Damage detection in beams by using artificial neural networks and dynamical parameters

In this paper is presented a multilayer perceptron neural network combined with the Nelder-Mead Simplex method to detect damage in multiple support beams. The input parameters are based on natural frequencies and modal flexibility. It was considered that only a number of modes were available and that only vertical degrees of freedom were measured. The reliability of the proposed methodology is assessed from the generation of random damages scenarios and the definition of three types of errors, which can be found during the damage identification process. Results show that the methodology can reliably determine the damage scenarios. However, its application to large beams may be limited by the high computational cost of training the neural network.

Long-Term Stability at High Temperatures for Birefringence in PAZO/PAH Layer-by-Layer Films

Optical memories with long-term stability at high temperatures have long been pursued in azopolymers with photoinduced birefringence. In this study, we show that the residual birefringence in layer-by-layer (LbL) films made with poly[1-[4-(3-carboxy-4 hydroxyphenylazo)benzene sulfonamido]-1,2-ethanediyl, sodium salt] (PAZO) alternated with poly(allylamine hydrochloride) (PAH) can be tuned by varying the extent of electrostatic interactions with film fabrication at different pHs for PAH. The dynamics of both writing and relaxation processes could be explained with a two-stage mechanism involving the orientation of the chromophores per se and the chain movement. Upon calculating the activation energies for these processes, we demonstrate semiquantitatively that reduced electrostatic interactions in films prepared at higher pH, for which PAH is less charged, are responsible for the longer stability at high temperatures. This is attributed to orientation of PAZO chromophores via cooperative aggregation, where the presence of counterions hindered relaxation.

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Enhancing weak signal transmission through a feedforward network

The ability to transmit and amplify weak signals is fundamental to signal processing of artificial devices in engineering. Using a multilayer feedforward network of coupled double-well oscillators as well as Fitzhugh-Nagumo oscillators, we here investigate the conditions under which a weak signal received by the first layer can be transmitted through the network with or without amplitude attenuation. We find that the coupling strength and the nodes' states of the first layer act as two-state switches, which determine whether the transmission is significantly enhanced or exponentially decreased. We hope this finding is useful for designing artificial signal amplifiers.

Tailoring Molecular Architectures with Cobalt Tetrasulfonated Phthalocyanine: Immobilization in Layer-by-Layer Films and Sensing Applications

In the field of organic thin films, manipulation at the nanoscale can be obtained by immobilization of different materials on platforms designed to enhance a specific property via the layer-by-layer technique. In this paper we describe the fabrication of nanostructured films containing cobalt tetrasulfonated phthalocyanine (CoTsPc) obtained through the layer-by-layer architecture and assembled with linear poly(allylamine hydrochloride) (PAH) and poly(amidoamine) dendrimer (PAMAM) polyelectrolytes. Film growth was monitored by UV-vis spectroscopy following the Q band of CoTsPc and revealed a linear growth for both systems. Fourier transform infrared (FTIR) spectroscopy showed that the driving force keeping the structure of the films was achieved upon interactions of CoTsPc sulfonic groups with protonated amine groups present in the positive polyelectrolyte. A comprehensive SPR investigation on film growth reproduced the deposition process dynamically and provided an estimation of the thicknesses of the layers. Both FTIR and SPR techniques suggested a preferential orientation of the Pc ring parallel to the substrate. The electrical conductivity of the PAH films deposited on interdigitated electrodes was found to be very sensitive to water vapor. These results point to the development of a phthalocyanine-based humidity sensor obtained from a simple thin film deposition technique, whose ability to tailor molecular organization was crucial to achieve high sensitivity.

