Surface mean flow and turbulence structure in tropical cyclone winds

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. ^ Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. ^ Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably. ^

Surface Mean Flow and Turbulence Structure in Tropical Cyclone Winds

Hurricanes are one of the deadliest and costliest natural hazards affecting the Gulf coast and Atlantic coast areas of the United States. An effective way to minimize hurricane damage is to strengthen structures and buildings. The investigation of surface level hurricane wind behavior and the resultant wind loads on structures is aimed at providing structural engineers with information on hurricane wind characteristics required for the design of safe structures. Information on mean wind profiles, gust factors, turbulence intensity, integral scale, and turbulence spectra and co-spectra is essential for developing realistic models of wind pressure and wind loads on structures. The research performed for this study was motivated by the fact that considerably fewer data and validated models are available for tropical than for extratropical storms. Using the surface wind measurements collected by the Florida Coastal Monitoring Program (FCMP) during hurricane passages over coastal areas, this study presents comparisons of surface roughness length estimates obtained by using several estimation methods, and estimates of the mean wind and turbulence structure of hurricane winds over coastal areas under neutral stratification conditions. In addition, a program has been developed and tested to systematically analyze Wall of Wind (WoW) data, that will make it possible to perform analyses of baseline characteristics of flow obtained in the WoW. This program can be used in future research to compare WoW data with FCMP data, as gust and turbulence generator systems and other flow management devices will be used to create WoW flows that match as closely as possible real hurricane wind conditions. Hurricanes are defined as tropical cyclones for which the maximum 1-minute sustained surface wind speeds exceed 74 mph. FCMP data include data for tropical cyclones with lower sustained speeds. However, for the winds analyzed in this study the speeds were sufficiently high to assure that neutral stratification prevailed. This assures that the characteristics of those winds are similar to those prevailing in hurricanes. For this reason in this study the terms tropical cyclones and hurricanes are used interchangeably.

Can mean shift trackers perform better?

Many tracking algorithms have difficulties dealing with occlusions and background clutters, and consequently don't converge to an appropriate solution. Tracking based on the mean shift algorithm has shown robust performance in many circumstances but still fails e.g. when encountering dramatic intensity or colour changes in a pre-defined neighbourhood. In this paper, we present a robust tracking algorithm that integrates the advantages of mean shift tracking with those of tracking local invariant features. These features are integrated into the mean shift formulation so that tracking is performed based both on mean shift and feature probability distributions, coupled with an expectation maximisation scheme. Experimental results show robust tracking performance on a series of complicated real image sequences. © 2010 IEEE.

Measurement of Training Intensity and Work During Submaximal Isokinetic Progressive Resistance Training Protocols

Physical exercise programmes are routinely prescribed in clinical practice to treat impairments, improve activity and participation in daily life because of their known physiological, health and psychological benefits (RCP, 2009). Progressive resistance exercise is a type of exercise prescribed specifically to improve skeletal muscle strength (Latham et al., 2004). The effectiveness of progressive resistance exercise varies considerably between studies and populations. This thesis focuses on how training parameters influence the delivery of progressive resistance exercise. In order to appropriately evaluate the influence of training parameters, this thesis argues the need to record training performance and the total work completed by participants as prescribed by training protocols. In the first study, participants were taken through a series of protocols differentiated by the intensity and volume of training. Training intensity was defined as a proportion of the mean peak torque achieved during maximal voluntary contractions and was set at 80% and 40% respectively of the MVC mean peak torque. Training volume was defined as the total external work achieved over the training period. Measures of training performance were developed to accurately report the intensity, repetitions and work completed during the training period. A second study evaluated training performance of the training protocols over repeated sessions. These protocols were then applied to 3 stroke survivors. Study 1 found sedentary participants could achieve a differentiated training intensity. Participants completing the high and low intensity protocols trained at 80% and 40% respectively of the MVC mean peak torque. The total work achieved in the high intensity low repetition protocol was lower than the total work achieved in the low intensity high repetition protocol. With repeated practice, study 2 found participants were able to improve in their ability to perform manoeuvres as shown by a reduction in the variation of the mean training intensity achieving total work as specified by the protocol to a lower margin of error. When these protocols were applied to 3 stroke survivors, they were able to achieve the specified training intensity but they were not able to achieve the total work as expected for the protocol. This is likely to be due to an inability in achieving a consistent force throughout the contraction. These results demonstrate evaluation of training characteristics and support the need to record and report training performance characteristics during progressive resistance exercise, including the total work achieved, in order to elucidate the influence of training parameters on progressive resistance exercise. The lack of accurate training performance may partly explain the inconsistencies between studies on optimal training parameters for progressive resistance exercise.

