Transportation disadvantage impedance indexing: A methodological approach to reduce policy shortcomings

Access to transport systems and the connection to such systems provided to essential economic and social activities are critical to determine households' transportation disadvantage levels. In spite of the developments in better identifying transportation disadvantaged groups, the lack of effective policies resulted in the continuum of the issue as a significant problem. This paper undertakes a pilot case investigation as test bed for a new approach developed to reduce transportation policy shortcomings. The approach, ‘disadvantage-impedance index’, aims to ease transportation disadvantages by employing representative parameters to measure the differences between policy alternatives run in a simulation environment. Implemented in the Japanese town of Arao, the index uses trip-making behaviour and resident stated preference data. The results of the index reveal that even a slight improvement in accessibility and travel quality indicators makes a significant difference in easing disadvantages. The index, integrated into a four-step model, proves to be highly robust and useful in terms of quick diagnosis in capturing effective actions, and developing potentially efficient policies.

New graph-based algorithms to efficiently solve large scale open pit mining optimisation problems

In the mining optimisation literature, most researchers focused on two strategic-level and tactical-level open-pit mine optimisation problems, which are respectively termed ultimate pit limit (UPIT) or constrained pit limit (CPIT). However, many researchers indicate that the substantial numbers of variables and constraints in real-world instances (e.g., with 50-1000 thousand blocks) make the CPIT’s mixed integer programming (MIP) model intractable for use. Thus, it becomes a considerable challenge to solve the large scale CPIT instances without relying on exact MIP optimiser as well as the complicated MIP relaxation/decomposition methods. To take this challenge, two new graph-based algorithms based on network flow graph and conjunctive graph theory are developed by taking advantage of problem properties. The performance of our proposed algorithms is validated by testing recent large scale benchmark UPIT and CPIT instances’ datasets of MineLib in 2013. In comparison to best known results from MineLib, it is shown that the proposed algorithms outperform other CPIT solution approaches existing in the literature. The proposed graph-based algorithms leads to a more competent mine scheduling optimisation expert system because the third-party MIP optimiser is no longer indispensable and random neighbourhood search is not necessary.

Application of simulated annealing to data distribution for all-to-all comparison problems in homogeneous systems

Distributed systems are widely used for solving large-scale and data-intensive computing problems, including all-to-all comparison (ATAC) problems. However, when used for ATAC problems, existing computational frameworks such as Hadoop focus on load balancing for allocating comparison tasks, without careful consideration of data distribution and storage usage. While Hadoop-based solutions provide users with simplicity of implementation, their inherent MapReduce computing pattern does not match the ATAC pattern. This leads to load imbalances and poor data locality when Hadoop's data distribution strategy is used for ATAC problems. Here we present a data distribution strategy which considers data locality, load balancing and storage savings for ATAC computing problems in homogeneous distributed systems. A simulated annealing algorithm is developed for data distribution and task scheduling. Experimental results show a significant performance improvement for our approach over Hadoop-based solutions.

Distributed computing of all-to-all comparison problems in heterogeneous systems

The requirement of distributed computing of all-to-all comparison (ATAC) problems in heterogeneous systems is increasingly important in various domains. Though Hadoop-based solutions are widely used, they are inefficient for the ATAC pattern, which is fundamentally different from the MapReduce pattern for which Hadoop is designed. They exhibit poor data locality and unbalanced allocation of comparison tasks, particularly in heterogeneous systems. The results in massive data movement at runtime and ineffective utilization of computing resources, affecting the overall computing performance significantly. To address these problems, a scalable and efficient data and task distribution strategy is presented in this paper for processing large-scale ATAC problems in heterogeneous systems. It not only saves storage space but also achieves load balancing and good data locality for all comparison tasks. Experiments of bioinformatics examples show that about 89\% of the ideal performance capacity of the multiple machines have be achieved through using the approach presented in this paper.