Valence band tail states in disordered superlattices embedded in wide parabolic AlGaAs well

Optical properties of intentionally disordered multiple quantum well (QW) system embedded in a wide AlGaAs parabolic well were investigated by photoluminescence (PL) measurements as functions of the laser excitation power and the temperature. The characterization of the carriers localized in the individual wells was allowed due to the artificial disorder that caused spectral separation of the photoluminescence lines emitted by different wells. We observed that the photoluminescence peak intensity from each quantum well shifted to high energy as the excitation power was increased. This blue-shift is associated with the filling of localized states in the valence band tail. We also found that the dependence of the peak intensity on the temperature is very sensitive to the excitation power. The temperature dependence of the photoluminescence peak energy from each QW was well fitted using a model that takes into account the thermal redistribution of the localized carriers. Our results demonstrate that the band tails in the studied structures are caused by alloy potential fluctuations and the band tail states dominate the emission from the peripheral wells. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4730769]

Structural aspects of polyanion and hydrophobically modified polycation multilayers on hydrophilic or hydrophobic surfaces

Multilayer films of carboxymethylcellulose (CMC), a polyanion, and bromide salts of poly(4-vinylpyridine) quaternized with linear aliphatic chains of 2 (ethyl) and 5 (pentyl) carbon atoms, coded as QPVP-C2 and QPVP-C5, respectively, were fabricated by layer-by-layer (LbL) self-assembly onto Si/SiO2 wafers (hydrophilic substrate) or polystyrene, PS, films (hydrophobic substrate). The films were characterized by means of ex situ and in situ ellipsometry, atomic force microscopy (AFM), contact angle measurements and sum frequency generation vibrational spectroscopy (SFG). Antimicrobial tests were used to assess the exposure of pyridinium moieties to the aqueous medium. In situ ellipsometry indicated that for Si/SiO2 the chains were more expanded than the PS films and both substrates systems composed of QPVP-C5 were thicker than those with QPVP-C2. For dried layers, the alkyl side group size had a small effect on the thickness evolution, regardless of the substrate. At pH 2 the multilayers showed high resistance, evidencing that the build-up is driven not only by cooperative polymer-polymer ion pairing, but also by hydrophobic interactions between the alkyl side chains. The LbL films became irregular as the number of depositions increased. After the last deposition, the wettability of QPVP-C2 or QPVP-C5 terminated systems on the Si/SiO2 wafers and PS films were similar, except for QPVP-C2 on Si/SiO2 wafers. Unlike the morphology observed for LbL films on Si/SiO2 wafers, PS induced the formation of porous structures. SFG showed that in air the molecular orientation of pyridinium groups in multilayers with QPVP-C5 was stronger than in those containing QPVP-C2. The exposure of pyridinium moieties to the aqueous medium was more pronounced when the LbL were assembled on Si/SiO2 wafers.

Emergence of sensory selection mechanisms in Artificial Life simulations

Background The evolutionary advantages of selective attention are unclear. Since the study of selective attention began, it has been suggested that the nervous system only processes the most relevant stimuli because of its limited capacity [1]. An alternative proposal is that action planning requires the inhibition of irrelevant stimuli, which forces the nervous system to limit its processing [2]. An evolutionary approach might provide additional clues to clarify the role of selective attention. Methods We developed Artificial Life simulations wherein animals were repeatedly presented two objects, "left" and "right", each of which could be "food" or "non-food." The animals' neural networks (multilayer perceptrons) had two input nodes, one for each object, and two output nodes to determine if the animal ate each of the objects. The neural networks also had a variable number of hidden nodes, which determined whether or not it had enough capacity to process both stimuli (Table 1). The evolutionary relevance of the left and the right food objects could also vary depending on how much the animal's fitness was increased when ingesting them (Table 1). We compared sensory processing in animals with or without limited capacity, which evolved in simulations in which the objects had the same or different relevances. Table 1. Nine sets of simulations were performed, varying the values of food objects and the number of hidden nodes in the neural networks. The values of left and right food were swapped during the second half of the simulations. Non-food objects were always worth -3. The evolution of neural networks was simulated by a simple genetic algorithm. Fitness was a function of the number of food and non-food objects each animal ate and the chromosomes determined the node biases and synaptic weights. During each simulation, 10 populations of 20 individuals each evolved in parallel for 20,000 generations, then the relevance of food objects was swapped and the simulation was run again for another 20,000 generations. The neural networks were evaluated by their ability to identify the two objects correctly. The detectability (d') for the left and the right objects was calculated using Signal Detection Theory [3]. Results and conclusion When both stimuli were equally relevant, networks with two hidden nodes only processed one stimulus and ignored the other. With four or eight hidden nodes, they could correctly identify both stimuli. When the stimuli had different relevances, the d' for the most relevant stimulus was higher than the d' for the least relevant stimulus, even when the networks had four or eight hidden nodes. We conclude that selection mechanisms arose in our simulations depending not only on the size of the neuron networks but also on the stimuli's relevance for action.

