883 resultados para applications in logistics


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The range of applications for plasmas in liquids, plasmas in contact with liquid surfaces and plasmas containing liquid drops is growing rapidly across a range of technologies. Here the focus is on plasmas where the electrodes are immersed in liquids and their applications in nanoscience. The physical phenomena in both high voltage (tens of kilovolts) and low voltage (a few hundred volts) plasmas in liquid are described together with a discussion of the plasma-induced chemistry. Studies show that in water the plasmas are formed in water vapour created by Joule heating as either channels in the liquid or as layers on the electrodes. The chemistry in these water vapour plasmas and at their interface with the liquid is discussed in the context of the highly reactive radicals produced, such as H and OH. The current use of a variety of plasmas-in-liquid systems in the area of nanoscience is discussed, with an emphasis on nanoparticle growth.

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We investigate a hitherto largely unexplored regime of cavity quantum electrodynamics in which a highly-reflective element positioned between the end-mirrors of a typical Fabry--P\'erot resonator strongly modifies the cavity response function, such that two longitudinal modes with different spatial parity are brought close to frequency degeneracy. We examine applications of this generic `optical coalescence' phenomenon for the generation of enhanced photon--phonon nonlinearities in optomechanics and atom--photon nonlinearities in cavity quantum electrodynamics with strongly-coupled emitters.

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Au nanoparticles (AuNPs) have attracted a great interest in fabrication of various biosensor systems for analysis of cellular and biomolecular recognitions. In conjunction with vast conjugation chemistry available, the materials are easily coupled with biomolecules such as nucleic acids, antigens or antibodies in order to achieve their many potential applications as ligand carriers or transducing platforms for preparation, detection and quantification purposes. Furthermore, the nanoparticles possess easily tuned and unique optical/ physical/ chemical characteristics, and high surface areas, making them ideal candidates to this end. In this topic, sensing mechanisms based on localized surface plasmon resonance (LSPR), particle aggregation, catalytic property, and Fluorescence Resonance Energy Transfer (FRET) of AuNPs as well as barcoding technologies including DNA biobarcodes will be discussed.

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Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

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We will outline recent progress, in the UK ASAIL laser-ion acceleration programme, which aims to advance laser-driven ion beams to the point at which they will become a serious alternative to conventional accelerators for radiotherapy.

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This study describes an innovative monolith structure designed for applications in automotive catalysis using an advanced manufacturing approach developed at Imperial College London. The production process combines extrusion with phase inversion of a ceramic-polymer-solvent mixture in order to design highly ordered substrate micro-structures that offer improvements in performance, including reduced PGM loading, reduced catalyst ageing and reduced backpressure.

This study compares the performance of the novel substrate for CO oxidation against commercially available 400 cpsi and 900 cpsi catalysts using gas concentrations and a flow rate equivalent to those experienced by a full catalyst brick when attached to a vehicle. Due to the novel micro-structure, no washcoat was required for the initial testing and 13 g/ft3 of Pd was deposited directly throughout the substrate structure in the absence of a washcoat.

Initial results for CO oxidation indicate that the advanced micro-structure leads to enhanced conversion efficiency. Despite an 79% reduction in metal loading and the absence of a washcoat, the novel substrate sample performs well, with a light-off temperature (LOT) only 15 °C higher than the commercial 400 cpsi sample.

To test the effects of catalyst ageing on light-off temperature, each sample was aged statically at a temperature of 1000 °C, based on the Bench Ageing Time (BAT) equation. The novel substrate performed impressively when compared to the commercial samples, with a variation in light-off temperature of only 3% after 80 equivalent hours of ageing, compared to 12% and 25% for the 400 cpsi and 900 cpsi monoliths, respectively.

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The volume aims at providing an outlet for some of the best papers presented at the 15th Annual Conference of the African Econometric Society, which is one of the “chapters” of the International Econometric Society. Many of these papers represent the state of the art in financial econometrics and applied econometric modeling, and some also provide useful simulations that shed light on the models' ability to generate meaningful scenarios for forecasting and policy analysis.