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

Endogenous Technology Adoption and R&D as Sources of Business Cycle Persistence

We examine the hypothesis that the slowdown in productivity following the Great Recession was in significant part an endogenous response to the contraction in demand that induced the downturn. We motivate, develop and estimate a model with an endogenous TFP mechanism that allows for costly development and adoption of technologies. Our main finding is that a significant fraction of the post-Great Recession fall in productivity was an endogenous phenomenon, suggesting that demand factors played an important role in the post-crisis slowdown of capacity growth. More generally, we provide insight into why recoveries from financial crises may be so slow

Comparison of AlphaLISA and RIA assays for measurement of wool cortisol concentrations

Radioimmunoassay (RIA) methods have always represented a technique of choice for the determination of steroids in biological samples. The Amplified Luminescent Proximity Homogenous Assay-Linked Immunosorbent Assay (AlphaLISA) is now emerging as the new-generation immunoassay technology that does not require washing/separation steps. The aim of this study was to adapt the Perkin-Elmer's AlphaLISA kit for wool cortisol and compare it with a RIA wool cortisol assay. Wool from lambs, 35 at birth (A0) and 54 at two months old (A2), was collected and each extract was evaluated for wool cortisol concentrations (HCC) both by RIA and AlphaLISA immunoassay. The two methods showed good precision, sensitivity and specificity for determining HCC. Both methods were able to detect significant differences between the high and the low HCC assessed in lambs at A0 and A2 (P < 0.01). The HCC assessed with RIA were significantly higher than those assessed with AlphaLISA (P < 0.01). Moreover, the correlation between HCC measured using the AlphaLISA and RIA methods was strong (r = 0.878). The regression analyses show a constant and not proportional error. This could be due to the diversity in the dosage steps and to the diversity of the molecules used in the two methods. Results support the validity of using AlphaLISA as an alternative method to RIA for the quantification of cortisol in sheep wool and considering the performances showed it has a great potential to be further applied as an excellent tool to evaluate HCC in samples derived from animal species

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

Embryonic and foetal mortality in buffalo species.

The aim of this study was to verify the incidence of late embryonic mortality (between 25 and 45 days post-insemination; LEM) and foetal mortality (between 45 and 70 days postinsemination; FM) in buffaloes synchronized and mated by AI during the transitional period. The trial was performed on 288 multiparous Mediterranean Buffaloes, synchronized and inseminated by AI. Trans-rectal ultrasonography was performed 25, 45, and 70 days post-insemination to assess embryonic development. Milk samples were collected on Days 10, 20, 25, 30, and 45 post-insemination to determine progesterone concentration in whey. Pregnancy rate on Day 25 after AI was 48.6% but declined to 35.4% and to 30.6% by Day 45 and 70 respectively, representing a LEM of 27.1% and a FM of 13.7%. Progesterone concentration was higher (P<0.01) in pregnant compared to LEM buffaloes after 20 days post-insemination. Differences (P<0.05) were found between FM and LEM buffaloes on Days 25 and 30. Furthermore, progesterone concentration in pregnant buffaloes was higher (P=0.09) than that of FM buffaloes on Day 30 and 45. In conclusion, the success of application of reproductive biotechnologies in the transitional period depends from the incidence of embryonic and foetal mortality

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

Postnatal and postweaning endocrine setting in dairy calves through hair cortisol, dehydroepiandrosterone and dehydroepiandrosterone sulphate

Importance of the work: The care of calves on dairy farms between birth and weaning can improve their long-term development and growth. In fact, a poor newborn health status and a high allostatic load may adversely affect development in dairy cows. To determine cortisol, dehydroepiandrosterone (DHEA) and dehydroepiandrosterone sulphate (DHEA-S) individually is useful for an understanding of the individual state, being biomarkers of hypothalamic-pituitary-adrenal (HPA) axis activity. Objectives: As a preliminary study, to investigate the hair concentrations of cortisol, DHEA, DHEA-S and their ratios in dairy calves in two key periods of their growth characterized by considerable environmental changes. Materials & Methods: Hair sampling was conducted on clinically healthy dairy calves during the postnatal period at age 64.8±0.65 d (POP; mean±standard error; n = 73) and during the postweaning period at age 155.3±0.85 d (PWP, n = 62). The hair hormone concentrations were measured using a radioimmunoassay. Results: Hair cortisol concentrations were higher in the POP than in the PWP. Furthermore, the cortisol:DHEA and cortisol:DHEA-S ratios were higher in the first period of evaluation, showing a higher animal allostatic load at birth. Main finding: Identification was achieved non-invasively of calves with a high allostatic load through biomarkers of HPA axis activity. The evaluation of this activity is very important given its influence on many biological processes, such as energy balance, development of the reproductive system and immune response

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