944 resultados para Input


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The Energy Center at the Ecole Polytechnique Fédérale de Lausanne (Swiss federal institute of technology) is coordinating a multi-stakeholder effort, the Roundtable on Sustainable Biofuels (http://energycenter.epfl.ch/biofuels), to develop global standards for sustainable biofuels production and processing. Given that many of the aspects related to biofuel production request a high scientific level of understanding, it is crucial that scientists take part in the discussion.

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CO2 emissions induced by human activities are the major cause of climate change; hence, strong environmental policy that limits the growing dependence on fossil fuel is indispensable. Tradable permits and environmental taxes are the usual tools used in CO2 reduction strategies. Such economic tools provide incentives to polluting industries to reduce their emissions through market signals. The aim of this work is to investigate the direct and indirect effects of an environmental tax on Spanish products and services. We apply an environmentally extended input-output (EIO) model to identify CO2 emission intensities of products and services and, accordingly, we estimate the tax proportional to these intensities. The short-term price effects are analyzed using an input-output price model. The effect of tax introduction on consumption prices and its influence on consumers’ welfare are determined. We also quantify the environmental impacts of such taxation in terms of the reduction in CO2 emissions. The results, based on the Spanish economy for the year 2007, show that sectors with relatively poor environmental profile are subjected to high environmental tax rates. And consequently, applying a CO2 tax on these sectors, increases production prices and induces a slight increase in consumer price index and a decrease in private welfare. The revenue from the tax could be used to counter balance the negative effects on social welfare and also to stimulate the increase of renewable energy shares in the most impacting sectors. Finally, our analysis highlights that the environmental and economic goals cannot be met at the same time with the environmental taxation and this shows the necessity of finding other (complementary or alternative) measures to ensure both the economic and ecological efficiencies. Keywords: CO2 emissions; environmental tax; input-output model, effects of environmental taxation.

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Measurement of arterial input function is a restrictive aspect for quantitative (18)F-FDG PET studies in rodents because of their small total blood volume and the related difficulties in withdrawing blood.

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The mutual information of independent parallel Gaussian-noise channels is maximized, under an average power constraint, by independent Gaussian inputs whose power is allocated according to the waterfilling policy. In practice, discrete signalling constellations with limited peak-to-average ratios (m-PSK, m-QAM, etc) are used in lieu of the ideal Gaussian signals. This paper gives the power allocation policy that maximizes the mutual information over parallel channels with arbitrary input distributions. Such policy admits a graphical interpretation, referred to as mercury/waterfilling, which generalizes the waterfilling solution and allows retaining some of its intuition. The relationship between mutual information of Gaussian channels and nonlinear minimum mean-square error proves key to solving the power allocation problem.

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We characterize the capacity-achieving input covariance for multi-antenna channels known instantaneously at the receiver and in distribution at the transmitter. Our characterization, valid for arbitrary numbers of antennas, encompasses both the eigenvectors and the eigenvalues. The eigenvectors are found for zero-mean channels with arbitrary fading profiles and a wide range of correlation and keyhole structures. For the eigenvalues, in turn, we present necessary and sufficient conditions as well as an iterative algorithm that exhibits remarkable properties: universal applicability, robustness and rapid convergence. In addition, we identify channel structures for which an isotropic input achieves capacity.

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We study the minimum mean square error (MMSE) and the multiuser efficiency η of large dynamic multiple access communication systems in which optimal multiuser detection is performed at the receiver as the number and the identities of active users is allowed to change at each transmission time. The system dynamics are ruled by a Markov model describing the evolution of the channel occupancy and a large-system analysis is performed when the number of observations grow large. Starting on the equivalent scalar channel and the fixed-point equation tying multiuser efficiency and MMSE, we extend it to the case of a dynamic channel, and derive lower and upper bounds for the MMSE (and, thus, for η as well) holding true in the limit of large signal–to–noise ratios and increasingly large observation time T.

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In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

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A key aspect of industrialization is theadoption of increasing-returns-to-scale, industrial,technologies. Two other, well-documented aspects arethat industrial technologies are adopted throughoutintermediate-input chains and that they use intermediateinputs intensively relative to the technologies theyreplace. These features of industrial technologiescombined imply that countries with access to similartechnologies may have very different levels ofindustrialization and income, even if the degree ofincreasing returns to scale at the firm level is relativelysmall. Furthermore, a small improvement in theproductivity of industrial technologies can trigger full-scaleindustrialization and a large increase in income.

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A simplc formulation Io compute thc envelope correlation of anantenna divemiry system is dcrired. 11 is shown how to compute theenvelope correlation hom the S-parameter descnplian of the antennasystem. This approach has the advantage that i t does not require thecomputation nor the measurement of the radiation panem of theantenna system. It also offers the advantage of providing a clcaunderstanding ofthe effects ofmutual coupling and input match on thediversity performance of the antcnnii system.

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Neural comparisons of bilateral sensory inputs are essential for visual depth perception and accurate localization of sounds in space. All animals, from single-cell prokaryotes to humans, orient themselves in response to environmental chemical stimuli, but the contribution of spatial integration of neural activity in olfaction remains unclear. We investigated this problem in Drosophila melanogaster larvae. Using high-resolution behavioral analysis, we studied the chemotaxis behavior of larvae with a single functional olfactory neuron on either the left or right side of the head, allowing us to examine unilateral or bilateral olfactory input. We developed new spectroscopic methods to create stable odorant gradients in which odor concentrations were experimentally measured. In these controlled environments, we observed that a single functional neuron provided sufficient information to permit larval chemotaxis. We found additional evidence that the overall accuracy of navigation is enhanced by the increase in the signal-to-noise ratio conferred by bilateral sensory input.

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The present research project was designed to determine thermal properties, such as coefficient of thermal expansion (CTE) and thermal conductivity, of Iowa concrete pavement materials. These properties are required as input values by the Mechanistic-Empirical Pavement Design Guide (MEPDG). In this project, a literature review was conducted to determine the factors that affect thermal properties of concrete and the existing prediction equations for CTE and thermal conductivity of concrete. CTE tests were performed on various lab and field samples of portland cement concrete (PCC) at the Iowa Department of Transportation and Iowa State University. The variations due to the test procedure, the equipment used, and the consistency of field batch materials were evaluated. The test results showed that the CTE variations due to test procedure and batch consistency were less than 5%, and the variation due to the different equipment was less than 15%. Concrete CTE values were significantly affected by different types of coarse aggregate. The CTE values of Iowa concrete made with limestone+graval, quartzite, dolomite, limestone+dolomite, and limestone were 7.27, 6.86, 6.68, 5.83, and 5.69 microstrain/oF (13.08, 12.35, 12.03, 10.50, and 10.25 microstrain/oC), respectively, which were all higher than the default value of 5.50 microstrain/oF in the MEPDG program. The thermal conductivity of a typical Iowa PCC mix and an asphalt cement concrete (ACC) mix (both with limestone as coarse aggregate) were tested at Concrete Technology Laboratory in Skokie, Illinois. The thermal conductivity was 0.77 Btu/hr•ft•oF (1.33 W/m•K) for PCC and 1.21 Btu/hr•ft•oF (2.09 W/m•K) for ACC, which are different from the default values (1.25 Btu/hr•ft•oF or 2.16 W/m•K for PCC and 0.67 Btu/hr•ft•oF or 1.16 W/m•K for ACC) in the MEPDG program. The investigations onto the CTE of ACC and the effects of concrete materials (such as cementitious material and aggregate types) and mix proportions on concrete thermal conductivity are recommended to be considered in future studies.