Using internet search queries for infectious disease surveillance: screening diseases for suitability

Background Internet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with increased internet availability and shifts in health-related information seeking behaviour. This approach to monitoring infectious diseases has, however, only been applied to single or small groups of select diseases. This study aims to systematically investigate the potential for developing surveillance and early warning systems using internet search data, for a wide range of infectious diseases. Methods Official notifications for 64 infectious diseases in Australia were downloaded and correlated with frequencies for 164 internet search terms for the period 2009–13 using Spearman’s rank correlations. Time series cross correlations were performed to assess the potential for search terms to be used in construction of early warning systems. Results Notifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 12 (70.6%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems. Conclusions The findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases

Global environmental emissions estimate: Application of multiple imputation

A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC) for CO2, SO2, PM10, and BOD. Policy implications for each type of emission are derived based on the results of the EKC using WRI. Finally, we predicted the future emissions trend and regional share of CO2 emissions. We found that East Asia and South Asia will be increasing their emissions share while other major CO2 emitters will still produce large shares of the total global emissions.

Can social resilience inform SA/SIA for adaptive planning for climate change in vulnerable regions?

This book represents a landmark effort to probe and analyze the theory and empirics of designing water disaster management policies. It consists of seven chapters that examine, in-depth and comprehensively, issues that are central to crafting effective policies for water disaster management. The authors use historical surveys, institutional analysis, econometric investigations, empirical case studies, and conceptual-theoretical discussions to clarify and illuminate the complex policy process. The specific topics studied in this book include a review and analysis of key policy areas and research priority areas associated with water disaster management, community participation in disaster risk reduction, the economics and politics of ‘green’ flood control, probabilistic flood forecasting for flood risk management, polycentric governance and flood risk management, drought management with the aid of dynamic inter-generational preferences, and how social resilience can inform SA/SIA for adaptive planning for climate change in vulnerable areas. A unique feature of this book is its analysis of the causes and consequences of water disasters and efforts to address them successfully through policy-rich, cross-disciplinary and transnational papers. This book is designed to help enrich the sparse discourse on water disaster management policies and galvanize water professionals to craft creative solutions to tackle water disasters efficiently, equitably, and sustainably. This book should also be of considerable use to disaster management professionals, in general, and natural resource policy analysts.

Teaching scenario analysis – An action learning pedagogy

In this paper we provide an introduction to our teaching of scenario analysis. Scenario analysis offers an excellent instructional vehicle for investigating ‘wicked problems’; issues that are complex and ambiguous and require trans-disciplinary inquiry. We outline the pedagogical underpinning based on action learning and provide a critical approach from the intuitive logics school of scenario analysis. We use this in our programme in which student groups engage in semi-structured, but divergent and inclusive analysis of a selected focal issue. They then develop a set of scenario storylines that outline the limits of possibility and plausibility for a selected time-horizon year. The scenarios are portrayed not as narratives, but as vehicles for exploration of the causes and outcomes of the interplay between forces in the contextual environment that drive the unfolding future in the context of the focal issue. In this way, we provide internally-generated challenges to both individual pre-conceptions and group-level thinking.

On the benefits of equicorrelation for portfolio allocation

The importance of modelling correlation has long been recognised in the field of portfolio management, with largedimensional multivariate problems increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating a number of models used to generate forecasts of the correlation matrix for large-dimensional problems.We find evidence in favour of assuming equicorrelation across various portfolio sizes, particularly during times of crisis. During periods of market calm, however, the suitability of the constant conditional correlation model cannot be discounted, especially for large portfolios. A portfolio allocation problem is used to compare forecasting methods. The global minimum variance portfolio and Model Confidence Set are used to compare methods, while portfolio weight stability and relative economic value are also considered.

