Estimating income and price elasticities of imports for Fiji in a cointegration framework

This paper estimates an import demand model for Fiji using the recently developed bounds testing approach to cointegration for the period 1972 to 1999. To estimate the long-run elasticities, we use three approaches: the autoregressive distributed lag (ARDL) model, the dynamic ordinary least squares (DOLS) approach and the fully modified ordinary least squares technique. Our results indicate a long-run cointegration relationship among the variables when import volume is the dependent variable. We find that the coefficient on income is elastic while the coefficient on relative prices (import price relative to domestic price) is unitary elastic in the long run. The error correction mechanism reveals that after any shock(s) to the determinants of import demand equilibrium is attained after 2 1/2 years.

Fourier transform infrared microspectroscopy as a tool to identify macroalgal propagules

Understanding of macroalgal dispersal has been hindered by the difficulty in identifying propagules. Different carrageenans typically occur in gametophytes and tetrasporophytes of the red algal family Gigartinaceae, and we may expect that carpospores and tetraspores also differ in composition of carrageenans. Using Fourier transform infrared (FT-IR) microspectroscopy, we tested the model that differences in carrageenans and other cellular constituents between nuclear phases should allow us to discriminate carpospores and tetraspores of Chondrus verrucosus Mikami. Spectral data suggest that carposporophytes isolated from the pericarp and female gametophytes contained κ-carrageenan, whereas tetrasporophytes contained λ-carrageenan. However, both carpospores and tetraspores exhibited absorbances in wave bands characteristic of κ-,ι-, and λ-carrageenans. Carpospores contained more proteins and may be more photosynthetically active than tetraspores, which contained more lipid reserves. We draw analogies to planktotrophic and lecithotrophic larvae. These differences in cellular chemistry allowed reliable discrimination of spores, but pretreatment of spectral data affected the accuracy of classification. The best classification of spores was achieved with extended multiplicative signal correction (EMSC) pretreatment using partial least squares discrimination analysis, with correct classification of 86% of carpospores and 83% of tetraspores. Classification may be further improved by using synchrotron FT-IR microspectroscopy because of its inherently higher signal-to-noise ratio compared with microspectroscopy using conventional sources of IR. This study demonstrates that FT-IR microspectroscopy and bioinformatics are useful tools to advance our understanding of algal dispersal ecology through discrimination of morphologically similar propagules both within and potentially between species.

OWA operators in linear regression and detection of outliers

We consider the use of Ordered Weighted Averaging (OWA) in linear regression. Our goal is to replace the traditional least squares, least absolute deviation, and maximum likelihood criteria with an OWA function of the residuals. We obtain several high breakdown robust regression methods as special cases (least median, least trimmed squares, trimmed likelihood methods). We also present new formulations of regression problem. OWA-based regression is particularly useful in the presence of outliers.

OWA operators in regression problems

We consider an application of fuzzy logic connectives to statistical regression. We replace the standard least squares, least absolute deviation, and maximum likelihood criteria with an ordered weighted averaging (OWA) function of the residuals. Depending on the choice of the weights, we obtain the standard regression problems, high-breakdown robust methods (least median, least trimmed squares, and trimmed likelihood methods), as well as new formulations. We present various approaches to numerical solution of such regression problems. OWA-based regression is particularly useful in the presence of outliers, and we illustrate the performance of the new methods on several instances of linear regression problems with multiple outliers.

Maximum likelihood estimation for rician distributed data in analytical q-ball imaging

Analytical q-ball imaging is widely used for reconstruction of orientation distribution function (ODF) using diffusion weighted MRI data. Estimating the spherical harmonic coefficients is a critical step in this method. Least squares (LS) is widely used for this purpose assuming the noise to be additive Gaussian. However, Rician noise is considered as a more appropriate model to describe noise in MR signal. Therefore, the current estimation techniques are valid only for high SNRs with Gaussian distribution approximating the Rician distribution. The aim of this study is to present an estimation approach considering the actual distribution of the data to provide reliable results particularly for the case of low SNR values. Maximum likelihood (ML) is investigated as a more effective estimation method. However, no closed form estimator is presented as the estimator becomes nonlinear for the noise assumption of the Rician distribution. Consequently, the results of LS estimator is used as an initial guess and the more refined answer is achieved using iterative numerical methods. According to the results, the ODFs reconstructed from low SNR data are in close agreement with ODFs reconstructed from high SNRs when Rician distribution is considered. Also, the error between the estimated and actual fiber orientations was compared using ML and LS estimator. In low SNRs, ML estimator achieves less error compared to the LS estimator.

