Kai Tai Chan

Analyses the work of choreographer and director Kai Tai Chan whose different pathway through dance and theatre opens up discourses about the nature of non-ballet concert dance in Australia. Orthodox paradigms of training and performance making are interrogated and a greater understanding of the relative nature of those practices is established by analysing the competing ideologies, philosophical frameworks and aesthetic understandings of these practitioners.

Improving the precision of the accumulated oxygen deficit using VO2-power regression points from below and above the lactate threshold

The accumulated oxygen deficit (AOD) method assumes a linear VO₂-power relationship for exercise intensities increasing from below the lactate threshold (BLT) to above the lactate threshold (ALT). Factors that were likely to effect the linearity of the VO₂-power regression and the precision of the estimated total energy demand (ETED) were investigated. These included the slow component of VO₂ kinetics (SC), a forced resting y-intercept and exercise intensities BLT and ALT. Criteria for linearity and precision included the Pearson correlation coefficient (PCC) of the VO₂-power relationship, the length of the 95% confidence interval (95% CI) of the ETED and the standard error of the predicted value (SEP), respectively. Eight trained male and one trained female triathlete completed the required cycling tests to establish the AOD when pedalling at 80 rev/min. The influence of the SC on the linear extrapolation of the ETED was reduced by measuring VO₂ after three min of exercise. Measuring VO₂ at this time provided a new linear extrapolation method consisting of ten regression points spread evenly from BLT and ALT. This method produced an ETED with increased precision compared to using regression equations developed from intensities BLT with no forced y-intercept value; (95%CI (L), 0.70±0.26 versus 1.85±1.10, P<0.01; SEP(L/Watt), 0.07±0.02 versus 0.28±0.17; P<0.01). Including a forced y-intercept value with five regression points either BLT or ALT increased the precision of estimating the total energy demand to the same level as when using 10 regression points, (5 points BLT + y-intercept versus 5 points ALT + y-intercept versus 10 points; 95%CI(l), 0.61±0.32, 0.87±0.40, 0.70±0.26; SEP(L/Watt), 0.07±0.03, 0.08±0.04, 0.07±0.02; p>0.05). The VO₂-power regression can be designed using a reduced number of regression points... ABSTRACT FROM AUTHOR

Cycling at 120 when compared to 80 rev/min increases the accumulated oxygen deficit but does not affect the precision of its calculation

The aim of the present study was to determine the influence of pedal rate on the precision and quantification of the accumulated oxygen deficit (AOD). Eight trained male triathletes completed a lactate threshold test, VO2 peak test, 10 x 3 min submaximal exercise bouts and a high-intensity exercise bout, all performed at 80 and 120 rev/min. For both pedal rates the intensities for the sub-maximal and high-intensity tests were relative to the lactate threshold and VO2 peak work rates. The VO2-power regressions were calculated using 5 intensities from above the lactate threshold combined with a y intercept value with VO2 measured after 3 min of exercise. For the 120 compared to the 80 rev/min tests, the lactate threshold work rate (255±13 versus 276±47 Watts) (p<0.01) and VO2 peak work rate (352±17 versus 382±20, Watts) (p<0.05) were lower at 120 rev/m. Conversely, the VO2 peak and the VO2 measured during the exhaustive exercise were the same for both pedal rates (p>0.05). Using linear regression modelling the slope of the VO2-power regression (0.0112 versus 0.010 L/Watt) (p<0.01), the estimated total energy demand (ETED) (5.13±0.75 versus 4.89±0.88 L/min) and the AOD (4.27±0.94 versus 3.66±1.25 L) (p<0.05) were greater at 120 rev/m. However, the 95% confidence interval for the ETED and the standard error of the predicted value were the same for both pedal rates (p>0.05). Our results demonstrate that pedal rate effects the size but not the precision of the calculated AOD and should therefore be considered when developing an AOD protocol.

