A school-based intervention incorporating smartphone technology to improve health-related fitness among adolescents : rationale and study protocol for the NEAT and ATLAS 2.0 cluster randomised controlled trial and dissemination study

INTRODUCTION: Physical inactivity has been described as a global pandemic. Interventions aimed at developing skills in lifelong physical activities may provide the foundation for an active lifestyle into adulthood. In general, school-based physical activity interventions targeting adolescents have produced modest results and few have been designed to be 'scaled-up' and disseminated. This study aims to: (1) assess the effectiveness of two physical activity promotion programmes (ie, NEAT and ATLAS) that have been modified for scalability; and (2) evaluate the dissemination of these programmes throughout government funded secondary schools. METHODS AND ANALYSIS: The study will be conducted in two phases. In the first phase (cluster randomised controlled trial), 16 schools will be randomly allocated to the intervention or a usual care control condition. In the second phase, the Reach, Effectiveness, Adoption, Implementation and Maintenance (Re-AIM) framework will be used to guide the design and evaluation of programme dissemination throughout New South Wales (NSW), Australia. In both phases, teachers will be trained to deliver the NEAT and ATLAS programmes, which will include: (1) interactive student seminars; (2) structured physical activity programmes; (3) lunch-time fitness sessions; and (4) web-based smartphone apps. In the cluster RCT, study outcomes will be assessed at baseline, 6 months (primary end point) and 12-months. Muscular fitness will be the primary outcome and secondary outcomes will include: objectively measured body composition, cardiorespiratory fitness, flexibility, resistance training skill competency, physical activity, self-reported recreational screen-time, sleep, sugar-sweetened beverage and junk food snack consumption, self-esteem and well-being.

Complex network theoretical analysis on information dissemination over vehicular networks

How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. In this paper, we start with analyzing characteristics of a taxi GPS dataset and then establishing the vehicular-to-infrastructure, vehicle-to-vehicle and the hybrid communication model, respectively. Moreover, we propose a clustering algorithm for station selection, a traffic allocation optimization model and an information source selection model based on the communication performances and complex network theory.

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

BIAS-CORRECTED MAXIMUM LIKELIHOOD ESTIMATION OF THE PARAMETERS OF THE WEIGHTED LINDLEY DISTRIBUTION

This report discusses the calculation of analytic second-order bias techniques for the maximum likelihood estimates (for short, MLEs) of the unknown parameters of the distribution in quality and reliability analysis. It is well-known that the MLEs are widely used to estimate the unknown parameters of the probability distributions due to their various desirable properties; for example, the MLEs are asymptotically unbiased, consistent, and asymptotically normal. However, many of these properties depend on an extremely large sample sizes. Those properties, such as unbiasedness, may not be valid for small or even moderate sample sizes, which are more practical in real data applications. Therefore, some bias-corrected techniques for the MLEs are desired in practice, especially when the sample size is small. Two commonly used popular techniques to reduce the bias of the MLEs, are ‘preventive’ and ‘corrective’ approaches. They both can reduce the bias of the MLEs to order O(n−2), whereas the ‘preventive’ approach does not have an explicit closed form expression. Consequently, we mainly focus on the ‘corrective’ approach in this report. To illustrate the importance of the bias-correction in practice, we apply the bias-corrected method to two popular lifetime distributions: the inverse Lindley distribution and the weighted Lindley distribution. Numerical studies based on the two distributions show that the considered bias-corrected technique is highly recommended over other commonly used estimators without bias-correction. Therefore, special attention should be paid when we estimate the unknown parameters of the probability distributions under the scenario in which the sample size is small or moderate.

Haemophilus influenzae clinical isolates with plasmid pB1000 bearing blaROB-1: fitness cost and interspecies dissemination

Plasmid pB1000 is a mobilizable replicon bearing the bla(ROB-1) beta-lactamase gene that we have recently described in Haemophilus parasuis and Pasteurella multocida animal isolates. Here we report the presence of pB1000 and a derivative plasmid, pB1000', in four Haemophilus influenzae clinical isolates of human origin. Pulsed-field gel electrophoresis showed unrelated patterns in all strains, indicating that the existence of pB1000 in H. influenzae isolates is not the consequence of clonal dissemination. The replicon can be transferred both by transformation and by conjugation into H. influenzae, giving rise to recipients resistant to ampicillin and cefaclor (MICs, > or =64 microg/ml). Stability experiments showed that pB1000 is stable in H. influenzae without antimicrobial pressure for at least 60 generations. Competition experiments between isogenic H. influenzae strains with and without pB1000 revealed a competitive disadvantage of 9% per 10 generations for the transformant versus the recipient. The complete nucleotide sequences of nine pB1000 plasmids from human and animal isolates, as well as the epidemiological data, suggest that animal isolates belonging to the Pasteurellaceae act as an antimicrobial resistance reservoir for H. influenzae. Further, since P. multocida is the only member of this family that can colonize both humans and animals, we propose that P. multocida is the vehicle for the transport of pB1000 between animal- and human-adapted members of the Pasteurellaceae.

