Effective shear modulus approach for two dimensional solids and plate bending problems by meshless point collocation method

For the analysis of material nonlinearity, an effective shear modulus approach based on the strain control method is proposed in this paper by using point collocation method. Hencky’s total deformation theory is used to evaluate the effective shear modulus, Young’s modulus and Poisson’s ratio, which are treated as spatial field variables. These effective properties are obtained by the strain controlled projection method in an iterative manner. To evaluate the second order derivatives of shape function at the field point, the radial basis function (RBF) in the local support domain is used. Several numerical examples are presented to demonstrate the efficiency and accuracy of the proposed method and comparisons have been made with analytical solutions and the finite element method (ABAQUS).

M-ary trees for combinatorial asset management decision problems

A novel m-ary tree based approach is presented to solve asset management decisions which are combinatorial in nature. The approach introduces a new dynamic constraint based control mechanism which is capable of excluding infeasible solutions from the solution space. The approach also provides a solution to the challenges with ordering of assets decisions.

Hierarchical robust design optimisation of shock control bump devices for airfoil drag reduction

The paper investigates a detailed Active Shock Control Bump Design Optimisation on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 to reduce cruise drag at transonic flow conditions using Evolutionary Algorithms (EAs) coupled to a robust design approach. For the uncertainty design parameters, the positions of boundary layer transition (xtr) and the coefficient of lift (Cl) are considered (250 stochastic samples in total). In this paper, two robust design methods are considered; the first approach uses a standard robust design method, which evaluates one design model at 250 stochastic conditions for uncertainty. The second approach is the combination of a standard robust design method and the concept of hierarchical (multi-population) sampling (250, 50, 15) for uncertainty. Numerical results show that the evolutionary optimization method coupled to uncertainty design techniques produces useful and reliable Pareto optimal SCB shapes which have low sensitivity and high aerodynamic performance while having significant total drag reduction. In addition,it also shows the benefit of using hierarchical robust method for detailed uncertainty design optimization.

On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Serving as a powerful tool for extracting localized variations in non-stationary signals, applications of wavelet transforms (WTs) in traffic engineering have been introduced; however, lacking in some important theoretical fundamentals. In particular, there is little guidance provided on selecting an appropriate WT across potential transport applications. This research described in this paper contributes uniquely to the literature by first describing a numerical experiment to demonstrate the shortcomings of commonly-used data processing techniques in traffic engineering (i.e., averaging, moving averaging, second-order difference, oblique cumulative curve, and short-time Fourier transform). It then mathematically describes WT’s ability to detect singularities in traffic data. Next, selecting a suitable WT for a particular research topic in traffic engineering is discussed in detail by objectively and quantitatively comparing candidate wavelets’ performances using a numerical experiment. Finally, based on several case studies using both loop detector data and vehicle trajectories, it is shown that selecting a suitable wavelet largely depends on the specific research topic, and that the Mexican hat wavelet generally gives a satisfactory performance in detecting singularities in traffic and vehicular data.

See-and-avoid quadcopter using fuzzy control optimized by cross-entropy

In this work we present an optimized fuzzy visual servoing system for obstacle avoidance using an unmanned aerial vehicle. The cross-entropy theory is used to optimise the gains of our controllers. The optimization process was made using the ROS-Gazebo 3D simulation with purposeful extensions developed for our experiments. Visual servoing is achieved through an image processing front-end that uses the Camshift algorithm to detect and track objects in the scene. Experimental flight trials using a small quadrotor were performed to validate the parameters estimated from simulation. The integration of cross- entropy methods is a straightforward way to estimate optimal gains achieving excellent results when tested in real flights.

Low rank Runge-Kutta methods, symplecticity and stochastic Hamiltonian problems with additive noise

In this paper we extend the ideas of Brugnano, Iavernaro and Trigiante in their development of HBVM($s,r$) methods to construct symplectic Runge-Kutta methods for all values of $s$ and $r$ with $s\geq r$. However, these methods do not see the dramatic performance improvement that HBVMs can attain. Nevertheless, in the case of additive stochastic Hamiltonian problems an extension of these ideas, which requires the simulation of an independent Wiener process at each stage of a Runge-Kutta method, leads to methods that have very favourable properties. These ideas are illustrated by some simple numerical tests for the modified midpoint rule.

Problems in the assessment of magnesium depletion in the rat by in vivo 31P NMR

Prior in vitro studies, utilizing 31Pn uclear magnetic resonance (31PN MR) to measure the chemical shift (CT) of 0-ATP and lengthening of the phosphocreatine spin-spin (7"') relaxation time, suggested an assessment of their efficacy in measuring magnesium depletion in vivo. Dietary magnesium depletion (Me$) produced markedly lower magnesium in plasma (0.44 vs 1. I3 mmol/liter) and bone (1 30 vs 190 pmol/g) but much smaller changes in muscle (41 vs 45 pmol/g, P < 0.01), heart (42.5 vs 44.6 prnol/g), and brain (30 vs 32 pmollg). NMR experiments in anesthetized rats in a Bruker 7-T vertical bore magnet showed that in M e $ rats there was a significant change in brain j3-ATP shift (16.15 vs 16.03 ppm, P < 0.05). These chemical shifts gave a calculated free [Mg"] of 0.71 mM (control) and 0.48 mM (MgZ+$). In muscle the change in j3-ATP shift was not significant (Me$ 15.99 ppm, controls 15.96 ppm), corresponding to a calculated free M P of 0.83 and 0.95 mM, respectively. Phosphccreatine Tz (Carr-Purcell, spin-echo pulse sequence) was no different with M e $ in muscle in vivo (surface coil) (M$+$ 136, control 142 ms) or in isolated perfused hearts (Helmholtz coil) (control 83, M e $ 92 ms). 3'P NMR is severely limited in its ability to detect dietary magnesium depletion in vivo. Measurement of j3-ATP shift in brain may allow studies of the effects of interaction in group studies but does not allow prediction of an individual magnesium status.

