3,595 research outputs found
Quantum mechanical Carnot engine
A cyclic thermodynamic heat engine runs most efficiently if it is reversible.
Carnot constructed such a reversible heat engine by combining adiabatic and
isothermal processes for a system containing an ideal gas. Here, we present an
example of a cyclic engine based on a single quantum-mechanical particle
confined to a potential well. The efficiency of this engine is shown to equal
the Carnot efficiency because quantum dynamics is reversible. The quantum heat
engine has a cycle consisting of adiabatic and isothermal quantum processes
that are close analogues of the corresponding classical processes.Comment: 10 page
Costs of compliance with EU regulations and competitiveness of the EU dairy sector
The introduction of cross-compliance mechanism in the European Union with its 2003 CAPreform might affect the costs of production and thus competitiveness of the EU. Little evidence is available to asses the costs of compliance with regulations and it implication for trade. In this study a farm level competitiveness analysis of the impacts of the Nitrate Directive and the Identification & registration Directive focuses on the dairy sector in Germany, France, Italy, Netherlands and UK (within EU), and the US and New Zealand (outside EU). The findings from this study are integrated into a trade analysis which assesses the impact of compliance costs on competitiveness of the various trading nations in global trade. Representative farm studies were used as a basis for the cost increase calculations. Best-estimates of compliance are used from the existing literature and expert judgements. The negative impact of these measures (for nitrates, and animal identification and registration) on EU imports and exports are less than 3 percent. If a smaller increase in compliance takes place, these already relatively small trade impacts will be further diminished. When the standards for nitrate pollution taken by the US and New Zealand are taken into account along with full compliance assumption in all countries analysed, this would only slightly improve the EU exports. The trade impacts obtained when no changes are assumed to happen in key competitor countries can thus be argued as providing the upper bound of the likely trade impacts
Order conditions for Runge--Kutta-like methods with solution-dependent coefficients
In recent years, many positivity-preserving schemes for initial value
problems have been constructed by modifying a Runge--Kutta (RK) method by
weighting the right-hand side of the system of differential equations with
solution-dependent factors. These include the classes of modified
Patankar--Runge--Kutta (MPRK) and Geometric Conservative (GeCo) methods.
Compared to traditional RK methods, the analysis of accuracy and stability of
these methods is more complicated. In this work, we provide a comprehensive and
unifying theory of order conditions for such RK-like methods, which differ from
original RK schemes in that their coefficients are solution-dependent. The
resulting order conditions are themselves solution-dependent and obtained using
the theory of NB-series, and thus, can easily be read off from labeled N-trees.
We present for the first time order conditions for MPRK and GeCo schemes of
arbitrary order; For MPRK schemes, the order conditions are given implicitly in
terms of the stages. From these results, we recover as particular cases all
known order conditions from the literature for first- and second-order GeCo as
well as first-, second- and third-order MPRK methods. Additionally, we derive
sufficient and necessary conditions in an explicit form for 3rd and 4th order
GeCo schemes as well as 4th order MPRK methods. We also present a new 4th order
MPRK method within this framework and numerically confirm its convergence rate.Comment: 28 pages, 1 figur
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Bayesian Model of Dynamic Image Stabilization in the Visual System
Humans can resolve the fine details of visual stimuli although the image projected on the retina is constantly drifting relative to the photoreceptor array. Here we demonstrate that the brain must take this drift into account when performing high acuity visual tasks. Further, we propose a decoding strategy for interpreting the spikes emitted by the retina, which takes into account the ambiguity caused by retinal noise and the unknown trajectory of the projected image on the retina. A main difficulty, addressed in our proposal, is the exponentially large number of possible stimuli, which renders the ideal Bayesian solution to the problem computationally intractable. In contrast, the strategy that we propose suggests a realistic implementation in the visual cortex. The implementation involves two populations of cells, one that tracks the position of the image and another that represents a stabilized estimate of the image itself. Spikes from the retina are dynamically routed to the two populations and are interpreted in a probabilistic manner. We consider the architecture of neural circuitry that could implement this strategy and its performance under measured statistics of human fixational eye motion. A salient prediction is that in high acuity tasks, fixed features within the visual scene are beneficial because they provide information about the drifting position of the image. Therefore, complete elimination of peripheral features in the visual scene should degrade performance on high acuity tasks involving very small stimuli.Molecular and Cellular Biolog