TAKING ORGANIZATIONS SERIOUSLY: RESPONSIBLE AGENCY, ORGANIZATIONS AND THE CRIMINAL LAW

In the post-Enlightenment period, Anglo-American criminal law has been applied with increased force, and an ever expanding scope, to collective actors like corporations and other organizations. Recent scholarship has focused on developing “truly organizational” bases of liability that break with the conventional approach of imputing individual conduct to an organization and instead analyze culpable conduct and intent in a way that reflects the distinct and independent capacity of organizations to pursue their interests or goals collaboratively. In 2004, Canada enacted amendments inspired by these ideas in the hope they would lead to more effective criminal enforcement against organizations. Twelve years later, however, the promise of Bill C-45 is largely unfulfilled. In this thesis, I explore how much of this failure of law reform to deliver transformational change is attributable to an individualist bias that permeates how we think about what it means to be responsible and how this then shapes the responsibility ascription process. Using an analytical framework that combines criminal law theory with selected aspects of rational-structural theory and organization culture, I suggest that a promising way forward may lie in reframing the essential qualities required to be a subject of the criminal law in a way that captures the unique attributes that make organizations different from individuals. The resulting organizational concept of responsible agency allows for an integration of organizational reality into how we assess organizational culpability while keeping the ambit of criminal liability within the limits of what is practicable and fair. This better aligns with the spirit of Bill C-45: to impose criminal liability in a way that takes organizations – and their crimes – seriously.

Keeping Variables within Bounds: Using Information between Observations

This research develops an econometric framework to analyze time series processes with bounds. The framework is general enough that it can incorporate several different kinds of bounding information that constrain continuous-time stochastic processes between discretely-sampled observations. It applies to situations in which the process is known to remain within an interval between observations, by way of either a known constraint or through the observation of extreme realizations of the process. The main statistical technique employs the theory of maximum likelihood estimation. This approach leads to the development of the asymptotic distribution theory for the estimation of the parameters in bounded diffusion models. The results of this analysis present several implications for empirical research. The advantages are realized in the form of efficiency gains, bias reduction and in the flexibility of model specification. A bias arises in the presence of bounding information that is ignored, while it is mitigated within this framework. An efficiency gain arises, in the sense that the statistical methods make use of conditioning information, as revealed by the bounds. Further, the specification of an econometric model can be uncoupled from the restriction to the bounds, leaving the researcher free to model the process near the bound in a way that avoids bias from misspecification. One byproduct of the improvements in model specification is that the more precise model estimation exposes other sources of misspecification. Some processes reveal themselves to be unlikely candidates for a given diffusion model, once the observations are analyzed in combination with the bounding information. A closer inspection of the theoretical foundation behind diffusion models leads to a more general specification of the model. This approach is used to produce a set of algorithms to make the model computationally feasible and more widely applicable. Finally, the modeling framework is applied to a series of interest rates, which, for several years, have been constrained by the lower bound of zero. The estimates from a series of diffusion models suggest a substantial difference in estimation results between models that ignore bounds and the framework that takes bounding information into consideration.

Continuing the conversation: 30 years of motivational interviewing dissemination

The systematic examination of motivational interviewing (MI) training outcomes provides a cautionary tale for the dissemination of evidence-based psychological interventions in the substance abuse field. We argue that in order to achieve sustained practice of MI, a greater understanding of successful implementation fidelity in real world settings is required.

