19 resultados para tracking of explosives

em University of Queensland eSpace - Australia


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his paper contains a warning for investors, executives, analysts and scientists about the sustainability of the biotechnology industry. The study upon which the paper is based examines the impact of market forces on the biotechnology industry and argues that the short-term focus of market driven policies and practices impacts on the sustainability of firms operating in the industry. The market is represented by the National Association of Securities Dealers, Automated Quotations Market (NASDAQ), considered to be one of the vehicles of the promotion of ''new economy'' companies and principles. Through the application of bibliometric data (using both refereed and non-refereed papers), matched with the long term tracking of the NASDAQ Biotechnology Index, the authors provide a clear indication that the short-term investment thinking is leading an industry that is characterised by long R&D cycles. There is an incompatibility between the shorter-term investment considerations and the long-term scientific developments the biotechnology industry is attempting to achieve. Graphs and illustrations are provided to portray the comparative data.

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Studies of plant and animal assemblages from both the terrestrial and the marine fossil records reveal persistence for extensive periods of geological time, sometimes millions of years. Persistence does not require lack of change or the absence of variation from one occurrence of the assemblage to the next in geological time. It does, however, imply that assemblage composition is bounded and that variation occurs within those bounds. The principal cause for these patterns appears to be species-, and perhaps clade-level, environmental fidelity that results in long-term tracking of physical conditions. Other factors that influence persistent recurrence of assemblages are historical, biogeographic effects, the law of large numbers, niche differentiation, and biotic interactions. Much research needs to be done in this area, and greater uniformity is needed in the approaches to studying the problem. However, great potential also exists for enhanced interaction between paleoecology and neoecology in understanding spatiotemporal complexity of ecological dynamics.

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The GuRm is a 1.2m tall, 23 degree of freedom humanoid consuucted at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRw projcct is the development of appropriate learning strategies for control and coodinadon of the robot’s many joints. The development of learning strategies is Seen as a way to sidestep the inherent intricacy of modeling a multi-DOP biped robot. This paper outlines the approach taken to generate an appmpria*e control scheme for the joinis of the GuRoo. The paper demonsrrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-fonward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on thc CMAC architecture. Results from tats on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

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Commercial explosives behave non-ideally in rock blasting. A direct and convenient measure of non-ideality is the detonation velocity. In this study, an alternative model fitted to experimental unconfined detonation velocity data is proposed and the effect of confinement on the detonation velocity is modelled. Unconfined data of several explosives showing various levels of nonideality were successfully modelled. The effect of confinement on detonation velocity was modelled empirically based on field detonation velocity measurements. Confined detonation velocity is a function of the ideal detonation velocity, unconfined detonation velocity at a given blasthole diameter and rock stiffness. For a given explosive and charge diameter, as confinement increases detonation velocity increases. The confinement model is implemented in a simple engineering based non-ideal detonation model. A number of simulations are carried out and analysed to predict the explosive performance parameters for the adopted blasting conditions.

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The morphology of the exine of Late Cretaceous and Tertiary specimens of Tricolpites reticulatus previously documented from Kerguelen, the Antarctic Peninsula, and the Otway Basin of southeastern Australia has been re-examined and compared with the three pollen types identified in the genus Gunnera. An Antarctic specimen of T reticulatus (Maastrichtian) has a uniform reticulum with elongated lumina, similar to that characterising pollen type 3a of Gunnera macrophylla (subgenus Pseudogunnera). Late Cretaceous (Maastrichtian) Australian specimens of T reticulatus differ; specimens from McNamara resemble pollen of subgenera Pseudogunnera and Milligania of type 3a or type 3b, while specimens of T reticulatus from Princes show more rounded and equidimensional lumina and are therefore tentatively attributed to pollen type 2 found in subgenera Gunnera, Misandra and Panke. Kerguelen Island T reticulatus (Miocene) are distinct from Vega Island specimens: a closer resemblance of Kerguelen T reticulatus and pollen type 2 of extant Gunnera is hypothesised. A comparison between specimens of the North American Tricolpites reticulatus/microreticulatus and pollen of Gunnera is also made. The clear similarity of the North American specimens of Tricolpites microreticulatus and pollen of Gunnera in shape and in the exine surface features of pollen suggests that this taxon should not be separated from T reticulatus but should be treated as a synonym of this species. (C) 2004 Elsevier B.V. All rights reserved.

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We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

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This paper presents a new method to measure the sinking rates of individual phytoplankton “particles” (cells, chains, colonies, and aggregates) in the laboratory. Conventional particle tracking and high resolution video imaging were used to measure particle sinking rates and particle size. The stabilizing force of a very mild linear salinity gradient (1 ppt over 15 cm) prevented the formation of convection currents in the laboratory settling chamber. Whereas bulk settling methods such as SETCOL provide a single value of sinking rate for a population, this method allows the measurement of sinking rate and particle size for a large number of individual particles or phytoplankton within a population. The method has applications where sinking rates vary within a population, or where sinking rate-size relationships are important. Preliminary data from experiments with both laboratory and field samples of marine phytoplankton are presented here to illustrate the use of the technique, its applications, and limitations. Whereas this paper deals only with sinking phytoplankton, the method is equally valid for positively buoyant species, as well as nonbiological particles.