Falling Weight Deflectometer (FWD) tests on granular pavement reinforced with geogrids– Case study

The use of geogrids in granular pavement layers could increase the modulus and the stiffness of granular layer and hence the required layer thickness can be reduced. Though, geogrids are being used in granular pavements to provide lateral restraint, bearing capacity, and membrane tension support, very limited studies have been carried out to investigate the effects of geogrids on modulus and stiffness of granular layer. In this study, two sections of a granular pavement were constructed: one with a geogrid at the bottom of the base layer and the other without a geogrid. Two sections were then tested using Falling Weight Deflectometer (FWD) and FWD results were analysed to determine the effect of geogrid on the overall modulus and stiffness of the granular pavement. The results suggested that the pavement section with geogrid has higher overall modulus and deflection ratio compared to the pavement section without geogrid.

Osteopenia and rickets in the extremely low birth weight infant: A survey of the incidence and a radiological classification

A review was carried out of the radiographs of twenty-five infants with birth weights under 1000 G, who survived for more than twenty-eight days; eighteen of these had enough suitable films for a survey of the progressive bone changes which occur in these infants, including estimation of humeral cortical cross-sectional area. The incidence of the changes has been assessed and a typical progression of radiographic appearances has been shown, with a suggested system of staging. All infants showed some loss of bone mineral, with frank changes of rickets occurring in forty-four percent. Aetiological factors are mainly concerned with the difficulty of supplying and ensuring absorption of sufficient bone mineral (calcium and phosphate) and vitamin D. Liver immaturity may be another factor. Disease states additional to prematurity accentuate the problem. Rib fractures occurring around 80–90 days post-nataEy commonly draw attention to the bone disorder and are probably the major clinical factor of importance; there is a high incidence of associated lung disease of uncertain pathology. Attention is drawn to possible confusion with other bone disorders in the post-natal period.

CBCT-guided radiotherapy for locally advanced head and cancer: dosimetric impact of weight loss on VMAT and IMRT plans for selected organs at risk structures (OARs)

Purpose: It is common for head and neck patients to be affected by time trend errors as a result of weight loss during a course of radiation treatment. The objective of this planning study was to investigate the impact of weight loss on Volumetric Modulated Arc Therapy (VMAT) as well as Intensity modulated radiation therapy (IMRT) for locally advanced head and neck cancer using automatic co-registration of the CBCT. Methods and Materials: A retrospective analysis of previously treated IMRT plans for 10 patients with locally advanced head and neck cancer patients was done. A VMAT plan was also produced for all patients. We calculated the dose–volume histograms (DVH) indices for spinal cord planning at risk volumes (PRVs), the brainstem PRVs (SC+0.5cm and BS+0.5cm, respectively) as well as mean dose to the parotid glands. Results: The results show that the mean difference in dose to the SC+0.5cm was 1.03% and 1.27% for the IMRT and VMAT plans, respectively. As for dose to the BS+0.5, the percentage difference was 0.63% for the IMRT plans and 0.61% for the VMAT plans. The analysis of the parotid gland doses shows that the percentage change in mean dose to left parotid was -8.0% whereas that of the right parotid was -6.4% for the IMRT treatment plans. In the VMAT plans, the percentages change for the left and the right parotid glands were -6.6% and -6.7% respectively. Conclusions: This study shows a clinically significant impact of weight loss on DVH indices analysed in head and neck organs at risk. It highlights the importance of adaptive radiotherapy in head and neck patients if organ at risk sparing is to be maintained.

Prospective decrease in progesterone concentrations in female lightweight rowers during the competition season compared with the off-season: A controlled study examining weight loss and intensive exercise

The purpose of this study was to monitor ovarian hormone function response to intense exercise and body weight changes in female athletes. Ovarian hormone function was evaluated in 12 female lightweight rowers and 10 age-height-weight matched sedentary controls. Ovarian hormone function was assessed during consecutive competition season and off season, by measurement of peak and average alternative day overnight urinary oestrone glucuronide (E1G) and pregnanediol glucuronide (PdG) excretion. Competition season was associated with a 5.8 kg (9.3%) body weight loss in the lightweight rowers. Significantly lower competition season peak and average urinary excretion of PdG were found in the lightweight rowers compared with the controls. Lower competition season peak and average urinary excretion of E1G were also found in the lightweight rowers compared with the controls, but the difference did not reach significance. The number of rowing training hours was a significant determinant of peak PdG excretion in the rowers (R2 = 0.40; p<0.02). The seasonal suppression of PdG excretion was associated with degree of weight loss (R2 = 0.46; p<0.01). The competition related decrease in E1G and PdG excretion for the lightweight rowers was predominantly restored during the off season when exercise intensity and duration were decreased and body weight increased. These results showed a significant (p<0.05) reduction in progesterone metabolite excretion and a non-significant decrease in oestrone metabolite excretion associated with intensive competition season training loads and body weight reduction in female lightweight rowers.

