38 resultados para aeration capacity


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This paper studies the fundamental operational limits of a class of Gaussian multicast channels with an interference setting. In particular, the paper considers two base stations multicasting separate messages to distinct sets of users. In the presence of channel state information at the transmitters and at the respective receivers, the capacity region of the Gaussian multicast channel with interference is characterized to within one bit. At the crux of this result is an extension to the multicast channel with interference of the Han-Kobayashi or the Chong-Motani-Garg achievable region for the interference channel.

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We examine a multiple-access communication system in which multiuser detection is performed without knowledge of the number of active interferers. Using a statistical-physics approach, we compute the single-user channel capacity and spectral efficiency in the large-system limit.

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In 1500, Europe was composed of hundreds of statelets and principalities, with weak central authority,no monopoly over the legitimate use of violence, and overlapping jurisdictions. By 1800, only ahandful of powerful, centralized nation states remained. We build a model that explains both the emergenceof capable states and growing divergence between European powers. We argue that the impactof war was crucial for state building, and depended on: i) the financial cost of war, and ii) a country sinitial level of domestic political fragmentation. We emphasize the role of the "Military Revolution",which raised the cost of war. Initially, this caused more cohesive states to invest in state capacity, whilemore divided states rationally dropped out of the competition, causing divergence between Europeanstates. As the cost of war escalated further, all states engaged in a "race to the top" towards greater statebuilding.

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An important policy issue in recent years concerns the number of people claimingdisability benefits for reasons of incapacity for work. We distinguish between workdisability , which may have its roots in economic and social circumstances, and healthdisability which arises from clear diagnosed medical conditions. Although there is a linkbetween work and health disability, economic conditions, and in particular the businesscycle and variations in the risk of unemployment over time and across localities, mayplay an important part in explaining both the stock of disability benefit claimants andinflows to and outflow from that stock. We employ a variety of cross?country andcountry?specific household panel data sets, as well as administrative data, to testwhether disability benefit claims rise when unemployment is higher, and also toinvestigate the impact of unemployment rates on flows on and off the benefit rolls. Wefind strong evidence that local variations in unemployment have an importantexplanatory role for disability benefit receipt, with higher total enrolments, loweroutflows from rolls and, often, higher inflows into disability rolls in regions and periodsof above?average unemployment. Although general subjective measures of selfreporteddisability and longstanding illness are also positively associated withunemployment rates, inclusion of self?reported health measures does not eliminate thestatistical relationship between unemployment rates and disability benefit receipt;indeed including general measures of health often strengthens that underlyingrelationship. Intriguingly, we also find some evidence from the United Kingdom and theUnited States that the prevalence of self?reported objective specific indicators ofdisability are often pro?cyclical that is, the incidence of specific forms of disability arepro?cyclical whereas claims for disability benefits given specific health conditions arecounter?cyclical. Overall, the analysis suggests that, for a range of countries and datasets, levels of claims for disability benefits are not simply related to changes in theincidence of health disability in the population and are strongly influenced by prevailingeconomic conditions. We discuss the policy implications of these various findings.

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While the theoretical industrial organization literature has long arguedthat excess capacity can be used to deter entry into markets, there islittle empirical evidence that incumbent firms effectively behave in thisway. Bagwell and Ramey (1996) propose a game with a specific sequence ofmoves and partially-recoverable capacity costs in which forward inductionprovides a theoretical rationalization for firm behavior in the field. Weconduct an experiment with a game inspired by their work. In our data theincumbent tends to keep the market, in contrast to what the forwardinduction argument of Bagwell and Ramey would suggest. The results indicatethat players perceive that the first mover has an advantage without havingto pre-commit capacity. In our game, evolution and learning do not driveout this perception. We back these claims with data analysis, atheoretical framework for dynamics, and simulation results.

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This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network

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Several European telecommunications regulatory agencies have recently introduced a fixed capacity charge (flat rate) to regulate access to the incumbent's network. The purpose of this paper is to show that the optimal capacity charge and the optimal access-minute charge analysed by Armstrong, Doyle, and Vickers (1996) have a similar structure and imply the same payment for the entrant. I extend the analysis tothe case where there is a competitor with market power. In this case, the optimalcapacity charge should be modified to avoid that the entrant cream-skims the market,fixing a longer or a shorter peak period than the optimal. Finally, I consider a multiproduct setting, where the effect of the product differentiation is exacerbated.

