Merits and Qualms of Work Fluctuations in Classical Fluctuation Theorems

Work is one of the most basic notion in statistical mechanics, with work fluctuation theorems being one central topic in nanoscale thermodynamics. With Hamiltonian chaos commonly thought to provide a foundation for classical statistical mechanics, here we present general salient results regarding how (classical) Hamiltonian chaos generically impacts on nonequilibrium work fluctuations. For isolated chaotic systems prepared with a microcanonical distribution, work fluctuations are minimized and vanish altogether in adiabatic work protocols. For isolated chaotic systems prepared at an initial canonical distribution at inverse temperature $\beta$, work fluctuations depicted by the variance of $e^{-\beta W}$ are also minimized by adiabatic work protocols. This general result indicates that if the variance of $e^{-\beta W}$ diverges for an adiabatic work protocol, then it diverges for all nonadiabatic work protocols sharing the same initial and final Hamiltonians. How such divergence explicitly impacts on the efficiency of using the Jarzynski's equality to simulate free energy differences is studied in a Sinai model. Our general insights shall boost studies in nanoscale thermodynamics and are of fundamental importance in designing useful work protocols.Comment: 11 pages, 5 figures, close to published versio

Meteoròlegs amb cara i ulls: exposició de meteoròlegs catalans de tots els temps

The Catalan meteorology has contributed in an important way to the international development of this science along the history. Some of the studious Catalan scientists of the atmosphere are very known, like Eduard Fontserè, but other, in spite of the important developed task they have remained, for diverse motives, forgotten, or do not know themselves well. Introducing the contribution and the figure of the main meteorologists of our country it has been the main goal of the Associació Catalana d’Observadors Meteorològics (ACOM) to promote in year 2006 the recovery and divulging of these characters, while carrying out some small sculptures of theirs bust, making expensive to this scientists

Mesoscale numerical simulations of heavy nocturnal rainbands associated with coastal fronts in the Mediterranean Basin

Three offshore rainbands associated with nocturnal coastal fronts formed near the Israeli coastline, the Gulf of Genoa and on the northeastern coast of the Iberian Peninsula, are simulated using version 3.3 of the WRF-ARW mesoscale model in order to study the dynamics of the atmosphere in each case. <br><br> The simulations show coastal fronts producing relatively high (in comparison with some other similar rainbands) 1 and 10 h accumulated precipitations that formed in the Mediterranean Basin. According to these simulations, the coastal fronts that formed near the Israeli coastline and over the Gulf of Genoa are quasi-stationary, while the one that formed on the northeastern coast of the Iberian Peninsula moves away from the coast. For the three events, we evaluate and intercompare some parameters related to convective triggering, deceleration induced by the cold pool in the upstream flow, and the blockage that the cold coastal front offers to the warmer maritime air mass

Gaussian process tomography for soft x-ray spectroscopy at WEST without equilibrium information

International audienceGaussian process tomography (GPT) is a recently developed tomography method based on the Bayesian probability theory [J. Svensson, JET Internal Report EFDA-JET-PR(11)24, 2011 and Li et al., Rev. Sci. Instrum. 84, 083506 (2013)]. By modeling the soft X-ray (SXR) emissivity field in a poloidal cross section as a Gaussian process, the Bayesian SXR tomography can be carried out in a robust and extremely fast way. Owing to the short execution time of the algorithm, GPT is an important candidate for providing real-time reconstructions with a view to impurity transport and fast magnetohydrodynamic control. In addition, the Bayesian formalism allows quantifying uncertainty on the inferred parameters. In this paper, the GPT technique is validated using a synthetic data set expected from the WEST tokamak, and the results are shown of its application to the reconstruction of SXR emissivity profiles measured on Tore Supra. The method is compared with the standard algorithm based on minimization of the Fisher information

EFFECTS OF YEAST-DERIVED MICROBIAL PROTEIN ON TRANSITION DAIRY COW HEALTH AND PERFORMANCE

The transition period for dairy cows is defined as the three weeks pre and postpartum. During the transition period, dairy cows experience a myriad of metabolic, managerial, and nutritional requirement changes. These changes lead to stress and increased susceptibility to diseases which can negatively affect lactational performance in the short and long term. However, dietary amino acid availability can have a dramatic impact on the health and performance of dairy cows around parturition. Thus, the objective of the thesis was to evaluate the effects of supplementing yeast-derived microbial protein, as an alternative protein source for dairy cows during the transition period. This was accomplished by using visual observations and precision dairy monitoring technologies to record disease, feeding behavior, and performance of dairy cows from 21 days prepartum to 150 days postpartum. Yeast-derived microbial protein was found to decrease dry matter intake but not negatively affect milk production or health of the animals. Yeast-derived microbial protein may be used as an alternative protein source for transition dairy cows as it did not negatively affect milk production or health of the animals