Manipulating the data: Teaching and NAPLAN in the control society

High-stakes testing is changing what it means to be a ‘good teacher’ in the contemporary school. This paper uses Deleuze and Guattari's ideas on the control society and dividuation in the context of National Assessment Program Literacy and Numeracy (NAPLAN) testing in Australia to suggest that the database generates new understandings of the ‘good teacher’. Media reports are used to look at how teachers are responding to the high-stakes database through manipulating the data. This article argues that manipulating the data is a regrettable, but logical, response to manifestations of teaching where only the data counts.

A mitochondrial genome phylogeny of owlet moths (Lepidoptera: Noctuoidea), and examination of the utility of mitochondrial genomes for lepidopteran phylogenetics

A phylogenetic hypothesis for the lepidopteran superfamily Noctuoidea was inferred based on the complete mitochondrial (mt) genomes of 12 species (six newly sequenced). The monophyly of each noctuoid family in the latest classification was well supported. Novel and robust relationships were recovered at the family level, in contrast to previous analyses using nuclear genes. Erebidae was recovered as sister to (Nolidae+(Euteliidae+Noctuidae)), while Notodontidae was sister to all these taxa (the putatively basalmost lineage Oenosandridae was not included). In order to improve phylogenetic resolution using mt genomes, various analytical approaches were tested: Bayesian inference (BI) vs. maximum likelihood (ML), excluding vs. including RNA genes (rRNA or tRNA), and Gblocks treatment. The evolutionary signal within mt genomes had low sensitivity to analytical changes. Inference methods had the most significant influence. Inclusion of tRNAs positively increased the congruence of topologies, while inclusion of rRNAs resulted in a range of phylogenetic relationships varying depending on other analytical factors. The two Gblocks parameter settings had opposite effects on nodal support between the two inference methods. The relaxed parameter (GBRA) resulted in higher support values in BI analyses, while the strict parameter (GBDH) resulted in higher support values in ML analyses.

The evolutionary history of termites as inferred from 66 mitochondrial genomes

Termites have colonized many habitats and are among the most abundant animals in tropical ecosystems, which they modify considerably through their actions. The timing of their rise in abundance and of the dispersal events that gave rise to modern termite lineages is not well understood. To shed light on termite origins and diversification, we sequenced the mitochondrial genome of 48 termite species and combined them with 18 previously sequenced termite mitochondrial genomes for phylogenetic and molecular clock analyses using multiple fossil calibrations. The 66 genomes represent most major clades of termites. Unlike previous phylogenetic studies based on fewer molecular data, our phylogenetic tree is fully resolved for the lower termites. The phylogenetic positions of Macrotermitinae and Apicotermitinae are also resolved as the basal groups in the higher termites, but in the crown termitid groups, including Termitinae + Syntermitinae + Nasutitermitinae + Cubitermitinae, the position of some nodes remains uncertain. Our molecular clock tree indicates that the lineages leading to termites and Cryptocercus roaches diverged 170 Ma (153-196 Ma 95% confidence interval [CI]), that modern Termitidae arose 54 Ma (46-66 Ma 95% CI), and that the crown termitid group arose 40 Ma (35-49 Ma 95% CI). This indicates that the distribution of basal termite clades was influenced by the final stages of the breakup of Pangaea. Our inference of ancestral geographic ranges shows that the Termitidae, which includes more than 75% of extant termite species, most likely originated in Africa or Asia, and acquired their pantropical distribution after a series of dispersal and subsequent diversification events.

Developments of the total entropy utility function for the dual purpose of model discrimination and parameter estimation in Bayesian design

The total entropy utility function is considered for the dual purpose of Bayesian design for model discrimination and parameter estimation. A sequential design setting is proposed where it is shown how to efficiently estimate the total entropy utility for a wide variety of data types. Utility estimation relies on forming particle approximations to a number of intractable integrals which is afforded by the use of the sequential Monte Carlo algorithm for Bayesian inference. A number of motivating examples are considered for demonstrating the performance of total entropy in comparison to utilities for model discrimination and parameter estimation. The results suggest that the total entropy utility selects designs which are efficient under both experimental goals with little compromise in achieving either goal. As such, the total entropy utility is advocated as a general utility for Bayesian design in the presence of model uncertainty.

A methodology for extracting legal norms from regulatory documents

We present a methodology to extract legal norms from regulatory documents for their formalisation and later compliance checking. The need for the methodology is motivated from the shortcomings of existing approaches where the rule type and process aspects relevant to the rules are largely overlook. The methodology incorporates the well–known IF. . . THEN structure extended with the process aspect and rule type, and guides how to properly extract the conditions and logical structure of the legal rules for reasoning and modelling of obligations for compliance checking.