Transdisciplinary synthesis for ecosystem science, policy and management: The Australian experience

Mitigating the environmental effects of global population growth, climatic change and increasing socio-ecological complexity is a daunting challenge. To tackle this requires synthesis: the integration of disparate information to generate novel insights from heterogeneous, complex situations where there are diverse perspectives. Since 1995, a structured approach to inter-, multi- and trans-disciplinary1 collaboration around big science questions has been supported through synthesis centres around the world. These centres are finding an expanding role due to ever-accumulating data and the need for more and better opportunities to develop transdisciplinary and holistic approaches to solve real-world problems. The Australian Centre for Ecological Analysis and Synthesis (ACEAS ) has been the pioneering ecosystem science synthesis centre in the Southern Hemisphere. Such centres provide analysis and synthesis opportunities for time-pressed scientists, policy-makers and managers. They provide the scientific and organisational environs for virtual and face-to-face engagement, impetus for integration, data and methodological support, and innovative ways to deliver synthesis products. We detail the contribution, role and value of synthesis using ACEAS to exemplify the capacity for synthesis centres to facilitate trans-organisational, transdisciplinary synthesis. We compare ACEAS to other international synthesis centres, and describe how it facilitated project teams and its objective of linking natural resource science to policy to management. Scientists and managers were brought together to actively collaborate in multi-institutional, cross-sectoral and transdisciplinary research on contemporary ecological problems. The teams analysed, integrated and synthesised existing data to co-develop solution-oriented publications and management recommendations that might otherwise not have been produced. We identify key outcomes of some ACEAS working groups which used synthesis to tackle important ecosystem challenges. We also examine the barriers and enablers to synthesis, so that risks can be minimised and successful outcomes maximised. We argue that synthesis centres have a crucial role in developing, communicating and using synthetic transdisciplinary research.

Parenting and the behavior problems of young children with an intellectual disability: Concurrent and longitudinal relationships in a population-based study

We examined parenting behaviors, and their association with concurrent and later child behavior problems. Children with an intellectual disability (ID) were identified from a UK birth cohort (N  =  516 at age 5). Compared to parents of children without an ID, parents of children with an ID used discipline less frequently, but reported a more negative relationship with their child. Among children with an ID, discipline, and home atmosphere had no long-term association with behavior problems, whereas relationship quality did: closer relationships were associated with fewer concurrent and later child behavior problems. Increased parent-child conflict was associated with greater concurrent and later behavior problems. Parenting programs in ID could target parent-child relationship quality as a potential mediator of behavioral improvements in children.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

We know this: How to apply what you already know to treat alcohol and other drug problems

Background Implementing effective AOD supports and treatments into our daily practice can occur via a range of strategies. While specialist treatments exclusively targeting pathways toward substance reduction are an option, it is often not within the scope of many psychologists working in generalist or tertiary mental health settings. Regardless of the perceived barriers for integrating AOD practice into our work, there are key principles and approaches that can be adopted to improve the outcomes for many clients. Aim Irrespective of the client’s perceived need to address AOD issues, significant substance use will impact on the development, prognosis and treatment of most mental health conditions. Embedding AOD practice across our clinical work requires an openness to consider evidence-based approaches for all levels of substance use. Method This presentation will outline a series of approaches that all practitioners can adopt, based on the principles of harm reduction and empowerment of client’s choice. An emphasis will be made toward outlining approaches that are consistent with best practice, easily accessible and do not require extensive resources to embed. Conclusion Applying effective AOD treatments as a standard treatment component is achievable for all practitioners and is essential for achieving better outcomes for a high proportion of the community accessing treatment from psychologists.

The effect of surface tension in porous wave maker problems

Using a mixed-type Fourier transform of a general form in the case of water of infinite depth and the method of eigenfunction expansion in the case of water of finite depth, several boundary-value problems involving the propagation and scattering of time harmonic surface water waves by vertical porous walls have been fully investigated, taking into account the effect of surface tension also. Known results are recovered either directly or as particular cases of the general problems under consideration.

Problems with geoengineering schemes to combat climate change

The accelerated rate of increase in atmospheric CO2 concentration in recent years has revived the idea of stabilizing the global climate through geoengineering schemes. Majority of the proposed geoengineering schemes will attempt to reduce the amount of solar radiation absorbed by our planet. Climate modelling studies of these so called 'sunshade geoengineering schemes' show that global warming from increasing concentrations of CO2 can be mitigated by intentionally manipulating the amount of sunlight absorbed by the climate system. These studies also suggest that the residual changes could be large on regional scales, so that climate change may not be mitigated on a local basis. More recent modelling studies have shown that these schemes could lead to a slow-down in the global hydrological cycle. Other problems such as changes in the terrestrial carbon cycle and ocean acidification remain unsolved by sunshade geoengineering schemes. In this article, I review the proposed geoengineering schemes, results from climate models and discuss why geoengineering is not the best option to deal with climate change.

