The impact of divergent historical and cultural factors on convergence in global communication practice

Communication practice is increasingly converging around globally consistent approaches and techniques shaped by both globalisation and globalising communications technologies. However, this paper argues, national and regional practice histories and cultural characteristics have shaped, and continue to shape, practice in individual markets. The paper analyses the extent of that these divergent histories and cultures have shaped the structure and practices of the public relations industry in Australia and other countries. The paper challenges the common assumptions about public relations development and industry practice having developed from a predominantly US-based model progressively disseminated globally. It traces the history of public relations in Australia, counterpointing its distinctive origins, to the US-origin thesis. It also examines the impact of demography and diverse national culture on industry shape and practice, comparing the Australian industry to that of other industries around the world. It uses mini-case studies of campaigns in specific countries to assess the extent to which they are culturally bound by historical and cultural differences and the extent to which they are capable of being transferred or adapted to individual markets. For instance, assumptions about globally consistent brand identities are contradicted by McDonald’s’ branding practices in markets such as Canada and Japan. The paper also discusses how emerging market PR industries are being shaped by distinctive and divergent cultures and development paths and may create new structural and practice models as the emerging economies becoming dominant internationally. The authors suggest that history and cultural diversity continue, and will continue to, shape national and regional practices.

Prediction of pedestrians routes within a built environment in normal conditions

Modelling and prediction of pedestrian routing behaviours within known built environments has recently attracted the attention of researchers across multiple disciplines, owing to the growing demand on urban resources and requirements for efficient use of public facilities. This study presents an investigation into pedestrians' routing behaviours within an indoor environment under normal, non-panic situations. A network-based method using constrained Delaunay triangulation is adopted, and a utility-based model employing dynamic programming is developed. The main contribution of this study is the formulation of an appropriate utility function that allows an effective application of dynamic programming to predict a series of consecutive waypoints within a built environment. The aim is to generate accurate sequence waypoints for the pedestrian walking path using only structural definitions of the environment as defined in a standard CAD format. The simulation results are benchmarked against those from the A* algorithm, and the outcome positively indicates the usefulness of the proposed method in predicting pedestrians' route selection activities. © 2014 Elsevier Ltd. All rights reserved.

Board structure and survival of new economy IPO firms

Research Question/Issue: This study examines the relevance of currently accepted best practice recommendations regarding board structure on the survival likelihood of new economy initial public offering companies. We argue that industry context determines governance outcomes. Research Findings/Insights: We study 125 Australian new economy firms listed between 1994 and 2002. Each firm is tracked until the end of 2007 for monitoring their survival. We find that board independence is associated with an increase in the likelihood of corporate survival. We also find that the benefits of board independence increase at a decreasing rate. Theoretical/Academic Implications: The standard best practice recommendation of board independence stems from the monitoring role of directors and is based on agency theory. The results from our study suggest that the recommendation regarding board independence does not work well for new economy firms. While the agency theory based model implies a monotonic relation between board independence and performance, our research suggests that the relationship is nonlinear. This variation occurs because of increased monitoring costs faced by outsiders due to higher information asymmetry and complexity of new economy firms. Our empirical results suggest that inside directors play a complementary role to outsiders in mitigating firm failure. Practitioner/Policy Implications: Our research offers insights to policy makers who are interested in setting best practice standards regarding board structure. Our research suggests that firm/industry characteristics play a crucial role in determining the optimal board structure. In firms/industries where outsiders face significantly higher information processing costs, insiders can play a valuable complementary role to outsiders in enhancing the effectiveness of the board. Thus future hard or soft regulations related to board structure should consider industry context.

