962 resultados para Montagnais Indians -- Missions.


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Background With the increasing prevalence of childhood obesity, the metabolic syndrome has been studied among children in many countries but not in Malaysia. Hence, this study aimed to compare metabolic risk factors between overweight/obese and normal weight children and to determine the influence of gender and ethnicity on the metabolic syndrome among school children aged 9-12 years in Kuala Lumpur and its metropolitan suburbs. Methods A case control study was conducted among 402 children, comprising 193 normal-weight and 209 overweight/obese. Weight, height, waist circumference (WC) and body composition were measured, and WHO (2007) growth reference was used to categorise children into the two weight groups. Blood pressure (BP) was taken, and blood was drawn after an overnight fast to determine fasting blood glucose (FBG) and full lipid profile, including triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). International Diabetes Federation (2007) criteria for children were used to identify metabolic syndrome. Results Participants comprised 60.9% (n = 245) Malay, 30.9% (n = 124) Chinese and 8.2% (n = 33) Indian. Overweight/obese children showed significantly poorer biochemical profile, higher body fat percentage and anthropometric characteristics compared to the normal-weight group. Among the metabolic risk factors, WC ≥90th percentile was found to have the highest odds (OR = 189.0; 95%CI 70.8, 504.8), followed by HDL-C≤1.03 mmol/L (OR = 5.0; 95%CI 2.4, 11.1) and high BP (OR = 4.2; 95%CI 1.3, 18.7). Metabolic syndrome was found in 5.3% of the overweight/obese children but none of the normal-weight children (p < 0.01). Overweight/obese children had higher odds (OR = 16.3; 95%CI 2.2, 461.1) of developing the metabolic syndrome compared to normal-weight children. Binary logistic regression showed no significant association between age, gender and family history of communicable diseases with the metabolic syndrome. However, for ethnicity, Indians were found to have higher odds (OR = 5.5; 95%CI 1.5, 20.5) compared to Malays, with Chinese children (OR = 0.3; 95%CI 0.0, 2.7) having the lowest odds. Conclusions We conclude that being overweight or obese poses a greater risk of developing the metabolic syndrome among children. Indian ethnicity is at higher risk compared to their counterparts of the same age. Hence, primary intervention strategies are required to prevent this problem from escalating.

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With the emergence of Unmanned Aircraft Systems (UAS) there is a growing need for safety standards and regulatory frameworks to manage the risks associated with their operations. The primary driver for airworthiness regulations (i.e., those governing the design, manufacture, maintenance and operation of UAS) are the risks presented to people in the regions overflown by the aircraft. Models characterising the nature of these risks are needed to inform the development of airworthiness regulations. The output from these models should include measures of the collective, individual and societal risk. A brief review of these measures is provided. Based on the review, it was determined that the model of the operation of an UAS over inhabited areas must be capable of describing the distribution of possible impact locations, given a failure at a particular point in the flight plan. Existing models either do not take the impact distribution into consideration, or propose complex and computationally expensive methods for its calculation. A computationally efficient approach for estimating the boundary (and in turn area) of the impact distribution for fixed wing unmanned aircraft is proposed. A series of geometric templates that approximate the impact distributions are derived using an empirical analysis of the results obtained from a 6-Degree of Freedom (6DoF) simulation. The impact distributions can be aggregated to provide impact footprint distributions for a range of generic phases of flight and missions. The maximum impact footprint areas obtained from the geometric template are shown to have a relative error of typically less than 1% compared to the areas calculated using the computationally more expensive 6DoF simulation. Computation times for the geometric models are on the order of one second or less, using a standard desktop computer. Future work includes characterising the distribution of impact locations within the footprint boundaries.

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Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

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CI chondrites are used pervasively in the meteorite literature as a cosmochemical reference point for bulk compositions[1], isotope analyses[2] and, within certain models of meteorite evolution, as an important component of an alteration sequence within the carbonaceous chondrite subset[3]. More recently, the chemical variablity of CI chondrite matrices (which comprise >80% of the meteorite), has been cited in discussions about the "chondritic" nature of spectroscopic data from P/comet Halley missions[4] and of chemical data from related materials such as interplanetary dust particles[5]. Most CI chondrites have been studied as bulk samples(e.g. major and trace element abundances)and considerable effort has also been focussed on accessory phases such as magnetites, olivine, sulphates and carbonates [6-8]. A number of early studies showed that the primary constituents of CI matrices are layer silicates and the most definitive structural study on powdered samples identified two minerals: montmorillonite and serpentine[9]. In many cases, as with the study by Bass[9],the relative scarcity of most CI chondrites restricts such bulk analyses to the Orgueil meteorite. The electron microprobe/SEM has been used on petrographic sections to more precisely define the "bulk" composition of at least four CI matrices[3], and as recently summarised by McSween[3], these data define a compositional trend quite different to that obtained for CM chondrite matrices. These "defocussed-beam" microprobe analyses average major element compositions over matrix regions ~lOOµm in diameter and provide only an approximation to silicate mineral composition(s) because their grain sizes are much less than the diameter of the beam. In order to (a) more precisely define the major element compositions of individual mineral grains within CI matrices, and (b)complement previous TEM studies [11,12], we have undertaken an analytical electron microscopy (AEM) study of Alais and Orgueil matrices.

