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Previous reports have demonstrated that running economy (RE), a measure of efficiency of locomotion, is superior in adults than in children; however, it is unclear how these differences come to be. Purpose: To identify the effect of maturity status, physical activity and various other anatomical and physiological factors on RE development in boys aged 8 to 16 years. Methods: Data were collected as part of the Saskatchewan Growth and Development Study (SGDS; 1964-1973). Using a pure longitudinal study design, anthropometric, maturity, physiological characteristics (treadmill run) and physical activity were assessed annually for nine consecutive years. Two-hundred and two eight year-old males were measured in 1965; by 1973, complete longitudinal data were available for 63 participants. During the treadmill run, a measure of submaximal oxygen consumption (VO2) was recorded, an index of RE. Four approaches of normalizing VO2 to body size were investigated. Maturity status was determined based upon chronological age at peak height velocity (PHV). Physical activity was assessed by two teacher ratings and two questionnaires. Results: Normalizing VO2 to body surface area was found to be the most appropriate body size adjustment. Submaximal VO2 (ml/m^2/min) at 9.6 km/h decreased with increasing chronological age (p<0.05). At common chronological age bands, late-maturing boys demonstrated superior RE than early-maturing boys from ages 10-14 years (p<0.05); average-maturing boys were also found to be more efficient than early-maturers at 12 and 13 years of age (p<0.05). Physical activity was not found to have any significant effect on the development of RE (p>0.05). A series of age-specific regression analyses identified body surface area and respiratory exchange ratio (RER) as variables which account for a significant portion of the variance in absolute VO2 (0.619<R^2<0.903); RER was not significant (p>0.05) at all chronological ages. Conclusion: Determining an appropriate approach for normalizing VO2 values is essential to allow for reliable investigation into factors other than size that affect RE. Maturity status was found to significantly affect RE development; however, only during the circumpubertal years. No effect of physical activity was found on RE development in boys 8-16 years. The relative influence of maturity status and RER are variable across different ages.

Previous reports have demonstrated that running economy (RE), a measure of efficiency of locomotion, is superior in adults than in children; however, it is unclear how these differences come to be. Purpose: To identify the effect of maturity status, physical activity and various other anatomical and physiological factors on RE development in boys aged 8 to 16 years. Methods: Data were collected as part of the Saskatchewan Growth and Development Study (SGDS; 1964-1973). Using a pure longitudinal study design, anthropometric, maturity, physiological characteristics (treadmill run) and physical activity were assessed annually for nine consecutive years. Two-hundred and two eight year-old males were measured in 1965; by 1973, complete longitudinal data were available for 63 participants. During the treadmill run, a measure of submaximal oxygen consumption (VO2) was recorded, an index of RE. Four approaches of normalizing VO2 to body size were investigated. Maturity status was determined based upon chronological age at peak height velocity (PHV). Physical activity was assessed by two teacher ratings and two questionnaires. Results: Normalizing VO2 to body surface area was found to be the most appropriate body size adjustment. Submaximal VO2 (ml/m^2/min) at 9.6 km/h decreased with increasing chronological age (p<0.05). At common chronological age bands, late-maturing boys demonstrated superior RE than early-maturing boys from ages 10-14 years (p<0.05); average-maturing boys were also found to be more efficient than early-maturers at 12 and 13 years of age (p<0.05). Physical activity was not found to have any significant effect on the development of RE (p>0.05). A series of age-specific regression analyses identified body surface area and respiratory exchange ratio (RER) as variables which account for a significant portion of the variance in absolute VO2 (0.619<R^2<0.903); RER was not significant (p>0.05) at all chronological ages. Conclusion: Determining an appropriate approach for normalizing VO2 values is essential to allow for reliable investigation into factors other than size that affect RE. Maturity status was found to significantly affect RE development; however, only during the circumpubertal years. No effect of physical activity was found on RE development in boys 8-16 years. The relative influence of maturity status and RER are variable across different ages.

