138 resultados para Localized algorithms
Resumo:
Localized plasmon resonances of spherical nanovoid arrays strongly enhance solar cell performance by a factor of 3.5 in external quantum efficiency at plasmonic resonances, and a four-fold enhancement in overall power conversion efficiency. Large area substrates of silver nanovoids are electrochemically templated through self-assembled colloidal spheres and organic solar cells fabricated on top. Our design represents a new class of plasmonic photovoltaic enhancement: that of localized plasmon-enhanced absorption within nanovoid structures. Angularly-resolved spectra demonstrate strong localized Mie plasmon modes within the nanovoids. Theoretical modelling shows varied spatial dependence of light intensity within the void region suggesting a first possible route towards Third Generation plasmonic photovoltaics. (C) 2011 Optical Society of America
Resumo:
Potentially inappropriate prescribing in older people is common in primary care and can result in increased morbidity, adverse drug events, hospitalizations and mortality. In Ireland, 36% of those aged 70 years or over received at least one potentially inappropriate medication, with an associated expenditure of over €45 million.The main objective of this study is to determine the effectiveness and acceptability of a complex, multifaceted intervention in reducing the level of potentially inappropriate prescribing in primary care.
Resumo:
(EN)Disclosed is a method of detecting bioproducts using Localized Surface Plasmon Resonance (LSPR) of gold nanoparticles, which can diagnose bioproducts based on changes in the maximum wavelength occurred by an antigen-antibody reaction after immobilization of the gold nanoparticles onto a glass panel. A sensor using such method exhibits high sensitivity, is low in price, and makes quick diagnosis possible, thereby being applicable to various biological fields associated with environmental contaminants, pathogens and the like, as well as diagnosis of diseases. Further, it provides a technology for manufacturing a sensor having higher sensitivity, low price and quick performance, as compared to conventional methods using SPR.
Resumo:
The application of the shape memory alloy NiTi in micro-electro-mechanical-systems (MEMSs) is extensive nowadays. In MEMS, complex while precise motion control is always vital. This makes the degradation of the functional properties of NiTi during cycling loading such as the appearance of residual strain become a serious problem to study, in particular for laser micro-welded NiTi in real applications. Although many experimental efforts have been put to study the mechanical properties of laser welded NiTi, surprisingly, up to the best of our understanding, there has not been attempts to quantitatively model the laser-welded NiTi under mechanical cycling in spite of the accurate prediction required in applications and the large number of constitutive models to quantify the thermo-mechanical behavior of shape memory alloys. As the first attempt to fill the gap, we employ a recent constitutive model, which describes the localized SIMT in NiTi under cyclic deformation; with suitable modifications to model the mechanical behavior of the laser welded NiTi under cyclic tension. The simulation of the model on a range of tensile cyclic deformation is consistent with the results of a series of experiments. From this, we conclude that the plastic deformation localized in the welded regions (WZ and HAZs) of the NiTi weldment can explain most of the extra amount of residual strain appearing in welded NiTi compared to the bare one. Meanwhile, contrary to common belief, we find that the ability of the weldment to memorize its transformation history, sometimes known as ‘return point memory’, still remains unchanged basically though the effective working limit of this ability reduces to within 6% deformation.
Resumo:
NiTi alloys have been widely used in the applications for micro-electro-mechanical-systems (MEMS), which often involve some precise and complex motion control. However, when using the NiTi alloys in MEMS application, the main problem to be considered is the degradation of functional property during cycling loading. This also stresses the importance of accurate prediction of the functional behavior of NiTi alloys. In the last two decades, a large number of constitutive models have been proposed to achieve the task. A portion of them focused on the deformation behavior of NiTi alloys under cyclic loading, which is a practical and non-negligible situation. Despite of the scale of modeling studies of the field in NiTi alloys, two experimental observations under uniaxial tension loading have not received proper attentions. First, a deviation from linearity well before the stress-induced martensitic transformation (SIMT) has not been modeled. Recent experiments confirmed that it is caused by the formation of stress-induced R phase. Second, the influence of the well-known localized Lüders-like SIMT on the macroscopic behavior of NiTi alloys, in particular the residual strain during cyclic loading, has not been addressed. In response, we develop a 1-D phenomenological constitutive model for NiTi alloys with two novel features: the formation of stress-induced R phase and the explicit modeling of the localized Lüders-like SIMT. The derived constitutive relations are simple and at the same time sufficient to describe the behavior of NiTi alloys. The accumulation of residual strain caused by R phase under different loading schemes is accurately described by the proposed model. Also, the residual strain caused by irreversible SIMT at different maximum loading strain under cyclic tension loading in individual samples can be explained by and fitted into a single equation in the proposed model. These results show that the proposed model successfully captures the behavior of R phase and the essence of localized SIMT.
Resumo:
Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.
Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.
Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.