Becoming-topologies of education: Deformations, networks and the database effect

This article uses topological approaches to suggest that education is becoming-topological. Analyses presented in a recent double-issue of Theory, Culture & Society are used to demonstrate the utility of topology for education. In particular, the article explains education's topological character through examining the global convergence of education policy, testing and the discursive ranking of systems, schools and individuals in the promise of reforming education through the proliferation of regimes of testing at local and global levels that constitute a new form of governance through data. In this conceptualisation of global education policy changes in the form and nature of testing combine with it the emergence of global policy network to change the nature of the local (national, regional, school and classroom) forces that operate through the ‘system’. While these forces change, they work through a discursivity that produces disciplinary effects, but in a different way. This new–old disciplinarity, or ‘database effect’, is here represented through a topological approach because of its utility for conceiving education in an increasingly networked world.

Priority threat management of invasive animals to protect biodiversity under climate change

Climate change is a major threat to global biodiversity, and its impacts can act synergistically to heighten the severity of other threats. Most research on projecting species range shifts under climate change has not been translated to informing priority management strategies on the ground. We develop a prioritization framework to assess strategies for managing threats to biodiversity under climate change and apply it to the management of invasive animal species across one-sixth of the Australian continent, the Lake Eyre Basin. We collected information from key stakeholders and experts on the impacts of invasive animals on 148 of the region's most threatened species and 11 potential strategies. Assisted by models of current distributions of threatened species and their projected distributions, experts estimated the cost, feasibility, and potential benefits of each strategy for improving the persistence of threatened species with and without climate change. We discover that the relative cost-effectiveness of invasive animal control strategies is robust to climate change, with the management of feral pigs being the highest priority for conserving threatened species overall. Complementary sets of strategies to protect as many threatened species as possible under limited budgets change when climate change is considered, with additional strategies required to avoid impending extinctions from the region. Overall, we find that the ranking of strategies by cost-effectiveness was relatively unaffected by including climate change into decision-making, even though the benefits of the strategies were lower. Future climate conditions and impacts on range shifts become most important to consider when designing comprehensive management plans for the control of invasive animals under limited budgets to maximize the number of threatened species that can be protected.

A decision support framework for prioritization of engineering asset management activities under uncertainty

Engineers and asset managers must often make decisions on how to best allocate limited resources amongst different interrelated activities, including repair, renewal, inspection, and procurement of new assets. The presence of project interdependencies and the lack of sufficient information on the true value of an activity often produce complex problems and leave the decision maker guessing about the quality and robustness of their decision. In this paper, a decision support framework for uncertain interrelated activities is presented. The framework employs a methodology for multi-criteria ranking in the presence of uncertainty, detailing the effect that uncertain valuations may have on the priority of a particular activity. The framework employs employing semi-quantitative risk measures that can be tailored to an organisation and enable a transparent and simple-to-use uncertainty specification by the decision maker. The framework is then demonstrated on a real world project set from a major Australian utility provider.

Microbial oil production from palm oil empty fruit bunch hydrolysates

This study explores the potential use of empty fruit bunch (EFB) residues from palm oil processing residues, as an alternative feedstock for microbial oil production. EFB is a readily available, lignocellulosic biomass that provides cheaper substrates for oil production in comparison to the use of pure sugars. In this study, potential oleaginous microorganisms were selected based on a multi-criteria analysis (MCA) framework which utilised Analytical Hierarchy Process (AHP) with Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) aided by Geometrical Analysis for Interactive Aid (GAIA). The MCA framework was used to evaluate several strains of microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa) and fungi (Aspergillus oryzae and Mucor plumbeus) on glucose, xylose and glycerol. Based on the results of PROMETHEE rankings and GAIA plane, fungal strains A. oryzae and M. plumbeus and yeast strain R. mucilaginosa showed great promise for oil production from lignocellulosic hydrolysates. The study further cultivated A. oryzae, M. plumbeus and R. mucilaginosa on EFB hydrolysates for oil production. EFB was pretreated with dilute sulfuric acid, followed by enzymatic saccharification of solid residue. Hydrolysates tested in this study are detoxified liquid hydrolysates (LH) and enzymatic hydrolysate (EH).

Barriers to good occupational health and safety (OHS) practices by small construction firms

The construction industry has long been considered to have unacceptably high injury and fatality rates. Previous research has shown that small construction companies sustain higher injury rates than large companies. However, despite the industry being dominated by a very large number of such small companies, little is known of their occupational health and safety (OHS) needs, practices and constraints. This paper takes a first step in aiming to identify the principal barriers that affect good OHS performance of small construction companies so that effective OHS practices can be developed to improve this in future. The contents of the literature are first summarised, in which three critical barriers to good OHS practice in small construction firms are proposed. They are : cost, time, lack of safety awareness and concern. The results of a questionnaire survey carried out with South East Queensland construction personnel are presented, which largely confirm what is suggested by the literature research and also succeed in providing an indication of their ranking in terms of importance and suggestions for overcoming these barriers. The research results provide a better understanding of the issues that restrict good OHS practice in small construction companies and potential measures for improvement.

