Communications materials on methods of development of revenue and cost estimates to non-technical audiences

This CDROM includes PDFs of presentations on the following topics: "TXDOT Revenue and Expenditure Trends;" "Examine Highway Fund Diversions, & Benchmark Texas Vehicle Registration Fees;" "Evaluation of the JACK Model;" "Future highway construction cost trends;" "Fuel Efficiency Trends and Revenue Impact"

Does metabolic compensation explain the majority of less-than-expected weight loss in obese adults during a short-term severe diet and exercise intervention?

Objective: We investigated to what extent changes in metabolic rate and composition of weight loss explained the less-than-expected weight loss in obese men and women during a diet-plus-exercise intervention. Design: 16 obese men and women (41 ± 9 years; BMI 39 ± 6 kg/m2) were investigated in energy balance before, after and twice during a 12-week VLED (565–650 kcal/day) plus exercise (aerobic plus resistance training) intervention. The relative energy deficit (EDef) from baseline requirements was severe (74-87%). Body composition was measured by deuterium dilution and DXA and resting metabolic rate (RMR) by indirect calorimetry. Fat mass (FM) and fat-free mass (FFM) were converted into energy equivalents using constants: 9.45 kcal/gFM and 1.13 kcal/gFFM. Predicted weight loss was calculated from the energy deficit using the '7700 kcal/kg rule'. Results: Changes in weight (-18.6 ± 5.0 kg), FM (-15.5 ± 4.3 kg), and FFM (-3.1 ± 1.9 kg) did not differ between genders. Measured weight loss was on average 67% of the predicted value, but ranged from 39 to 94%. Relative EDef was correlated with the decrease in RMR (R=0.70, P<0.01) and the decrease in RMR correlated with the difference between actual and expected weight loss (R=0.51, P<0.01). Changes in metabolic rate explained on average 67% of the less-than-expected weight loss, and variability in the proportion of weight lost as FM accounted for a further 5%. On average, after adjustment for changes in metabolic rate and body composition of weight lost, actual weight loss reached 90% of predicted values. Conclusion: Although weight loss was 33% lower than predicted at baseline from standard energy equivalents, the majority of this differential was explained by physiological variables. While lower-than-expected weight loss is often attributed to incomplete adherence to prescribed interventions, the influence of baseline calculation errors and metabolic down-regulation should not be discounted.

Higher education for capacity development or revenue maximisation? Lessons from transnational higher education programs at two Indonesian universities

HE has been changing rapidly due to globalisation that has increased the interconnectedness between nations and people throughout the world (Mok, 2012). As HE has manifested into different forms and governed by competing rationales in recent years, this paper focuses on transnational HE, which is an example of the interconnectedness of universities beyond the national borders. Indonesia is also influenced by the above changes. It took part in free-trade agreements that include HE as a sector to be liberated and accessed by international providers (Nizam, 2006). Indonesian universities found themselves bracing for the global competition for students and simultaneously having to improve their quality in order to survive amidst the growing competition. This competition gave birth to joint transnational HE programs with overseas partners among many Indonesian universities (Macaranas, 2010).

Spatial modelling of population health screening : the role of accessibility in predicting expected patient flows

This paper describes a generalised linear mixed model (GLMM) approach for understanding spatial patterns of participation in population health screening, in the presence of multiple screening facilities. The models presented have dual focus, namely the prediction of expected patient flows from regions to services and relative rates of participation by region- service combination, with both outputs having meaningful implications for the monitoring of current service uptake and provision. The novelty of this paper lies with the former focus, and an approach for distributing expected participation by region based on proximity to services is proposed. The modelling of relative rates of participation is achieved through the combination of different random effects, as a means of assigning excess participation to different sources. The methodology is applied to participation data collected from a government-funded mammography program in Brisbane, Australia.

The effect of injury diagnosis on expected Postconcussion Syndrome (PCS) symptom reporting and illness perception

Objective: To determine if systematic variation of diagnostic terminology (i.e. concussion, minor head injury [MHI], mild traumatic brain injury [mTBI]) following a standardized injury description produced different expected symptoms and illness perceptions. We hypothesized that worse outcomes would be expected of mTBI, compared to other diagnoses, and that MHI would be perceived as worse than concussion. Method:108 volunteers were randomly allocated to conditions in which they read a vignette describing a motor vehicle accident-related mTBI followed by: a diagnosis of mTBI (n=27), MHI (n=24), concussion (n=31); or, no diagnosis (n=26). All groups rated: a) event ‘undesirability’; b) illness perception, and; c) expected Postconcussion Syndrome (PCS) and Posttraumatic Stress Disorder (PTSD) symptoms six months post injury. Results: On average, more PCS symptomatology was expected following mTBI compared to other diagnoses, but this difference was not statistically significant. There was a statistically significant group effect on undesirability (mTBI>concussion & MHI), PTSD symptomatology (mTBI & no diagnosis>concussion), and negative illness perception (mTBI & no diagnosis>concussion). Conclusion: In general, diagnostic terminology did not affect anticipated PCS symptoms six months post injury, but other outcomes were affected. Given that these diagnostic terms are used interchangeably, this study suggests that changing terminology can influence known contributors to poor mTBI outcome.