Management control systems use, organisational capabilities and performance in universities: application of the resource-based view

Invoking the resource-based view (RBV), this study investigates relationships between management control systems (MCSs) use, including information use from performance measurement systems (PMSs), and organisational capabilities in the context of academic units of Australian universities. Increased competition and attention to distinctive capabilities amongst universities, particularly at their strategic operating unit level of Schools 1, provides the setting for application of this theoretic perspective. The objective of this study is to model various relationships between diagnostic and interactive use of MCSs, attention given to centrally-imposed and discretionary types of PMS information, the strength of capabilities of the academic unit and, in turn, performance of the academic units. This objective is investigated using a field survey in which a mail survey instrument is administered to a census of all Heads of Schools in all 39 universities in Australia. Valid responses were received from 166 Heads. Principal components factor analysis finds that Heads conceived capabilities of their unit in functional dimensions, not in generic dimensions as found in prior literature; Heads also considered performance measures in terms of their importance (critical or discretionary) rather than type (financial versus non-financial). Partial least-squares analysis is then used for path modelling, and several significant results are obtained. Highlights are that diagnostic MCS use and centrally-imposed performance measures, i.e., key performance indicators, but not interactive MCS use or discretionary performance measures, significantly relate to some or all of the strength of capabilities in the fields of teaching, research and networking, and in turn indirectly relate to performance of the academic units. The findings have practical implications for styles of control systems use; focus on selected key performance measures; and development of organisational capabilities for achievement of superior performance by academic schools in universities.

The pricing of infrastructure initial public offerings : evidence from Australia

This paper explores first-day returns on infrastructure entity initial public offerings (IPOs) in Australia from 1996 to 2007. While a good deal has been written on the first-day returns of industrial and mining company IPOs and Real Estate Investment Trust IPOs, first-day returns of infrastructure entity IPOs have yet to be reported in the literature. The study uses ordinary least squares regression analysis to identify factors that might influence the percentage first-day returns theoretically available to investing subscribers and factors that might influence the aggregate amount of money left to subscribers by issuers. The study finds that first-day returns, on average, are not significantly different from zero. There is evidence, however, that suggests higher dividend yields and higher percentage direct costs of capital raising influence these first-day returns. The study also finds that infrastructure entity IPOs that seek to raise more equity capital leave less money on the table for subscribing investors.

N-acetyl cysteine for depressive symptoms in bipolar disorder - a double blind, randomized, placebo-controlled trial

Background: Treatment-resistant subthreshold depression is a major problem in bipolar disorder. Both depression and bipolar disorderare complicated by glutathione depletion. We hypothesized that treatment with N-acetyl cysteine (NAC), a safe, orally bioavailable precursor of glutathione, may improve the depressive component of bipolar disorder.

Methods: A randomized, double-blind, multicenter, placebo-controlled study of individuals (n 75) with bipolar disorder in the maintenance phase treated with NAC (1 g twice daily) adjunctive to usual medication over 24 weeks, with a 4-week washout. The two primary outcomes were the Montgomery Asberg Depression Rating Scale (MADRS) and time to a mood episode. Secondary outcomes included the Bipolar Depression Rating Scale and 11 other ratings of clinical status, quality of life, and functioning.

Results: NAC treatment caused a significant improvement on the MADRS (least squares mean difference [95% confidence interval]: 8.05 [13.16, 2.95], p .002) a n d most secondary scales at end point. Benefit was evident by 8 weeks on the Global Assessment of Functioning Scale and Social and Occupational Functioning Assessment Scale and at 20 weeks on the MADRS. Improvements were lost after washout. There was no effect of NAC on time to a mood episode (log-rank test: p .968) and no significant between-group differences inadverse events. Effect sizes at end point were medium to high for improvements in MADRS and 9 of the 12 secondary readouts.

Conclusions: NAC appears a safe and effective augmentation strategy for depressive symptoms in bipolar  disorder.

Agility in information systems : enabling capabilities for the IT function

This research identifies how the IT function can create agility in existing information systems. Agility is the capability to quickly sense and respond to environmental perturbations. We contrasted perspectives on agility from a widely used industry framework and that of the IS research literature. Beer’s Viable System Model was a useful meta-level theory to house agility elements from IS research and it introduced cybernetic principles to identify the processes required of the IT function. Indeed, our surveys of 70 organizations confirmed that the applied theory better correlates with reported agility than does existing industry best practice.

The research conducted two quantitative surveys to test the applied theory. The first survey mailed a Likert-type questionnaire to the clients of an Australian IT consultancy. The second survey invited international members of professional interest groups to complete a web-based questionnaire. The responses from the surveys were analyzed using partial-least-squares modeling. The data analysis positively correlated the maturity of IT function processes prescribed by the VSM and the likelihood of agility in existing information systems. We claim our findings generalize to other large organizations in OECD member countries.