Feasibility of perflutren microsphere contrast transthoracic echocardiography in the visualization of ventricular endocardium during venovenous extracorporeal membrane oxygenation in a validated ovine model

Background: Transthoracic echocardiography (TTE) during extra corporeal membrane oxygenation (ECMO) is important but can be technically challenging. Contrast-specific TTE can improve imaging in suboptimal studies. These contrast microspheres are hydrodynamically labile structures. This study assessed the feasibility of contrast echocardiography (CE) during venovenous (VV) ECMO in a validated ovine model. Method: Twenty-four sheep were commenced on VV ECMO. Parasternal long-axis (Plax) and short-axis (Psax) views were obtained pre- and postcontrast while on VV ECMO. Endocardial definition scores (EDS) per segment were graded: 1 = good, 2 = suboptimal 3 = not seen. Endocardial border definition score index (EBDSI) was calculated for each view. Endocardial length (EL) in the Plax view for the left ventricle (LV) and right ventricle (RV) was measured. Results: Summation EDS data for the LV and RV for unenhanced TTE (UE) versus CE TTE imaging: EDS 1 = 289 versus 346, EDS 2 = 38 versus 10, EDS 3 = 33 versus 4, respectively. Wilcoxon matched-pairs rank-sign tests showed a significant ranking difference (improvement) pre- and postcontrast for the LV (P < 0.0001), RV (P < 0.0001) and combined ventricular data (P < 0.0001). EBDSI for CE TTE was significantly lower than UE TTE for the LV (1.05 ± 0.17 vs. 1.22 ± 0.38, P = 0.0004) and RV (1.06 ± 0.22 vs. 1.42 ± 0.47, P = 0.0.0006) respectively. Visualized EL was significantly longer in CE versus UE for both the LV (58.6 ± 11.0 mm vs. 47.4 ± 11.7 mm, P < 0.0001) and the RV (52.3 ± 8.6 mm vs. 36.0 ± 13.1 mm, P < 0.0001), respectively. Conclusions: Despite exposure to destructive hydrodynamic forces, CE is a feasible technique in an ovine ECMO model. CE results in significantly improved EDS and increased EL.

Generalizing the use of geographical weights in biodiversity modelling

Aim Determining how ecological processes vary across space is a major focus in ecology. Current methods that investigate such effects remain constrained by important limiting assumptions. Here we provide an extension to geographically weighted regression in which local regression and spatial weighting are used in combination. This method can be used to investigate non-stationarity and spatial-scale effects using any regression technique that can accommodate uneven weighting of observations, including machine learning. Innovation We extend the use of spatial weights to generalized linear models and boosted regression trees by using simulated data for which the results are known, and compare these local approaches with existing alternatives such as geographically weighted regression (GWR). The spatial weighting procedure (1) explained up to 80% deviance in simulated species richness, (2) optimized the normal distribution of model residuals when applied to generalized linear models versus GWR, and (3) detected nonlinear relationships and interactions between response variables and their predictors when applied to boosted regression trees. Predictor ranking changed with spatial scale, highlighting the scales at which different species–environment relationships need to be considered. Main conclusions GWR is useful for investigating spatially varying species–environment relationships. However, the use of local weights implemented in alternative modelling techniques can help detect nonlinear relationships and high-order interactions that were previously unassessed. Therefore, this method not only informs us how location and scale influence our perception of patterns and processes, it also offers a way to deal with different ecological interpretations that can emerge as different areas of spatial influence are considered during model fitting.

Genome-wide association study for sight-threatening diabetic retinopathy reveals association with genetic variation near the GRB2 gene

Aims/hypothesis Diabetic retinopathy is a serious complication of diabetes mellitus and can lead to blindness. A genetic component, in addition to traditional risk factors, has been well described although strong genetic factors have not yet been identified. Here, we aimed to identify novel genetic risk factors for sight-threatening diabetic retinopathy using a genome-wide association study. Methods Retinopathy was assessed in white Australians with type 2 diabetes mellitus. Genome-wide association analysis was conducted for comparison of cases of sight-threatening diabetic retinopathy (n = 336) with diabetic controls with no retinopathy (n = 508). Top ranking single nucleotide polymorphisms were typed in a type 2 diabetes replication cohort, a type 1 diabetes cohort and an Indian type 2 cohort. A mouse model of proliferative retinopathy was used to assess differential expression of the nearby candidate gene GRB2 by immunohistochemistry and quantitative western blot. Results The top ranked variant was rs3805931 with p = 2.66 × 10−7, but no association was found in the replication cohort. Only rs9896052 (p = 6.55 × 10−5) was associated with sight-threatening diabetic retinopathy in both the type 2 (p = 0.035) and the type 1 (p = 0.041) replication cohorts, as well as in the Indian cohort (p = 0.016). The study-wide meta-analysis reached genome-wide significance (p = 4.15 × 10−8). The GRB2 gene is located downstream of this variant and a mouse model of retinopathy showed increased GRB2 expression in the retina. Conclusions/interpretation Genetic variation near GRB2 on chromosome 17q25.1 is associated with sight-threatening diabetic retinopathy. Several genes in this region are promising candidates and in particular GRB2 is upregulated during retinal stress and neovascularisation.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

