Increased cardio-metabolic risk is associated with increased TV viewing time

Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

Quantitative electroencephalographic comodulation : an investigation of patterns in chronic fatigue syndrome

Introduction. This is a pilot study of quantitative electro-encephalographic (QEEG) comodulation analysis, which is used to assist in identifying regional brain differences in those people suffering from chronic fatigue syndrome (CFS) compared to a normative database. The QEEG comodulation analysis examines spatial-temporal cross-correlation of spectral estimates in the resting dominant frequency band. A pattern shown by Sterman and Kaiser (2001) and referred to as the anterior posterior dissociation (APD) discloses a significant reduction in shared functional modulation between frontal and centro-parietal areas of the cortex. This research attempts to examine whether this pattern is evident in CFS. Method. Eleven adult participants, diagnosed by a physician as having CFS, were involved in QEEG data collection. Nineteen-channel cap recordings were made in five conditions: eyes-closed baseline, eyes-open, reading task one, math computations task two, and a second eyes-closed baseline. Results. Four of the 11 participants showed an anterior posterior dissociation pattern for the eyes-closed resting dominant frequency. However, seven of the 11 participants did not show this pattern. Examination of the mean 8-12 Hz amplitudes across three cortical regions (frontal, central and parietal) indicated a trend of higher overall alpha levels in the parietal region in CFS patients who showed the APD pattern compared to those who did not have this pattern. All patients showing the pattern were free of medication, while 71% of those absent of the pattern were using antidepressant medications. Conclusions. Although the sample is small, it is suggested that this method of evaluating the disorder holds promise. The fact that this pattern was not consistently represented in the CFS sample could be explained by the possibility of subtypes of CFS, or perhaps co-morbid conditions. Further, the use of antidepressant medications may mask the pattern by altering the temporal characteristics of the EEG. The results of this pilot study indicate that further research is warranted to verify that the pattern holds across the wider population of CFS sufferers.

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.

Understanding the literacy difficulties of students with Asperger's syndrome in middle years' classrooms

Among the students in Australian classrooms who are experiencing learning difficulties are increasing numbers of children who have been diagnosed with Asperger's syndrome. Although the general cognitive and language abilities of these students are comparable with most of their peers, they experience significant difficulties with social communication, social interactions and social-emotional/behavioural functioning. Despite indications that there are features inherent in Asperger's syndrome that are likely to have a negative effect on the development of advanced literacy skills, studies to date have primarily focused on social-emotional/behavioural challenges. Without effective literacy skills, however, students' access to educational and career opportunities may be curtailed. This article reviews features of Asperger's syndrome that appear to have a negative impact upon the development of advanced literacy skills and suggests ways in which inclusive classroom teachers could support the development of their learners.

A longitudinal study of motivation and competence in children with Down syndrome : early childhood to early adolescence

Background Motivation has been identified as an area of difficulty for children with Down syndrome. Although individual differences in mastery motivation are presumed to have implications for subsequent competence, few longitudinal studies have addressed the stability of motivation and the predictive validity of early measures for later academic achievement, especially in atypical populations. Method The participants were 25 children with Down syndrome. Mastery motivation, operationalised as persistence, was measured in early childhood and adolescence using tasks and parent report. At the older age, preference for challenge, another aspect of mastery motivation, was also measured and the children completed assessments of academic competence. Results There were significant concurrent correlations among measures of persistence at both ages, and early task persistence was associated with later persistence. Persistence in early childhood was related to academic competence in adolescence, even when the effects of cognitive ability at the younger age were controlled. Conclusions For children with Down syndrome, persistence appears to be an individual characteristic that is relatively stable from early childhood to early adolescence. The finding that early mastery motivation is significant for later achievement has important implications for the focus of early interventions.

Maternal support for autonomy : relationships with persistence for children with Down syndrome and typically developing children

Maternal behaviors and child mastery behaviors were examined in 25 children with Down syndrome and 43 typically developing children matched for mental age (24–36 months). During a shared problem-solving task, there were no group differences in maternal directiveness or support for autonomy, and mothers in the two groups used similar verbal strategies when helping their child. There were also no group differences in child mastery behaviors, measured as persistence with two optimally challenging tasks. However, the two groups differed in the relationships of maternal style with child persistence. Children with Down syndrome whose mothers were more supportive of their autonomy in the shared task displayed greater persistence when working independently on a challenging puzzle, while children of highly directive mothers displayed lower levels of persistence. For typically developing children, persistence was unrelated to maternal style, suggesting that mother behaviors may have different causes or consequences in the two groups.

Selecting, optimizing and fusing ‘salient’ Gabor features for facial expression recognition

This paper describes a novel framework for facial expression recognition from still images by selecting, optimizing and fusing ‘salient’ Gabor feature layers to recognize six universal facial expressions using the K nearest neighbor classifier. The recognition comparisons with all layer approach using JAFFE and Cohn-Kanade (CK) databases confirm that using ‘salient’ Gabor feature layers with optimized sizes can achieve better recognition performance and dramatically reduce computational time. Moreover, comparisons with the state of the art performances demonstrate the effectiveness of our approach.

