Evaluation of fruit and vegetable intakes of Australian adults: the nutrition survey 1995

Objective: To evaluate the fruit and vegetable intakes of Australian adults aged 19-64 years. Methods: Intake data were collected as part of the National Nutrition Survey 1995 representing all Australian States and Territories, including city, metropolitan, rural and remote areas. Dietary intake of 8,891 19-to-64 year-olds was assessed using a structured 24-hour recall. Intake frequency was assessed as the proportion of participants consuming fruit and vegetables on the day prior to interview and variety was assessed as the number of subgroups of fruit and vegetables consumed. Intake levels were compared with the recommendations of the Australian Guide to Healthy Eating (AGHE). Results: Sixty-two per cent of participants consumed some fruit and 89% consumed some vegetables on the day surveyed. Males were less likely to consume fruit and younger adults less likely to consume fruit and vegetables compared with females and older adults respectively. Variety was primarily low (1 subcategory) for fruit and medium (3-4 subcategories) for vegetables. Thirty-two per cent of adults consumed the minimum two serves of fruit and 30% consumed the minimum five serves of vegetables as recommended by the AGHE. Eleven per cent of adults met the minimum recommendations for both fruit and vegetables. Conclusion: A large proportion of adults have fruit and vegetable intakes below the AGHE minimum recommendations. Implications: A nationally integrated, longterm campaign to increase fruit and vegetable consumption, supported by policy changes to address structural barriers to consumption, is vital to improve fruit and vegetable consumption among adults

What do IPAQ questions mean to older adults? Lessons from cognitive interviews

Background Most questionnaires used for physical activity (PA) surveillance have been developed for adults aged ≤65 years. Given the health benefits of PA for older adults and the aging of the population, it is important to include adults aged 65+ years in PA surveillance. However, few studies have examined how well older adults understand PA surveillance questionnaires. This study aimed to document older adults’ understanding of questions from the International PA Questionnaire (IPAQ), which is used worldwide for PA surveillance. Methods Participants were 41 community-dwelling adults aged 65-89 years. They each completed IPAQ in a face-to-face semi-structured interview, using the “think-aloud” method, in which they expressed their thoughts out loud as they answered IPAQ questions. Interviews were transcribed and coded according to a three-stage model: understanding the intent of the question; performing the primary task (conducting the mental operations required to formulate a response); and response formatting (mapping the response into pre-specified response options). Results Most difficulties occurred during the understanding and performing the primary task stages. Errors included recalling PA in an “average” week, not in the previous 7 days; including PA lasting ≤10 minutes/session; reporting the same PA twice or thrice; and including the total time of an activity for which only a part of that time was at the intensity specified in the question. Participants were unclear what activities fitted within a question’s scope and used a variety of strategies for determining the frequency and duration of their activities. Participants experienced more difficulties with the moderate-intensity PA and walking questions than with the vigorous-intensity PA questions. The sitting time question, particularly difficult for many participants, required the use of an answer strategy different from that used to answer questions about PA. Conclusions These findings indicate a need for caution in administering IPAQ to adults aged ≥65 years. Most errors resulted in over-reporting, although errors resulting in under-reporting were also noted. Given the nature of the errors made by participants, it is possible that similar errors occur when IPAQ is used in younger populations and that the errors identified could be minimized with small modifications to IPAQ.

Computationally efficient numerical methods for time- and space-fractional Fokker–Planck equations

Fractional Fokker–Planck equations have been used to model several physical situations that present anomalous diffusion. In this paper, a class of time- and space-fractional Fokker–Planck equations (TSFFPE), which involve the Riemann–Liouville time-fractional derivative of order 1-α (α(0, 1)) and the Riesz space-fractional derivative (RSFD) of order μ(1, 2), are considered. The solution of TSFFPE is important for describing the competition between subdiffusion and Lévy flights. However, effective numerical methods for solving TSFFPE are still in their infancy. We present three computationally efficient numerical methods to deal with the RSFD, and approximate the Riemann–Liouville time-fractional derivative using the Grünwald method. The TSFFPE is then transformed into a system of ordinary differential equations (ODE), which is solved by the fractional implicit trapezoidal method (FITM). Finally, numerical results are given to demonstrate the effectiveness of these methods. These techniques can also be applied to solve other types of fractional partial differential equations.

Coast control for mass rapid transit railways with searching methods

With daily commercial and social activity in cities, regulation of train service in mass rapid transit railways is necessary to maintain service and passenger flow. Dwell-time adjustment at stations is one commonly used approach to regulation of train service, but its control space is very limited. Coasting control is a viable means of meeting the specific run-time in an inter-station run. The current practice is to start coasting at a fixed distance from the departed station. Hence, it is only optimal with respect to a nominal operational condition of the train schedule, but not the current service demand. The advantage of coasting can only be fully secured when coasting points are determined in real-time. However, identifying the necessary starting point(s) for coasting under the constraints of current service conditions is no simple task as train movement is governed by a large number of factors. The feasibility and performance of classical and heuristic searching measures in locating coasting point(s) is studied with the aid of a single train simulator, according to specified inter-station run times.

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Statistical and Econometric Methods for Transportation Data Analysis, 2nd edition

Now in its second edition, this book describes tools that are commonly used in transportation data analysis. The first part of the text provides statistical fundamentals while the second part presents continuous dependent variable models. With a focus on count and discrete dependent variable models, the third part features new chapters on mixed logit models, logistic regression, and ordered probability models. The last section provides additional coverage of Bayesian statistical modeling, including Bayesian inference and Markov chain Monte Carlo methods. Data sets are available online to use with the modeling techniques discussed.

Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

Railway junction traffic control by heuristic methods

Traffic conflicts at railway junctions are very conmon, particularly on congested rail lines. While safe passage through the junction is well maintained by the signalling and interlocking systems, minimising the delays imposed on the trains by assigning the right-of-way sequence sensibly is a bonus to the quality of service. A deterministic method has been adopted to resolve the conflict, with the objective of minimising the total weighted delay. However, the computational demand remains significant. The applications of different heuristic methods to tackle this problem are reviewed and explored, elaborating their feasibility in various aspects and comparing their relative merits for further studies. As most heuristic methods do not guarantee a global optimum, this study focuses on the trade-off between computation time and optimality of the resolution.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

‘You can interview me, but I don’t have a story’: Local Accounts of Wandering Women, Rewondering Queensland Landscapes.

This paper investigates how contemporary works of women’s travel writing are reworking canonical formations of environmental literature by presenting imaginative accounts of travel writing that are both literal and metaphorical. In this context, the paper considers how women who travel/write may intersect the spatial hybridities of travel writing and nature writing, and in doing so, create a new genre of environmental literature that is not only ecologically sensitive but gendered. As the role of female travel writers in generating this knowledge is immense but largely unexamined, this paper will investigate how a feminist geography can be applied, both critically and creatively, to local accounts of travel. It will draw on my own travels around Queensland in an attempt to explore how many female storytellers situate themselves, in and against, various discourses of mobility and morality.