Questionnaire design for airport passenger experience survey

Assessing airport service performance requires understanding of a complete set of passenger experiences covering all activities from departures to arrivals. Weight-based indicator models allow passengers to express their priority on certain evaluation criteria (airport domains) and their service attributes over the others. The application of multilevel regression analysis in questionnaire design is expected to overcome limitations of traditional questionnaires, which require application of all indicators with equal weight. The development of a Taxonomy of Passenger Activities (TOPA), which captures all passenger processing and discretionary activities, has provided a novel perspective in understanding passenger experience in various airport domains. Based on further literature reviews on various service attributes at airport passenger terminals, this paper constitutes questionnaire design to employ a weighting method for all activities from the time passengers enter an airport domain at the departure terminal until leaving the arrival terminal (i.e. seven airport domains for departure, four airport domains during transit, and seven airport domains for arrival). The procedure of multilevel regression analysis is aimed not only at identifying the ranking of each evaluation criterion from the most important to the least important but also to explain the relationship between service attributes in each airport domain and overall service performance.

Artificial Neural Network Based Automatic Emergency Landing Site Selection for UAVs and Highly Automated Aircraft

In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.

Rapid assessment of genotype-by-environment interactions and heritability for growth rate in aquaculture species using in vitro fertilisation and DNA tagging

Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment This fraction is the result of undesirable genotype-by-environment interactions (G x E) and measured by the genetic correlation (r(g)) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of G x E over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels

General ranked set sampling with cost considerations

Nahhas, Wolfe, and Chen (2002, Biometrics 58, 964-971) considered optimal set size for ranked set sampling (RSS) with fixed operational costs. This framework can be very useful in practice to determine whether RSS is beneficial and to obtain the optimal set size that minimizes the variance of the population estimator for a fixed total cost. In this article, we propose a scheme of general RSS in which more than one observation can be taken from each ranked set. This is shown to be more cost-effective in some cases when the cost of ranking is not so small. We demonstrate using the example in Nahhas, Wolfe, and Chen (2002, Biometrics 58, 964-971), by taking two or more observations from one set even with the optimal set size from the RSS design can be more beneficial.

An analysis of theories of search and search behavior

Theories of search and search behavior can be used to glean insights and generate hypotheses about how people interact with retrieval systems. This paper examines three such theories, the long standing Information Foraging Theory, along with the more recently proposed Search Economic Theory and the Interactive Probability Ranking Principle. Our goal is to develop a model for ad-hoc topic retrieval using each approach, all within a common framework, in order to (1) determine what predictions each approach makes about search behavior, and (2) show the relationships, equivalences and differences between the approaches. While each approach takes a different perspective on modeling searcher interactions, we show that under certain assumptions, they lead to similar hypotheses regarding search behavior. Moreover, we show that the models are complementary to each other, but operate at different levels (i.e., sessions, patches and situations). We further show how the differences between the approaches lead to new insights into the theories and new models. This contribution will not only lead to further theoretical developments, but also enables practitioners to employ one of the three equivalent models depending on the data available.

Comparative study on green building supportive policies of pacific-rim countries most vulnerable to climate change

- Problem Climate change is affecting the world in numerous ways such as increased temperatures, sea level rise, and increased droughts and floods. Governments worldwide, especially in the most vulnerable countries, are urged to seek better solutions for sustainable development. The construction industry and buildings have enormous impacts on humans and the environment, meaning green building must be one of the solutions. Government involvement is widely considered as one of the essential and most effective ways to promote green building and drive the construction market towards sustainability. This paper will review green building policy of the Pacific-Rim countries that are most vulnerable to climate change according to the recent Standard and Poor’s ranking, including: Cambodia, Vietnam, Fiji, Philippines, Papua New Guinea and Indonesia. Methodology: This paper will review policy related publications including journal and conference papers, portal websites of governments, legislation documents and reports of international organisations. It will focus on the policies and governmental instruments that support the adoption of green building practices. - Findings All six governments have launched climate change adaptation policies, showing a great concern regarding the damages caused by the phenomenon. All countries except Papua New Guinea have promulgated energy efficiency policy and programs which indirectly promote the adoption of green building practices. The comparison study shows that Philippines and Indonesia motivate the adoption of renewable energy generation, energy efficiency and green building through either financial or advocacy instruments, while other four countries tend to implement regulatory tools to mandate energy conservation. Through comparison, Cambodia and Vietnam – the two countries providing vision to develop green building - can learn from Philippines and Indonesia’s policy and instruments. - Research limitations Language differences between the countries and limit of formal sources may pose difficulties in searching for information. While much English language literature exists, sources from Cambodia, Philippines and Indonesia are less accessible. - Takeaway for practice As the paper provides more understanding about the supportive policy of those countries, it will introduce more opportunities for green property developers to invest in construction markets of those Pacific-Rim countries. - Originality There is little research reviewing green building supportive policies of developing and less-wealthy countries that are forecasted to be most vulnerable and most impacted by climate change. The originality of this paper lies in its investigation on how those countries intend to respond to this phenomenon and whether and to what extent they support the green building market by using policy tools.