Efficiency in milk and calf yield for dairy cows: measurements, environmental factors, genetic parameters

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Emission Spectra from Internal Shocks in Gamma-Ray-Burst Sources

Unsteady activity of gamma-ray burst sources leads to internal shocks in their emergent relativistic wind. We study the emission spectra from such shocks, assuming that they produce a power-law distribution of relativistic electrons and posses strong magnetic fields. The synchrotron radiation emitted by the accelerated electrons is Compton up-scattered multiple times by the same electrons. A substantial component of the scattered photons acquires high energies and produces e+e- pairs. The pairs transfer back their kinetic energy to the radiation through Compton scattering. The generic spectral signature from pair creation and multiple Compton scattering is highly sensitive to the radius at which the shock dissipation takes place and to the Lorentz factor of the wind. The entire emission spectrum extends over a wide range of photon energies, from the optical regime up to TeV energies. For reasonable values of the wind parameters, the calculated spectrum is found to be in good agreement with the burst spectra observed by BATSE.Comment: 12 pages, latex, 2 figures, submitted to ApJ

an adaptive neural network model for thermal characterization of building components

Abstract Building materials are usually characterized in stationary or almost-stationary conditions and mono dimensional heat flow regime. The existing standards (such as ISO 9869 or EN ISO 6946, EN 12664, EN 12667, ISO 8302 etc), require experiments carried out in steady-state conditions, with a very fine control of the measuring parameters with the aim to apply a simple and reproducible procedure for the determination of thermal properties. However, the thermodynamic conditions that lead to a steady-state operating mode and mono dimensional flow are very difficult to obtain (in real conditions) or very expensive and time consuming (in climate chambers). In this paper the authors present the development of a method for thermal characterization of building components, inferring the steady-state conditions, when only measures in transient conditions are available. The method, based on an adaptive linear neural network (ALNN) model also could be have the potentialities to determine the thermal diffusivity from a significant transient behavior ad hoc imposed. The study targets multilayered walls homogeneous and the results are compared with the experimental data measured by a climate chamber that operate according to the standard EN 1266

An Adaptive Neural Network model for thermal characterization of building components

Building materials are usually characterized in stationary or almost-stationary conditions and mono dimensional heat flow regime. The existing standards (such as ISO 9869 or EN ISO 6946, EN 12664, EN 12667, ISO 8302 etc), require experiments carried out in steady-state conditions, with a very fine control of the measuring parameters with the aim to apply a simple and reproducible procedure for the determination of thermal properties. However, the thermodynamic conditions that lead to a steady-state operating mode and mono dimensional flow are very difficult to obtain (in real conditions) or very expensive and time consuming (in climate chambers). In this paper the authors present the development of a method for thermal characterization of building components, inferring the steady-state conditions, when only measures in transient conditions are available. The method, based on an adaptive linear neural network (ALNN) model also could be have the potentialities to determine the thermal diffusivity from a significant transient behavior ad hoc imposed. The study targets multilayered walls homogeneous and the results are compared with the experimental data measured by a climate chamber that operate according to the standard EN 12667 (c) 2017The Authors. Published by Elsevier Ltd

Characterization of the fecal microbiome in cats with inflammatory bowel disease or alimentary small cell lymphoma.

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats and mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Both IBD and SCL in cats share features with chronic enteropathies such as IBD and monomorphic epitheliotropic intestinal T-cell lymphoma in humans. The aim of this study was to characterize the fecal microbiome of 38 healthy cats and 27 cats with CE (13 cats with IBD and 14 cats with SCL). Alpha diversity indices were significantly decreased in cats with CE (OTU p = 0.003, Shannon Index p = 0.008, Phylogenetic Diversity p = 0.019). ANOSIM showed a significant difference in bacterial communities, albeit with a small effect size (P = 0.023, R = 0.073). Univariate analysis and LEfSE showed a lower abundance of facultative anaerobic taxa of the phyla Firmicutes (families Ruminococcaceae and Turicibacteraceae), Actinobacteria (genus Bifidobacterium) and Bacteroidetes (i.a. Bacteroides plebeius) in cats with CE. The facultative anaerobic taxa Enterobacteriaceae and Streptococcaceae were increased in cats with CE. No significant difference between the microbiome of cats with IBD and those with SCL was found. Cats with CE showed patterns of dysbiosis similar to those in found people with IBD

A New Technique for Finding Needles in Haystacks: A Geometric Approach to Distinguishing Between a New Source and Random Fluctuations

We propose a new test statistic based on a score process for determining the statistical significance of a putative signal that may be a small perturbation to a noisy experimental background. We derive the reference distribution for this score test statistic; it has an elegant geometrical interpretation as well as broad applicability. We illustrate the technique in the context of a model problem from high-energy particle physics. Monte Carlo experimental results confirm that the score test results in a significantly improved rate of signal detection.Comment: 5 pages, 4 figure