Decreased fatty acit Â-oxidation in riboflavin-responsive, multiple acylocoenzyme a dehydrogenase-deficient patients is associated with an increase in uncoupling protein-3

Riboflavin-responsive, multiple acylcoenzyme A dehydrogenase deficiency (RR-MAD), a lipid storage myopathy, is characterized by, among others, a decrease in fatty acid (FA) ß-oxidation capacity. Muscle uncoupling protein 3 (UCP3) is up-regulated under conditions that either increase the levels of circulating free FA and/or decrease FA ß-oxidation. Using a relatively large cohort of seven RR-MAD patients, we aimed to better characterize the metabolic disturbances of this disease and to explore the possibility that it might increase UCP3 expression. A battery of biochemical and molecular tests were performed, which demonstrated decreases in FA ß-oxidation and in the activities of respiratory chain complexes I and II. These metabolic alterations were associated with increases of 3.1- and 1.7-fold in UCP3 mRNA and protein expression, respectively. All parameters were restored to control values after riboflavin treatment. We postulate that the up-regulation of UCP3 in RR-MAD is due to the accumulation of muscle FA/acylCoA. RR-MAD is an optimal model to support the hypothesis that UCP3 is involved in the outward translocation of an excess of FA from the mitochondria and to show that, in humans, the effects of FA on UCP3 expression are direct and independent of fatty acid ß-oxidation.

Regulation of metabolic transcriptional co-activators and transcription factors with acute exercise

Endurance exercise improves insulin sensitivity and increases fat oxidation, which are partly facilitated by the induction of metabolic transcription factors. Next to exercise, increased levels of FFA's also increase the gene expression of transcription factors, hence making it difficult to discern the effects from contractile signals produced during exercise, from those produced by increased circulatory FFA's. We aimed to investigate, in human skeletal muscle, whether acute exercise affects gene expression of metabolic transcriptional co-activators and transcription factors, including PGC-1α, PRC, PPARα, β/δ, and γ and RXR, SREBP-1c and FKHR, and to discern the effect of exercise per se from those of elevated levels of FFA. Two hours of endurance exercise was performed either in the fasted state, or following carbohydrate ingestion prior to and during exercise, thereby blunting the fasting-induced increase in FA availability and oxidation. Of the genes measured, PGC-1α and PRC mRNA increased immediately after, while PPARβ/δ and FKHR mRNA increased 1–4 h after exercise, irrespective of the increases in FFA's. Our results suggest that the induction in vivo of metabolic transcription factors implicated in mitochondrial biogenesis are under the control of inherent signals, (PGC-1α, PRC), while those implicated in substrate selection are under the control of associated signals (PPARβ/δ, FKHR) stimulated from the contracting skeletal muscle that are independent of circulating FFA levels.

Additive effect of interferential therapyover pelvic floor exercise alone in the treatment of female urinary stress and urge incontinence: A randomized controlled trial

This pilot study attempted to examine the additional efficacy of interferential therapy in reducing the symptoms of urinary stress and urge incontinence. Twenty-four subjects were randomly allocated to the experimental group, which received interferential therapy plus pelvic floor exercises, or the control group, which received pelvic floor exercises only. Treatment was given three times a week for 4 weeks. Subjects were given urinary diaries to record urinary symptoms (including frequency of passing urine and number of times woken by desire to pass urine) for 5 days prior to and after treatment. Perineometer readings, pad weighing test and start/stop test were also performed in a physiotherapy clinic before and at completion of treatment regimes. Significant improvements were observed in all the outcome variables in the experimental group, but in only the perineometer readings in controls. When the changes from pre- to post-treatment were compared between the two groups, four of the dependent variables did not reach statistical significance. Power analysis indicated that the sample size for each group needed to be 70 for all results to be statistically significant. This study shows that interferential therapy plus pelvic floor exercise appears to be a more effective treatment modality than pelvic floor muscle strengthening exercise alone for incontinence, but a larger trial with longer followup is needed before definitive conclusions can be reached.

Software warehouse and software mining : the impact of data mining to software engineering

Automating Software Engineering is the dream of software Engineers for decades. To make this dream to come to true, data mining can play an important role. Our recent research has shown that to increase the productivity and to reduce the cost of software development, it is essential to have an effective and efficient mechanism to store, manage and utilize existing software resources, and thus to automate software analysis, testing, evaluation and to make use of existing software for new problems. This paper firstly provides a brief overview of traditional data mining followed by a presentation on data mining in broader sense. Secondly, it presents the idea and the technology of software warehouse as an innovative approach in managing software resources using the idea of data warehouse where software assets are systematically accumulated, deposited, retrieved, packaged, managed and utilized driven by data mining and OLAP technologies. Thirdly, we presented the concepts and technology and their applications of data mining and data matrix including software warehouse to software engineering. The perspectives of the role of software warehouse and software mining in modern software development are addressed. We expect that the results will lead to a streamlined high efficient software development process and enhance the productivity in response to modern challenges of the design and development of software applications.