Adoption dynamics of increasing-return technologies in systemic contexts

Many systemic, complex technologies have been suggested to exhibit increasing returns to adoption, whereby the initial increase in adoption leads to increasing experience with the technology, which drives technological improvements and use, subsequently leading to further adoption. In addition, in the systemic context, mimetic behavior may lend support to increasing returns as technology adoption is witnessed among other agents in the systemic context. Finally, inter-dependencies in the systemic context also sensitize the adoption behavior to fundamental changes in technology provisioning, and this may lend support for the increasing returns type of dynamics in adoption. Our empirical study examines the dynamics of organizational technology adoption when technology is provisioned by organizations in another sub-system in a systemic context. We hypothesize that innovation, imitation, and technological change effects are present in creating increasing returns in the systemic context. Our empirical setting considers 24 technologies represented by 2282 data points in the computer industry. Our results provide support for our prediction that imitation effects are present in creating increasing returns to adoption. We further discuss the managerial and research implications of our results.

The role of context and motivation variables in mobile commerce usage: A further perspective on Chong (2013)

We comment on a recent article by Chong (2013) on the roles of demographic and motivation variables in mobile commerce usage. Drawing on the recent research on the service-dominant logic, socioemotional selectivity theory, and data from a first empirical study, we argue that a broader discussion on the value relevance of mobile commerce activities for customers and the consideration of consumers' future time perspectives would provide a richer, potentially more appropriate picture of the drivers of mobile commerce usage. Furthermore, using data from a second empirical study, we highlight several validity issues of the used scales. We hope to motivate a replication and extension of Chong's study and also provide recommendations for future research on this area.

Groundwater balance research to improve the accuracy of drawdown predictions in the Surat Basin, Queensland

Groundwater modelling studies rely on an accurate determination of inputs and outputs that make up the water balance. Often there is large uncertainty associated with estimates of recharge and unmetered groundwater use. This can translate to equivalent uncertainty in the forecasting of sustainable yields, impacts of extraction, and susceptibility of groundwater dependent ecosystems. In the case of Coal Seam Gas, it is important to characterise the temporal and special distribution of depressurisation in the reservoir and how this may or may not extend to the adjacent aquifers. A regional groundwater flow model has been developed by the Queensland Government to predict drawdown impacts due to Coal Seam Gas activities in the Surat basin. This groundwater model is undergoing continued refinement and there is currently scope to address some of the key areas of uncertainty including better quantification of groundwater recharge and unmetered groundwater extractions. Research is currently underway to improve the accuracy of estimates of both of these components of the groundwater balance in order to reduce uncertainty in predicted groundwater drawdowns due to CSG activities.

Modelling interregional links in electricity price spikes

Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to dealwith spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account.

Predicting the speed of a Wave Glider autonomous surface vehicle from wave model data

A key component of robotic path planning is ensuring that one can reliably navigate a vehicle to a desired location. In addition, when the features of interest are dynamic and move with oceanic currents, vehicle speed plays an important role in the planning exercise to ensure that vehicles are in the right place at the right time. Aquatic robot design is moving towards utilizing the environment for propulsion rather than traditional motors and propellers. These new vehicles are able to realize significantly increased endurance, however the mission planning problem, in turn, becomes more difficult as the vehicle velocity is not directly controllable. In this paper, we examine Gaussian process models applied to existing wave model data to predict the behavior, i.e., velocity, of a Wave Glider Autonomous Surface Vehicle. Using training data from an on-board sensor and forecasting with the WAVEWATCH III model, our probabilistic regression models created an effective method for forecasting WG velocity.

Effect of upstream traffic signal on capacity of a downstream TWSC intersection

This paper investigates the platoon dispersion model that is part of the 2010 Highway Capacity Manual that is used for forecasting downstream traffic flows for analyzing both signalized and TWSC intersections. The paper focuses on the effect of platoon dispersion on the proportion of time blocked, the conflicting flow rate, and the capacity flow rate for the major street left turn movement at a TWSC intersection. The existing HCM 2010 methodology shows little effect on conflicting flow or capacity for various distances downstream from the signalized intersection. Two methods are suggested for computing the conflicting flow and capacity of minor stream movements at the TWSC intersection that have more desirable properties than the existing HCM method. Further, if the existing HCM method is retained, the results suggest that the upstream signals model be dropped from the HCM method for TWSC intersections.

