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Abstract:Although social factors affecting recycling have been widely researched, the effect of spatial and physical factors posed by medium-density housing, such as townhouses, is less understood. Using the Theory of Planned Behaviour, the relative effect of three sets of factors on household recycling in townhouses are examined, including 'attitude' (about recycling), 'subjective norm' (social pressure), and 'perceived behaviour control' (ability to recycle). A questionnaire survey of 300 households was conducted in Equestria, an enclosed middle-income residential estate consisting of several townhouse complexes. Confirmatory factor analysis verified the three factor measurement model for recycling participation. Both recyclers and non-recyclers showed positive attitudes toward recycling and felt social pressure to recycle. Non-recyclers, however, felt significantly less able to recycle. Most recyclers as well as non-recyclers indicated that certain proposals for increasing recycling may cause them to recycle more, in particular a system through which the management agency arranges access for a recycling company to collect recyclables from strategically located collection points inside the complex. Urban planning and design recommendations for facilitating recycling in townhouses are discussed.

What methodologies do we write about, and what type of research do we actually conduct and build upon in planning? Since the 1980s, planners have argued for more qualitative research within an interpretative paradigm. A content analysis of articles in Journal of Planning Education and Research do show a majority of qualitative studies, but cast within a pragmatic rather than an interpretative paradigm. More recently, planners have reiterated the need for qualitative research, especially participatory and applied forms of research within a critical social science paradigm. Some recommendations for planning education and research are discussed.

In this paper we discuss the challenges and optimisations opportunities when solving a large number of small, equally sized discretised PDEs on regular grids. We present an extension of the OPS (Oxford Parallel library for Structured meshes) embedded Domain Specific Language, and show how support can be added for solving multiple systems, and how OPS makes it easy to deploy a variety of transformations and optimisations. The new capabilities in OPS allow to automatically apply data structure transformations, as well as execution schedule transformations to deliver high performance on a variety of hardware platforms. We evaluate our work on an industrially representative finance simulation on Intel CPUs, as well as NVIDIA GPUs.

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We demonstrate the flexibility and ease of use of C++ algorithmic differentiation (AD) tools based on overloading to numerical patterns (kernels) arising in computational finance. While adjoint methods and AD have been known in the finance literature for some time, there are few tools capable of handling and integrating with the C++ codes found in production. Adjoint methods are also known to be very powerful but to potentially have infeasible memory requirements. We present several techniques for dealing with this problem and demonstrate them on numerical kernels which occur frequently in finance. We build the discussion around our own AD tool dco/c++ which is designed to handle arbitrary C++ codes and to be highly flexible, however the sketched concepts can certainly be transferred to other AD solutions including in-house tools. An archive of the source code for the numerical kernels as well as all the AD solutions discussed can be downloaded from an accompanying website. This includes documentation for the code and dco/c++. Trial licences for dco/c++ are available from NAG.

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