Normalizing Foucault? A rhizomatic approach to plateaus in anglophone educational research

This paper offers a rhizomatic reading of Foucault scholarship in anglophone educational research. It delineates unique parameters of an educational field, the conditions of receptivity for Foucault's work, and identifies three temporary plateau-formations that have erupted in educational research. Indebted to (non-formulaic) principles of connectivity and heterogeneity, multiplicity, and asignifying ruptures the analysis brings to notice the recombinatorial attributes of the discipline of education through attention to what is encamped and what seeps in debates over his work.

Crystal engineering in two dimensions: An approach to molecular nanopatterning

We describe a surprising cooperative adsorption process observed by scanning tunneling microscopy (STM) at the liquid−solid interface. The process involves the association of a threefold hydrogen-bonding unit, trimesic acid (TMA), with straight-chain aliphatic alcohols of varying length (from C7 to C30), which coadsorb on highly oriented pyrolytic graphite (HOPG) to form linear patterns. In certain cases, the known TMA “flower pattern” can coexist temporarily with the linear TMA−alcohol patterns, but it eventually disappears. Time-lapsed STM imaging shows that the evolution of the flower pattern is a classical ripening phenomenon. The periodicity of the linear TMA−alcohol patterns can be modulated by choosing alcohols with appropriate chain lengths, and the precise structure of the patterns depends on the parity of the carbon count in the alkyl chain. Interactions that lead to this odd−even effect are analyzed in detail. The molecular components of the patterns are achiral, yet their association by hydrogen bonding leads to the formation of enantiomeric domains on the surface. The interrelation of these domains and the observation of superperiodic structures (moiré patterns) are rationalized by considering interactions with the underlying graphite surface and within the two-dimensional crystal of the adsorbed molecules. Comparison of the observed two-dimensional structures with the three-dimensional crystal structures of TMA−alcohol complexes determined by X-ray crystallography helps reveal the mechanism of molecular association in these two-component systems.

Examining the profile and experiences of older sub-acute patients who present to public hospital emergency departments in South East Queensland: A mixed methods approach

There is a scarcity of research that informs Interface Health Service (IHS) development. This research applied a mixed methods approach to profile older emergency department patients and patterns of health service use and to explore their ED experiences in public hospital EDs in South-East Queensland. IHS was under-utilised by older people with complex co-morbidities. Lack of communication and need identification were factors that undermined the effectiveness of IHS in reaching this cohort which highlighted a need for change.

Governance and regional planning outcomes: Using governance indicators to support a policy implementation approach

Regional planning faces numerous decision making uncertainties related to the complex interdependencies between urban and regional centres. Questions about how to achieve sustainable planning solutions across regions are a key uncertainty and relate to a lack of information about the actual achievement of outcomes as proposed by the objectives of a plan. Regional plan implementation and its impact on environmental, social and economic outcomes have been little explored within Australian urban and regional planning research. Despite a desire to improve the conditions across Australian regions, ambiguity persists regarding the results of regional planning efforts. Of the variables affecting regional planning, scholars argue that governance has a significant impact on achieving outcomes (see Pahl-Wostl 2009). In order to better analyse the impact of governance, we propose a set of governance indicators to examine decisions across regional planning institutions and apply this to governance models across Queensland’s regions. We contend that these governance indicators can support a more rigorous assessment of the impacts of governance models on plan implementation and outcomes. We propose that this is a way to better understand the relationship between planning and outcomes across urban and regional areas.

An integrated mathematical approach to measure the capacity of MMTS

This article focusses upon multi-modal transportation systems (MMTS) and the issues surrounding the determination of system capacity. For that purpose a multi-objective framework is advocated that integrates all the different modes and many different competing capacity objectives. This framework is analytical in nature and facilitates a variety of capacity querying and capacity expansion planning.

Load estimation with uncertainties from opportunistic sampling data: A semiparametric approach

We consider estimating the total load from frequent flow data but less frequent concentration data. 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 that minimizes the biases and makes use of informative predictive variables. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized rating-curve approach with additional predictors that capture unique features in the flow data, such as the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and the discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. Forming 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 for two rivers delivering to the Great Barrier Reef, Queensland, Australia. One is a data set from the Burdekin River, and consists of the total suspended sediment (TSS) and nitrogen oxide (NO(x)) and gauged flow for 1997. The other dataset is from the Tully River, for the period of July 2000 to June 2008. For NO(x) Burdekin, the new estimates are very similar to the ratio estimates even when there is no relationship between the concentration and the flow. However, for the Tully dataset, by incorporating the additional predictive variables namely the discounted flow and flow phases (rising or recessing), we substantially improved the model fit, and thus the certainty with which the load is estimated.

Rank regression for analysis of clustered data: A natural induced smoothing approach

We consider rank regression for clustered data analysis and investigate the induced smoothing method for obtaining the asymptotic covariance matrices of the parameter estimators. We prove that the induced estimating functions are asymptotically unbiased and the resulting estimators are strongly consistent and asymptotically normal. The induced smoothing approach provides an effective way for obtaining asymptotic covariance matrices for between- and within-cluster estimators and for a combined estimator to take account of within-cluster correlations. We also carry out extensive simulation studies to assess the performance of different estimators. The proposed methodology is substantially Much faster in computation and more stable in numerical results than the existing methods. We apply the proposed methodology to a dataset from a randomized clinical trial.

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.