Modeling sleep mode gains in energy-aware networks

Nowadays two main approaches are being pursued to reduce energy consumption of networks: the use of sleep modes in which devices enter a low-power state during inactivity periods, and the adoption of energy proportional mechanisms where the device architecture is designed to make energy consumption proportional to the actual load. Common to all the proposals is the evaluation of energy saving performance by means of simulation or experimental evidence, which typically consider a limited set of benchmarking scenarios.     

Ultraviolet B (UVB) Irradiation-Induced Apoptosis in Various Cell Lineages in Vitro

Ultraviolet B (UVB) radiation acts as a strong apoptotic trigger in many cell types, in tumor and normal cells. Several studies have demonstrated that UVB-induced cell death occurs through the generation of reactive oxygen species. The consequent oxidative stress includes the impairment of cellular antioxidants, the induction of DNA damage and the occurrence of apoptosis. In this review, we investigated UVB apoptotic action in various cell models by using ultrastructural, molecular and cytofluorimetric techniques. Myeloid leukemia HL-60, T-lymphoblastoid Molt-4 and myelomonocytic U937 human cells, generally affected by apoptotic stimuli, were studied. Human chondrocytes and C2C12 skeletal muscle cells, known to be more resistant to damage, were also considered. All of them, when exposed to UVB radiation, revealed a number of characteristic apoptotic markers. Membrane blebbing, cytoplasm shrinkage and chromatin condensation were detected by means of electron microscopy. DNA cleavage, investigated by using agarose gel electrophoresis and TUNEL reaction, was observed in suspended cells. Differently, in chondrocytes and in skeletal muscle cells, oligonucleosomic DNA fragmentation did not appear, even if a certain TUNEL positivity was detected. These findings demonstrate that UVB radiation appears to be an ideal tool to study the apoptotic behavior.     

Semantics-driven best view of 3D shapes

The problem of automatically selecting the pose of a 3D object that corresponds to the most informative and intuitive view of the shape is known as the best view problem. In this paper we address the selection of the best view driven by the meaningful features of the shape, in order to maximize the visibility of salient components from the context or from the application point of view. Meaningful features can be automatically detected by means of semantic-oriented segmentations: we tested several approaches with very pleasant results in the automatic generation of thumbnails for large 3D model databases.     

Optimization of the working cycle for a hydrogen production and power generation plant based on aluminum combustion with water

The working cycle of a novel hydrogen and power generation system based on aluminum combustion with water is analyzed in order to evaluate the best performance in terms of energy conversion efficiency. The system exploits the exothermic reaction between aluminum and steam and produces thermal power for a super-heated steam cycle and hydrogen as a by-product of the reaction.     

Effects of loud noise exposure on mouse myocardium: a comparison with the rat

Loud noise is an environmental stressor of everyday life, which affects different organs and apparati, in particular the cardiovascular system. We have already reported that noise exposure produces significant alterations in the rat myocardium, consisting of mitochondrial damage, which is evident as lysis of the cristae and dilution of the matrix. Since there are high similarities between mouse and human species, the aim of our study was to investigate the effects of acute noise exposure on the mouse heart. We found that noise exposure affects mouse myocardium at similar subcellular sites to those already described in the rat; nonetheless, quantitative analysis of the percentage of altered mitochondria in both species disclosed a clear difference between mouse and rat myocardium, which strongly suggests a different sensitivity to noise stimulus. We hypothesize that the species differences on the extent of myocardial alterations here observed might be due to the zonal pattern of cardiac noradrenergic receptors, which should be the final effectors for noise-induced myocardial changes.     

Hierarchical mesh segmentation based on fitting primitives

In this paper, we describe a hierarchical face clustering algorithm for triangle meshes based on fitting primitives belonging to an arbitrary set. The method proposed is completely automatic, and generates a binary tree of clusters, each of which is fitted by one of the primitives employed. Initially, each triangle represents a single cluster; at every iteration, all the pairs of adjacent clusters are considered, and the one that can be better approximated by one of the primitives forms a new single cluster. The approximation error is evaluated using the same metric for all the primitives, so that it makes sense to choose which is the most suitable primitive to approximate the set of triangles in a cluster. Based on this approach, we have implemented a prototype that uses planes, spheres and cylinders, and have experimented that for meshes made of 100 K faces, the whole binary tree of clusters can be built in about 8 s on a standard PC. The framework described here has natural application in reverse engineering processes, but it has also been tested for surface denoising, feature recovery and character skinning.     

Globally convergent autocalibration using interval analysis

We address the problem of autocalibration of a moving camera with unknown constant intrinsic parameters. Existing autocalibration techniques use numerical optimization algorithms whose convergence to the correct result cannot be guaranteed, in general. To address this problem, we have developed a method where an interval branch-and-bound method is employed for numerical minimization. Thanks to the properties of interval analysis this method converges to the global solution with mathematical certainty and arbitrary accuracy and the only input information it requires from the user are a set of point correspondences and a search interval. The cost function is based on the Huang-Faugeras constraint of the essential matrix. A recently proposed interval extension based on Bernstein polynomial forms has been investigated to speed up the search for the solution. Finally, experimental results are presented.     

Parametric and semi-parametric approaches in the analysis of short-term effects of air pollution on health

Generalized additive models (GAMs) have become the standard tool for the analysis of short-term effects of air pollution on human health. Usually, the confounding effect of seasonality and long-term trend is described by flexible parametric or non-parametric functions of calendar time. Two different modeling strategies, i.e. GAM with penalized regression splines and GAM with regression splines, were compared by means of a simulation study, addressing attention to the inference on air pollutant effect. Simulation results indicated that GAM with regression splines provides negligibly biased estimates of air pollutant effect and it is robust to misspecification of the degrees of freedom of the spline. GAM with penalized regression splines requires a certain amount of undersmoothing in order to reduce the bias of the estimates and to improve the coverage of confidence intervals. These findings agree with asymptotic results developed in the context of partially splined models.