Determination of degree of ionization of poly(allylamine hydrochloride) (PAH) and poly[1-[4-(3-carboxy‑4 hydroxyphenylazo)benzene sulfonamido]-1,2-ethanediyl, sodium salt] (PAZO) in layer-by-layer films using vacuum photoabsorption spectroscopy

Electrostatic and hydrophobic interactions govern most of the properties of supramolecular systems, which is the reason determining the degree of ionization of macromolecules has become crucial for many applications. In this paper, we show that highresolution ultraviolet spectroscopy (VUV) can be used to determine the degree of ionization and its effect on the electronic excitation energies of layer-by-layer (LbL) films of poly(allylamine hydrochloride) (PAH) and poly[1-[4-(3-carboxy-4 hydroxyphenylazo)- benzene sulfonamido]-1,2-ethanediyl, sodium salt] (PAZO). A full assignment of the VUV peaks of these polyelectrolytes in solution and in cast or LbL films could be made, with their pH dependence allowing us to determine the p'K IND. a' using the Henderson-Hasselbach equation. The p'K IND. a' for PAZO increased from ca. 6 in solution to ca. 7.3 in LbL films owing to the charge transfer from PAH. Significantly, even using solutions at a fixed pH for PAH, the amount adsorbed on the LbL films still varied with the pH of the PAZO solutions due to these molecular-level interactions. Therefore, the procedure based on a comparison of VUV spectra from solutions and films obtained under distinct conditions is useful to determine the degree of dissociation of macromolecules, in addition to permitting interrogation of interface effects in multilayer films.

Shallow and deep deformation in northern Apennines region using seismological data

