Medium Term Business Cycles

Over the postwar, the U.S., Europe and Japan have experienced what may be thought of as medium frequency oscillations between persistent periods of robust growth and persistent periods of relative stagnation. These medium frequency movements, further, appear to bear some relation to the high frequency volatility of output. That is, periods of stagnation are often associated with significant recessions, while persistent booms typically are either free of recessions or are interrupted only by very modest downturns. In this paper we explore the idea of medium term cycles, which we define as reflecting the sum of the high and medium frequency variation in the data. We develop a methodology for identifying these kinds of fluctuations and then show that a number of important macroeconomic time series exhibit significant medium term cycles. The cycles feature strong procyclical movements in both disembodied and embodied technological change, research & development, and the efficiency of resource utilization. We then develop a model to explain the medium term cycle that features both disembodied and embodied endogenous technological change, along with countercyclical markups and variable factor utilization. The model is able to generate medium term fluctuations in output, technological change, and resource utilization that resemble the data, with a non-technological shock as the exogenous disturbance. In particular, the model offers a unified approach to explaining both high and medium frequency variation in aggregate business activity.BUSINESS CYCLE; ENDOGENOUS TECHNOLOGICAL CHANGE.

Identifying the starting point of a spreading process in complex networks

When dealing with the dissemination of epidemics, one important question that can be asked is the location where the contamination began. In this paper, we analyze three spreading schemes and propose and validate an effective methodology for the identification of the source nodes. The method is based on the calculation of the centrality of the nodes on the sampled network, expressed here by degree, betweenness, closeness and eigenvector centrality. We show that the source node tends to have the highest measurement values. The potential of the methodology is illustrated with respect to three theoretical complex network models as well as a real-world network, the email network of the University Rovira i Virgili

Determining the Surface-To-Bulk Progression in the Normal-State Electronic Structure of Sr2RuO4 by Angle-Resolved Photoemission and Density Functional Theory

In search of the potential realization of novel normal-state phases on the surface of Sr2RuO4 - those stemming from either topological bulk properties or the interplay between spin-orbit coupling (SO) and the broken symmetry of the surface - we revisit the electronic structure of the top-most layers by ARPES with improved data quality as well as ab-initio LDA slab calculations. We find that the current model of a single surface layer (\surd2x\surd2)R45{\deg} reconstruction does not explain all detected features. The observed depth-dependent signal degradation, together with the close quantitative agreement with LDA+SO slab calculations based on the LEED-determined surface crystal structure, reveal that (at a minimum) the sub-surface layer also undergoes a similar although weaker reconstruction. This points to a surface-to-bulk progression of the electronic states driven by structural instabilities, with no evidence for Dirac and Rashba-type states or surface magnetism.Comment: 4 pages, 4 figures, 1 table. Further information and PDF available at: http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/articles.htm

A systematic comparison of supervised classifiers

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration

Metodologia para medir a emissão de CH4, CO2 e H2S em compostagem de dejetos de suínos

bitstream/item/58043/1/CUsersPiazzonDocuments479.pdfProjeto: 16.00.30.004

Dispersive charge density wave excitations and temperature dependent commensuration in Bi2Sr2CaCu2O8+{\delta}

Experimental evidence on high-Tc cuprates reveals ubiquitous charge density wave (CDW) modulations, which coexist with superconductivity. Although the CDW had been predicted by theory, important questions remain about the extent to which the CDW influences lattice and charge degrees of freedom and its characteristics as functions of doping and temperature. These questions are intimately connected to the origin of the CDW and its relation to the mysterious cuprate pseudogap. Here, we use ultrahigh resolution resonant inelastic x-ray scattering (RIXS) to reveal new CDW character in underdoped Bi2Sr2CaCu2O8+{\delta} (Bi2212). At low temperature, we observe dispersive excitations from an incommensurate CDW that induces anomalously enhanced phonon intensity, unseen using other techniques. Near the pseudogap temperature T*, the CDW persists, but the associated excitations significantly weaken and the CDW wavevector shifts, becoming nearly commensurate with a periodicity of four lattice constants. The dispersive CDW excitations, phonon anomaly, and temperature dependent commensuration provide a comprehensive momentum space picture of complex CDW behavior and point to a closer relationship with the pseudogap state

Resolving the nature of electronic excitations in resonant inelastic x-ray scattering

The study of elementary bosonic excitations is essential toward a complete description of quantum electronic solids. In this context, resonant inelastic X-ray scattering (RIXS) has recently risen to becoming a versatile probe of electronic excitations in strongly correlated electron systems. The nature of the radiation-matter interaction endows RIXS with the ability to resolve the charge, spin and orbital nature of individual excitations. However, this capability has been only marginally explored to date. Here, we demonstrate a systematic method for the extraction of the character of excitations as imprinted in the azimuthal dependence of the RIXS signal. Using this novel approach, we resolve the charge, spin, and orbital nature of elastic scattering, (para-)magnon/bimagnon modes, and higher energy dd excitations in magnetically-ordered and superconducting copper-oxide perovskites (Nd2CuO4 and YBa2Cu3O6.75). Our method derives from a direct application of scattering theory, enabling us to deconstruct the complex scattering tensor as a function of energy loss. In particular, we use the characteristic tensorial nature of each excitation to precisely and reliably disentangle the charge and spin contributions to the low energy RIXS spectrum. This procedure enables to separately track the evolution of spin and charge spectral distributions in cuprates with doping. Our results demonstrate a new capability that can be integrated into the RIXS toolset, and that promises to be widely applicable to materials with intertwined spin, orbital, and charge excitations

Avaliação do desempenho da ma ravalha e da palha de azevém (Lollium Multiflorum) como substratos na co-compostagem dos dejetos de suínos.

Projeto: 11.11.11.111

Charge order driven by Fermi-arc instability in Bi2201

The understanding of the origin of superconductivity in cuprates has been hindered by the apparent diversity of intertwining electronic orders in these materials. We combined resonant x-ray scattering (REXS), scanning-tunneling microscopy (STM), and angle-resolved photoemission spectroscopy (ARPES) to observe a charge order that appears consistently in surface and bulk, and in momentum and real space within one cuprate family, Bi2201. The observed wave vectors rule out simple antinodal nesting in the single-particle limit but match well with a phenomenological model of a many-body instability of the Fermi arcs. Combined with earlier observations of electronic order in other cuprate families, these findings suggest the existence of a generic charge-ordered state in underdoped cuprates and uncover its intimate connection to the pseudogap regime.Comment: A high resolution version can be found at http://www.phas.ubc.ca/~quantmat/ARPES/PUBLICATIONS/Articles/Bi2201_CDW_REXS_STM.pdf