Local temperature in quantum thermal states

We consider blocks of quantum spins in a chain at thermal equilibrium, focusing on their properties from a thermodynamical perspective. Whereas in classical systems the temperature behaves as an intensive magnitude, a deviation from this behavior is expected in quantum systems. In particular, we see that under some conditions the description of the blocks as thermal states with the same global temperature as the whole chain fails. We analyze this issue by employing the quantum fidelity as a figure of merit, singling out in detail the departure from the classical behavior. The influence in this sense of zero-temperature quantum phase transitions can be clearly observed within this approach. Then we show that the blocks can be considered indeed as thermal states with a high fidelity, provided an effective local temperature is properly identified. Such a result originates from typical properties of reduced sub-systems of energy-constrained Hilbert spaces. Finally, the relation between local and global temperature is analyzed as a function of the size of the blocks and the system parameters.Comment: 10 pages, 10 figures. New fidelity measure with similar result

Brote de dermatofilosis en bovinos del altiplano de Jujuy, Argentina

Se describe un brote de dermatofilosis (Dermatophilus congolensis) en bovinos de la puna de Jujuy. El cuadro se presentó en un rodeo bovino criollo nativo, durante la estación lluviosa en el verano climático de la región. Los animales afectados presentaron dermatitis exudativa proliferativa no pruriginosa con formación de costras, afectando el espacio interdigital de los cuatro miembros, y en forma severa y localmente extensiva en los miembros posteriores y el interior de las fosas nasales. El diagnóstico se realizó en base a la presentación clínica, la identificación del agente causal en frotis obtenido del material dérmico, y las características epidemiológicas, considerando que los factores climáticos y las condiciones de manejo favorecieron la presentación de la enfermeda

A methodology for the structural and functional analysis of signaling and regulatory networks

BACKGROUND: Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks. RESULTS: We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the dynamic behavior. We have implemented these methods in our software tool CellNetAnalyzer (successor of FluxAnalyzer) and illustrate their applicability using a logical model of T-Cell receptor signaling providing non-intuitive results regarding feedback loops, essential elements, and (logical) signal processing upon different stimuli. CONCLUSION: The methods and formalisms we propose herein are another step towards the comprehensive functional analysis of cellular interaction networks. Their potential, shown on a realistic T-cell signaling model, makes them a promising tool

Assessment of agglomerated corks and PVC foams cores crashworthiness under multiple-impact events in different loading conditions

Thanks to the unique flexural properties, sandwich composites are considered as irreplaceable structures in many industrial fields, but their susceptibility to impact events is still a considerable drawback that undermines their structural integrity determining a reduction of their load-bearing capabilities. Considering that the core material plays the major role to distance the skins, the knowledge of its multiple-impacts response becomes a key design parameter in order to ensure a long-term stability to the structure. In view of this, the present work addresses the multiple-impacts behavior in dynamic compression and puncture impact conditions of bio-based agglomerated cork cores taking into account the effect of density and providing a meaningful comparison with more traditional petroleum-based foams. Despite the inherently higher mechanical properties of the PVC (polyvinyl chloride) foams, agglomerated cork demonstrated to provide a higher dimensional stability to the structure after repeated impacts thanks to its unique microstructure. With a reduction lower than 25% of its initial height after 10 impacts, agglomerated cork NL25 proved to be an exceptional alternative to the common HP130 foam, which undergoes a halving of its initial height after only 3 impacts, to obtain a more eco-friendly and performing sandwich composite

Bulging brains

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.Brain swelling is a serious condition associated with an accumulation of fluid inside the brain that can be caused by trauma, stroke, infection, or tumors. It increases the pressure inside the skull and reduces blood and oxygen supply. To relieve the intracranial pressure, neurosurgeons remove part of the skull and allow the swollen brain to bulge outward, a procedure known as decompressive craniectomy. Decompressive craniectomy has been preformed for more than a century; yet, its effects on the swollen brain remain poorly understood. Here we characterize the deformation, strain, and stretch in bulging brains using the nonlinear field theories of mechanics. Our study shows that even small swelling volumes of 28 to 56 ml induce maximum principal strains in excess of 30 %. For radially outward-pointing axons, we observe maximal normal stretches of 1.3 deep inside the bulge and maximal tangential stretches of 1.3 around the craniectomy edge. While the stretch magnitude varies with opening site and swelling region, our study suggests that the locations of maximum stretch are universally shared amongst all bulging brains. Our model has the potential to inform neurosurgeons and rationalize the shape and position of the skull opening, with the ultimate goal to reduce brain damage and improve the structural and functional outcomes of decompressive craniectomy in trauma patients.We thank Allan L. Reiss and his group for providing the MRI scans. This work was supported by the Timoshenko Scholar Award to Alain Goriely and by the Humboldt Research Award and the National Institutes of Health grant U01 HL119578 to Ellen Kuhl

A cost-effective chemical approach to retaining and regenerating the strength of thermally recycled glass fibre

The purpose of this research study was to investigate the efficacy of alkaline treatments on restoring mechanical strength of thermally damaged glass fibres for potential reuse as reinforcement material. Here, E-glass fibres were heat treated in a furnace at 450 °C for 25 minutes in order to simulate the harsh thermal conditions required for the recycling of glass fibre thermosetting composites. Following heat conditioning, fibres were treated with three different alkaline solutions: sodium hydroxide (NaOH), potassium hydroxide (KOH) and lithium hydroxide (LiOH). Results showed little effect of LiOH solution, however both NaOH and KOH were proved to be successful in regenerating strength of fibres heat treated at 450 °C. It is believed these alkaline treatments might improve fibre strength by etching away surface defects. Factors such as concentration of alkali and treatment time were investigated in order to find optimum conditions for strength regeneration

Phantom membrane microfluidic cross-flow filtration device for the direct optical detection of water pollutants

The diffusion of autonomous sensing platforms capable of a remote large-scale surveillance of environmental water basins is currently limited by the cost and complexity of standard analytical methods. In order to create a new generation of water analysis systems suitable for continuous monitoring of a large number of sites, novel technical solutions for fluid handling and detection are needed. Here we present a microfluidic device hosting a perfluorinated microporous membrane with refractive index similar to that of water, which enables the combination of filtration and label-free sensing of adsorbing substances, mainly pollutants, in environmental water samples. The cross-flow design of the microfluidic device avoids the clogging of the membrane due to particulate, whereas molecules with some hydrophobic moiety contained in the crossing flow are partially retained and their adhesion on the inner surface of the membrane yields an increase of light scattering intensity, which can be easily measured using a simple instrument based on Light Emitting Diode illumination. By cycling sample water and pure water as a reference, we demonstrate the detection of 0.5 \uce\ubcM of a model cationic surfactant and regeneration of the sensing surface. The optical response of the membrane sensor was characterized using a simple theoretical model that enables to quantify the concentration of target molecules from the amplitude and kinetics of the measured binding curves. The device was tested with real water samples containing large amount of environmental particles, without showing clogging of the membrane, and enabling nonspecific quantification of adsorbing substances in a few minutes