A decentralized cloud firewall framework with resources provisioning cost optimization

Cloud computing is becoming popular as the next infrastructure of computing platform. Despite the promising model and hype surrounding, security has become the major concern that people hesitate to transfer their applications to clouds. Concretely, cloud platform is under numerous attacks. As a result, it is definitely expected to establish a firewall to protect cloud from these attacks. However, setting up a centralized firewall for a whole cloud data center is infeasible from both performance and financial aspects. In this paper, we propose a decentralized cloud firewall framework for individual cloud customers. We investigate how to dynamically allocate resources to optimize resources provisioning cost, while satisfying QoS requirement specified by individual customers simultaneously. Moreover, we establish novel queuing theory based model M/Geo/1 and M/Geo/m for quantitative system analysis, where the service times follow a geometric distribution. By employing Z-transform and embedded Markov chain techniques, we obtain a closed-form expression of mean packet response time. Through extensive simulations and experiments, we conclude that an M/Geo/1 model reflects the cloud firewall real system much better than a traditional M/M/1 model. Our numerical results also indicate that we are able to set up cloud firewall with affordable cost to cloud customers.

Hierarchical dirichlet process for tracking complex topical structure evolution and its application to autism research literature

In this paper we describe a novel framework for the discovery of the topical content of a data corpus, and the tracking of its complex structural changes across the temporal dimension. In contrast to previous work our model does not impose a prior on the rate at which documents are added to the corpus nor does it adopt the Markovian assumption which overly restricts the type of changes that the model can capture. Our key technical contribution is a framework based on (i) discretization of time into epochs, (ii) epoch-wise topic discovery using a hierarchical Dirichlet process-based model, and (iii) a temporal similarity graph which allows for the modelling of complex topic changes: emergence and disappearance, evolution, splitting and merging. The power of the proposed framework is demonstrated on the medical literature corpus concerned with the autism spectrum disorder (ASD) - an increasingly important research subject of significant social and healthcare importance. In addition to the collected ASD literature corpus which we made freely available, our contributions also include two free online tools we built as aids to ASD researchers. These can be used for semantically meaningful navigation and searching, as well as knowledge discovery from this large and rapidly growing corpus of literature.

Successional specialization in a reptile community cautions against widespread planned burning and complete fire suppression

Summary: Conservation of biodiversity in fire-prone regions depends on understanding responses to fire in animal communities and the mechanisms governing these responses. We collated data from an Australian semi-arid woodland reptile community (4796 individuals captured over 6 years) to: (i) determine the ability of commonly used shorter-term (2 years) surveys to detect reptile responses to time since fire (TSF) and (ii) investigate whether ecological traits of species reliably predicted their responses to fire. Of 16 reptile species analysed, four had responses to TSF consistent with shorter-term surveys and three showed no response to TSF. Nine species had responses to TSF not detected in previous studies using smaller but substantial subsets of the same data. Among the 13 affected species, times of peak abundance ranged from 1 to 50 years after fire. Nocturnal, burrowing species tended to be early successional and leaf-litter dwellers to be late successional, but these were only weak trends. Synthesis and applications. We found only limited support for a generalizable, trait-based model of succession in reptiles. However, our study revealed that the majority of common reptile species in our study region specialize on a post-fire successional stage and may therefore become threatened if homogeneous fire regimes predominate. Our study highlights the importance of interpreting results from time- or sample-limited fire studies of reptiles with the knowledge that many ecological responses may not have been detected. In such cases, an adaptive or precautionary approach to fire management may be necessary. We found only limited support for a generalizable, trait-based model of succession in reptiles. However, our study revealed that the majority of common reptile species in our study region specialize on a post-fire successional stage and may therefore become threatened if homogeneous fire regimes predominate. Our study highlights the importance of interpreting results from time- or sample-limited fire studies of reptiles with the knowledge that many ecological responses may not have been detected. In such cases, an adaptive or precautionary approach to fire management may be necessary.

