Synchrotron-FTIR microspectroscopy enables the distinction of lipid accumulation in thraustochytrid strains through analysis of individual live cells

The superior characteristics of high photon flux and diffraction-limited spatial resolution achieved by synchrotron-FTIR microspectroscopy allowed molecular characterization of individual live thraustochytrids. Principal component analysis revealed distinct separation of the single live cell spectra into their corresponding strains, comprised of new Australasian thraustochytrids (AMCQS5-5 and S7) and standard cultures (AH-2 and S31). Unsupervised hierarchical cluster analysis (UHCA) indicated close similarities between S7 and AH-7 strains, with AMCQS5-5 being distinctly different. UHCA correlation conformed well to the fatty acid profiles, indicating the type of fatty acids as a critical factor in chemotaxonomic discrimination of these thraustochytrids and also revealing the distinctively high polyunsaturated fatty acid content as key identity of AMCQS5-5. Partial least squares discriminant analysis using cross-validation approach between two replicate datasets was demonstrated to be a powerful classification method leading to models of high robustness and 100% predictive accuracy for strain identification. The results emphasized the exceptional S-FTIR capability to perform real-time in vivo measurement of single live cells directly within their original medium, providing unique information on cell variability among the population of each isolate and evidence of spontaneous lipid peroxidation that could lead to deeper understanding of lipid production and oxidation in thraustochytrids for single-cell oil development.

Panel versus GARCH information in unit root testing with an application to financial markets

In a search for more powerful unit root tests, some researchers have recently proposed accounting for the information contained in the GARCH of the innovations. However, while promising, tests with GARCH are difficult to implement, which has made them quite uncommon in the empirical literature. A computationally attractive alternative is to account not for GARCH but the information contained in a panel of multiple time series. The purpose of the current note is to compare the relative power achievable from these two information sources. © 2014 Elsevier B.V.

Performing research as a method of analysis

This paper outlines a theatre-based research method undertaken as a means of analysing and representing data from a study into first-year teachers’ identity transformation. It reports on the processes employed, and the attempt by the researcher to bring together complimentary and innovative ways of interpreting interview data. Interview data from twelve teachers throughout their first year of teaching were scripted, rehearsed and performed to ‘expert’ audiences. The written script provided the basis for analysis of the teachers’ identity transformation as seen through their firsts – epiphanic and/or revelatory experiences that marked a moment of transition or transformation. The script served as an effective tool for data analysis, particularly when developing an understanding of the process of data reduction. Initially dissatisfied with the term ‘data reduction’, believing it to be counter-intuitive to ‘reduce’ the participants’ descriptions of their experiences, the process of scripting emphasised the importance of honing in on meaning, and reconciled such concerns by creating a snapshot of each participant’s first as representative of their experiences. Later, the performance revealed more nuanced understandings of the participants’ experiences as viewed through the eyes of the teacher-actors and audiences. The actors selected to represent the experiences of the first-year teachers in the performance were also teachers. The process of casting, and the teacher-actors’ experiences of rehearsing and performing the work ‘The First Time’ over the past two years will also be discussed. This paper concludes with some of the feedback from various audiences of both the performance and the written thesis from arts- and non-arts-based practitioners. Some feedback contends that the theatre-based method was less rigorous than other more ‘traditional’ methods. Such feedback prompts the consideration of weighing the benefits of employing theatre-based research against the risk of alienating some members of the audiences (both of the performance and the page). This paper includes live/digital excerpts of the theatre-based performance ‘The First Time’.

Optimal second best taxation of addictive goods in dynamic general equilibrium: a revenue raising perspective

In this paper we derive conditions under which optimal tax rates for addictive goods exceed tax rates for non-addictive consumption goods within a rational addiction framework where exogenous government spending cannot be financed with lump sum taxes. We reexamine classic results on optimal commodity taxation and find a rich set of new findings. Two dynamic effects exist. First, households anticipating higher future addictive tax rates reduce current addictive consumption, so they will be less addicted when the tax rate increases. Therefore, addictive tax revenue falls prior to the tax increase. Surprisingly, the optimal tax rate on addictive goods is generally decreasing in the strength of tolerance, since strong tolerance strengthens this tax anticipation effect. Second, high current tax rates on addictive goods make households less addicted in the future, affecting all future tax revenues in a way which depends on how elasticities are changing over time. Classic results on uniform commodity taxation emerge as special cases when elasticities are constant and the addiction function is homogeneous of degree one. Finally, we also study features of addictive goods such as complementarity to leisure that, while not directly related to the definition of addiction, are nonetheless properties many addictive goods display.

Energy consumption at the state level: the unit root null hypothesis from Australia

In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

Does electricity consumption panel Granger cause GDP? A new global evidence

The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP. © 2010 Elsevier Ltd. All rights reserved.

Structural damage identification based on self-fitting ARMAX model and multi-sensor data fusion

Statistical time series methods have proven to be a promising technique in structural health monitoring, since it provides a direct form of data analysis and eliminates the requirement for domain transformation. Latest research in structural health monitoring presents a number of statistical models that have been successfully used to construct quantified models of vibration response signals. Although a majority of these studies present viable results, the aspects of practical implementation, statistical model construction and decision-making procedures are often vaguely defined or omitted from presented work. In this article, a comprehensive methodology is developed, which essentially utilizes an auto-regressive moving average with exogenous input model to create quantified model estimates of experimentally acquired response signals. An iterative self-fitting algorithm is proposed to construct and fit the auto-regressive moving average with exogenous input model, which is capable of integrally finding an optimum set of auto-regressive moving average with exogenous input model parameters. After creating a dataset of quantified response signals, an unlabelled response signal can be identified according to a 'closest-fit' available in the dataset. A unique averaging method is proposed and implemented for multi-sensor data fusion to decrease the margin of error with sensors, thus increasing the reliability of global damage identification. To demonstrate the effectiveness of the developed methodology, a steel frame structure subjected to various bolt-connection damage scenarios is tested. Damage identification results from the experimental study suggest that the proposed methodology can be employed as an efficient and functional damage identification tool. © The Author(s) 2014.