Resource scaling improves the capability of a datacenter or group of datacenters collaborated together to provide resources at low cost in order to meet the demands and objectives of application services, but, it is substantial to determine the requirements of the user, especially in the large projects like XIFI. It is important to estimate the number of users, their arrival rate and types of applications that are often requested for resource allocation, to expand the resource dimensions to proportionate degree. In this study we frame a structure that provides deep insights to comprehend XIFI infrastructure. Furthermore, we model behavior of users that approach the node for resource allocation to run their applications. We aim to provide an understanding on how the user behavior influences the resource scaling in XIFI node. The main objective of this thesis is to investigate different types of applications chosen by users who request for resource allocations and impact of their choice on the resource availability. In the systematic review, a number of deliverables of XIFI to understand the specifications of XIFI architecture are reviewed and analyzed. A model that meets basic requirements, which can be denoted as a XIFI node is developed and the developed design is implemented in a simulator. We simulated the designed structure for 30 iterations and analyzed 10,000 user requests for two cases where total RAM of the node is increased in the second case when compared to the first case. We analyze the reason for the failure of the number of requests and different types of virtual machines for different types of applications, due to unavailable resources. From the obtained results, we conclude that, by increasing total RAM in a XIFI node the failure of average number of requests can be reduced. Also the failure percentage of virtual machines that are to be instantiated, as requested by users decreases when the RAM is scaled to twice the present value. We also conclude that the user behavior that imposes load on the system, decides the degree of scalability of resources in the XIFI node.

Recent theoretical and empirical advances, in particular the fractal branching model of West, Brown and Enquist (WBE model), have highlighted the importance of exchange surfaces in understanding the integration of whole plant form, and functional traits. Key insights have arisen from an increased understanding of how the properties of distributive vessel networks influence whole plant metabolic and physiological traits. Here I show that an extension of WBE model, one in which network geometry is continuously variable, provides a robust foundation to understand the diversity of scaling relationships in plants and the organs of which they are composed. Central to the original WBE model has been the assumption of energy minimization as a selective force shaping the evolution of internal and external plant surface areas and morphology. Here I demonstrate how additional selection on traits not detailed in the original WBE formulation can lead to departures from strict energy minimization, and can thus explain much of the variation and covariation in observed scaling central tendencies in plant gross morphology observed within, and across natural plant communities. I test the predictions from this model extension with data from both regional and global datasets, from the leaf to whole plant level, across herbaceous, succulent, woody, annual and perennial taxa. These data demonstrate that the model extension is quite robust and should serve as a foundation upon which more detailed future models can be constructed.

Rock physical properties are usually associated with important geologic features within mineral deposits and can be used to define the location, depth and size of the deposit, type of ore, or physical property contrast between the host and country rock. Geophysical surveys are sensitive to physical properties and therefore are widely used in mining exploration, especially in concealed terrains. The surveys can be performed at multiple scales, resulting in corresponding physical property datasets at different scales. Survey scale can vary from core or hand sample, involving few cubic centimeters, to regional-scale surveys providing information about physical property contrasts between distinct regional geological features. The understanding of the relationship between the physical property distributions with the sample volume (e.g. district, deposit, and drill-hole scale) is required where point scale physical property measurements are going to be consistent with measurements at larger volumetric scales during the integration of data for geophysical modeling The approach used to address the problem of understanding the scaling relations of physical properties, was achieved by considering them as second order stationary regionalized variables and then applying the random function formalism, provided by geostatistics theory. Geostatistics provide the required framework to characterize, quantify, model and link the spatial variability of the random variable at the different volumetric scales. The aim of this study is to apply geostatistics to effectively integrate data collected at several scales and bring knowledge to the understanding of the scaling relations of magnetic susceptibility. For this purpose, measurements of magnetic susceptibility available from Flin Flon copper-zinc district in Canada will be used. The data available at point scale were collected with hand portable magnetic susceptibility meter. The larger volumetric scale dataset were acquired using frequency domain electromagnetic instruments capable of measuring larger sample volumes, and then used to obtain magnetic susceptibility models using geophysical inversion algorithms. Once different scale models of magnetic susceptibility were available, quantification of the scaling relation using geostatistics, specifically variogram models and dispersion variance were determined. The understanding provided by the scaling analysis of the Flin-Flon magnetic data is applied to data from the Rio Blanco copper district in central Chile. Magnetic susceptibility measurements collected with a hand magnetic susceptibility meter on drill-core is integrated in larger scale volumes used for geophysical inversion modeling of regional scale airborne magnetic field measurements to recover magnetic susceptibility models. The methodology resulting from this application of geostatistics is used to address the problem of integrating multiple scales of physical property data in an effective way. The resulting physical property models capture the small-scale magnetic susceptibility variability observed and can guide larger-scale variability within geophysical inversion models. Establishing reliable statistical correlations between physical properties and rock units controlling ore within deposits are crucial steps leading predictive mine exploration tools. Any numerical modeling approach to establish these correlations should consider in some way the scaling nature of both physical property and ore content.

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