Bias of damage awards and free options in securities litigation

Damage measures in securities fraud cases are very imprecise because they are based on security price changes that reflect both the correction of previous misrepresentation and other independent information. Consequently, potential plaintiffs have a valuable “free option” to decide whether or not to file suit, and average damage awards are greater than actual damages, much greater when markets are volatile. The “Private Securities Litigation Reform Act of 1995” was intended to curb abusive litigation and to address the problem of excessive damage awards. Motivated by a misdiagnosis that excess awards are due to temporary price drops, the Act limits damages to the difference between the purchase price and the time-averaged trading price from the release of the corrective information until 90 days later or until the sale of the security, whichever is first. Unfortunately, the Act's modified measure of damages suffers from a more severe free-option problem than did the traditional measure. Also, the Act introduced an additional new option to time the sale of the security; the effects of these options may be mitigated by the impact of the positive drift in stock prices over time, if the time-averaged price is not adjusted for market movements. As a result, the bias can be larger or smaller under the new Act, depending on how severe the free-option problem is. We propose an alternative approach to addressing the issue of excessive damages: courts should adopt a threshold of measured damages below which no damage would be awarded. The threshold would depend on several factors, most notably the volatility of the stock in the period under question. That is, damages will be awarded only if measured damages exceed the threshold, and awards would be capped by the formula presented in the Reform Act.

Graph theory based QoE-driven cooperation stimulation for content dissemination in device-To-device communication

With multimedia dominating the digital contents, Device-To-Device (D2D) communication has been proposed as a promising data offloading solution in the big data area. As the quality of experience (QoE) is a major determining factor in the success of new multimedia applications, we propose a QoEdriven cooperative content dissemination (QeCS) scheme in this work. Specifically, all users predict the QoE of the potential connections characterized by the mean opinion score (MOS), and send the results to the content provider (CP). Then CP formulates a weighted directed graph according to the network topology and MOS of each potential connection. In order to stimulate cooperation among the users, the content dissemination mechanism is designed through seeking 1-factor of the weighted directed graph with the maximum weight thus achieving maximum total user MOS. Additionally, a debt mechanism is adopted to combat the cheat attacks. Furthermore, we extend the proposed QeCS scheme by considering a constrained condition to the optimization problem for fairness improvement. Extensive simulation results demonstrate that the proposed QeCS scheme achieves both efficiency and fairness especially in large scale and density networks.

Prejudicial evaluation: bias in self-and-peer-assessments of teamwork contributions to design

This chapter considers a simple but important question: can students fairly assess each other’s individual contribution to team designs? The chapter focuses on a key problem when using online self-and-peerassessment to individualising design grades for team assignments, namely rater bias – the possibility of students being biased when assessing their own and their peers’ contributions. Three rater-bias issuesare considered in depth: (1) self-overmarking; (2) gender bias and gender differences; and (3) out-group bias in the peer assessment of international students in multicultural cohorts. Each issue is explored viathe analysis of eight years of quantitative data from the use of an online self-and-peer assessment tool. Evidence is found of self-overmarking and of out-group bias in nonhomogeneous cohorts. However, no evidence is found of gender bias. The chapter concludes with recommendations for design teachers around the assessment of individual contributions to teamwork using self-and-peer assessment.

SEMD: secure and efficient message dissemination with policy enforcement in VANET

Vehicular ad hoc network (VANET) is an increasing important paradigm, which not only provides safety enhancement but also improves roadway system efficiency. However, the security issues of data confidentiality, and access control over transmitted messages in VANET have remained to be solved. In this paper, we propose a secure and efficient message dissemination scheme (SEMD) with policy enforcement in VANET, and construct an outsourcing decryption of ciphertext-policy attribute-based encryption (CP-ABE) to provide differentiated access control services, which makes the vehicles delegate most of the decryption computation to nearest roadside unit (RSU). Performance evaluation demonstrates its efficiency in terms of computational complexity, space complexity, and decryption time. Security proof shows that it is secure against replayable choosen-ciphertext attacks (RCCA) in the standard model.

Assemblage, size and abundance bias in a novel sandy shore macro-infaunal sampling technique

Sampling sandy shore macro-invertebrate fauna is critical in enhancing our understanding of beach ecology and conservation, and is a common monitoring approach. The traditional, and almost universal, method of sampling involves sieving sand to locate infauna, but here we describe a novel Hydraulic Sampling Device (HSD), a candidate method for future macro-invertebrate sampling, which has the potential to be faster and more effective at sampling invertebrates. We compared the results obtained by these two methods. Macro-invertebrate fauna of six beaches on Phillip Island, southern Victoria, Australia were sampled in the upper and lower beach. On average, the HSD sampled a smaller size range of fauna than the sieving method, perhaps because of longer handling times and escape of larger individuals. The sieving method found more individuals and a higher species richness. The methods we describe do not produce directly comparable results. On balance, the sieving method is simpler, apparently not as prone to ‘escape bias’, and reports higher abundances and richness of beach infauna.