A conceptual model for reflecting on expected learning vs. demonstrated student performance

Educators are faced with many challenging questions in designing an effective curriculum. What prerequisite knowledge do students have before commencing a new subject? At what level of mastery? What is the spread of capabilities between bare-passing students vs. the top performing group? How does the intended learning specification compare to student performance at the end of a subject? In this paper we present a conceptual model that helps in answering some of these questions. It has the following main capabilities: capturing the learning specification in terms of syllabus topics and outcomes; capturing mastery levels to model progression; capturing the minimal vs. aspirational learning design; capturing confidence and reliability metrics for each of these mappings; and finally, comparing and reflecting on the learning specification against actual student performance. We present a web-based implementation of the model, and validate it by mapping the final exams from four programming subjects against the ACM/IEEE CS2013 topics and outcomes, using Bloom's Taxonomy as the mastery scale. We then import the itemised exam grades from 632 students across the four subjects and compare the demonstrated student performance against the expected learning for each of these. Key contributions of this work are the validated conceptual model for capturing and comparing expected learning vs. demonstrated performance, and a web-based implementation of this model, which is made freely available online as a community resource.

Computer-based assessments of expected satiety predict behavioural measures of portion-size selection and food intake

Previously, expected satiety (ES) has been measured using software and two-dimensional pictures presented on a computer screen. In this context, ES is an excellent predictor of self-selected portions, when quantified using similar images and similar software. In the present study we sought to establish the veracity of ES as a predictor of behaviours associated with real foods. Participants (N = 30) used computer software to assess their ES and ideal portion of three familiar foods. A real bowl of one food (pasta and sauce) was then presented and participants self-selected an ideal portion size. They then consumed the portion ad libitum. Additional measures of appetite, expected and actual liking, novelty, and reward, were also taken. Importantly, our screen-based measures of expected satiety and ideal portion size were both significantly related to intake (p < .05). By contrast, measures of liking were relatively poor predictors (p > .05). In addition, consistent with previous studies, the majority (90%) of participants engaged in plate cleaning. Of these, 29.6% consumed more when prompted by the experimenter. Together, these findings further validate the use of screen-based measures to explore determinants of portion-size selection and energy intake in humans.

The valuation accuracy of multiples in mergers and acquisitions, and their association with firm misvaluation

This study explores the accuracy and valuation implications of the application of a comprehensive list of equity multiples in the takeover context. Motivating the study is the prevalent use of equity multiples in practice, the observed long-run underperformance of acquirers following takeovers, and the scarcity of multiplesbased research in the merger and acquisition setting. In exploring the application of equity multiples in this context three research questions are addressed: (1) how accurate are equity multiples (RQ1); which equity multiples are more accurate in valuing the firm (RQ2); and which equity multiples are associated with greater misvaluation of the firm (RQ3). Following a comprehensive review of the extant multiples-based literature it is hypothesised that the accuracy of multiples in estimating stock market prices in the takeover context will rank as follows (from best to worst): (1) forecasted earnings multiples, (2) multiples closer to bottom line earnings, (3) multiples based on Net Cash Flow from Operations (NCFO) and trading revenue. The relative inaccuracies in multiples are expected to flow through to equity misvaluation (as measured by the ratio of estimated market capitalisation to residual income value, or P/V). Accordingly, it is hypothesised that greater overvaluation will be exhibited for multiples based on Trading Revenue, NCFO, Book Value (BV) and earnings before interest, tax, depreciation and amortisation (EBITDA) versus multiples based on bottom line earnings; and that multiples based on Intrinsic Value will display the least overvaluation. The hypotheses are tested using a sample of 147 acquirers and 129 targets involved in Australian takeover transactions announced between 1990 and 2005. The results show that first, the majority of computed multiples examined exhibit valuation errors within 30 percent of stock market values. Second, and consistent with expectations, the results provide support for the superiority of multiples based on forecasted earnings in valuing targets and acquirers engaged in takeover transactions. Although a gradual improvement in estimating stock market values is not entirely evident when moving down the Income Statement, historical earnings multiples perform better than multiples based on Trading Revenue or NCFO. Third, while multiples based on forecasted earnings have the highest valuation accuracy they, along with Trading Revenue multiples for targets, produce the most overvalued valuations for acquirers and targets. Consistent with predictions, greater overvaluation is exhibited for multiples based on Trading Revenue for targets, and NCFO and EBITDA for both acquirers and targets. Finally, as expected, multiples based Intrinsic Value (along with BV) are associated with the least overvaluation. Given the widespread usage of valuation multiples in takeover contexts these findings offer a unique insight into their relative effectiveness. Importantly, the findings add to the growing body of valuation accuracy literature, especially within Australia, and should assist market participants to better understand the relative accuracy and misvaluation consequences of various equity multiples used in takeover documentation and assist them in subsequent investment decision making.

