Perturbation expansion for 2-D Hubbard model

We develop an efficient method to calculate the third-order corrections to the self-energy of the hole-doped two-dimensional Hubbard model in space-time representation. Using the Dyson equation we evaluate the renormalized spectral function in various parts of the Brillouin zone and find significant modifications with respect to the second-order theory even for rather small values of the coupling constant U. The spectral function becomes unphysical for $U \simeq W$, where W is the half-width of the conduction band. Close to the Fermi surface and for U<W, the single-particle spectral weight is reduced in a finite energy interval around the Fermi energy. The increase of U opens a gap between the occupied and unoccupied parts of the spectral function.Comment: 17 pages, 11 Postscript figures, Phys. Rev. B, accepte

Estudio paleopatológico de la necrópolis mudéjar de la calle Colón, 3 (Novelda, Alicante)

X Congreso Nacional de Paleopatología. Univesidad Autónoma de Madrid, septiembre de 200

La medicina rural: una visión mirando al futuro

The management of any large building stock with limited resources poses a problem of prioritization of refurbishment actions. Also, available technical information about the building stock is often incomplete and the process of standardization and updating is expensive and time consuming. Some public owners are developing preliminary BIM models of their stock, but they are willing to limit the complexity of the models within the lowest amount of information required for management and maintenance, so as to make that process affordable. Indeed, administrations are challenged by their duty relative to planning regular maintenance and operation of buildings, because of the legislation in force, which requires monitoring of their facilities. For the reasons stated above, this paper presents a decision support tool that can help prioritize refurbishment actions on large building assets. To this purpose, many requirements must be jointly considered in this examination, each requirement being assessed by means of one or several indicators. Then the indicators are compared one another, according to a multi-criteria approach, that weighs the several criteria and rank the assets. In order to deal with the extensive and uncertain information that must be managed in this process, indicators are estimated by means of Bayesian Networks. This tool is used first to assess the technical indicators and rank the assets, while marking any facilities not complying with regulations. Then, additional Bayesian Networks are in charge of estimating the budget needed to upgrade non-compliant facilities with minimum legislation requirements. The outcomes of this research can be used even to assess the level of detail of the information that must be included in BIM models of the stock, in fact acting as guidelines for their development. Finally, the application of the decision tool on a real test case will be presented

Time–frequency representation of autoionization dynamics in helium

Autoionization, which results from the interference between direct photoionization and photoexcitation to a discrete state decaying to the continuum by configuration interaction, is a well known example of the important role of electron correlation in light–matter interaction. Information on this process can be obtained by studying the spectral, or equivalently, temporal complex amplitude of the ionized electron wave packet. Using an energy-resolved interferometric technique, we measure the spectral amplitude and phase of autoionized wave packets emitted via the sp2+ and sp3+ resonances in helium. These measurements allow us to reconstruct the corresponding temporal profiles by Fourier transform. In addition, applying various time–frequency representations, we observe the build-up of the wave packets in the continuum, monitor the instantaneous frequencies emitted at any time and disentangle the dynamics of the direct and resonant ionization channels

Prevalence and molecular epidemiology of bovine leukemia virus in Colombian cattle

Bovine leukemia virus (BLV) is one of the five agents considered most significant for cattle. It is important to determine the prevalence and molecular epidemiology of BLV throughout the country in order to gain a more thorough understanding of the current situation of BLV and to reveal the possibility of masked genotypes that the primers used by OIE are unable to identify. Blood samples were collected at random from 289 cows distributed in 75 farms across the country. PCR amplification of env, gag and tax gene segments was performed. The obtained amplicons were sequenced and then subjected to phylogenetic analyses. A total of 62% of the cows present at 92% of the farms were BLV-positive for gag fragment. Genotype 1 was exclusively detected by env gene segment when analyzed using previously reported primers. However, tax gene analysis revealed circulation of genotype 6 variants, which were also detected based on env gene analysis with newly designed primers. These results indicate that current genotyping approaches based on partial env sequencing may bias BLV genetic variability approaches and underestimate the diversity of the detected BLV genotypes. This report is one of the first molecular and epidemiological studies of BLV conducted in Colombia, which contributes to the global epidemiology of the virus; it also highlights the substantial impact of BLV on the country's livestock and thus is a useful resource for farmers and government entities

Direct quality prediction in resistance spot welding process: Sensitivity, specificity and predictive accuracy comparative analysis

In this work, several of the most popular and state-of-the-art classification methods are compared as pattern recognition tools for classification of resistance spot welding joints. Instead of using the result of a non-destructive testing technique as input variables, classifiers are trained directly with the relevant welding parameters, i.e. welding current, welding time and the type of electrode (electrode material and treatment). The algorithms are compared in terms of accuracy and area under the receiver operating characteristic (ROC) curve metrics, using nested cross-validation. Results show that although there is not a dominant classifier for every specificity/sensitivity requirement, support vector machines using radial kernel, boosting and random forest techniques obtain the best performance overallSpanish MICINN Project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010) and by the Junta de Castilla y León GREX251-200