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An increased interest in utilising groups of Unmanned Aerial Vehicles (UAVs) with heterogeneous capabilities and autonomy is presenting the challenge to effectively manage such during missions and operations. This has been the focus of research in recent years, moving from a traditional UAV management paradigm of n-to-1 (n operators for one UAV, with n being at least two operators) toward 1-to-n (one operator, multiple UAVs). This paper has expanded on the authors’ previous work on UAV functional capability framework, by incorporating the concept of Functional Level of Autonomy (F-LOA) with two configurations: The lower F-LOA configuration contains sufficient information for the operator to generate solutions and make decisions to address perturbation events. Alternatively, the higher F-LOA configuration presents information reflecting on the F-LOA of the UAV, allowing the operator to interpret solutions and decisions generated autonomously, and decide whether to veto from this decision.

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The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

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As sustainability becomes an important principle guiding various human activities around the globe, the higher education sector is being asked to take an active part in educating and promoting sustainability due to its moral responsibility, social obligation and its own needs to adapt to new circumstances. There is a global trend of higher education institutions embarking on responses to the sustainability challenge. On-campus building performance is one of the most important indicators for “sustainable universities”, because buildings carry substantially environmental burden such as considerable consumption of raw materials and energy as well as huge amount of waste generation and greenhouse gas emission. Plus, much research proves that building performance can impact on students and staff’s awareness about and behaviours related to sustainability. The past studies rarely discussed about sustainable construction projects in universities’ unique context. Universities are labeled with distinct characteristics such as complex governance, multiple cultures and juggling missions and so on. It is necessary and meaningful to examine the project management system in terms of universities’ organizational environment. Thus, this research project applies Delphi study to identify primary barriers to green technology application in on-campus buildings, critical factors for sustainable project success, key actions in project phases and strategies for project improvement. Through three rounds of questionnaires among panel experts, the authors obtain a profound understanding of project delivery system in universities. The research results are expected to provide sustainability practitioners with holistic understanding and generic information about sustainable construction project performance on campus as an assistance tool.

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Osteocyte cells are the most abundant cells in human bone tissue. Due to their unique morphology and location, osteocyte cells are thought to act as regulators in the bone remodelling process, and are believed to play an important role in astronauts’ bone mass loss after long-term space missions. There is increasing evidence showing that an osteocyte’s functions are highly affected by its morphology. However, changes in an osteocyte’s morphology under an altered gravity environment are still not well documented. Several in vitro studies have been recently conducted to investigate the morphological response of osteocyte cells to the microgravity environment, where osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours before microgravity experiments. Morphology changes of osteocyte cells in microgravity were then studied by comparing the cell area to 1g control cells. However, osteocyte cells found in vivo are with a more 3D morphology, and both cell body and dendritic processes are found sensitive to mechanical loadings. A round shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to mechanical stimulations compared with flat cellular morphology. Thus, the relative flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s morphological characteristics in culture may lead to subjective and noncomprehensive conclusions of how altered gravity impacts on an osteocyte’s morphology. Through this work empirical models were developed to quantitatively predicate the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the response of osteocyte cells, which are relatively round in shape, to hyper-gravity stimulation has also been investigated. The morphology changes of MLO-Y4 cells in culture were quantified by measuring cell area and three dimensionless shape features including aspect ratio, circularity and solidity by using widely accepted image analysis software (ImageJTM). MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in morphology were recorded over 10 hours. Based on the data obtained from the imaging analysis, empirical models were developed using the non-linear regression method. The developed empirical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analysing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary. The morphological response of MLO-Y4 cells with a relatively round morphology to hyper-gravity environment has been investigated using a centrifuge. After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in the morphology of MLO-Y4 cells are quantitatively analysed by measuring the average value of cell area and dimensionless shape factors such as aspect ratio, solidity and circularity. In this study, no significant morphology changes were detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins) compared with 1g control cells.