Exercise and secondary lymphedema : safety, potential benefits, and research issues

Participating in regular physical activity is encouraged following breast cancer (BC) treatment, except for those who have subsequently developed lymphoedema. We designed a randomised controlled trial to investigate the effect of participating in a supervised, mixed-type, moderate-intensity exercise program among women with lymphoedema following breast cancer. Women <76 years who had completed BC treatment at least six months prior and subsequently developed unilateral, upper-limb lymphoedema were randomly allocated to an intervention (n=16) or control (n=16) group. The intervention group (IG) participated in 20 supervised group exercise sessions over 12 weeks, while the control group (CG) was instructed to continue habitual activities. Lymphoedema status was assessed by bioimpedance spectroscopy (impedance ratio between limbs) and perometry (volume difference between limbs). Mean baseline measures were similar for the IG (1.13+0.15 and 337+307ml, respectively) and CG (1.13+0.15 and 377+416ml, respectively) and no changes were observed over time. However, 2 women in the IG no longer had evidence of lymphoedema by study end. Average attendance was over 70% of supervised sessions, and there were no withdrawals. The results indicate that, at worst, exercise does not exacerbate secondary lymphoedema. Women with secondary lymphoedema should be encouraged to be physically active, optimising their physical and psychosocial recovery.

A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean

Phase-type distributions represent the time to absorption for a finite state Markov chain in continuous time, generalising the exponential distribution and providing a flexible and useful modelling tool. We present a new reversible jump Markov chain Monte Carlo scheme for performing a fully Bayesian analysis of the popular Coxian subclass of phase-type models; the convenient Coxian representation involves fewer parameters than a more general phase-type model. The key novelty of our approach is that we model covariate dependence in the mean whilst using the Coxian phase-type model as a very general residual distribution. Such incorporation of covariates into the model has not previously been attempted in the Bayesian literature. A further novelty is that we also propose a reversible jump scheme for investigating structural changes to the model brought about by the introduction of Erlang phases. Our approach addresses more questions of inference than previous Bayesian treatments of this model and is automatic in nature. We analyse an example dataset comprising lengths of hospital stays of a sample of patients collected from two Australian hospitals to produce a model for a patient's expected length of stay which incorporates the effects of several covariates. This leads to interesting conclusions about what contributes to length of hospital stay with implications for hospital planning. We compare our results with an alternative classical analysis of these data.

Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors

Light Detection and Ranging (LIDAR) has great potential to assist vegetation management in power line corridors by providing more accurate geometric information of the power line assets and vegetation along the corridors. However, the development of algorithms for the automatic processing of LIDAR point cloud data, in particular for feature extraction and classification of raw point cloud data, is in still in its infancy. In this paper, we take advantage of LIDAR intensity and try to classify ground and non-ground points by statistically analyzing the skewness and kurtosis of the intensity data. Moreover, the Hough transform is employed to detected power lines from the filtered object points. The experimental results show the effectiveness of our methods and indicate that better results were obtained by using LIDAR intensity data than elevation data.

Assessment of Health Impacts of Heatwaves in Brisbane, Australia : How to Best Define A Heatwave?

