally, the proposed modified Clustream algorithm enables the system to both continuously update the system’s knowledge and to effectively retrieve the information learned in a given context. The outcomes from this research are: (a) A context-based framework for automatic detecting suspicious behaviour which can be used by an intelligent video surveillance in making decisions; (b) A modified Clustream data stream clustering algorithm which continuously updates the system knowledge and is able to retrieve contextually related information effectively; and (c) An update-describe approach which extends the capability of the existing human local motion features called interest points based features to the data stream environment.

Non-invasive assessment of tear film surface quality

The tear film plays an important role preserving the health of the ocular surface and maintaining the optimal refractive power of the cornea. Moreover dry eye syndrome is one of the most commonly reported eye health problems. This syndrome is caused by abnormalities in the properties of the tear film. Current clinical tools to assess the tear film properties have shown certain limitations. The traditional invasive methods for the assessment of tear film quality, which are used by most clinicians, have been criticized for the lack of reliability and/or repeatability. A range of non-invasive methods of tear assessment have been investigated, but also present limitations. Hence no “gold standard” test is currently available to assess the tear film integrity. Therefore, improving techniques for the assessment of the tear film quality is of clinical significance and the main motivation for the work described in this thesis. In this study the tear film surface quality (TFSQ) changes were investigated by means of high-speed videokeratoscopy (HSV). In this technique, a set of concentric rings formed in an illuminated cone or a bowl is projected on the anterior cornea and their reflection from the ocular surface imaged on a charge-coupled device (CCD). The reflection of the light is produced in the outer most layer of the cornea, the tear film. Hence, when the tear film is smooth the reflected image presents a well structure pattern. In contrast, when the tear film surface presents irregularities, the pattern also becomes irregular due to the light scatter and deviation of the reflected light. The videokeratoscope provides an estimate of the corneal topography associated with each Placido disk image. Topographical estimates, which have been used in the past to quantify tear film changes, may not always be suitable for the evaluation of all the dynamic phases of the tear film. However the Placido disk image itself, which contains the reflected pattern, may be more appropriate to assess the tear film dynamics. A set of novel routines have been purposely developed to quantify the changes of the reflected pattern and to extract a time series estimate of the TFSQ from the video recording. The routine extracts from each frame of the video recording a maximized area of analysis. In this area a metric of the TFSQ is calculated. Initially two metrics based on the Gabor filter and Gaussian gradient-based techniques, were used to quantify the consistency of the pattern’s local orientation as a metric of TFSQ. These metrics have helped to demonstrate the applicability of HSV to assess the tear film, and the influence of contact lens wear on TFSQ. The results suggest that the dynamic-area analysis method of HSV was able to distinguish and quantify the subtle, but systematic degradation of tear film surface quality in the inter-blink interval in contact lens wear. It was also able to clearly show a difference between bare eye and contact lens wearing conditions. Thus, the HSV method appears to be a useful technique for quantitatively investigating the effects of contact lens wear on the TFSQ. Subsequently a larger clinical study was conducted to perform a comparison between HSV and two other non-invasive techniques, lateral shearing interferometry (LSI) and dynamic wavefront sensing (DWS). Of these non-invasive techniques, the HSV appeared to be the most precise method for measuring TFSQ, by virtue of its lower coefficient of variation. While the LSI appears to be the most sensitive method for analyzing the tear build-up time (TBUT). The capability of each of the non-invasive methods to discriminate dry eye from normal subjects was also investigated. The receiver operating characteristic (ROC) curves were calculated to assess the ability of each method to predict dry eye syndrome. The LSI technique gave the best results under both natural blinking conditions and in suppressed blinking conditions, which was closely followed by HSV. The DWS did not perform as well as LSI or HSV. The main limitation of the HSV technique, which was identified during the former clinical study, was the lack of the sensitivity to quantify the build-up/formation phase of the tear film cycle. For that reason an extra metric based on image transformation and block processing was proposed. In this metric, the area of analysis was transformed from Cartesian to Polar coordinates, converting the concentric circles pattern into a quasi-straight lines image in which a block statistics value was extracted. This metric has shown better sensitivity under low pattern disturbance as well as has improved the performance of the ROC curves. Additionally a theoretical study, based on ray-tracing techniques and topographical models of the tear film, was proposed to fully comprehend the HSV measurement and the instrument’s potential limitations. Of special interested was the assessment of the instrument’s sensitivity under subtle topographic changes. The theoretical simulations have helped to provide some understanding on the tear film dynamics, for instance the model extracted for the build-up phase has helped to provide some insight into the dynamics during this initial phase. Finally some aspects of the mathematical modeling of TFSQ time series have been reported in this thesis. Over the years, different functions have been used to model the time series as well as to extract the key clinical parameters (i.e., timing). Unfortunately those techniques to model the tear film time series do not simultaneously consider the underlying physiological mechanism and the parameter extraction methods. A set of guidelines are proposed to meet both criteria. Special attention was given to a commonly used fit, the polynomial function, and considerations to select the appropriate model order to ensure the true derivative of the signal is accurately represented. The work described in this thesis has shown the potential of using high-speed videokeratoscopy to assess tear film surface quality. A set of novel image and signal processing techniques have been proposed to quantify different aspects of the tear film assessment, analysis and modeling. The dynamic-area HSV has shown good performance in a broad range of conditions (i.e., contact lens, normal and dry eye subjects). As a result, this technique could be a useful clinical tool to assess tear film surface quality in the future.