A methodological survey of future mobility literature: Opportunities for design research

This research establishes that the study of mobility and transportation is multi-disciplinary and highly complex, involving the diverse interplay between infrastructural and psychological factors. Coincidently, a new paradigm in personal mobility is developing. A new generation of mobility solutions is becoming widely available in the form of car and ride sharing services. These services build on the assumption that customers no longer need ownership of a product in order to benefit from it. With the emergence of this new paradigm, this paper presents a methodological review of current practises used by the wider research community. Therefore, this research piece aims to explore methodological approaches involved in the study the effect of community on an individual’s attitudes, perceptions and behaviours of future mobility solutions. The results of this review indicate that the majority of published literature uses quantitative methods as opposed to qualitative and even fewer studies have sought to understand the human factors in these new mobility solutions. This gap in knowledge is a valuable opportunity for design. Inherently qualitative and human focused, design research can fill this gap in knowledge by applying distinctly user-centred methods such as persona design, narrative storytelling, and in-depth observations to discover deeper human insights.

Estimation of mineral-adhered biomass of Thiobacillusferrooxidans by protein assay-some problems and remedies

Enumeration of adhered cells of Thiobacillus ferrooxidans on sulphide minerals through protein assay poses problems due to interference from dissolved mineral constituents. The manner in which sulphide minerals such as pyrite, chalcopyrite, sphalerite, arsenopyrite and pyrrhotite interfere with bacterial protein estimation is demonstrated. Such interferences can be minimised either through dilution or addition of H2O2 to the filtrate after hot alkaline digestion of the biotreated mineral samples.

Maximal regularity for second order non-autonomous Cauchy problems

We consider some non-autonomous second order Cauchy problems of the form u + B(t)(u) over dot + A(t)u = f (t is an element of [0, T]), u(0) = (u) over dot(0) = 0. We assume that the first order problem (u) over dot + B(t)u = f (t is an element of [0, T]), u(0) = 0, has L-p-maximal regularity. Then we establish L-p-maximal regularity of the second order problem in situations when the domains of B(t(1)) and A(t(2)) always coincide, or when A(t) = kappa B(t).

A three-dimensional hybrid smoothed finite element method (H-SFEM) for nonlinear solid mechanics problems

This paper presents a novel three-dimensional hybrid smoothed finite element method (H-SFEM) for solid mechanics problems. In 3D H-SFEM, the strain field is assumed to be the weighted average between compatible strains from the finite element method (FEM) and smoothed strains from the node-based smoothed FEM with a parameter α equipped into H-SFEM. By adjusting α, the upper and lower bound solutions in the strain energy norm and eigenfrequencies can always be obtained. The optimized α value in 3D H-SFEM using a tetrahedron mesh possesses a close-to-exact stiffness of the continuous system, and produces ultra-accurate solutions in terms of displacement, strain energy and eigenfrequencies in the linear and nonlinear problems. The novel domain-based selective scheme is proposed leading to a combined selective H-SFEM model that is immune from volumetric locking and hence works well for nearly incompressible materials. The proposed 3D H-SFEM is an innovative and unique numerical method with its distinct features, which has great potential in the successful application for solid mechanics problems.

A pseudo-dynamical systems approach to a class of inverse problems in engineering

A pseudo-dynamical approach for a class of inverse problems involving static measurements is proposed and explored. Following linearization of the minimizing functional associated with the underlying optimization problem, the new strategy results in a system of linearized ordinary differential equations (ODEs) whose steady-state solutions yield the desired reconstruction. We consider some explicit and implicit schemes for integrating the ODEs and thus establish a deterministic reconstruction strategy without an explicit use of regularization. A stochastic reconstruction strategy is then developed making use of an ensemble Kalman filter wherein these ODEs serve as the measurement model. Finally, we assess the numerical efficacy of the developed tools against a few linear and nonlinear inverse problems of engineering interest.