Interactive exploration of data with visual metaphors

Visual Analytics (VA) is an approach to data analysis by means of visual manipulation of data representation, which relies on innate human abilities of perception and cognition. Even though current visual toolkits in the Business Analytics (BA) domain have improved the effectiveness of data exploration, analysis and reporting, their features are often not intuitive, and can be confusing and difficult to use. Moreover, visualizations generated from these toolkits are mostly accessible to specialist users. Thus, there is a need for analytic environments that support data exploration, interpretation and communication of insight that do not add to the cognitive load of the analyst and their non-technical clients. In this conceptual paper, we explore the potential of primary metaphors, which arise out of human lived and sensory-motor experiences, in the design of immersive visual analytics environments. Primary metaphors provide ideas for representation of time, space, quantity, similarity, actions and team work. Using examples developed in our own work, we also explain how to combine such metaphors to create complex and cognitively acceptable visual metaphors, such as 3D data terrains that approximate our intuition of reality and create opportunities for data to be viewed, navigated, explored, touched, changed, discussed, reported and described to others, individually or collaboratively.

Confocal laser scanning microscopy elucidation of the micromorphology of the leaf cuticle and analysis of its chemical composition

Electron microscopy techniques such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM) have been invaluable tools for the study of the micromorphology of plant cuticles. However, for electron microscopy, the preparation techniques required may invariably introduce artefacts in cuticle preservation. Further, there are a limited number of methods available for quantifying the image data obtained through electron microscopy. Therefore, in this study, optical microscopy techniques were coupled with staining procedures and, along with SEM were used to qualitatively and quantitatively assess the ultrastructure of plant leaf cuticles. Leaf cryosections of Triticum aestivum (wheat), Zea mays (maize), and Lupinus angustifolius (lupin) were stained with either fat-soluble azo stain Sudan IV or fluorescent, diarylmethane Auramine O and were observed under confocal laser scanning microscope (CLSM). For all the plant species tested, the cuticle on the leaf surfaces could be clearly resolved in many cases into cuticular proper (CP), external cuticular layer (ECL), and internal cuticular layer (ICL). Novel image data analysis procedures for quantifying the epicuticular wax micromorphology were developed, and epicuticular waxes of L. angustifolius were described here for the first time. Together, application of a multifaceted approach involving the use of a range of techniques to study the plant cuticle has led to a better understanding of cuticular structure and provides new insights into leaf surface architecture.

Preference mining techniques for customer behavior analysis

The thesis has studied a number of critical problems in data mining for customer behavior analysis and has proposed novel techniques for better modeling of the customers’ decision making process, more efficient analysis of their travel behavior, and more effective identification of their emerging preference.

Is there a Kuznets' process in Southeast Asia?

Relatively little is known about the determinants of inequality in Southeast Asia. This paper fills this void by comprehensively testing Kuznets’ hypothesis for Southeast Asia. We estimate both unconditional and conditional Kuznets’ curves using panel data for 8 countries. The analysis suggests the existence of a Kuznets’ curve with respect to per capita income; the path of inequality is nonlinear with respect to economic development. There is no evidence of a Kuznets curve with respect to non-agricultural employment. There is some evidence in terms of urbanization, though this is not robust. There is robust evidence on the role of national governments and education in shaping the path of inequality in the region. Government involvement reduces inequality. Education appears to have a non-linear effect on inequality.

A study and a directory of energy consumption data sets of buildings

Energy consumption data are required to perform analysis, modelling, evaluation, and optimisation of energy usage in buildings. While a variety of energy consumption data sets have been examined and reported in the literature, there is a lack of a comprehensive categorisation and analysis of the available data sets. In this study, an overview of energy consumption data of buildings is provided. Three common strategies for generating energy consumption data, i.e., measurement, survey, and simulation, are described. A number of important characteristics pertaining to each strategy and the resulting data sets are discussed. In addition, a directory of energy consumption data sets of buildings is developed. The data sets are collected from either published papers or energy related organisations. The main contributions of this study include establishing a resource pertaining to energy consumption data sets and providing information related to the characteristics and availability of the respective data sets; therefore facilitating and promoting research activities in energy consumption data analysis.

Testing for stock return predictability in a large Chinese panel

This paper proposes a simple panel data test for stock return predictability that is flexible enough to accommodate three key salient features of the data, namely, predictor persistency and endogeneity, and cross-sectional dependence. Using a large panel of Chinese stock market data comprising more than one million observations, we show that most financial and macroeconomic predictors are in fact able to predict returns. We also show how the extent of the predictability varies across industries and firm sizes.

On the use of panel cointegration tests in energy economics

There is a burgeoning literature based on using panel cointegration techniques to study the relationship between energy consumption and GDP. Most panel cointegration tests employed take no cointegration as the null hypothesis. The current paper illustrates how a rejection by such a test cannot be taken as evidence of cointegration for the panel as a whole, a fact that seems to have gone largely unnoticed in the literature. Hence, even if the no cointegration null is rejected, this evidence is not enough to ensure that the relationship can be meaningfully estimated, as most (if not all) estimators in the literature require that the panel is cointegrated as a whole.