Evolutionary biology of Gondwanan non-biting midges (Diptera: Chironomidae)

The potential restriction to effective dispersal and gene flow caused by habitat fragmentation can apply to multiple levels of evolutionary scale; from the fragmentation of ancient supercontinents driving diversification and speciation on disjunct landmasses, to the isolation of proximate populations as a result of their inability to cross intervening unsuitable habitat. Investigating the role of habitat fragmentation in driving diversity within and among taxa can thus include inferences of phylogenetic relationships among taxa, assessments of intraspecific phylogeographic structure and analyses of gene flow among neighbouring populations. The proposed Gondwanan clade within the chironomid (non-biting midge) subfamily Orthocladiinae (Diptera: Chironomidae) represents a model system for investigating the role that population fragmentation and isolation has played at different evolutionary scales. A pilot study by Krosch et al (2009) indentified several highly divergent lineages restricted to ancient rainforest refugia and limited gene flow among proximate sites within a refuge for one member of this clade, Echinocladius martini Cranston. This study provided a framework for investigating the evolutionary history of this taxon and its relatives more thoroughly. Populations of E. martini were sampled in the Paluma bioregion of northeast Queensland to investigate patterns of fine-scale within- and among-stream dispersal and gene flow within a refuge more rigorously. Data was incorporated from Krosch et al (2009) and additional sites were sampled up- and downstream of the original sites. Analyses of genetic structure revealed strong natal site fidelity and high genetic structure among geographically proximate streams. Little evidence was found for regular headwater exchange among upstream sites, but there was distinct evidence for rare adult flight among sites on separate stream reaches. Overall, however, the distribution of shared haplotypes implied that both larval and adult dispersal was largely limited to the natal stream channel. Patterns of regional phylogeographic structure were examined in two related austral orthoclad taxa – Naonella forsythi Boothroyd from New Zealand and Ferringtonia patagonica Sæther and Andersen from southern South America – to provide a comparison with patterns revealed in their close relative E. martini. Both taxa inhabit tectonically active areas of the southern hemisphere that have also experienced several glaciation events throughout the Plio-Pleistocene that are thought to have affected population structure dramatically in many taxa. Four highly divergent lineages estimated to have diverged since the late Miocene were revealed in each taxon, mirroring patterns in E. martini; however, there was no evidence for local geographical endemism, implying substantial range expansion post-diversification. The differences in pattern evident among the three related taxa were suggested to have been influenced by variation in the responses of closed forest habitat to climatic fluctuations during interglacial periods across the three landmasses. Phylogeographic structure in E. martini was resolved at a continental scale by expanding upon the sampling design of Krosch et al (2009) to encompass populations in southeast Queensland, New South Wales and Victoria. Patterns of phylogeographic structure were consistent with expectations and several previously unrecognised lineages were revealed from central- and southern Australia that were geographically endemic to closed forest refugia. Estimated divergence times were congruent with the timing of Plio-Pleistocene rainforest contractions across the east coast of Australia. This suggested that dispersal and gene flow of E. martini among isolated refugia was highly restricted and that this taxon was susceptible to the impacts of habitat change. Broader phylogenetic relationships among taxa considered to be members of this Gondwanan orthoclad group were resolved in order to test expected patterns of evolutionary affinities across the austral continents. The inferred phylogeny and estimated divergence times did not accord with expected patterns based on the geological sequence of break-up of the Gondwanan supercontinent and implied instead several transoceanic dispersal events post-vicariance. Difficulties in appropriate taxonomic sampling and accurate calibration of molecular phylogenies notwithstanding, the sampling regime implemented in the current study has been the most intensive yet performed for austral members of the Orthocladiinae and unsurprisingly has revealed both novel taxa and phylogenetic relationships within and among described genera. Several novel associations between life stages are made here for both described and previously unknown taxa. Investigating evolutionary relationships within and among members of this clade of proposed Gondwanan orthoclad taxa has demonstrated that a complex interaction between historical population fragmentation and dispersal at several levels of evolutionary scale has been important in driving diversification in this group. While interruptions to migration, colonisation and gene flow driven by population fragmentation have clearly contributed to the development and maintenance of much of the diversity present in this group, long-distance dispersal has also played a role in influencing diversification of continental biotas and facilitating gene flow among disjunct populations.