Goodbye Brigadoon: Place, Production, and Identity in Global Glasgow

Goodbye Brigadoon examines the shifting role media production plays in the economic and cultural strategies of global cities in small market nations, specifically Glasgow, Scotland. In particular, this project focuses on the formation of a digital media village along the banks of the River Clyde to argue the site constitutes a logical component to Glasgow’s ongoing transformation into a cosmopolitan center. Yet, as the regional government’s economic strategies and policy directives work to transform the abandoned waterfront into a center of cultural activity, this project also underscores the contradictory cultural dynamics to emerge from media production’s new role in the post-industrial city. At its core, the media hub reveals a regional government more interested in the technology used to deliver “national” stories than the manner of the stories themselves or the cultural practices responsible for creating them. Indeed, Goodbye Brigadoon is most interested in how media professionals based at the emergent cluster negotiate a sense of cultural identity and creative license against the institutional constraints, policy matters, and commercial logic they also must navigate in their workaday rituals. Ultimately, the conclusions offered in this project argue for a more complicated conception of the global-local location where these professionals work. Glasgow’s digital media village, in other words, is much more than an innocuous site of competitive advantage, urban regeneration, and job growth. It is best understood as a site of intense social struggle and unequal power relations where local mediamakers often find the site’s impetus for multiplatform media production an institutionally enforced false promise at odds with the realities of creative labor in the city.

Decisions and actions of distracted drivers at the onset of yellow light

Driving on an approach to a signalized intersection while distracted is relatively risky, as potential vehicular conflicts and resulting angle collisions tend to be relatively more severe compared to other locations. Given the prevalence and importance of this particular scenario, the objective of this study was to examine the decisions and actions of distracted drivers during the onset of yellow lights. Driving simulator data were obtained from a sample of 69 drivers under baseline and handheld cell phone conditions at the University of Iowa – National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examinations have been conducted from a traditional regression-based approach, which do not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that the probability of yellow light running increases with the increase in driving speed at the onset of yellow. Both young (18–25 years) and middle-aged (30–45 years) drivers reveal reduced propensity for yellow light running whilst distracted across the entire speed range, exhibiting possible risk compensation during this critical driving situation. The propensity for yellow light running for both distracted male and female older (50–60 years) drivers is significantly higher. Driver experience captured by age interacts with distraction, resulting in their combined effect having slower physiological response and being distracted particularly risky.

Statistical literacy in the elementary school: Opportunities for problem posing

This chapter addresses opportunities for problem posing in developing young children’s statistical literacy, with a focus on student-directed investigations. Although the notion of problem posing has broadened in recent years, there nevertheless remains limited research on how problem posing can be integrated within the regular mathematics curriculum, especially in the areas of statistics and probability. The chapter first reviews briefly aspects of problem posing that have featured in the literature over the years. Consideration is next given to the importance of developing children’s statistical literacy in which problem posing is an inherent feature. Some findings from a school playground investigation conducted in four, fourth-grade classes illustrate the different ways in which children posed investigative questions, how they made predictions about their outcomes and compared these with their findings, and the ways in which they chose to represent their findings.

A preference-based semantics for CTD reasoning

In [8] the authors developed a logical system based on the definition of a new non-classical connective ⊗ capturing the notion of reparative obligation. The system proved to be appropriate for handling well-known contrary-to-duty paradoxes but no model-theoretic semantics was presented. In this paper we fill the gap and define a suitable possible-world semantics for the system for which we can prove soundness and completeness. The semantics is a preference-based non-normal one extending and generalizing semantics for classical modal logics.

Bayesian predictive modeling and comparison of oil samples

Statistical comparison of oil samples is an integral part of oil spill identification, which deals with the process of linking an oil spill with its source of origin. In current practice, a frequentist hypothesis test is often used to evaluate evidence in support of a match between a spill and a source sample. As frequentist tests are only able to evaluate evidence against a hypothesis but not in support of it, we argue that this leads to unsound statistical reasoning. Moreover, currently only verbal conclusions on a very coarse scale can be made about the match between two samples, whereas a finer quantitative assessment would often be preferred. To address these issues, we propose a Bayesian predictive approach for evaluating the similarity between the chemical compositions of two oil samples. We derive the underlying statistical model from some basic assumptions on modeling assays in analytical chemistry, and to further facilitate and improve numerical evaluations, we develop analytical expressions for the key elements of Bayesian inference for this model. The approach is illustrated with both simulated and real data and is shown to have appealing properties in comparison with both standard frequentist and Bayesian approaches

A Model to Estimate the Population Contributing to the Wastewater Using Samples Collected on Census Day

