Biomechanical and physiological comparison of conventional webbing and the M83 assault vest

This study compared the effect of load distribution using two different webbing designs on oxygen consumption and running kinematics of soldiers. It was hypothesised that running with webbing that distributes the load closer to the body (M83 Assault Vest) would expend less energy compared to running with conventional webbing (CON). Seven soldiers randomly completed three treadmill trials; an unloaded VO(2)max test, and two loaded (8 kg) efficiency tests using either the M83 or CON webbing. The VO(2)max test and the loaded efficiency tests had 4-min stages at 5, 8, 10 and 12km h(-1). Energy expenditure was measured via indirect calorimetry and video analysis was used to determine stride frequency (SF) and stride length (SL) during each trial. Participants using the M83 webbing expended significantly (p < 0.05) less energy at all four running velocities compared to the CON trials. The M83 webbing resulted in smaller changes to SL and SF from the unloaded trial when compared to the CON trial. These results indicate that the M83 vest that is designed to distribute the load closer to the body may have an energy efficiency advantage over conventional webbing when soldiers are running. (C) 2004 Published by Elsevier Ltd.

In vivo demonstration of load-induced fluid flow in the rat tibia and its potential implications for processes associated with functional adaptation

Load-induced extravascular fluid flow has been postulated to play a role in mechanotransduction of physiological loads at the cellular level. Furthermore, the displaced fluid serves as a carrier for metabolites, nutrients, mineral precursors and osteotropic agents important for cellular activity. We hypothesise that load-induced fluid flow enhances the transport of these key substances, thus helping to regulate cellular activity associated with processes of functional adaptation and remodelling. To test this hypothesis, molecular tracer methods developed previously by our group were applied in vivo to observe and quantify the effects of load-induced fluid flow under four-point-bending loads. Preterminal tracer transport studies were carried out on 24 skeletally mature Sprague Dawley rats. Mechanical loading enhanced the transport of both small- and larger-molecular-mass tracers within the bony tissue of the tibial mid-diaphysis. Mechanical loading showed a highly significant effect on the number of periosteocytic spaces exhibiting tracer within the cross section of each bone. For all loading rates studied, the concentration of Procion Red tracer was consistently higher in the tibia subjected to pure bending loads than in the unloaded, contralateral tibia, Furthermore, the enhancement of transport was highly site-specific. In bones subjected to pure bending loads, a greater number of periosteocytic spaces exhibited the presence of tracer in the tension band of the cross section than in the compression band; this may reflect the higher strains induced in the tension band compared with the compression band within the mid-diaphysis of the rat tibia. Regardless of loading mode, the mean difference between the loaded side and the unloaded contralateral control side decreased with increasing loading frequency. Whether this reflects the length of exposure to the tracer or specific frequency effects cannot be determined by this set of experiments. These in vivo experimental results corroborate those of previous ex vivo and in vitro studies, Strain-related differences in tracer distribution provide support for the hypothesis that load-induced fluid flow plays a regulatory role in processes associated with functional adaptation.

Load profiling and data mining techniques in electricity deregulated market

This paper presents load profiles of electricity customers, using the knowledge discovery in databases (KDD) procedure, a data mining technique, to determine the load profiles for different types of customers. In this paper, the current load profiling methods are compared using data mining techniques, by analysing and evaluating these classification techniques. The objective of this study is to determine the best load profiling methods and data mining techniques to classify, detect and predict non-technical losses in the distribution sector, due to faulty metering and billing errors, as well as to gather knowledge on customer behaviour and preferences so as to gain a competitive advantage in the deregulated market. This paper focuses mainly on the comparative analysis of the classification techniques selected; a forthcoming paper will focus on the detection and prediction methods.