Benchmarking local E-Government

Increasingly, almost everything we do in our daily lives is being influenced by information and communications technologies (ICTs) including the Internet. The task of governance is no exception with an increasing number of national, state, and local governments utilizing ICTs to support government operations, engage citizens, and provide government services. As with other things, the process of governance is now being prefixed with an “e”. E-governance can range from simple Web sites that convey basic information to complex sites that transform the customary ways of delivering all sorts of government services. In this respect local e-government is the form of e-governance that specifically focuses on the online delivery of suitable local services by local authorities. In practice local e-government reflects four dimensions, each one dealing with the functions of government itself. The four are: (a) e-services, the electronic delivery of government information, programs, and services often over the Internet; (b) e-management, the use of information technology to improve the management of government. This might range from streamlining business processes to improving the flow of information within government departments; (c) e-democracy the use of electronic communication vehicles, such as e-mail and the Internet, to increase citizen participation in the public decision-making process; (d) e-commerce, the exchange of money for goods and services over the Internet which might include citizens paying taxes and utility bills, renewing vehicle registrations, and paying for recreation programs, or government buying office supplies and auctioning surplus equipment (Cook, LaVigne, Pagano, Dawes, & Pardo, 2002). Commensurate with the rapid increase in the process of developing e-governance tools, there has been an increased interest in benchmarking the process of local e-governance. This benchmarking, which includes the processes involved in e-governance as well as the extent of e-governance adoption or take-up is important as it allows for improved processes and enables government agencies to move towards world best practice. It is within this context that this article discusses benchmarking local e-government. It brings together a number of discussions regarding the significance of benchmarking, best practices and actions for local e-government, and key elements of a successful local e-government project.

Early osteogenic response of osteoprogenitor cells on modified titanium implant surfaces leads to improved osteogenesis

Background: Implant surface micro-roughness and hydrophilicity are known to improve the osteogenic differentiation potential of osteoprogenitor cells. This study was aimed to determine whether topographically and chemically modified titanium implant surfaces stimulate an initial osteogenic response in osteoprogenitor cells, which leads to their improved osteogenesis. ----- ----- Methods: Statistical analysis of microarray gene expression profiling data available from studies (at 72 hours) on sand-blasted, large grit acid etched (SLA) titanium surfaces was performed. Subsequently, human osteoprogenitor cells were cultured on SLActive (hydrophilic SLA), SLA and polished titanium surfaces for 24 hours, 3 days and 7 days. The expression of BMP2, BMP6, BMP2K, SP1, ACVR1, FZD6, WNT5A, PDLIM7, ITGB1, ITGA2, OCN, OPN, ALP and RUNX2 were studied using qPCR. ----- ----- Results: Several functional clusters related to osteogenesis were highlighted when genes showing statistically significant differences (from microarray data at 72 hours) in expression on SLA surface (compared with control surface) were analysed using DAVID (online tool). This indicates that differentiation begins very early in response to modified titanium surfaces. At 24 hours, ACVR1 (BMP pathway), FZD6 (Wnt pathway) and SP1 (TGF-β pathway) were significantly up-regulated in cultures on the SLActive surface compared to the other surfaces. WNT5A and ITGB1 also showed higher expression on the modified surfaces. Gene expression patterns on Day 3 and Day 7 did not reveal any significant differences.----- ----- Conclusion: These results suggest that the initial molecular response of osteoprogenitor cells to modified titanium surfaces may be responsible for an improved osteogenic response via the BMP and Wnt signalling pathways.