The effect of varying diagnostic terminology within patient discharge information on expected mild traumatic brain injury outcome

This study aimed to determine if systematic variation of the diagnostic terminology embedded within written discharge information (i.e., concussion or mild traumatic brain injury, mTBI) would produce different expected symptoms and illness perceptions. We hypothesized that compared to concussion advice, mTBI advice would be associated with worse outcomes. Sixty-two volunteers with no history of brain injury or neurological disease were randomly allocated to one of two conditions in which they read a mTBI vignette followed by information that varied only by use of the embedded terms concussion (n = 28) or mTBI (n = 34). Both groups reported illness perceptions (timeline and consequences subscale of the Illness Perception Questionnaire-Revised) and expected Postconcussion Syndrome (PCS) symptoms 6 months post injury (Neurobehavioral Symptom Inventory, NSI). Statistically significant group differences due to terminology were found on selected NSI scores (i.e., total, cognitive and sensory symptom cluster scores (concussion > mTBI)), but there was no effect of terminology on illness perception. When embedded in discharge advice, diagnostic terminology affects some but not all expected outcomes. Given that such expectations are a known contributor to poor mTBI outcome, clinicians should consider the potential impact of varied terminology on their patients.

Defining expected cost for the air conditioning to avoid a price spike of electricity market under DSR model

This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

Is intent-aware expected reciprocal rank sufficient to evaluate diversity?

In this paper we define two models of users that require diversity in search results; these models are theoretically grounded in the notion of intrinsic and extrinsic diversity. We then examine Intent-Aware Expected Reciprocal Rank (ERR-IA), one of the official measures used to assess diversity in TREC 2011-12, with respect to the proposed user models. By analyzing ranking preferences as expressed by the user models and those estimated by ERR-IA, we investigate whether ERR-IA assesses document rankings according to the requirements of the diversity retrieval task expressed by the two models. Empirical results demonstrate that ERR-IA neglects query-intents coverage by attributing excessive importance to redundant relevant documents. ERR-IA behavior is contrary to the user models that require measures to first assess diversity through the coverage of intents, and then assess the redundancy of relevant intents. Furthermore, diversity should be considered separately from document relevance and the documents positions in the ranking.

Music streaming revenue structures stacked against artists

Streaming services like Spotify and Pandora pay many millions of dollars each year for the rights to the music they play. But how much of this ends up back with artists and songwriters? The answer: not an awful lot.

Feature selection using expected attainable discrimination

We propose expected attainable discrimination (EAD) as a measure to select discrete valued features for reliable discrimination between two classes of data. EAD is an average of the area under the ROC curves obtained when a simple histogram probability density model is trained and tested on many random partitions of a data set. EAD can be incorporated into various stepwise search methods to determine promising subsets of features, particularly when misclassification costs are difficult or impossible to specify. Experimental application to the problem of risk prediction in pregnancy is described.

Deconstructing expected passenger experience in airports

The effect of passenger satisfaction on airport profitability has been widely acknowledged in the aviation industry. As a result, there has been much attention directed towards developing a deeper understanding of the factors that influence the passenger experience. In this paper, we explore passenger experience from a novel perspective - that of the activities expected to be undertaken by passengers while in the airport terminal building. Using the Taxonomy of Passenger Experience (TOPA) as our framework, we look at the pre-travel interview data of 48 participants. The results of our analysis are used to construct an activity-centred account of the expected passenger experience for international departures. Our exploration of the expected passenger experienced revealed that not all of the TOPA activities have an equal impact on the passengers' expected experience. The processing, consumptive, preparatory and queuing activity groups featured most prominently in passengers' accounts of their upcoming airport experiences. Of these, the preparatory category was found to have the most direct impact on passenger satisfaction. Additionally, our analysis indicated that utilising queue time to prepare passengers for upcoming processing activities could have a positive effect on both satisfaction and processing efficiency. A further outcome of this research was the observation that "shopping" did not form a part of the expected experience of any of the interviewed participants. The outcomes of this study can be used by airports to assist in the management of passengers' expected experience in the terminal building. As passenger expectations and passenger satisfaction are intrinsically linked, understanding which activities have the most impact on satisfaction provides a basis from which alternate design choices can be evaluated when constructing, or fine-tuning, airport terminal designs.

The expected and unexpected consequences of implementing energy efficient vehicle incentives

Completed as part of a Joint PhD program between Queensland University of Technology and the Royal Institute of Technology in Stockholm, Sweden, this thesis examines the effects of different government incentive policies on the demand, usage and pricing of energy efficient vehicles. This study outlines recommendations for policy makers aiming to increase the uptake of energy efficient vehicles. The study finds that whilst many government incentives have been successful in encouraging the uptake of energy efficient vehicles, policy makers need to both recognise and attempt to minimise the potential unintended consequences of such initiatives.