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation’s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.

Underlying scaling relationships between solar activity and geomagnetic activity revealed by multifractal analyses

his paper identifies some scaling relationships between solar activity and geomagnetic activity. We examine the scaling properties of hourly data for two geomagnetic indices (ap and AE), two solar indices (solar X-rays Xl and solar flux F10.7), and two inner heliospheric indices (ion density Ni and flow speed Vs) over the period 1995–2001 by the universal multifractal approach and the traditional multifractal analysis. We found that the universal multifractal model (UMM) provides a good fit to the empirical K(q) and τ(q) curves of these time series. The estimated values of the Lévy index α in the UMM indicate that multifractality exists in the time series for ap, AE, Xl, and Ni, while those for F10.7 and Vs are monofractal. The estimated values of the nonconservation parameter H of this model confirm that these time series are conservative which indicate that the mean value of the process is constant for varying resolution. Additionally, the multifractal K(q) and τ(q) curves, and the estimated values of the sparseness parameter C1 of the UMM indicate that there are three pairs of indices displaying similar scaling properties, namely ap and Xl, AE and Ni, and F10.7 and Vs. The similarity in the scaling properties of pairs (ap,Xl) and (AE,Ni) suggests that ap and Xl, AE and Ni are better correlated—in terms of scaling—than previous thought, respectively. But our results still cannot be used to advance forecasting of ap and AE by Xl and Ni, respectively, due to some reasons

Local music repertoire and the digitization of the international music industry: An empirical analysis 1994 – 2013

In some of the countries where there has been a rapid increase in the use of online music distribution technologies, analysts have reported about declining sales of local music repertoire (e.g. Nordgård, 2013). The analysts are concerned about such tendencies since local music repertoire accounts for a sizable share of an average country’s total recorded music sales (e.g. IFPI, 2012). This paper searches for empirical evidence that may confirm these reports in a number of music markets in North America, Europe and Australasia. The paper makes a contribution to the literature on the digital transformation of the music industry since it combines and analyses data sources that previously have not been used in this context and gives a new perspective on changing user consumption practices in the music industry. The paper also examines the variation of geographic diversity over time among international acts that become commercially successful in the countries covered by the study.

Comparison of the Cosmed K4 b2 and the Deltatrac II™ metabolic cart in measuring resting energy expenditure in adults

Background and Aims: The objective of the study was to compare data obtained from the Cosmed K4 b2 and the Deltatrac II™ metabolic cart for the purpose of determining the validity of the Cosmed K4 b2 in measuring resting energy expenditure. Methods: Nine adult subjects (four male, five female) were measured. Resting energy expenditure was measured in consecutive sessions using the Cosmed K4 b2, the Deltatrac II™ metabolic cart separately and the Cosmed K4 b2 and Deltatrac II™ metabolic cart simultaneously, performed in random order. Resting energy expenditure (REE) data from both devices were then compared with values obtained from predictive equations. Results: Bland and Altman analysis revealed a mean bias for the four variables, REE, respiratory quotient (RQ), VCO2, VO2 between data obtained from Cosmed K4 b2 and Deltatrac II™ metabolic cart of 268 ± 702 kcal/day, -0.0±0.2, 26.4±118.2 and 51.6±126.5 ml/min, respectively. Corresponding limits of agreement for the same four variables were all large. Also, Bland and Altman analysis revealed a larger mean bias between predicted REE and measured REE using Cosmed K4 b2 data (-194±603 kcal/day) than using Deltatrac™ metabolic cart data (73±197 kcal/day). Conclusions: Variability between the two devices was very high and a degree of measurement error was detected. Data from the Cosmed K4 b2 provided variable results on comparison with predicted values, thus, would seem an invalid device for measuring adults. © 2002 Elsevier Science Ltd. All rights reserved.