The research offers an agility-capability model of the IT function to explain and predict agility in existing information systems. A further contribution is to improve industry ‘best practice’ frameworks by prescribing processes of the IT function to develop in maturity.

Immobilized artificial membrane chromatography : quantitative structure-retention relationships of structurally diverse drugs

The chromatographic capacity factors (log k‘) for 32 structurally diverse drugs were determined by high performance liquid chromatography (HPLC) on a stationary phase composed of phospholipids, the so-called immobilized artificial membrane (IAM). In addition, quantitative structure-retention relationships (QSRR) were developed in order to explain the dependence of retention on the chemical structure of the neutral, acidic, and basic drugs considered in this study. The obtained retention data were modeled by means of multiple regression analysis (MLR) and partial least squares (PLS) techniques. The structures of the compounds under study were characterized by means of calculated physicochemical properties and several nonempirical descriptors. For the carboxylic compounds included in the analysis, the obtained results suggest that the IAM-retention is governed by hydrophobicity factors followed by electronic effects due to polarizability in second place. Further, from the analysis of the results obtained of two developed quantitative structure-permeability studies for 20 miscellaneous carboxylic compounds, it may be concluded that the balance between polarizability and hydrophobic effects is not the same toward IAM phases and biological membranes. These results suggest that the IAM phases could not be a suitable model in assessing the acid-membrane interactions. However, it is not possible to generalize this observation, and further work in this area needs to be done to obtain a full understanding of the partitioning of carboxylic compounds in biological membranes. For the non-carboxylic compounds included in the analysis, this work shows that the hydrophobic factors are of prime importance for the IAM-retention of these compounds, while the specific polar interactions, such as electron pair donor−acceptor interactions and electrostatic interactions, are also involved, but they are not dominant.

Determinants of local abundance in a major radiation of Australian passerines (Aves: Meliphagoidea)

Aim  To identify the factors that contribute to variation in abundance (population density), and to investigate whether habitat breadth and diet breadth predict macroecological patterns in a suborder of passerine birds (Meliphagoidea).
Location  Australia (including Tasmania).
Methods  Mean abundance data were collated from site surveys of bird abundance (the Australian Bird Count); range size and latitudinal position data from published distribution maps; and body mass and diet breadth information from published accounts. A diversity index of habitats used (habitat breadth) was calculated from the bird census data. We used bivariate correlation and multiple regression techniques, employing two phylogenetic comparative methods: phylogenetic generalized least squares and independent contrasts.

Results  Body mass and latitude were the only strong predictors of abundance, with larger-bodied and lower-latitude species existing at lower densities. Together, however, body mass and latitude explained only 11.1% of the variation in mean abundance. Range size and habitat breadth were positively correlated, as were diet breadth and body mass. However, neither range size, nor habitat breadth and diet breadth, explained patterns in abundance either directly or indirectly.
Main conclusions  Levels of abundance (population density) in meliphagoid birds are most closely linked to body mass and latitudinal position, but not range size. As with many other macroecological analyses, we find little evidence for aspects of niche breadth having an effect on patterns of abundance. We hypothesize that evolutionary age may also have a determining effect on why species tend to be rarer (less abundant) in the tropics.

Range size-abundance relationships in Australian passerines

Aim  To investigate the relationship between geographical range size and abundance (population density) in Australian passerines.
Location  Australia (including Tasmania).
Methods   We analysed the relationship between range size and local abundance for 272 species of Australian passerines, across the whole order and within families. We measured abundance as mean and maximum abundance, and used a phylogenetic generalized least-squares regression method within a maximum-likelihood framework to control for effects of phylogeny. We also analysed the relationship within seven different habitat types.
Results  There was no correlation between range size and abundance for the whole set of species across all habitats. Analyses within families revealed some strong correlations but showed no consistent pattern. Likewise we found little evidence for any relationship or conflicting patterns in different habitats, except that woodland/forest habitat species exhibit a negative correlation between mean abundance and range size, whilst species in urban habitats exhibit a significant positive relationship between maximum abundance and range size. Despite the general lack of correlation, the raw data plots of range size and abundance in this study occupied a triangular space, with narrowly distributed species exhibiting a greater variation in abundances than widely distributed species. However, using a null model analysis, we demonstrate that this was due to a statistical artefact generated by the frequency distributions for the individual variables.
Conclusions   We find no evidence for a positive range size-abundance relationship among Australian passerines. This absence of a relationship cannot be explained by any conflicting effects introduced by comparing across different habitats, nor is it explained by the fact that large proportions of Australia are arid. We speculate that the considerable isolation and evolutionary age of Australian passerines may be an explanatory factor.