An examination on the performance of MML causal induction

This paper presents an examination report on the performance of the improved MML based causal model discovery algorithm. In this paper, We firstly describe our improvement to the causal discovery algorithm which introduces a new encoding scheme for measuring the cost of describing the causal structure. Stiring function is also applied to further simplify the computational complexity and thus works more efficiently. It is followed by a detailed examination report on the performance of our improved discovery algorithm. The experimental results of the current version of the discovery system show that: (l) the current version is capable of discovering what discovered by previous system; (2) current system is capable of discovering more complicated causal networks with large number of variables; (3) the new version works more efficiently compared with the previous version in terms of time complexity.

Discovering linear causal model from incomplete data

One common drawback in algorithms for learning Linear Causal Models is that they can not deal with incomplete data set. This is unfortunate since many real problems involve missing data or even hidden variable. In this paper, based on multiple imputation, we propose a three-step process to learn linear causal models from incomplete data set. Experimental results indicate that this algorithm is better than the single imputation method (EM algorithm) and the simple list deletion method, and for lower missing rate, this algorithm can even find models better than the results from the greedy learning algorithm MLGS working in a complete data set. In addition, the method is amenable to parallel or distributed processing, which is an important characteristic for data mining in large data sets.

Ensemble parameter estimation for graphical models

Parameter Estimation is one of the key issues involved in the discovery of graphical models from data. Current state of the art methods have demonstrated their abilities in different kind of graphical models. In this paper, we introduce ensemble learning into the process of parameter estimation, and examine ensemble parameter estimation methods for different kind of graphical models under complete data set and incomplete data set. We provide experimental results which show that ensemble method can achieve an improved result over the base parameter estimation method in terms of accuracy. In addition, the method is amenable to parallel or distributed processing, which is an important characteristic for data mining in large data sets.

Modelling of porosity defects in high pressure die casting with a neural network

High Pressure Die Casting (HPDC) is a complex process that results in casting defects if configured improperly. However, finding out the optimal configuration is a non-trivial task as eliminating one of the casting defects (for example, porosity) can result in occurrence of other casting defects. The industry generally tries to eliminate the defects by trial and error which is an expensive and error -prone process. This paper aims to improve current modelling and understanding of defects formation in HPDC machines. We have conducted conventional die casting tests with a neural network model of HPDC machine and compared the obtained results with the current understanding of formation of porosity. While most of our findings correspond well to established knowledge in the field, some of our findings are in conflict with the previous studies of die casting.

Disparity estimation using TI multi-wavelet transform

A multi-resolution image matching technique based on translation invariant discrete multi-wavelet transform followed by a coarse to fine matching strategy is presented. The technique addresses the estimation of optimal corresponding points and the corresponding disparity maps in the presence of occlusion, ambiguity and illuminative variations in the two perspective views taken by two different cameras or at different lighting conditions. The problem of occlusion and ambiguity is addressed explicitly by a geometric optimization approach along with the uniqueness constraint whereas the illuminative variation is dealt with by using windowed normalized correlation on the discrete multi-wavelet coefficients.

Self-perceived quality of life of children and adolescents with physical disabilities in Hong Kong

Although illnesses and diseases are thought to adversely affect quality of life (QoL), whether children who have physical disabilities (PD) from a young age adapt to the effect of developmental disabilities has rarely been investigated. This study attempted to assess the subjective wellbeing, and examine the correlation between objective and subjective QoL, of children with PD. Using a self-reported non-disease-specific questionnaire, the QoL of 72 young persons (13.5 ± 2.0 years) with PD was contrasted with those who do not have disabilities (n = 510; age-matched). MANOVA analyses revealed that the PD group had lower objective QoL score (63.0 ± 7.4 vs. 66.8 ± 5.7, p < 0.001) but the two groups were not significantly different in subjective QoL score (70.9 ± 11.4 vs. 69.6 ± 13.6, p = 0.466). No correlation was found between objective and subjective QoL in the PD group (r ranged from 0.06 to 0.19), while weak to medium correlations (r ranged from 0.03 to 0.41) were observed for the controls. The apparent detachment of subjective feeling and objective circumstances in the PD group may reflect adjustment to developmental disabilities.