An important uncertainty when estimating per capita consumption of, for example, illicit drugs by means of wastewater analysis (sometimes referred to as “sewage epidemiology”) relates to the size and variability of the de facto population in the catchment of interest. In the absence of a day-specific direct population count any indirect surrogate model to estimate population size lacks a standard to assess associated uncertainties. Therefore, the objective of this study was to collect wastewater samples at a unique opportunity, that is, on a census day, as a basis for a model to estimate the number of people contributing to a given wastewater sample. Mass loads for a wide range of pharmaceuticals and personal care products were quantified in influents of ten sewage treatment plants (STP) serving populations ranging from approximately 3500 to 500 000 people. Separate linear models for population size were estimated with the mass loads of the different chemical as the explanatory variable: 14 chemicals showed good, linear relationships, with highest correlations for acesulfame and gabapentin. De facto population was then estimated through Bayesian inference, by updating the population size provided by STP staff (prior knowledge) with measured chemical mass loads. Cross validation showed that large populations can be estimated fairly accurately with a few chemical mass loads quantified from 24-h composite samples. In contrast, the prior knowledge for small population sizes cannot be improved substantially despite the information of multiple chemical mass loads. In the future, observations other than chemical mass loads may improve this deficit, since Bayesian inference allows including any kind of information relating to population size.

Childhood sexual abuse and adult sexual dysfunction: Response to commentary by Rind and Tromovitch (2007)

Rind and Tromovitch (2007) raised four concerns relating to our article (Najman, Dunne, Purdie, Boyle, & Coxeter, 2005. Archives of Sexual Behavior, 34, 517-526.) which suggested a causal association between childhood sexual abuse (CSA) and adult sexual dysfunction. We consider each of these concerns: magnitude of effect, cause and effect, confounding, and measurement error. We suggest that, while the concerns they raise represent legitimate reservations about the validity of our findings, on balance the available evidence indicates an association between CSA and sexual dysfunction that is of "moderate" magnitude, probably causal, and unlikely to be a consequence of confounding or measurement error.

Relationships between user experience and intuitiveness of visual and physical interactions

This paper investigates the effects of experience on the intuitiveness of physical and visual interactions performed by airport security screeners. Using portable eye tracking glasses, 40 security screeners were observed in the field as they performed search, examination and interface interactions during airport security x-ray screening. Data from semi structured interviews was used to further explore the nature of visual and physical interactions. Results show there are positive relationships between experience and the intuitiveness of visual and physical interactions performed by security screeners. As experience is gained, security screeners are found to perform search, examination and interface interactions more intuitively. In addition to experience, results suggest that intuitiveness is affected by the nature and modality of activities performed. This inference was made based on the dominant processing styles associated with search and examination activities. The paper concludes by discussing the implications that this research has for the design of visual and physical interfaces. We recommend designing interfaces that build on users’ already established intuitive processes, and that reduce the cognitive load incurred during transitions between visual and physical interactions.

Analysis of differential gene expression based on Bayesian estimation of variance

Gene expression is arguably the most important indicator of biological function. Thus identifying differentially expressed genes is one of the main aims of high throughout studies that use microarray and RNAseq platforms to study deregulated cellular pathways. There are many tools for analysing differentia gene expression from transciptomic datasets. The major challenge of this topic is to estimate gene expression variance due to the high amount of ‘background noise’ that is generated from biological equipment and the lack of biological replicates. Bayesian inference has been widely used in the bioinformatics field. In this work, we reveal that the prior knowledge employed in the Bayesian framework also helps to improve the accuracy of differential gene expression analysis when using a small number of replicates. We have developed a differential analysis tool that uses Bayesian estimation of the variance of gene expression for use with small numbers of biological replicates. Our method is more consistent when compared to the widely used cyber-t tool that successfully introduced the Bayesian framework to differential analysis. We also provide a user-friendly web based Graphic User Interface for biologists to use with microarray and RNAseq data. Bayesian inference can compensate for the instability of variance caused when using a small number of biological replicates by using pseudo replicates as prior knowledge. We also show that our new strategy to select pseudo replicates will improve the performance of the analysis. - See more at: http://www.eurekaselect.com/node/138761/article#sthash.VeK9xl5k.dpuf

Nonlinear Enzyme Kinetics Can Lead to High Metabolic Flux Control Coefficients: Implications for the Evolution of Dominance

In a classic study, Kacser & Burns (1981, Genetics 97, 639-666) demonstrated that given certain plausible assumptions, the flux in a metabolic pathway was more or less indifferent to the activity of any of the enzymes in the pathway taken singly. It was inferred from this that the observed dominance of most wild-type alleles with respect to loss-of-function mutations did not require an adaptive, meaning selectionist, explanation. Cornish-Bowden (1987, J. theor. Biol. 125, 333-338) showed that the Kacser-Burns inference was not valid when substrate concentrations were large relative to the relevant Michaelis constants. We find that in a randomly constructed functional pathway, even when substrate levels are small, one can expect high values of control coefficients for metabolic flux in the presence of significant nonlinearities as exemplified by enzymes with Hill coefficients ranging from two to six, or by the existence of oscillatory loops. Under these conditions the flux can be quite sensitive to changes in enzyme activity as might be caused by inactivating one of the two alleles in a diploid. Therefore, the phenomenon of dominance cannot be a trivial ''default'' consequence of physiology but must be intimately linked to the manner in which metabolic networks have been moulded by natural selection.