Hybrid and optical packet switching supporting different service classes in data center network

Photonic Network Communications - Optical packet switching is a prominent technology proposing not only a reduction in the energy consumption by the elimination of numerous...     

Study of the synergistic effect of boron nitride and carbon nanotubes in the improvement of thermal conductivity of epoxy composites

The enhancement of the thermal conductivity, keeping the electrical insulation, of epoxy thermosets through the addition of pristine and oxidized carbon nanotubes (CNTs) and microplatelets of boron nitride (BN) was studied. Two different epoxy resins were selected: a cycloaliphatic (ECC) epoxy resin and a glycidylic (DGEBA) epoxy resin. The characteristics of the composites prepared were evaluated and compared in terms of thermal, thermomechanical, rheological and electrical properties. Two different dispersion methods were used in the addition of pristine and oxidized CNTs depending on the type of epoxy resin used. Slight changes in the kinetics of the curing reaction were observed in the presence of the fillers. The addition of pristine CNTs led to a greater enhancement of the mechanical properties of the ECC composite whereas the oxidized CNTs presented a greater effect in the DGEBA matrix. The addition of CNTs alone led to a marked decrease of the electrical resistivity of the composites. Nevertheless, in the presence of BN, which is an electrically insulating material, it was possible to increase the proportion of pristine CNTs to 0.25 wt% in the formulation without deterioration of the electrical resistivity. A small but significant synergic effect was determined when both fillers were added together. Improvements of about 750% and 400% in thermal conductivity were obtained in comparison to the neat epoxy matrix for the ECC and DGEBA composites, respectively. © 2019 Society of Chemical Industry     

Milk from cows fed a diet with a high forage:concentrate ratio improves inflammatory state,oxidative stress,and mitochondrial function in rats

Excessive energy intake may evoke complex biochemical processes characterized by inflammation, oxidative stress, and impairment of mitochondrial function that represent the main factors underlying noncommunicable diseases. Because cow milk is widely used for human nutrition and in food industry processing, the nutritional quality of milk is of special interest with respect to human health. In our study, we analyzed milk produced by dairy cows fed a diet characterized by a high forage:concentrate ratio (high forage milk, HFM). In view of the low n-6:n-3 ratio and high content of conjugated linoleic acid of HFM, we studied the effects of this milk on lipid metabolism, inflammation, mitochondrial function, and oxidative stress in a rat model. To this end, we supplemented for 4 wk the diet of male Wistar rats with HFM and with an isocaloric amount (82 kJ, 22 mL/d) of milk obtained from cows fed a diet with low forage:concentrate ratio, and analyzed the metabolic parameters of the animals. Our results indicate that HFM may positively affect lipid metabolism, leptin:adiponectin ratio, inflammation, mitochondrial function, and oxidative stress, providing the first evidence of the beneficial effects of HFM on rat metabolism.     

Passive target detection and tracking from electromagnetic field measurements

This paper presents a novel approach to the localization of moving targets in a complex environment based on the measurement of the perturbations induced by the target presence on an independently‐generated time‐varying electromagnetic field. Field perturbations are measured via a set of sensors deployed over the domain of interest and used to detect and track a possible target by resorting to a particle Bernoulli filter (PBF). To comply with real‐time operation, the PBF works along with an artificial neural network (ANN) model of the environment trained offline via finite elements (FEs). The performance of the proposed algorithm is assessed via simulation experiments.     

A Lattice Approach to Image Segmentation

After a formal definition of segmentation as the largest partition of the space according to a criterion σ and a function f, the notion of a morphological connection is reminded. It is used as an input to a central theorem of the paper (Theorem 8), that identifies segmentation with the connections that are based on connective criteria. Just as connections, the segmentations can then be regrouped by suprema and infima. The generality of the theorem makes it valid for functions from any space to any other one. Two propositions make precise the AND and OR combinations of connective criteria. The soundness of the approach is demonstrated by listing a series of segmentation techniques. One considers first the cases when the segmentation under study does not involve initial seeds. Various modes of regularity are discussed, which all derive from Lipschitz functions. A second category of examples involves the presence of seeds around which the partition of the space is organized. An overall proposition shows that these examples are a matter for the central theorem. Watershed and jump connection based segmentations illustrate this type of situation. The third and last category of examples deals with cases when the segmentation occurs in an indirect space, such as an histogram, and is then projected back on the actual space under study. The relationships between filtering and segmentation are then investigated. A theoretical chapter introduces and studies the two notions of a pulse opening and of a connected operator. The conditions under which a family of pulse openings can yield a connected filter are clarified. The ability of segmentations to generate pyramids, or hierarchies, is analyzed. A distinction is made between weak hierarchies where the partitions increase when going up in the pyramid, and the strong hierarchies where the various levels are structured as semi-groups, and particularly as granulometric semi-groups. The last section is based on one example, and goes back over the controversy about “lattice” versus “functional” optimization. The problem is now tackled via a case of colour segmentation, where the saturation serves as a cursor between luminance and hue. The emphasis is put on the difficulty of grouping the various necessary optimizations into a single one.     

Computation of mutual entropy in quantum markov chains

There are several damping phenomena in quantum optics. Such phenomena have been usually explained by open systems. In statistical physics, open system dynamics have been used to study the irreversibility and the approach to equilibrium. In this paper, the dynamical change of the mutual entropy for an open system, frequently studied in the quantum optics literature, is rigorously computed through a model of quantum Markov chain. In particular, the concrete formula of Stinespring expression for such a model is obtained and applied to the derivation of the mutual entropy, and some computational results are presented.     

Biodegradable hollow microfibres to produce bioactive scaffolds

Biodegradable hollow microfibres containing particles loaded with specific active agents can be potentially employed to produce a special kind of substrate for tissue engineering, able to function as a scaffold and at the same time to act as a drug‐releasing system. Biodegradable hollow microfibres based on poly(lactic acid) were produced by a dry–wet spinning procedure. Drug‐loaded microparticles were prepared by a simple oil‐in‐water emulsion and entrapped inside the fibres. The morphology of both fibres and particles was investigated by scanning electron microscopy. The mechanical and thermal properties of the fibres were investigated by tensile tests and differential scanning calorimetry. In vitro tests were performed to evaluate the release of the drug from the fibres loaded with the particles Copyright © 2004 Society of Chemical Industry