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Lean body mass (LBM) and muscle mass remains difficult to quantify in large epidemiological studies due to non-availability of inexpensive methods. We therefore developed anthropometric prediction equations to estimate the LBM and appendicular lean soft tissue (ALST) using dual energy X-ray absorptiometry (DXA) as a reference method. Healthy volunteers (n= 2220; 36% females; age 18-79 y) representing a wide range of body mass index (14-44 kg/m2) participated in this study. Their LBM including ALST was assessed by DXA along with anthropometric measurements. The sample was divided into prediction (60%) and validation (40%) sets. In the prediction set, a number of prediction models were constructed using DXA measured LBM and ALST estimates as dependent variables and a combination of anthropometric indices as independent variables. These equations were cross-validated in the validation set. Simple equations using age, height and weight explained > 90% variation in the LBM and ALST in both men and women. Additional variables (hip and limb circumferences and sum of SFTs) increased the explained variation by 5-8% in the fully adjusted models predicting LBM and ALST. More complex equations using all the above anthropometric variables could predict the DXA measured LBM and ALST accurately as indicated by low standard error of the estimate (LBM: 1.47 kg and 1.63 kg for men and women, respectively) as well as good agreement by Bland Altman analyses. These equations could be a valuable tool in large epidemiological studies assessing these body compartments in Indians and other population groups with similar body composition.

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Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

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This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

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The aim of this on-going research is to interrogate the era of colonialism in Australia (1896-1966) and the denial of paid employment of Aboriginal women. The 1897 Aborigines Protection and the Restriction of the Sale of Opium Act witnessed thousands of Aboriginal people placed on Government run reserves and missions. This resulted in all aspects of their lives being controlled through state mechanisms. Under various Acts of Parliament, Aboriginal women were sent to privately owned properties to be utilised as ‘domestic servants’ through a system of forced indentured labour, which continued until the 1970’s. This paper discusses the hidden histories of these women through the use of primary sources documents including records from the Australian Department of Native Affairs and Department of Home and Health. This social history research reveals that the practice of removing Aboriginal women from their families at the age of 12 or 13 and to white families was more common practice than not. These women were often: not paid, worked up to 15 hour days, not allowed leave and subjected to many forms of abuse. Wages that were meant to be paid were re-directed to other others, including the Government. Whilst the retrieval of these ‘stolen wages’ is now an on-going issue resulting in the Queensland Government in 2002 offering AUS $2,000 to $4,000 in compensation for a lifetime of work, Aboriginal women were also asked to waive their legal right to further compensation. There are few documented histories of these Aboriginal women as told through the archives. This hidden Aboriginal Australian women’s history needs to be revealed to better understand the experiences and depth of misappropriation of Aboriginal women as domestic workers. In doing so, it also reveals a more accurate reflection of women’s work in Australia.

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Aims Child-feeding practices may be modifiable risk factors for childhood obesity; however investigation of feeding practices in non-Western populations is scarce. This cross-sectional study examines feeding practices of affluent Indian mothers with children aged 1-5 years residing in Australia and Mumbai, India. The secondary aim was to study the association between maternal and child characteristics and feeding practices. Methods In Australia 230 and in Mumbai 301 mothers completed either a hardcopy or online questionnaire. Self-reported maternal feeding practices (restriction, monitoring, pressure to eat, passive and responsive feeding) were measured using established scales and culturally-specific items. Results Mothers in both samples were equally likely to use non-responsive feeding practices, namely dietary restriction, pressure and passive feeding. Similarly, at least 50% of mothers in both samples did not feed their child responsively (mother decides what and the child decides how much to eat). The only difference observed after controlling for covariates (mothers’ age, BMI, religion, education, questionnaire type, child’s age, birth place, gender, number of siblings, and weight-for-age (WAZ) scores) was that mothers in the Australian sample used higher levels of dietary monitoring (β= 0.2, P= 0.006). Mothers with a higher BMI (OR: 0.84, CI: 0.89-0.99, p=0.03) and following Hinduism (OR: 0.50, CI: 0.33-0.83, p=0.008) were less likely to feed responsively. Conclusions These results suggest that Indian mothers in both the samples may benefit from interventions that promote responsive child-feeding practices.

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Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

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Indians tend to have lower lean body mass than other ethnic groups which increases the risk of chronic diseases. Three complementary studies included in this thesis advanced knowledge on determinants of lean body mass in Indians and the techniques to measure it. The first study examined the determinants of lean body mass in young Indian adults and highlighted the importance of diet and physical activity for development of lean body mass. This study has important implications for policy on prevention of chronic diseases in India. The other two studies helped refinement of the techniques of lean body mass measurement and are expected to facilitate future research in this area. The thesis is presented in the form of publications in high ranking journals.