Analyzing multi-fiber reconstruction in high angular resolution diffusion imaging using the tensor distribution function

High-angular resolution diffusion imaging (HARDI) can reconstruct fiber pathways in the brain with extraordinary detail, identifying anatomical features and connections not seen with conventional MRI. HARDI overcomes several limitations of standard diffusion tensor imaging, which fails to model diffusion correctly in regions where fibers cross or mix. As HARDI can accurately resolve sharp signal peaks in angular space where fibers cross, we studied how many gradients are required in practice to compute accurate orientation density functions, to better understand the tradeoff between longer scanning times and more angular precision. We computed orientation density functions analytically from tensor distribution functions (TDFs) which model the HARDI signal at each point as a unit-mass probability density on the 6D manifold of symmetric positive definite tensors. In simulated two-fiber systems with varying Rician noise, we assessed how many diffusionsensitized gradients were sufficient to (1) accurately resolve the diffusion profile, and (2) measure the exponential isotropy (EI), a TDF-derived measure of fiber integrity that exploits the full multidirectional HARDI signal. At lower SNR, the reconstruction accuracy, measured using the Kullback-Leibler divergence, rapidly increased with additional gradients, and EI estimation accuracy plateaued at around 70 gradients.

Priority threat management of invasive animals to protect biodiversity under climate change

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one-sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost-effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost-effectiveness was relatively unaffected by including climate change into decision-making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.

Randomised clinical trial of a family-based lifestyle intervention for childhood obesity involving parents as the exclusive agents of change

Parent-centred interventions for childhood obesity aim to improve parents' skills and confidence in managing children's dietary and activity patterns, and in promoting a healthy lifestyle in their family. However, few studies assess changes in parenting over the course of treatment. This study describes the evaluation of a lifestyle-specific parenting program (Group Lifestyle Triple P) on multiple child and parent outcomes. One-hundred-and-one families with overweight and obese 4- to 11-year-old children participated in an intervention or waitlist control condition. The 12-week intervention was associated with significant reductions in child BMI z score and weight-related problem behaviour. At the end of the intervention, parents reported increased confidence in managing children's weight-related behaviour, and less frequent use of inconsistent or coercive parenting practices. All short-term intervention effects were maintained at one-year follow-up assessment, with additional improvements in child body size. The results support the efficacy of Group Lifestyle Triple P and suggest that parenting influences treatment outcomes. Further research is needed to evaluate the long-term effectiveness of the intervention and to elucidate the mechanisms of change. © 2010 Elsevier Ltd.

Site and gender specificity of inheritance of bone mineral density

Differences in genetic control of BMD by skeletal sites and genders were examined by complex segregation analysis in 816 members of 147 families with probands with extreme low BMD. Spine BMD correlated more strongly in male-male comparisons and hip BMD in female-female comparisons, consistent with gender- and site-specificity of BMD heritability. Introduction: Evidence from studies in animals and humans suggests that the genetic control of bone mineral density (BMD) may differ at different skeletal sites and between genders. This question has important implications for the design and interpretation of genetic studies of osteoporosis. Methods: We examined the genetic profile of 147 families with 816 individuals recruited through probands with extreme low BMD (T-score < −2.5, Z-score < −2.0). Complex segregation analysis was performed using the Pedigree Analysis Package. BMD was measured by DXA at both lumbar spine (L1-L4) and femoral neck. Results: Complex segregation analysis excluded purely monogenic and environmental models of segregation of lumbar spine and femoral neck BMD in these families. Pure polygenic models were excluded at the lumbar spine when menopausal status was considered as a covariate, but not at the femoral neck. Mendelian models with a residual polygenic component were not excluded. These models were consistent with the presence of a rare Mendelian genotype of prevalence 3–19 %, causing high BMD at the hip and spine in these families, with additional polygenic effects. Total heritability range at the lumbar spine was 61–67 % and at the femoral neck was 44–67 %. Significant differences in correlation of femoral neck and lumbar spine BMD were observed between male and female relative pairs, with male-male comparisons exhibiting stronger lumbar spine BMD correlation than femoral neck, and female-female comparisons having greater femoral neck BMD correlation than lumbar spine. These findings remained true for parent-offspring correlations when menopausal status was taken into account. The recurrence risk ratio for siblings of probands of a Z-score < −2.0 was 5.4 at the lumbar spine and 5.9 at the femoral neck. Conclusions: These findings support gender- and site-specificity of the inheritance of BMD. These results should be considered in the design and interpretation of genetic studies of osteoporosis.

Extended Kalman filters using explicit and derivative-free local linearizations

We propose three variants of the extended Kalman filter (EKF) especially suited for parameter estimations in mechanical oscillators under Gaussian white noises. These filters are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDE-s). Besides a basic linearization of the non-linear drift functions via one-term replacements, linearizations using replacements through explicit Euler and Newmark expansions are also attempted in order to ensure higher closeness of true solutions with the linearized ones. Thus, unlike the conventional EKF, the proposed filters do not need computing derivatives (tangent matrices) at any stage. The measurements are synthetically generated by corrupting with noise the numerical solutions of the SDE-s through implicit versions of these linearizations. In order to demonstrate the effectiveness and accuracy of the proposed methods vis-à-vis the conventional EKF, numerical illustrations are provided for a few single degree-of-freedom (DOF) oscillators and a three-DOF shear frame with constant parameters.

