What the problem may be with family intervention . . . and with dissemination more generally: A commentary

While the two decades since the study by Kavanagh et al. (1993) has given additional insights into effective dissemination of family interventions, the accompanying papers show that progress remains limited. The effectiveness trial that triggered this series of papers offers a cautionary tale. Despite management support, 30–35 hr of workshop training and training of local supervisors who could act as champions, use of the full intervention was limited. In part, this seemed due to the demanding nature of the intervention and its incompatibility with practitioners’ roles, in part, to limitations in the training, among other factors. While the accompanying papers note these and other barriers to dissemination, they miss a more disturbing finding in the original paper: Practitioners said they were using several aspects in routine care, despite being unable to accurately describe what they were. This finding highlights the risks in taking practitioners’ reports of their practice in files or supervision sessions at face value and potentially has implications for reports of other clinical work. The fidelity of disseminated treatments can only be assured by audits of practice, accompanied by affirming but also corrective feedback.

Managing uncertainty to improve the cost performance of complex infrastructure projects

There has been a recent spate of high profile infrastructure cost overruns in Australia and internationally. This is just the tip of a longer-term and more deeply-seated problem with initial budget estimating practice, well recognised in both academic research and industry reviews: the problem of uncertainty. A case study of the Sydney Opera House is used to identify and illustrate the key causal factors and system dynamics of cost overruns. It is conventionally the role of risk management to deal with such uncertainty, but the type and extent of the uncertainty involved in complex projects is shown to render established risk management techniques ineffective. This paper considers a radical advance on current budget estimating practice which involves a particular approach to statistical modelling complemented by explicit training in estimating practice. The statistical modelling approach combines the probability management techniques of Savage, which operate on actual distributions of values rather than flawed representations of distributions, and the data pooling technique of Skitmore, where the size of the reference set is optimised. Estimating training employs particular calibration development methods pioneered by Hubbard, which reduce the bias of experts caused by over-confidence and improve the consistency of subjective decision-making. A new framework for initial budget estimating practice is developed based on the combined statistical and training methods, with each technique being explained and discussed.

Building teachers' pedagogy practices in reasoning, to improve students' dispositions towards mathematics

Drawing on participatory action research, this study identifies the pedagogies necessary to advance reasoning, which is one of the proficiencies from the Australian Curriculum Mathematics, and explores how reasoning leads to greater productive disposition. With the current emphasis on STEM in schools, this research is timely. This thesis makes an original and substantive contribution to the understanding of why and how teachers can most effectively advance student proficiency in reasoning through targeted instructional strategies and style of instruction. The study explores the ways in which teacher practices, when focused on reasoning, enhance the disposition of students towards greater mathematical proficiency.

[B4O9H2] Cyclic Borate Units as the Building Unit in a Family of Zinc Borate Structures

A solvothermal reaction of ZnO, boric acid (B(OH)(3)), and aliphatic airlines in a water-pyridine mixture gave four zinc borate phases of different dimensionalities: [Zn(B4O8H2)(C3H10N2)], I (one-dimensional); [Zn(B4O8H2)(C3H10N2)] H2O, II (two-dimensional); [Zn(B5O10H3)(C10H24N4)]center dot H2O, III (two-dimensional): and [Zn-2(B8O15H2)(C3H10N2)(2)], IV (three-dimensional). The structures are formed by the connectivity involving polyborate chains and layers with Zn2+ species. In all the compounds, the amine molecules act its file ligand binding either the same or different zn centers. The formation of two different structures, II and IV, from the same amine by varying the reaction time is noteworthy. Transformation studies on II indicate that the formation of IV. from II, is facile and has been investigated for the first time. Two of file compounds, I and III, exhibit activity for second-order nonlinear optical behavior. The UV exposure of the sample indicates the absorption of all the UV radiation suggesting that the zinc borate compounds could be exploited for UV-blocking applications. The compounds have been characterized by powder X-ray diffraction, infrared spectroscopy, thermogravimetric analysis, UV-vis, photoluminescence, and NMR studies.

Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Particle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

A Combinatorial Optimization Problem for High Order PODs with Few Sensors

Experimental characterization of high dimensional dynamic systems sometimes uses the proper orthogonal decomposition (POD). If there are many measurement locations and relatively fewer sensors, then steady-state behavior can still be studied by sequentially taking several sets of simultaneous measurements. The number required of such sets of measurements can be minimized if we solve a combinatorial optimization problem. We aim to bring this problem to the attention of engineering audiences, summarize some known mathematical results about this problem, and present a heuristic (suboptimal) calculation that gives reasonable, if not stellar, results.