925 resultados para monolithic stationary phases


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We show how a quantum property, a geometric phase, associated with scattering states can be exhibited in nanoscale electronic devices. We propose an experiment to use interference to directly measure the effect of this geometric phase. The setup involves a double-path interferometer, adapted from that used to measure the phase evolution of electrons as they traverse a quantum dot (QD). Gate voltages on the QD could be varied cyclically and adiabatically, in a manner similar to that used to observe quantum adiabatic charge pumping. The interference due to the geometric phase results in oscillations in the current collected in the drain when a small bias across the device is applied. We illustrate the effect with examples of geometric phases resulting from both Abelian and non-Abelian gauge potentials.

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Listeria monocytogenes is a food-borne Gram-positive bacterium that is responsible for a variety of infections (worldwide) annually. The organism is able to survive a variety of environmental conditions and stresses, however, the mechanisms by which L. monocytogenes adapts to environmental change are yet to be fully elucidated. An understanding of the mechanism(s) by which L. monocytogenes survives unfavourable environmental conditions will aid in developing new food processing methods to control the organism in foodstuffs. We have utilized a proteomic approach to investigate the response of L. monocytogenes batch cultures to the transition from exponential to stationary growth phase. Proteomic analysis showed that batch cultures of L. monocytogenes perceived stress and began preparations for stationary phase much earlier (approximately A(600) = 0.75, mid-exponential) than predicted by growth characteristics alone. Global analysis of the proteome revealed that the expression levels of more than 50% of all proteins observed changed significantly over a 7-9 h period during this transition phase. We have highlighted ten proteins in particular whose expression levels appear to be important in the early onset of the stationary phase. The significance of these findings in terms of functionality and the mechanistic picture are discussed.

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Iron is the most common and detrimental impurity in aluminum casting alloys and has long been associated with an increase in casting defects. While the negative effects of iron are clear, the mechanism involved is not fully understood. It is generally believed to be associated with the formation of Fe-rich intermetallic phases. Many factors, including alloy composition, melt superheating, Sr modification, cooling, rate, and oxide bifilms, could play a role. In the present investigation, the interactions between iron and each individual element commonly present in aluminum casting alloys, were investigated using a combination of thermal analysis and interrupted quenching tests. The Fe-rich intermetallic phases were characterized using optical microscope, scanning electron microscope, and electron probe microanalysis (EPMA), and the results were compared with the predictions by Thermocalc. It was found that increasing the iron content changes the precipitation sequence of the beta phase, leading to the precipitation of coarse binary beta platelets at a higher temperature. In contrast, manganese, silicon, and strontium appear to suppress the coarse binary beta platelets, and Mn further promotes the formation of a more compact and less harmful a phase. They are therefore expected to reduce the negative effects of the phase. While reported in the literature, no effect of P on the amount of beta platelets was observed. Finally, attempts are made to correlate the Fe-rich intermetallic phases to the formation of casting defects. The role of the beta phase as a nucleation site for eutectic Si and the role of the oxide bifilms and AIP as a heterogeneous substrate of Fe intermetallics are also discussed.

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Geometric phases of scattering states in a ring geometry are studied on the basis of a variant of the adiabatic theorem. Three timescales, i.e., the adiabatic period, the system time and the dwell time, associated with adiabatic scattering in a ring geometry play a crucial role in determining geometric phases, in contrast to only two timescales, i.e., the adiabatic period and the dwell time, in an open system. We derive a formula connecting the gauge invariant geometric phases acquired by time-reversed scattering states and the circulating (pumping) current. A numerical calculation shows that the effect of the geometric phases is observable in a nanoscale electronic device.

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Experiments for the investigation of the flow of granular solids in a pyrolysis pilot-scale rotary kiln are presented. These experiments consisted first in measuring the volumetric filling ratio (steady-state experiences) for several operating conditions and second in recording the exit flow rates after a positive or negative step in one of the operating parameters (dynamic experiences). A dynamical model computing the evolution of the flow rate of granular solids through the kiln has been developed based on Saeman model [Chem. Eng. Prog. 47 (1951) 508]. The simulations are compared with experimental results; the model gives good results for the rolling mode, but for the slipping mode too. (C) 2004 Elsevier B.V. All rights reserved.

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Many populations have a negative impact on their habitat or upon other species in the environment if their numbers become too large. For this reason they are often subjected to some form of control. One common control regime is the reduction regime: when the population reaches a certain threshold it is controlled (for example culled) until it falls below a lower predefined level. The natural model for such a controlled population is a birth-death process with two phases, the phase determining which of two distinct sets of birth and death rates governs the process. We present formulae for the probability of extinction and the expected time to extinction, and discuss several applications. (c) 2006 Elsevier Inc. All rights reserved.

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Introduction: Walking programmes are recommended as part of the initial treatment for intermittent claudication (IC). However, for many patients factors such as frailty, the severe leg discomfort associated with walking and safety concerns about exercising in public areas reduce compliance to such prescription. Thus, there is a need to identify a mode of exercise that provides the same benefits as regular walking while also offering convenience and comfort for these patients. The present study aims to provide evidence for the first time of the efficacy of a supervised cycle training programme compared with a conventional walking programme for the treatment of IC. Methods: Thus far 33 patients have been randomized to: a treadmill-training group (n = 12); a cycle-training group (n = 11); or a control group (n = 10). Training groups participated in three sessions of supervised training per week for a period of 6 weeks. Control patients received no experimental intervention. Maximal incremental treadmill testing was performed at baseline and after the 6 weeks of training. Measures included pain-free (PFWT) and maximal walking time (MWT), continuous heart rate and gas-analysis recording, and ankle-brachial index assessment. Results: In the treadmill trained group MWT increased significantly from 1016.7 523.7 to 1255.2 432.2 s (P < 0.05). MWT tended to increase with cycle training (848.72 333.18 to 939.54 350.35 s, P = 0.14), and remained unchanged in the control group (1555.1 683.23 to 1534.7 689.87 s). For PFWT, there was a non-significant increase in the treadmill-training group from 414.4 262.3 to 592.9 381.9 s, while both the cycle training and control groups displayed no significant change in this time (226.7 147.1 s to 192.3 56.8 and 499.4 503.7 s to 466.0 526.1 s, respectively). Conclusions: These preliminary results might suggest that, unlike treadmill walking, cycling has no clear effect on walking performance in patients with IC. Thus the current recommendations promoting walking based programmes appear appropriate. The present study was funded by the National Heart Foundation of Australia.

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This paper reports preliminary progress on a principled approach to modelling nonstationary phenomena using neural networks. We are concerned with both parameter and model order complexity estimation. The basic methodology assumes a Bayesian foundation. However to allow the construction of pragmatic models, successive approximations have to be made to permit computational tractibility. The lowest order corresponds to the (Extended) Kalman filter approach to parameter estimation which has already been applied to neural networks. We illustrate some of the deficiencies of the existing approaches and discuss our preliminary generalisations, by considering the application to nonstationary time series.