Dependence of metal Auger intensity ratios on the effective charge on metal atoms

Metal Auger line intensity ratios were shown by Rao and others to be directly related to the occupancy of valence states. It is now shown that these intensity ratios are more generally related to the effective charge on the metal atom. The Auger intensity ratios are also directly proportional to valence band intensities of metals. Correlations of the intensity ratios with Auger parameters have also been examined.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

Characterization of Ion-Exchange Fibers for Controlled Drug Delivery

Increasing attention has been focused on methods that deliver pharmacologically active compounds (e.g. drugs, peptides and proteins) in a controlled fashion, so that constant, sustained, site-specific or pulsatile action can be attained. Ion-exchange resins have been widely studied in medical and pharmaceutical applications, including controlled drug delivery, leading to commercialisation of some resin based formulations. Ion-exchangers provide an efficient means to adjust and control drug delivery, as the electrostatic interactions enable precise control of the ion-exchange process and, thus, a more uniform and accurate control of drug release compared to systems that are based only on physical interactions. Unlike the resins, only few studies have been reported on ion-exchange fibers in drug delivery. However, the ion-exchange fibers have many advantageous properties compared to the conventional ion-exchange resins, such as more efficient compound loading into and release from the ion-exchanger, easier incorporation of drug-sized compounds, enhanced control of the ion-exchange process, better mechanical, chemical and thermal stability, and good formulation properties, which make the fibers attractive materials for controlled drug delivery systems. In this study, the factors affecting the nature and strength of the binding/loading of drug-sized model compounds into the ion-exchange fibers was evaluated comprehensively and, moreover, the controllability of subsequent drug release/delivery from the fibers was assessed by modifying the conditions of external solutions. Also the feasibility of ion-exchange fibers for simultaneous delivery of two drugs in combination was studied by dual loading. Donnan theory and theoretical modelling were applied to gain mechanistic understanding on these factors. The experimental results imply that incorporation of model compounds into the ion-exchange fibers was attained mainly as a result of ionic bonding, with additional contribution of non-specific interactions. Increasing the ion-exchange capacity of the fiber or decreasing the valence of loaded compounds increased the molar loading, while more efficient release of the compounds was observed consistently at conditions where the valence or concentration of the extracting counter-ion was increased. Donnan theory was capable of fully interpreting the ion-exchange equilibria and the theoretical modelling supported precisely the experimental observations. The physico-chemical characteristics (lipophilicity, hydrogen bonding ability) of the model compounds and the framework of the fibrous ion-exchanger influenced the affinity of the drugs towards the fibers and may, thus, affect both drug loading and release. It was concluded that precisely controlled drug delivery may be tailored for each compound, in particularly, by choosing a suitable ion-exchange fiber and optimizing the delivery system to take into account the external conditions, also when delivering two drugs simultaneously.

A modified pseudolikelihood approach for analysis of longitudinal data

We consider the analysis of longitudinal data when the covariance function is modeled by additional parameters to the mean parameters. In general, inconsistent estimators of the covariance (variance/correlation) parameters will be produced when the "working" correlation matrix is misspecified, which may result in great loss of efficiency of the mean parameter estimators (albeit the consistency is preserved). We consider using different "Working" correlation models for the variance and the mean parameters. In particular, we find that an independence working model should be used for estimating the variance parameters to ensure their consistency in case the correlation structure is misspecified. The designated "working" correlation matrices should be used for estimating the mean and the correlation parameters to attain high efficiency for estimating the mean parameters. Simulation studies indicate that the proposed algorithm performs very well. We also applied different estimation procedures to a data set from a clinical trial for illustration.

Bias reduction using stochastic approximation

The paper studies stochastic approximation as a technique for bias reduction. The proposed method does not require approximating the bias explicitly, nor does it rely on having independent identically distributed (i.i.d.) data. The method always removes the leading bias term, under very mild conditions, as long as auxiliary samples from distributions with given parameters are available. Expectation and variance of the bias-corrected estimate are given. Examples in sequential clinical trials (non-i.i.d. case), curved exponential models (i.i.d. case) and length-biased sampling (where the estimates are inconsistent) are used to illustrate the applications of the proposed method and its small sample properties.

