The role of digital screens in urban life: New opportunities for placemaking

Large digital screens are becoming prevalent across today’s cities dispersing into everyday urban spaces such as public squares and cultural precincts. Examples, such as Federation Square, demonstrate the opportunities for using digital screens to create a sense of place and to add long-term social, cultural and economic value for citizens, who live and work in those precincts. However, the challenge of implementing digital screens in new urban developments is to ensure they respond appropriately to the physical and sociocultural environment in which they are placed. Considering the increasing rate at which digital screens are being embedded into public spaces, it is surprising that the programs running on these screens still seem to be stuck in the cinematic model. The availability of advanced networking and interaction technologies offers opportunities for information access that goes beyond free-to-air television and advertising. This chapter revisits the history and current state of digital screens in urban life and discusses a series of research studies that involve digital screens as interface between citizens and the city. Instead of focusing on technological concerns, the chapter presents a holistic analysis of these studies, with the aim to move towards a more comprehensive understanding of the sociocultural potential of this new media platform, and how the digital content is linked with the spatial quality of the physical space, as well as the place and role of digital screens within the smart city movement.

Assessment of body composition in Sri Lankan children: Validation of a bioelectrical impedance prediction equation

Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2 O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2/Ω), weight and sex code (male = 1; female = 0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1l. PRESS statistics was 2.1l with press residuals of 1.2l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias±1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.

Assessing environmental inequalities in ambient air pollution across urban Australia

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.

Robust estimation using the Huber function with a data-dependent tuning constant

Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

Iterative estimating equations: Linear convergence and asymptotic properties

We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the special case of linear models, the procedure reduces to iterative reweighted least squares. Finite sample performance of the procedure is studied by simulations, and compared with other methods. A numerical example from a medical study is considered to illustrate the application of the method.

Unbiased estimating equations from working correlation models for irregularly timed repeated measures

The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance

The method of generalised estimating equations for regression modelling of clustered outcomes allows for specification of a working matrix that is intended to approximate the true correlation matrix of the observations. We investigate the asymptotic relative efficiency of the generalised estimating equation for the mean parameters when the correlation parameters are estimated by various methods. The asymptotic relative efficiency depends on three-features of the analysis, namely (i) the discrepancy between the working correlation structure and the unobservable true correlation structure, (ii) the method by which the correlation parameters are estimated and (iii) the 'design', by which we refer to both the structures of the predictor matrices within clusters and distribution of cluster sizes. Analytical and numerical studies of realistic data-analysis scenarios show that choice of working covariance model has a substantial impact on regression estimator efficiency. Protection against avoidable loss of efficiency associated with covariance misspecification is obtained when a 'Gaussian estimation' pseudolikelihood procedure is used with an AR(1) structure.

Estimating equations for parameters in stochastic growth models from tag-recapture data

James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.

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.

Public Open Spaces in Kathmandu Valley: A Review of Contemporary Problems and Historic Precedents

The current growth of Kathmandu Valley has been malignant in many ways which suggests a decline of public realm in the city. As the current efforts for planning and design of public open space exhibit numerous problems related to both physical and social aspects of city building, this book examines the shortcomings with contemporary urban development from urban planning and design point of view and attempts to suggest methods to overcome such shortcomings based on the study of historic urban squares. This book identifies the inherent urban design qualities of the historic urban squares in order to learn from them and also attempts to put forward the principles and guidelines for contemporary public space design based on such findings.

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.

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.

HR-MAS NMR spectroscopy shows regional metabolite variation in bovine articular cartilage

Mechanical stress is an important external factor effecting the development and maintenance of articular cartilage. The metabolite profile of diseased cartilage has been well studied but there is limited information about the variation in metabolite profile of healthy cartilage. With the importance of load in maintaining healthy cartilage, regional differences in metabolite profile associated with differences in load may provide information on how load contributes to the maintenance of healthy cartilage. HR-MAS NMR spectroscopy allows the assessment of tissue samples without modification and was used for assessing the difference in metabolic profile between the load bearing and non-load bearing regions of the bovine articular cartilage. In this preliminary study, we examined cartilage from tibia and femur of four knee joints. Sixteen pairs of 1D-NOESY spectra were acquired. Principle component analysis (PCA) identified chemical shifts responsible for variance. SBASE (AMIX) and the Human Metabolome Database were used in conjunction with previous reported cartilage data for identifying metabolites associated with the PCA results. The major contributors to load-related differences in metabolite profile were N-acetyl groups, lactate and phosphocholine peaks. Integrals of these regions were further analysed using a Student's t-test. In load bearing cartilage regions. N-acetyl groups and phosphocholine were found at significantly higher concentration (p < 0.05 and p < 0.005, respectively) in both femur and tibia, while lactate was reduced in load bearing cartilage (p < 0.005). The results of this pilot HR-MAS NMR study demonstrate its ability to provide useful metabolite information for healthy cartilage.

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.