Weight bearing physical activity for performance and bone health in prepubertal girls

This study assessed the status of bone and cardiovascular health in young, prepubertal females (aged 9 to 11 years) during a school based intervention program involving weight bearing physical activity. A study of 10 months duration was conducted in four primary schools in the Melbourne suburbs. It involved a physical activity group (n=38) and an aged-matched control group (n=33). Baseline data including pubertal status, health-related fitness, bone mass and body composition were obtained pre and post the intervention programme. All children had their bone mineral density monitored. Bone mineral density and body composition measurements were performed by DXA using the Hologic QDR 2000 bone densitometer. At the completion of the program the activity group had accrued significantly greater bone mass at total body, lumbar spine, leg and femoral neck when expressed as BMC or BMD.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Low birth weight in MZ twins discordant for birth weight is associated with shorter telomere length and lower IQ, but not anxiety/depression in later life

Shorter telomere length (TL) has found to be associated with lower birth weight and with lower cognitive ability and psychiatric disorders. However, the direction of causation of these associations and the extent to which they are genetically or environmentally mediated are unclear. Within-pair comparisons of monozygotic (MZ) and dizygotic (DZ) twins can throw light on these questions. We investigated correlations of within pair differences in telomere length, IQ, and anxiety/depression in an initial sample from Brisbane (242 MZ pairs, 245 DZ same sex (DZSS) pairs) and in replication samples from Amsterdam (514 MZ pairs, 233 DZSS pairs) and Melbourne (19 pairs selected for extreme high or low birth weight difference). Intra-pair differences of birth weight and telomere length were significantly correlated in MZ twins, but not in DZSS twins. Greater intra-pair differences of telomere length were observed in the 10% of MZ twins with the greatest difference in birth weight compared to the bottom 90% in both samples and also in the Melbourne sample. Intra-pair differences of telomere length and IQ, but not of TL and anxiety/depression, were correlated in MZ twins, and to a smaller extent in DZSS twins. Our findings suggest that the same prenatal effects that reduce birth weight also influence telomere length in MZ twins. The association between telomere length and IQ is partly driven by the same prenatal effects that decrease birth weight.

An efficient and light-weight multi-tasking model to achieve Intra-Agent concurrency for SAGE

Multi-agent systems implicate a high degree of concurrency at both the Inter- and Intra-Agent levels. Scalable, fault tolerant, Agent Grooming Environment (SAGE), the second generation, FIPA compliant MAS requires a built in mechanism to achieve both the Inter- and Intra-Agent concurrency. This paper dilates upon an attempt to provide a reliable, efficient and light-weight solution to provide intra-agent concurrency with-in the internal agent architecture of SAGE. It addresses the issues related to using the JAVA threading model to provide this level of concurrency to the agent and provides an alternative approach that is based on an eventdriven, concurrent and user-scalable multi-tasking model for the agent's internal model. The findings of this paper show that our proposed approach is suitable for providing an efficient and lightweight concurrent task model for SA GE and considerably outweighs the performance of multithreaded tasking model based on JAVA in terms of throughput and efficiency. This has been illustrated using the practical implementation and evaluation of both models. © 2004 IEEE.

Maternal perception of weight status in first-born Australian toddlers aged 12–16 months – the NOURISH and SAIDI cohorts

Background The preference amongst parents for heavier infants is in contrast to obesity prevention efforts worldwide. Parents are poor at identifying overweight in older children, but few studies have investigated maternal perception of weight status amongst toddlers and none in the Australian setting. Methods Mothers (n = 290) completed a self-administered questionnaire at child age 12–16 months, defining their child's weight status as underweight, normal weight, somewhat overweight or very overweight. Weight-for-length z-score was derived from measured weight and length, and children categorized as underweight, normal weight, at risk overweight or obese (WHO standards). Objective classification was compared with maternal perception of weight status. Mean weight-for-length z-score was compared across categories of maternal perception using one-way ANOVA. Multinomial logistic regression was used to determine child or maternal characteristics associated with inaccurate weight perception. Results Most children (83%) were perceived as normal weight. Twenty nine were described as underweight, although none were. Sixty-six children were at risk of overweight, but 57 of these perceived as normal weight. Of the 14 children who were overweight, only 4 were identified as somewhat overweight by their mother. Compared with mothers who could accurately classify their normal weight child, mothers who were older had higher odds of perceiving their normal weight child as underweight, while mothers with higher body mass index had slightly higher odds of describing their overweight/at risk child as normal weight. Conclusion The leaner but healthy weight toddler was perceived as underweight, while only the heaviest children were recognized as overweight. Mothers unable to accurately identify children at risk are unlikely to act to prevent further excess weight gain. Practitioners can lead a shift in attitudes towards weight in infants and young children, promoting routine growth monitoring and adequate but not rapid weight gain.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.