978 resultados para Exponential Sum
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Using the once and thrice energy-weighted moments of the random-phase-approximation strength function, we have derived compact expressions for the average energy of surface collective oscillations of clusters and spheres of metal atoms. The L=0 volume mode has also been studied. We have carried out quantal and semiclassical calculations for Na and Ag systems in the spherical-jellium approximation. We present a rather thorough discussion of surface diffuseness and quantal size effects on the resonance energies.
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The nucleon spectral function in nuclear matter fulfills an energy weighted sum rule. Comparing two different realistic potentials, these sum rules are studied for Greens functions that are derived self-consistently within the T matrix approximation at finite temperature.
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The neutron and proton single-particle spectral functions in asymmetric nuclear matter fulfill energy-weighted sum rules. The validity of these sum rules within the self-consistent Green's function approach is investigated. The various contributions to these sum rules and their convergence as a function of energy provide information about correlations induced by the realistic interaction between the nucleons. The study of the sum rules in asymmetric nuclear matter exhibits the isospin dependence of the nucleon-nucleon correlations.
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We study energy-weighted sum rules of the pion and kaon propagator in nuclear matter at finite temperature. The sum rules are obtained from matching the Dyson form of the meson propagator with its spectral Lehmann representation at low and high energies. We calculate the sum rules for specific models of the kaon and pion self-energy. The in-medium spectral densities of the K and (K) over bar mesons are obtained from a chiral unitary approach in coupled channels that incorporates the S and P waves of the kaon-nucleon interaction. The pion self-energy is determined from the P-wave coupling to particle-hole and Delta-hole excitations, modified by short-range correlations. The sum rules for the lower-energy weights are fulfilled satisfactorily and reflect the contributions from the different quasiparticle and collective modes of the meson spectral function. We discuss the sensitivity of the sum rules to the distribution of spectral strength and their usefulness as quality tests of model calculations.
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A better prediction of the outcome after ischemia and estimation of onset time at early time points would greatly facilitate clinical decisions. Therefore, the aim of the present study was to use magnetic resonance spectroscopy to identify neurochemical markers for outcome prediction at early time points after ischemia.ICR-CD1 mice were subjected to 10-minute, 30-minute or permanent middle cerebral artery occlusion (MCAO). The regional cerebral blood flow (CBF) was monitored in all animals by laser-Doppler flowmetry. All MR studies were carried out in a horizontal 14.1T magnet. Fast spin echo images with T2-weighted parameters were Bacquired to localize the volume of interest and evaluate the lesion size. Immediately after adjustment of field inhomogeneities, localized 1H MRS was applied to obtain the neurochemical profile from the striatum (6-8 μl) or the cortex (2.2-2.5 μl). Six animals (sham group) underwent nearly identical procedures without MCAO.By comparing the evolution of several metabolites in ischemia of varying severity, we observed that glutamine increases early after transient ischemia independently of severity, but decreases in permanent ischemia. On the opposite, GABA increased in permanent ischemia and decreased in transient. We also observed a decrease in the sum of N-acetyl aspartate + glutamate + taurine in all irreversibly damaged tissues, independently of reperfusion and severity. Finally, we have observed that some metabolites decrease exponentially after ischemia. This exponential decrease could be used to determine the time of ischemia onset in permanent ischemia.In Conclusion, magnetic resonance spectroscopy can be used as a prognostic and diagnostic tool to monitor reperfusion, identify reversibly and irreversibly damaged tissue and evaluate the time of ischemia onset. If these Results can be translated to stroke patients, this technique would greatly improve the diagnosis and help with clinical decisions.
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Fast-track multimodal rehabilitation after cesarean, the sum of all tricks Fast-track multimodal rehabilitation after caesarean is an interdisciplinary concept allowing an accelerated return to normal physiology. Fast-track rehabilitation combines minimising surgical trauma, regional anaesthesia and active management of pain control, minimally invasive postoperative care while promoting return to autonomy.
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Let $ E_{\lambda}(z)=\lambda {\rm exp}(z), \lambda\in \mathbb{C}$, be the complex exponential family. For all functions in the family there is a unique asymptotic value at 0 (and no critical values). For a fixed $ \lambda$, the set of points in $ \mathbb{C}$ with orbit tending to infinity is called the escaping set. We prove that the escaping set of $ E_{\lambda}$ with $ \lambda$ Misiurewicz (that is, a parameter for which the orbit of the singular value is strictly preperiodic) is a connected set.
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The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.
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The objective of this work was to evaluate basal temperature, thermal sum at different phenological stages, phenological phase duration, yield and seasonality of one nectarine and 14 peach cultivars, between 2006 and 2009. The considered phenological phases were: pruning-sprouting; sprouting-flowering, from swollen bud to open flower; flowering-fruiting, from petal fall to medium-sized fruit; and ripening. Minimum basal temperatures (Tb) obtained were: pruning-sprouting, 8°C, irrespective of the cultivars; sprouting-flowering, 10°C, except for 'Cascata 968', which required 8°C Tb; flowering-fruiting, 12°C, except for 'Oro Azteca', which required 14°C Tb; ripening, 14°C, except for 'Sunblaze', 'Diamante Mejorado' and 'Precocinho' with 12°C Tb. For most cultivars, the maximum basal temperatures were 30, 34, 34 and 28ºC for phases pruning-sprouting, sprouting-flowering, flowering-fruiting and ripening, respectively. 'Turmalina', 'Marli' and 'Tropic Beauty' showed average yields of 3,945.0, 3,969.3 and 3,954.0 kg ha-1, respectively, in 2009, while the nectarine 'Sunblaze' showed around 3,900 kg ha-1 in 2008 and 2009. The cultivars differed for their total cycle and for the accumulated thermal sums which varied, respectively, from 245 days and 1,881.4 degree-days for 'Oro Azteca', to144 days and 1,455.7 degree-days for 'Precocinho'.
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Référence bibliographique : Toledano, Marieschi, 8d