Determining the optimal proportion of design in design-build request for proposals (RFPs)

The design-build (DB) system is a popular and effective delivery method of construction projects worldwide. After owners decide to procure their projects through the DB system, they may wish to determine the optimal proportion of design to be provided in the DB request for proposals (RFPs), which serve as solicitations for design-builders and describe the scope of work. However, this presents difficulties to DB owners and there is little, if any, systematic research in this area. This paper reports on an empirical study in the USA entailing both an online questionnaire survey and Delphi survey to identify and evaluate the factors influencing owners’ decisions in determining the proportion of design to include in DB RFPs. Eleven factors are identified, i.e. (1) clarity of project scope; (2) applicability of performance specifications; (3) desire for design innovation; (4) site constraints; (5) availability of competent design-builders; (6) project control requirements; (7) user group involvement level; (8) third party requirements; (9) owner experience with DB; (10) project complexity; and (11) schedule constraints. A statistically significant agreement on the eleven factors was also obtained from the (mainly non-owner) Delphi experts. Although some of the experts hold different opinions on how these factors affect the proportion of design, these findings furnish various stakeholders with a better understanding of the delivery process of DB projects and the appropriate provision of project information in DB RFPs. As the result is mainly industry opinion concerning the optimal proportion of design, in addition and for completeness, future studies should be conducted to obtain a big picture of the optimal proportion of design by means of seeking owners’ inputs.

A randomised trial of a psychosocial intervention for cancer patients integrated into routine care: The PROMPT study (promoting optimal outcomes in mood through tailored psychosocial therapies)

Background Despite evidence that up to 35% of patients with cancer experience significant distress, access to effective psychosocial care is limited by lack of systematic approaches to assessment, a paucity of psychosocial services, and patient reluctance to accept treatment either because of perceived stigma or difficulties with access to specialist psycho-oncology services due to isolation or disease burden. This paper presents an overview of a randomised study to evaluate the effectiveness of a brief tailored psychosocial Intervention delivered by health professionals in cancer care who undergo focused training and participate in clinical supervision. Methods/design Health professionals from the disciplines of nursing, occupational therapy, speech pathology, dietetics, physiotherapy or radiation therapy will participate in training to deliver the psychosocial Intervention focusing on core concepts of supportive-expressive, cognitive and dignity-conserving care. Health professional training will consist of completion of a self-directed manual and participation in a skills development session. Participating health professionals will be supported through structured clinical supervision whilst delivering the Intervention. In the stepped wedge design each of the 5 participating clinical sites will be allocated in random order from Control condition to Training then delivery of the Intervention. A total of 600 patients will be recruited across all sites. Based on level of distress or risk factors eligible patients will receive up to 4 sessions, each of up to 30 minutes in length, delivered face-to-face or by telephone. Participants will be assessed at baseline and 10-week follow-up. Patient outcome measures include anxiety and depression, quality of life, unmet psychological and supportive care needs. Health professional measures include psychological morbidity, stress and burnout. Process evaluation will be conducted to assess perceptions of participation in the study and the factors that may promote translation of learning into practice. Discussion This study will provide important information about the effectiveness of a brief tailored psychological Intervention for patients with cancer and the potential to prevent development of significant distress in patients considered at risk. It will yield data about the feasibility of this model of care in routine clinical practice and identify enablers and barriers to its systematic implementation in cancer settings.

Smart grid-demand side response model for optimization air conditioning

The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of Global Navigation Satellite Systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods, and compared with the decorrelation number and with the condition number which are currently used as the judging criterion to measure the correlation of ambiguity variance-covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations respectively, showing the potential for processing high dimension integer parameters in multi-GNSS environment.

Types of foot problems seen by Australian podiatrists

Background: Understanding frequency of foot problems can assist health care planners with resource deployment to new and emerging services such as paediatric podiatry and focus future research on the most salient foot conditions. Methods: A review of 2187 patient consultations during a three month period was conducted. Patient medical and podiatric history was coded using industry standards. All patients were recruited for convenience from a metropolitan university podiatry clinic. Results: 392 new patients were identified with mean age 40.6 years old (range 1–95), with 65% being female. Arthritic diseases, asthma, hypertension and allergies were the most common medical conditions reported. The frequency of new consultations in younger people (n = 102; 27%) exceeded those of the elderly (n = 75; 20%). Conversely, the elderly were nearly three times more prevalent in this cohort (n = 910; 43%) compared to younger people (n = 332; 16%). Conclusion: This study illustrates the diverse nature of pathology seen by podiatrists. Knowledge that skin lesions are highly prevalent is of relevance to health departments, given the aging nature of most populations. Moreover there appears to be a growing trend in the number of young people who present for care, however government funded access to these services are limited.

Identification of evidence-based biospecimen quality-control tools

Control of biospecimen quality that is linked to processing is one of the goals of biospecimen science. Consensus is lacking, however, regarding optimal sample quality-control (QC) tools (ie, markers and assays). The aim of this review was to identify QC tools, both for fluid and solid-tissue samples, based on a comprehensive and critical literature review. The most readily applicable tools are those with a known threshold for the preanalytical variation and a known reference range for the QC analyte. Only a few meaningful markers were identified that meet these criteria, such as CD40L for assessing serum exposure at high temperatures and VEGF for assessing serum freeze-thawing. To fully assess biospecimen quality, multiple QC markers are needed. Here we present the most promising biospecimen QC tools that were identified.

Glider path-planning for optimal sampling of mesocale eddies

Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.