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Computing Complex Visual Features with Retinal Spike Times
Neurons in sensory systems can represent information not only by their firing rate, but also by the precise timing of individual spikes. For example, certain retinal ganglion cells, first identified in the salamander, encode the spatial structure of a new image by their first-spike latencies. Here we explore how this temporal code can be used by downstream neural circuits for computing complex features of the image that are not available from the signals of individual ganglion cells. To this end, we feed the experimentally observed spike trains from a population of retinal ganglion cells to an integrate-and-fire model of post-synaptic integration. The synaptic weights of this integration are tuned according to the recently introduced tempotron learning rule. We find that this model neuron can perform complex visual detection tasks in a single synaptic stage that would require multiple stages for neurons operating instead on neural spike counts. Furthermore, the model computes rapidly, using only a single spike per afferent, and can signal its decision in turn by just a single spike. Extending these analyses to large ensembles of simulated retinal signals, we show that the model can detect the orientation of a visual pattern independent of its phase, an operation thought to be one of the primitives in early visual processing. We analyze how these computations work and compare the performance of this model to other schemes for reading out spike-timing information. These results demonstrate that the retina formats spatial information into temporal spike sequences in a way that favors computation in the time domain. Moreover, complex image analysis can be achieved already by a simple integrate-and-fire model neuron, emphasizing the power and plausibility of rapid neural computing with spike times.Molecular and Cellular Biolog
Mixed convection in a rotating porous cavity having local heater
Numerical simulation of convective heat transfer inside a rotating porous square cavity with local heater of constant temperature has been performed. Governing equations formulated on the basis of mass, momentum and energy conservation laws written using the dimensionless stream function, vorticity and temperature have been solved by the finite difference method. The effects of Rayleigh and Taylor numbers on periodic flow and heat transfer have been studied
Progressive Transient Photon Beams
In this work we introduce a novel algorithm for transient rendering in
participating media. Our method is consistent, robust, and is able to generate
animations of time-resolved light transport featuring complex caustic light
paths in media. We base our method on the observation that the spatial
continuity provides an increased coverage of the temporal domain, and
generalize photon beams to transient-state. We extend the beam steady-state
radiance estimates to include the temporal domain. Then, we develop a
progressive version of spatio-temporal density estimations, that converges to
the correct solution with finite memory requirements by iteratively averaging
several realizations of independent renders with a progressively reduced kernel
bandwidth. We derive the optimal convergence rates accounting for space and
time kernels, and demonstrate our method against previous consistent transient
rendering methods for participating media
Resolution of the clinical features of tyrosinemia following orthotopic liver transplantation for hepatoma
The clinical history before transplantation and subsequent clinical and biochemical course of 3 children and one adult with hereditary tyrosinemia treated by orthotopic hepatic transplantation is described. All four patients are now free of their previous dietary restrictions and appear to be cured of both their metabolic disease and their hepatic neoplasm. © 1986 Elsevier Science Publishers B.V. All rights reserved
Large Predicted Self-Field Critical Current Enhancements In Superconducting Strips Using Magnetic Screens
A transport current distribution over a wide superconducting sheet is shown
to strongly change in a presence of bulk magnetic screens of a soft magnet with
a high permeability. Depending on the geometry, the effect may drastically
suppress or protect the Meissner state of the sheet through the enhancement or
suppression of the edge barrier critical current. The total transport current
in the magnetically screened Meissner state is expected to compete with the
critical current of the flux-filled sheet only for samples whose critical
current is initially essentially controlled by the edge barrier effect.Comment: 6 figure
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