Background and Objective: As global warming continues, the frequency, intensity and duration of heatwaves are likely to increase. However, a heatwave is unlikely to be defined uniformly because acclimatisation plays a significant role in determining the heat-related impact. This study investigated how to best define a heatwave in Brisbane, Australia. Methods: Computerised datasets on daily weather, air pollution and health outcomes between 1996 and 2005 were obtained from pertinent government agencies. Paired t-tests and case-crossover analyses were performed to assess the relationship between heatwaves and health outcomes using different heatwave definitions. Results: The maximum temperature was as high as 41.5°C with a mean maximum daily temperature of 26.3°C. None of the five commonly-used heatwave definitions suited Brisbane well on the basis of the health effects of heatwaves. Additionally, there were pros and cons when locally-defined definitions were attempted using either a relative or absolute definition for extreme temperatures. Conclusion: The issue of how to best define a heatwave is complex. It is important to identify an appropriate definition of heatwave locally and to understand its health effects.

Exercise alone is not enough : weight loss also needs a healthy (Mediterranean) diet?

Objective: In the majority of exercise intervention studies, the aggregate reported weight loss is often small. The efficacy of exercise as a weight loss tool remains in question. The aim of the present study was to investigate the variability in appetite and body weight when participants engaged in a supervised and monitored exercise programme. ---------- Design: Fifty-eight obese men and women (BMI = 31·8 ± 4·5 kg/m2) were prescribed exercise to expend approximately 2092 kJ (500 kcal) per session, five times a week at an intensity of 70 % maximum heart rate for 12 weeks under supervised conditions in the research unit. Body weight and composition, total daily energy intake and various health markers were measured at weeks 0, 4, 8 and 12. ---------- Results: Mean reduction in body weight (3·2 ± 1·98 kg) was significant (P < 0·001); however, there was large individual variability (−14·7 to +2·7 kg). This large variability could be largely attributed to the differences in energy intake over the 12-week intervention. Those participants who failed to lose meaningful weight increased their food intake and reduced intake of fruits and vegetables. ---------- Conclusion: These data have demonstrated that even when exercise energy expenditure is high, a healthy diet is still required for weight loss to occur in many people.

Measurement properties of the Australian Women's Activity Survey

Purpose: The Australian Women’s Activity Survey (AWAS) was developed based on a systematic review and qualitative research on how to measure activity patterns of women with young children (WYC). AWAS assesses activity performed across five domains (planned activities, employment, childcare, domestic responsibilities and transport), and intensity levels (sitting, light-intensity, brisk walking, moderate-intensity and vigorous-intensity) in a typical week in the past month. The purpose of this study was to assess the test-retest reliability and criterion validity of the AWAS. Methods: WYC completed the AWAS on two occasions 7-d apart (test-retest reliability protocol) and/or wore an MTI ActiGraph accelerometer for 7-d in between (validity protocol). Forty WYC (mean age 35 ± 5yrs) completed the test-retest reliability protocol and 75 WYC (mean age 33 ± 5yrs) completed the validity protocol. Interclass Correlation Coefficients (ICC) between AWAS administrations and Spearman’s Correlation Coefficients (rs) between AWAS and MTI data were calculated. Results: AWAS showed good test-retest reliability (ICC=0.80 (0.65-0.89)) and acceptable criterion validity (rs= 0.28, p=0.01) for measuring weekly health-enhancing physical activity. AWAS also provided repeatable and valid estimates of sitting time (test-retest reliability ICC=0.42 (0.13-0.64), and criterion validity (rs= 0.32, p=0.006)). Conclusion: The measurement properties of the AWAS are comparable to those reported for existing self-report measures of physical activity. However, AWAS offers a more comprehensive and flexible alternative for accurately assessing different domains and intensities of activity relevant to WYC. Future research should investigate whether the AWAS is a suitable measure of intervention efficacy by examining its sensitivity to change.