A spatially explicit multi-competitor coexistence model of penaeid (shrimp) distribution on the Australian Great Barrier Reef

A spatially explicit multi-competitor coexistence model was developed for meta-populations of prawns (shrimp) occupying habitat patches across the Great Barrier Reef, where dispersal was localised and dispersal rates varied between species. Prawns were modelled as individuals moving to and from patches or cells according to pre-set decision rules. The landscape was simulated as a matrix of cells with each cell having a spatially explicit survival index for each species. Mixed species prawn assemblages moved over this simplified spatially explicit landscape. A low level of chronic random environmental disturbance was assumed (cyclone and tropical storm damage) with additional acute spatially confined disturbance due to commercial trawling, modelled as an increase in mortality affecting inter-specific competition. The general form of the results was for increased disturbance to favour good-colonising "generalist" species at the expense of good-competitor "specialists". Increasing fishing mortality (local patch extinctions) combined with poor colonising ability resulted in low equilibrium abundance for even the best competitor, while in the same circumstances the poorest competitor but best coloniser could have the highest equilibrium abundance. This mimics the switch from high-value prawn species to lower-value prawn species as trawl effort increases, reflected in historic catch and effort logbook data and reported anecdotaly from the north Queensland trawl fleet. To match the observed distribution and behaviour of prawn assemblages, a combination inter-species competition, a spatially explicit landscape, and a defined pattern of disturbance (trawling) was required. Modelling this combination could simulate not only general trends in spatial distribution of each of prawn species but also localised concentrations observed in the survey data

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Modelling the impact of traffic incidents on travel time reliability

Traffic incidents are recognised as one of the key sources of non-recurrent congestion that often leads to reduction in travel time reliability (TTR), a key metric of roadway performance. A method is proposed here to quantify the impacts of traffic incidents on TTR on freeways. The method uses historical data to establish recurrent speed profiles and identifies non-recurrent congestion based on their negative impacts on speeds. The locations and times of incidents are used to identify incidents among non-recurrent congestion events. Buffer time is employed to measure TTR. Extra buffer time is defined as the extra delay caused by traffic incidents. This reliability measure indicates how much extra travel time is required by travellers to arrive at their destination on time with 95% certainty in the case of an incident, over and above the travel time that would have been required under recurrent conditions. An extra buffer time index (EBTI) is defined as the ratio of extra buffer time to recurrent travel time, with zero being the best case (no delay). A Tobit model is used to identify and quantify factors that affect EBTI using a selected freeway segment in the Southeast Queensland, Australia network. Both fixed and random parameter Tobit specifications are tested. The estimation results reveal that models with random parameters offer a superior statistical fit for all types of incidents, suggesting the presence of unobserved heterogeneity across segments. What factors influence EBTI depends on the type of incident. In addition, changes in TTR as a result of traffic incidents are related to the characteristics of the incidents (multiple vehicles involved, incident duration, major incidents, etc.) and traffic characteristics.

Patterns of release of the secondary conidia of Claviceps africana, the sorghum ergot pathogen in Australia

Trials were conducted in southern Queensland, Australia between March and May 2003, 2004 and 2005 to study patterns of hourly and daily release of the secondary conidia of Claviceps africana and their relationships with weather parameters. Conidia were trapped for at least one hour on most (> 90%) days in 2003 and 2004, but only on 55% of days in 2005. Both the highest daily concentration of conidia, and the highest number of hours per day when conidia were trapped, were recorded 1-3 days after rainfall events. Although the pattern of conidial release was different every day, the highest hourly conidial concentrations occurred between 10.00 hours and 17.00 hours on 73% of all days in the three trials. Hours when conidia were trapped were characterized by higher median values of temperature, windspeed and vapour pressure deficit, lower relative humidity, and leaf wetness values of 0%, than hours when no conidia were recorded. The results indicate that fungicides need to be applied to the highly ergot-susceptible male sterile (A-) lines of sorghum in hybrid seed production blocks and breeders' nurseries as soon as possible after rainfall events to minimize ergot severity.

Long-term impacts of harvest residue management on nutrition, growth and productivity of an exotic pine plantation of sub-tropical Australia

Residue retention is an important issue in evaluating the sustainability of production forestry. However, its long-term impacts have not been studied extensively, especially in sub-tropical environments. This study investigated the long-term impact of harvest residue retention on tree nutrition, growth and productivity of a F1 hybrid (Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis) exotic pine plantation in sub-tropical Australia, under three harvest residue management regimes: (1) residue removal, RR0; (2) single residue retention, RR1; and (3) double residue retention, RR2. The experiment, established in 1996, is a randomised complete block design with 4 replicates. Tree growth measurements in this study were carried out at ages 2, 4, 6, 8 and 10 years, while foliar nutrient analyses were carried out at ages 2, 4, 6 and 10 years. Litter production and litter nitrogen (N) and phosphorus (P) measurements were carried out quarterly over a 15-month period between ages 9 and 10 years. Results showed that total tree growth was still greater in residue-retained treatments compared to the RR0 treatment. However, mean annual increments of diameter at breast height (MAID) and basal area (MAIB) declined significantly after age 4 years to about 68-78% at age 10 years. Declining foliar N and P concentrations accounted for 62% (p < 0.05) of the variation of growth rates after age 4 years, and foliar N and P concentrations were either marginal or below critical concentrations. In addition, litter production, and litter N and P contents were not significantly different among the treatments. This study suggests that the impact of residue retention on tree nutrition and growth rates might be limited over a longer period, and that the integration of alternative forest management practices is necessary to sustain the benefits of harvest residues until the end of the rotation.