Metabolic syndrome and serum carotenoids : findings of a cross-sectional study in Queensland, Australia

Several components of the metabolic syndrome, particularly diabetes and cardiovascular disease, are known to be oxidative stress-related conditions and there is research to suggest that antioxidant nutrients may play a protective role in these conditions. Carotenoids are compounds derived primarily from plants and several have been shown to be potent antioxidant nutrients. The aim of this study was to examine the associations between metabolic syndrome status and major serum carotenoids in adult Australians. Data on the presence of the metabolic syndrome, based on International Diabetes Federation 2005 criteria, were collected from 1523 adults aged 25 years and over in six randomly selected urban centers in Queensland, Australia, using a cross-sectional study design. Weight, height, BMI, waist circumference, blood pressure, fasting and 2-hour blood glucose and lipids were determined, as well as five serum carotenoids. Mean serum alpha-carotene, beta-carotene and the sum of the five carotenoid concentrations were significantly lower (p<0.05) in persons with the metabolic syndrome (after adjusting for age, sex, education, BMI status, alcohol intake, smoking, physical activity status and vitamin/mineral use) than persons without the syndrome. Alpha, beta and total carotenoids also decreased significantly (p<0.05) with increased number of components of the metabolic syndrome, after adjusting for these confounders. These differences were significant among former smokers and non-smokers, but not in current smokers. Low concentrations of serum alpha-carotene, beta-carotene and the sum of five carotenoids appear to be associated with metabolic syndrome status. Additional research, particularly longitudinal studies, may help to determine if these associations are causally related to the metabolic syndrome, or are a result of the pathologies of the syndrome.

Long-term exposure to gaseous air pollutants and cardio-respiratory mortality in Brisbane, Australia

Air pollution is ranked by the World Health Organisation as one of the top ten contributors to the global burden of disease and injury. Exposure to gaseous air pollutants, even at a low level, has been associated with cardiorespiratory diseases (Vedal, Brauer et al. 2003). Most recent epidemiological studies of air pollution have used time-series analyses to explore the relationship between daily mortality or morbidity and daily ambient air pollution concentrations based on the same day or previous days (Hajat, Armstrong et al. 2007). However, most of the previous studies have examined the association between air pollution and health outcomes using air pollution data from a single monitoring site or average values from a few monitoring sites to represent the whole population of the study area. In fact, for a metropolitan city, ambient air pollution levels may differ significantly among the different areas. There is increasing concern that the relationships between air pollution and mortality may vary with geographical area (Chen, Mengersen et al. 2007). Additionally, some studies have indicated that socio-economic status can act as a confounder when investigating the relation between geographical location and health (Scoggins, Kjellstrom et al. 2004). This study examined the spatial variation in the relationship between long-term exposure to gaseous air pollutants (including nitrogen dioxide (NO2), ozone (O3) and sulphur dioxide (SO2)), and cardiorespiratory mortality in Brisbane, Australia, during the period 1996 - 2004.

Facial feature detection for in-car environment

Acoustically, vehicles are extremely noisy environments and as a consequence audio-only in-car voice recognition systems perform very poorly. Seeing that the visual modality is immune to acoustic noise, using the visual lip information from the driver is seen as a viable strategy in circumventing this problem. However, implementing such an approach requires a system being able to accurately locate and track the driver’s face and facial features in real-time. In this paper we present such an approach using the Viola-Jones algorithm. Using this system, we present our results which show that using the Viola-Jones approach is a suitable method of locating and tracking the driver’s lips despite the visual variability of illumination and head pose.

Comprehensive standardized data definitions for acute coronary syndrome research in emergency departments in Australasia

Patients with chest discomfort or other symptoms suggestive of acute coronary syndrome (ACS) are one of the most common categories seen in many Emergency Departments (EDs). While the recognition of patients at high-risk of ACS has improved steadily, identifying the majority of chest pain presentations who fall into the low-risk group remains a challenge. Research in this area needs to be transparent, robust, applicable to all hospitals from large tertiary centres to rural and remote sites, and to allow direct comparison between different studies with minimum patient spectrum bias. A standardised approach to the research framework using a common language for data definitions must be adopted to achieve this. The aim was to create a common framework for a standardised data definitions set that would allow maximum value when extrapolating research findings both within Australasian ED practice, and across similar populations worldwide. Therefore a comprehensive data definitions set for the investigation of non-traumatic chest pain patients with possible ACS was developed, specifically for use in the ED setting. This standardised data definitions set will facilitate ‘knowledge translation’ by allowing extrapolation of useful findings into the real-life practice of emergency medicine.

Exploring visual features through Gabor representations for facial expression detection

Gabor representations have been widely used in facial analysis (face recognition, face detection and facial expression detection) due to their biological relevance and computational properties. Two popular Gabor representations used in literature are: 1) Log-Gabor and 2) Gabor energy filters. Even though these representations are somewhat similar, they also have distinct differences as the Log-Gabor filters mimic the simple cells in the visual cortex while the Gabor energy filters emulate the complex cells, which causes subtle differences in the responses. In this paper, we analyze the difference between these two Gabor representations and quantify these differences on the task of facial action unit (AU) detection. In our experiments conducted on the Cohn-Kanade dataset, we report an average area underneath the ROC curve (A`) of 92.60% across 17 AUs for the Gabor energy filters, while the Log-Gabor representation achieved an average A` of 96.11%. This result suggests that small spatial differences that the Log-Gabor filters pick up on are more useful for AU detection than the differences in contours and edges that the Gabor energy filters extract.