An improved Fabens method for estimation of growth parameters in the vonBertalanffy model with individual asymptotes

In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.

Difference covering arrays and pseudo-orthogonal Latin squares

A pair of Latin squares, A and B, of order n, is said to be pseudo-orthogonal if each symbol in A is paired with every symbol in B precisely once, except for one symbol with which it is paired twice and one symbol with which it is not paired at all. A set of t Latin squares, of order n, are said to be mutually pseudo-orthogonal if they are pairwise pseudo-orthogonal. A special class of pseudo-orthogonal Latin squares are the mutually nearly orthogonal Latin squares (MNOLS) first discussed in 2002, with general constructions given in 2007. In this paper we develop row complete MNOLS from difference covering arrays. We will use this connection to settle the spectrum question for sets of 3 mutually pseudo-orthogonal Latin squares of even order, for all but the order 146.

Public trust in Australian charities: Accounting for cause and effect

This paper reports on a study of the key determinants of public trust in charitable organisations, using survey data commissioned by the Australian Charities and Not-for-profits Commission. Data analysis used partial least squares structural equation modelling to examine both antecedents of trust and the influence of trust on charitable donative intentions. We found that people tend to trust charities with which they are familiar, and which are transparent in their reporting. Organisational size, importance, reputation and national significant were also antecedents of trust. People are more likely to volunteer or donate to charities they trust. The practical implications of this are that charities seeking to enhance their volunteer and donation base should pay attention to their marketing, reputation and disclosure activities, as well as to doing good work on an ongoing basis in the community. Theoretically, the implications are that transparency and reputation do not result directly in donations and volunteering, but they do create trust, and it is trust which then leads to donations and volunteering.

Systematic analysis of changes in cannabis use among participants in control conditions of randomised controlled trials

Introduction Cannabis remains the most used illegal substance across the globe, and negative outcomes and disorders are common. A spotlight therefore falls on reductions in cannabis use in people with cannabis use disorder. Current estimates of unassisted cessation or reduction in cannabis use rely on community surveys, and few studies focus on individuals with disorder. A key interest of services and researchers is to estimate effect size of reductions in consumption among treatment seekers who do not obtain treatment. Effects within waiting list or information-only control conditions of randomised controlled trials offer an opportunity to study this question. Method This paper examines the extent of reductions in days of cannabis use in the control groups of randomised controlled trials on treatment of cannabis use disorders. A systematic literature search was performed to identify trials that reported days of cannabis use in the previous 30 (or equivalent). Results Since all but one of the eight identified studies had delayed treatment controls, results could only be summarised across 2–4 months. Average weighted days of use in the previous 30 days fell from 24.5 to 19.9, and a meta-analysis using a random effects model showed an average reduction of 0.442 SD. However, every study had at least one significant methodological issue. Conclusions While further high-quality data is needed to confirm the observed effects, these results provide a baseline from which researchers and practitioners can estimate the extent of change required to detect effects of cannabis treatments in services or treatment trials.

Enterprise system investments for competitive advantage: An empirical study of Swiss SMEs

Previous research identifies various reasons companies invest in information technology (IT), often as a means to generate value. To add to the discussion of IT value generation, this study investigates investments in enterprise software systems that support business processes. Managers of more than 500 Swiss small and medium-sized enterprises (SMEs) responded to a survey regarding the levels of their IT investment in enterprise software systems and the perceived utility of those investments. The authors use logistic and ordinary least squares regression to examine whether IT investments in two business processes affect SMEs' performance and competitive advantage. Using cluster analysis, they also develop a firm typology with four distinct groups that differ in their investments in enterprise software systems. These findings offer key implications for both research and managerial practice.

Factors influencing kinetic and equilibrium behaviour of sodium ion exchange with strong acid cation resin

This study reports an investigation of the ion exchange treatment of sodium chloride solutions in relation to use of resin technology for applications such as desalination of brackish water. In particular, a strong acid cation (SAC) resin (DOW Marathon C) was studied to determine its capacity for sodium uptake and to evaluate the fundamentals of the ion exchange process involved. Key questions to answer included: impact of resin identity; best models to simulate the kinetics and equilibrium exchange behaviour of sodium ions; difference between using linear least squares (LLS) and non-linear least squares (NLLS) methods for data interpretation; and, effect of changing the type of anion in solution which accompanied the sodium species. Kinetic studies suggested that the exchange process was best described by a pseudo first order rate expression based upon non-linear least squares analysis of the test data. Application of the Langmuir Vageler isotherm model was recommended as it allowed confirmation that experimental conditions were sufficient for maximum loading of sodium ions to occur. The Freundlich expression best fitted the equilibrium data when analysing the information by a NLLS approach. In contrast, LLS methods suggested that the Langmuir model was optimal for describing the equilibrium process. The Competitive Langmuir model which considered the stoichiometric nature of ion exchange process, estimated the maximum loading of sodium ions to be 64.7 g Na/kg resin. This latter value was comparable to sodium ion capacities for SAC resin published previously. Inherent discrepancies involved when using linearized versions of kinetic and isotherm equations were illustrated, and despite their widespread use, the value of this latter approach was questionable. The equilibrium behaviour of sodium ions form sodium fluoride solution revealed that the sodium ions were now more preferred by the resin compared to the situation with sodium chloride. The solution chemistry of hydrofluoric acid was suggested as promoting the affinity of the sodium ions to the resin.

A relational approach to direct mail consumption

- Purpose This paper aims to investigate how direct mail consumption contributes to brand relationship quality. Store flyers and other direct mailings continue to play a significant role in many companies’ communication strategies. Research on this topic predominantly investigates driving store traffic and sales. Less is known regarding the consumer side, such as the value that consumers may derive from the consumption of direct mailings and the effects of such a value on brand relationship quality. To address this limitation, this paper tests a causal model of the contribution of direct mail value to brand commitment, drawing on a value framework that integrates social theory of engagement regimes and literature on experiential customer value. - Design/methodology/approach The empirical work of this paper is based on a rigorous four-study mixed methods design, involving qualitative study, confirmatory factor analysis and partial least squares structural modeling. - Findings The authors develop two second-order formatively designed scales – familiar value and planned value scales – that illustrate the role of engagement regimes in consumer behavior. Although both types of value contribute equally to direct mail attachment, they exert contrasting effects on other mediational consumer responses, such as reading and gratitude. Finally, the proposed theoretical model appears to be robust in predicting customers’ brand commitment. - Research limitations/implications This study provides new insights into the research on consumer value and brand relational communication. - Originality/value This study is the first to consider consumer benefits from the social perspective of engagement regimes.

Characterization of anomalous relaxation using the time-fractional Bloch equation and multiple echo T2 *-weighted magnetic resonance imaging at 7T

PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.