Infection Control in design and construction work

Objective: To clarify how infection control requirements are represented, communicated, and understood in work interactions through the medical facility construction project life cycle. To assist project participants with effective infection control management by highlighting the nature of such requirements and presenting recommendations to aid practice. Background: A 4-year study regarding client requirement representation and use on National Health Service construction projects in the United Kingdom provided empirical evidence of infection control requirement communication and understanding through design and construction work interactions. Methods: An analysis of construction project resources (e.g., infection control regulations and room data sheets) was combined with semi-structured interviews with hospital client employees and design and construction professionals to provide valuable insights into the management of infection control issues. Results: Infection control requirements are representationally indistinct but also omnipresent through all phases of the construction project life cycle: Failure to recognize their nature, relevance, and significance can result in delays, stoppages, and redesign work. Construction project resources (e.g., regulatory guidance and room data sheets) can mask or obscure the meaning of infection control issues. Conclusions: A preemptive identification of issues combined with knowledge sharing activities among project stakeholders can enable infection control requirements to be properly understood and addressed. Such initiatives should also reference existing infection control regulatory guidance and advice.

Climate and construction delays: case study in Chile

Purpose – Construction projects usually suffer delays, and the causes of these delays and its cost overruns have been widely discussed, the weather being one of the most recurrent. The purpose of this paper is to analyze the influence of climate on standard construction work activities through a case study. Design/methodology/approach – By studying the extent at which some weather variables impede outdoor work from being effectively executed, new maps and tables for planning for delays are presented. In addition, a real case regarding the construction of several bridges in southern Chile is analyzed. Findings – Few studies have thoroughly addressed the influences of major climatic agents on the most common outdoor construction activities. The method detailed here provides a first approximation for construction planners to assess to what extent construction productivity will be influenced by the climate. Research limitations/implications – Although this study was performed in Chile, the simplified method proposed is entirely transferable to any other country, however, other weather or combinations of weather variables could be needed in other environments or countries. Practical implications – The implications will help reducing the negative social, economic and environmental outcomes that usually emerge from project delays. Originality/value – Climatic data were processed using extremely simple calculations to create a series of quantitative maps and tables that would be useful for any construction planner to decide the best moment of the year to start a project and, if possible, where to build it.

The (il)logical problem of heritage speaker bilingualism and incomplete acquisition

This Forum challenges and problematizes the term incomplete acquisition, which has been widely used to describe the state of competence of heritage speaker (HS) bilinguals for well over a decade (see, e.g., Montrul, 2008). It is suggested and defended that HS competence, while often different from monolingual peers, is in fact not incomplete (given any reasonable definition by the word incomplete), but simply distinct for reasons related to the realities of their environment.

Exposing the myth of the 1:5:200 ratio relating initial cost, maintenance and staffing costs of office buildings

In an attempt to focus clients' minds on the importance of considering the construction and maintenance costs of a commercial office building (both as a factor in staff productivity and as a fraction of lifetime staff costs) there is an often-quoted ratio of costs of 1:5:200, where for every one pound spent on construction cost, five are spent on maintenance and building operating costs and 200 on staffing and business operating costs. This seems to stem from a paper published by the Royal Academy of Engineering, in which no data is given and no derivation or defence of the ratio appears. The accompanying belief that higher quality design and construction increases staff productivity, and simultaneously reduces maintenance costs, how ever laudable, appears unsupported by research, and carries all the hallmarks of an "urban myth". In tracking down data about real buildings, a more realistic ratio appears to depend on a huge variety of variables, as well as the definition of the number of "lifetime" years. The ill-defined origins of the original ratio (1:5:200) describing these variables have made replication impossible. However, by using published sources of data, we have found that for three office buildings, a more realistic ratio is 1:0.4:12. As there is nothing in the public domain about what comprised the original research that gave rise to 1:5:200, it is not possible to make a true comparison between these new calculations and the originals. Clients and construction professionals stand to be misled because the popularity and widespread use of the wrong ratio appears to be mis-informing important investment and policy decisions.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

Perspectives on the specification of Building Integrated Photovoltaic (BIPV) technology in construction projects

Innovative, low carbon technologies are already available for use in the construction of buildings, but the impact of their specification on construction projects is unclear. This exploratory research identifies issues which arise following the specification of BIPV in non-residential construction projects. Rather than treating the inclusion of a new technology as a technical problem, the research explores the issue from a socio-technical perspective to understand the accommodations which the project team makes and their effect on the building and the technology. The paper is part of a larger research project which uses a Social Construction of Technology Approach (SCOT) to explore the accommodations made to working practices and design when Building Integrated PhotoVoltaic (BIPV) technology is introduced. The approach explores how the requirements of the technology from different groups of actors (Relevant Social Groups or RSG's) give rise to problems and create solutions. As such it rejects the notion of a rational linear view of innovation diffusion; instead it suggests that the variety and composition of the Relevant Social Groups set the agenda for problem solving and solutions as the project progresses. The research explores the experiences of three people who have extensive histories of involvement with BIPV in construction, looks at how SCOT can inform our understanding of the issues involved and identifies themes and issues in the specification of BIPV on construction projects. A key finding concerns the alignment of inflection points at which interviewees have found themselves changing from one RSG to another as new problems and solutions are identified. The points at which they change RSG often occurred at points which mirror conventional construction categories (in terms of project specification, tender, design and construction).

Conditioning and preconditioning of the optimal state estimation problem

Optimal state estimation is a method that requires minimising a weighted, nonlinear, least-squares objective function in order to obtain the best estimate of the current state of a dynamical system. Often the minimisation is non-trivial due to the large scale of the problem, the relative sparsity of the observations and the nonlinearity of the objective function. To simplify the problem the solution is often found via a sequence of linearised objective functions. The condition number of the Hessian of the linearised problem is an important indicator of the convergence rate of the minimisation and the expected accuracy of the solution. In the standard formulation the convergence is slow, indicating an ill-conditioned objective function. A transformation to different variables is often used to ameliorate the conditioning of the Hessian by changing, or preconditioning, the Hessian. There is only sparse information in the literature for describing the causes of ill-conditioning of the optimal state estimation problem and explaining the effect of preconditioning on the condition number. This paper derives descriptive theoretical bounds on the condition number of both the unpreconditioned and preconditioned system in order to better understand the conditioning of the problem. We use these bounds to explain why the standard objective function is often ill-conditioned and why a standard preconditioning reduces the condition number. We also use the bounds on the preconditioned Hessian to understand the main factors that affect the conditioning of the system. We illustrate the results with simple numerical experiments.