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A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

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Background: Short-term OE (oleoyl-estrone) treatment causes significant decreases in rat weight mainly due to adipose tissue loss. The aim of this work was to determine if OE treatment affects the expression of genes that regulate lipid metabolism in white adipose tissue. Results: Gene expression in adipose tissue from female treated rats (48 hours) was analysed by hybridization to cDNA arrays and levels of specific mRNAs were determined by real-time PCR. Treatment with OE decreased the expression of 232 genes and up-regulated 75 other genes in mesenteric white adipose tissue. The use of real-time PCR validate that, in mesenteric white adipose tissue, mRNA levels for Lipoprotein Lipase (LPL) were decreased by 52%, those of Fatty Acid Synthase (FAS) by 95%, those of Hormone Sensible Lipase (HSL) by 32%, those of Acetyl CoA Carboxylase (ACC) by 92%, those of Carnitine Palmitoyltransferase 1b (CPT1b) by 45%, and those of Fatty Acid Transport Protein 1 (FATP1) and Adipocyte Fatty Acid Binding Protein (FABP4) by 52% and 49%, respectively. Conversely, Tumour Necrosis Factor (TNF¿) values showed overexpression (198%). Conclusion: Short-term treatment with OE affects adipose tissue capacity to extract fatty acids from lipoproteins and to deal with fatty acid transport and metabolism.

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Several European telecommunications regulatory agencies have recently introduced a fixed capacity charge (flat rate) to regulate access to the incumbent's network. The purpose of this paper is to show that the optimal capacity charge and the optimal access-minute charge analysed by Armstrong, Doyle, and Vickers (1996) have a similar structure and imply the same payment for the entrant. I extend the analysis tothe case where there is a competitor with market power. In this case, the optimalcapacity charge should be modified to avoid that the entrant cream-skims the market,fixing a longer or a shorter peak period than the optimal. Finally, I consider a multiproduct setting, where the effect of the product differentiation is exacerbated.

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Climate change may pose challenges and opportunities to viticulture, and much research has focused in studying the likely impacts on grapes and wine production in different regions worldwide. This study assesses the vulnerability and adaptive capacity of the viticulture sector under changing climate conditions, based on a case study in El Penedès region, Catalonia. Farm assets, livelihood strategies, farmer-market interactions and climate changes perceptions are analysed through semi-structured interviews with different types of wineries and growers. Both types of actors are equally exposed to biophysical stressors but unevenly affected by socioeconomic changes. While wineries are vulnerable because of the current economic crisis and the lack of diversification of their work, which may affect their income or production, growers are mainly affected by the low prices of their products and the lack of fix contracts. These socioeconomic stressors strongly condition their capacity to adapt to climate change, meaning that growers prioritize their immediate income problems, rather than future socioeconomic or climate threats. Therefore, growers undertake reactive adaptation to climate changing conditions, mainly based on ancient knowledge, whilst wineries combine both reactive and anticipatory adaptation practices. These circumstances should be addressed in order to allow better anticipatory adaptation to be implemented, thus avoiding future climate threats.

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This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.

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This paper proposes a novel high capacity robust audio watermarking algorithm by using the high frequency band of the wavelet decomposition at which the human auditory system (HAS) is not very sensitive to alteration. The main idea is to divide the high frequency band into frames and, for embedding, to change the wavelet samples depending on the average of relevant frame¿s samples. The experimental results show that the method has a very high capacity (about 11,000 bps), without significant perceptual distortion (ODG in [¿1 ,0] and SNR about 30dB), and provides robustness against common audio signal processing such as additive noise, filtering, echo and MPEG compression (MP3).

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In this paper we introduce a highly efficient reversible data hiding system. It is based on dividing the image into tiles and shifting the histograms of each image tile between its minimum and maximum frequency. Data are then inserted at the pixel level with the largest frequency to maximize data hiding capacity. It exploits the special properties of medical images, where the histogram of their nonoverlapping image tiles mostly peak around some gray values and the rest of the spectrum is mainlyempty. The zeros (or minima) and peaks (maxima) of the histograms of the image tiles are then relocated to embed the data. The grey values of some pixels are therefore modified.High capacity, high fidelity, reversibility and multiple data insertions are the key requirements of data hiding in medical images. We show how histograms of image tiles of medical images can be exploited to achieve these requirements. Compared with data hiding method applied to the whole image, our scheme can result in 30%-200% capacity improvement and still with better image quality, depending on the medical image content. Additional advantages of the proposed method include hiding data in the regions of non-interest and better exploitation of spatial masking.