Novel decentralized adaptive strategies for the synchronization of complex networks

This paper is concerned with the analysis of the synchronization of networks of nonlinear oscillators through an innovative local adaptive approach. In particular, time-varying feedback coupling gains are considered, whose gradient is a function of the local synchronization error over each edge in the network. It is shown that, under appropriate conditions, the strategy is indeed successful in guaranteeing the achievement of a common synchronous evolution for all oscillators in the network. The theoretical derivation is complemented by its validation on a set of representative examples.     

Morphogenetic approach to system identification

In this paper, we propose a novel approach to system identification based on morphogenetic theory (MT). Given a context H defined by a set of M objects, each described by a set of N attributes, and a vector X of desired outputs for each object, MT combines notions from formal concept analysis and tensor calculus so as to generate a morphogenetic system (MS). The MS is defined by a set of weights s¹, …, s^N, one for each attribute. Given H and X, weights are computed so as to generate the projection Y of X on the space of the attributes with the minimum distance between Y and X. An MS can be represented as a neuron, morphogenetic neuron, with a number of synapses equal to the number of attributes and synaptic weights equal to s¹, …, s^N. Unlike traditional neural network paradigm, which adopts an iterative process to determine synaptic weights, in MT, weights are computed at once. We introduce a method to generate a morphogenetic neural network (MNN) for identification problems. The method is based on extending appropriately and iteratively the attribute space so as to reduce the error between desired output and computed output. By using four well‐known datasets, we show that an MNN can identify an unknown system with a precision comparable with classical multilayer perceptron with complexity similar to the MNN but reducing drastically the time needed to generate the neural network. Furthermore, the structure of the MNN is generated automatically by the method and does not require a trial‐and‐error approach often applied in classical neural networks. © 2009 Wiley Periodicals, Inc.     

Strength of hierarchical materials

Many biological materials exhibit a hierarchical structure over more than one length scale. Understanding how hierarchy affects their mechanical properties emerges as a primary concern, since it can guide the synthesis of new materials to be tailored for specific applications. In this paper the strength and stiffness of hierarchical materials are investigated by means of a fractal approach. A new model is proposed, based both on geometric and material considerations and involving simple recursive formulas.     

3D scanning of cultural heritage with consumer depth cameras

Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate.     

Phosphazene-bound Rose Bengal: A novel photosensitizer for singlet oxygen generation

In this paper we report the synthesis and the characterization of cyclo- and polyphosphazenes supporting Rose Bengal. These substrates are suitable for the photosensitized generation of singlet oxygen, both in homogeneous and in heterogeneous phase. The efficiency of¹O₂ production has been measured in homogeneous solution using, as photosensitizer, the cyclophosphazene-bound Rose Bengal and considering, as testing reaction, the oxidation of 1,3-diphenylisobenzofuran; it was found comparable to that of free Rose Bengal in the same experimental conditions.Presented in part at the Nato Workshop on Inorganic and Organometallic Polymers with Special Properties, Cap D'Agde, France, September 10–14, 1990.     

In situ spectroelectrochemical measurements during the electro-oxidation of ethanol on WC-supported Pt-black, based on sum-frequency generation spectroscopy

In this paper we report in situ sum-frequency generation (SFG) spectroscopy experiments, carried out during the electro-oxidation of ethanol on Pt-black supported on tungsten carbide (WC). Well-defined SFG resonances were measured in the 1320-1350 cm⁻¹ spectral range with the VIS beam set at 523.5 nm. The assignment of SFG bands was carried out with the aid of vibrational spectra calculated in the framework of Density Functional Theory (DFT). The spectra recorded in situ showed various kinds of changes in terms of spectral patterns and peak intensities, as a function of the applied potential and of the oxidation time, yielding information on the modification of the catalyst-adsorbate structure. To the best of the authors’ knowledge, this is the first in situ electrochemical SFG work carried out in this particular wavelength range - specially diagnostic for electrocatalysis and made accessible by use of the CLIO IR free-electron laser - and with an electrode functionalised with a real catalyst, in powder form.     

Brown rot fungal early stage decay mechanism as a biological pretreatment for softwood biomass in biofuel production

A current barrier to the large-scale production of lignocellulosic biofuels is the cost associated with the energy and chemical inputs required for feedstock pretreatment and hydrolysis. The use of controlled partial biological degradation to replace elements of the current pretreatment technologies would offer tangible energy and cost benefits to the whole biofuel process. It has been known for some time from studies of wood decay that, in the early stages of growth in wood, brown rot fungi utilise a mechanism that causes rapid and extensive depolymerisation of the carbohydrate polymers of the wood cell wall. The brown rot hyphae act as delivery vectors to the plant cell wall for what is thought to be a combination of a localised acid pretreatment and a hydroxyl radical based depolymerisation of the cell wall carbohydrate polymers. It is this quality that we have exploited in the present work to enhance the saccharification potential of softwood forest residues for biofuel production. Here we show that after restricted exposure of pine sapwood to brown rot fungi, glucose yields following enzymatic saccharification are significantly increased. Our results demonstrate the potential of using brown rot fungi as a biological pretreatment for biofuel production.     

Verbal learning strategies in Parkinson's disease.

Word-list learning was studied in patients with Parkinson's disease (PD) and normal control (NC) participants by means of the selective-reminding procedure of H. Buschke and P. A. Fuld (1974) in 3 learning conditions using semantically unrelated items; semantically related items, whose implicit categorical structure had to be spontaneously guessed; and semantically related items, whose explicit categorical structure was known in advance. The PD patients displayed poor learning in all 3 conditions. To identify the functional locus of the PD patients' deficits, the authors performed a stochastic Markov chain analysis, which allowed individual measurements of encoding, retrieval, and category clustering abilities. PD patients were never significantly impaired in encoding word engrams; their impairment was confined to automatic and intentional retrieval and to the ability to benefit from explicit semantic clues. (PsycINFO Database Record (c) 2010 APA, all rights reserved)