Detecting subclinical diabetic cardiac autonomic neuropathy by analyzing ventricular repolarization dynamics

In this study, a linear parametric modeling technique was applied to model ventricular repolarization (VR) dynamics. Three features were selected from the surface ECG recordings to investigate the changes in VR dynamics in healthy and cardiac autonomic neuropathy (CAN) participants with diabetes including heart rate variability (calculated from RR intervals), repolarization variability (calculated from QT intervals), and respiration [calculated by ECG-derived respiration (EDR)]. Surface ECGs were recorded in a supine resting position from 80 age-matched participants (40 with no cardiac autonomic neuropathy (NCAN) and 40 with CAN). In the CAN group, 25 participants had early/subclinical CAN (ECAN) and 15 participants were identified with definite/clinical CAN (DCAN). Detecting subclinical CAN is crucial for designing an effective treatment plan to prevent further cardiovascular complications. For CAN diagnosis, VR dynamics was analyzed using linear parametric autoregressive bivariate (ARXAR) and trivariate (ARXXAR) models, which were estimated using 250 beats of derived QT, RR, and EDR time series extracted from the first 5 min of the recorded ECG signal. Results showed that the EDR-based models gave a significantly higher fitting value (p < 0.0001) than models without EDR, which indicates that QT-RR dynamics is better explained by respiratory-information-based models. Moreover, the QT-RR-EDR model fitting values gradually decreased from the NCAN group to ECAN and DCAN groups, which indicate a decoupling of QT from RR and the respiration signal with the increase in severity of CAN. In this study, only the EDR-based model significantly distinguished ECAN and DCAN groups from the NCAN group (p < 0.05) with large effect sizes (Cohen's d > 0.75) showing the effectiveness of this modeling technique in detecting subclinical CAN. In conclusion, the EDR-based trivariate QT-RR-EDR model was found to be better in detecting the presence and severity of CAN than the bivariate QT-RR model. This finding also establishes the importance of adding respiratory information for analyzing the gradual deterioration of normal VR dynamics in pathological conditions, such as diabetic CAN.

Lung cancer prediction from microarray data by gene expression programming

Lung cancer is a leading cause of cancer-related death worldwide. The early diagnosis of cancer has demonstrated to be greatly helpful for curing the disease effectively. Microarray technology provides a promising approach of exploiting gene profiles for cancer diagnosis. In this study, the authors propose a gene expression programming (GEP)-based model to predict lung cancer from microarray data. The authors use two gene selection methods to extract the significant lung cancer related genes, and accordingly propose different GEP-based prediction models. Prediction performance evaluations and comparisons between the authors' GEP models and three representative machine learning methods, support vector machine, multi-layer perceptron and radial basis function neural network, were conducted thoroughly on real microarray lung cancer datasets. Reliability was assessed by the cross-data set validation. The experimental results show that the GEP model using fewer feature genes outperformed other models in terms of accuracy, sensitivity, specificity and area under the receiver operating characteristic curve. It is concluded that GEP model is a better solution to lung cancer prediction problems.

The use of traits to interpret responses to large scale - edge effects: a study of epigaeic beetle assemblages across a Eucalyptus forest and pine plantation edge

Context: Edge effects due to habitat loss and fragmentation have pervasive impacts on many natural ecosystems worldwide. Objective: We aimed to explore whether, in tandem with the resource-based model of edge effects, species feeding-guild and flight-capacity can help explain species responses to an edge. Methods: We used a two-sided edge gradient that extended from 1000 m into native Eucalyptus forest to 316 m into an exotic pine plantation. We used generalised additive models to examine the continuous responses of beetle species, feeding-guild species richness and flight-capable group species richness to the edge gradient and environmental covariates. Results: Phytophagous species richness was directly related to variation in vegetation along the edge gradient. There were more flight-capable species in Eucalyptus forest and more flightless species in exotic pine plantation. Many individual species exhibited multiple-peaked edge-profiles. Conclusions: The resource based model for edge effects can be used in tandem with traits such as feeding-guild and flight-capacity to understand drivers of large scale edge responses. Some trait-groups can show generalisable responses that can be linked with drivers such as vegetation richness and habitat structure. Many trait-group responses, however, are less generalisable and not explained by easily measured habitat variables. Difficulties in linking traits with resources along the edge could be due to unmeasured variation and indirect effects. Some species’ responses reached the limits of the edge gradient demonstrating the need to examine edge effects at large scales, such as kilometres.