For its particular position and the complex geological history, the Northern Apennines has been considered as a natural laboratory to apply several kinds of investigations. By the way, it is complicated to joint all the knowledge about the Northern Apennines in a unique picture that explains the structural and geological emplacement that produced it. The main goal of this thesis is to put together all information on the deformation - in the crust and at depth - of this region and to describe a geodynamical model that takes account of it. To do so, we have analyzed the pattern of deformation in the crust and in the mantle. In both cases the deformation has been studied using always information recovered from earthquakes, although using different techniques. In particular the shallower deformation has been studied using seismic moment tensors information. For our purpose we used the methods described in Arvidsson and Ekstrom (1998) that allowing the use in the inversion of surface waves [and not only of the body waves as the Centroid Moment Tensor (Dziewonski et al., 1981) one] allow to determine seismic source parameters for earthquakes with magnitude as small as 4.0. We applied this tool in the Northern Apennines and through this activity we have built up the Italian CMT dataset (Pondrelli et al., 2006) and the pattern of seismic deformation using the Kostrov (1974) method on a regular grid of 0.25 degree cells. We obtained a map of lateral variations of the pattern of seismic deformation on different layers of depth, taking into account the fact that shallow earthquakes (within 15 km of depth) in the region occur everywhere while most of events with a deeper hypocenter (15-40 km) occur only in the outer part of the belt, on the Adriatic side. For the analysis of the deep deformation, i.e. that occurred in the mantle, we used the anisotropy information characterizing the structure below the Northern Apennines. The anisotropy is an earth properties that in the crust is due to the presence of aligned fluid filled cracks or alternating isotropic layers with different elastic properties while in the mantle the most important cause of seismic anisotropy is the lattice preferred orientation (LPO) of the mantle minerals as the olivine. This last is a highly anisotropic mineral and tends to align its fast crystallographic axes (a-axis) parallel to the astenospheric flow as a response to finite strain induced by geodynamic processes. The seismic anisotropy pattern of a region is measured utilizing the shear wave splitting phenomenon (that is the seismological analogue to optical birefringence). Here, to do so, we apply on teleseismic earthquakes recorded on stations located in the study region, the Sileny and Plomerova (1996) approach. The results are analyzed on the basis of their lateral and vertical variations to better define the earth structure beneath Northern Apennines. We find different anisotropic domains, a Tuscany and an Adria one, with a pattern of seismic anisotropy which laterally varies in a similar way respect to the seismic deformation. Moreover, beneath the Adriatic region the distribution of the splitting parameters is so complex to request an appropriate analysis. Therefore we applied on our data the code of Menke and Levin (2003) which allows to look for different models of structures with multilayer anisotropy. We obtained that the structure beneath the Po Plain is probably even more complicated than expected. On the basis of the results obtained for this thesis, added with those from previous works, we suggest that slab roll-back, which created the Apennines and opened the Tyrrhenian Sea, evolved in the north boundary of Northern Apennines in a different way from its southern part. In particular, the trench retreat developed primarily south of our study region, with an eastward roll-back. In the northern portion of the orogen, after a first stage during which the retreat was perpendicular to the trench, it became oblique with respect to the structure.

Caratterizzazione di membrane da nanofiltrazione

Nanofiltration (NF) is a pressure-driven membrane process, intermediate between reverse osmosis and ultrafiltration. Commercially available polymeric membranes have been used in a wide range of applications, such as drinking, process industry and waste water treatment. For all the applications requiring high stability and harsh washing procedures inorganic membranes are preferred due to their high chemical inertia. Typically, γ – Al2O3 as well as TiO2 and ZrO2 selective layers are used; the latter show higher chemical stability in a wide range of pH and temperatures. In this work the experimental characterization of two different type of membrane has been performed in order to investigate permeation properties, separation performance and efficiency with aqueous solutions containing strong inorganic electrolytes. The influence of salt concentration and feed pH as well as the role of concentration polarization and electrolyte type on the membrane behavior are investigated. Experimentation was performed testing a multi–layer structured NF membrane in α-Al2O3, TiO2 and ZrO2, and a polymeric membrane, in polyamide supported on polysulfone, with binary aqueous solutions containing NaCl, Na2SO4 or CaCl2; the effect of salt composition and pH in the feed side was studied both on flux and salt rejection. All the NF experimental data available for the two membranes were used to evaluate the volumetric membrane charge (X) corresponding to each operative conditions investigated, through the Donnan Steric Pore Model and Dielectric Exclusion (DSPM&DE). The results obtained allow to understand which are the main phenomena at the basis of the different behaviors observed.

Flüssigkristalline Ionomere zum Aufbau von Multischichtstrukturen

Die vorliegende Arbeit beschäftigt sich mit der Synthese und Charakterisierung von nematischen und smektischen LC-Polyestern, die mit ionischen Gruppen funktionalisiert wurden. Als ionische Gruppen wurden Phosphonsäure-salze und Phosphonium- oder Ammoniumgruppen verwendet. Je nach Polymerrückgrat erhält man LC-Ionomere, bei denen die ionischen Gruppen entweder an das Mesogen oder an den Hauptkettenspacer gebunden sind. Diese LC-Ionomere können zusammen mit amorphen Polyelektrolyten oder anorganischen Schichtmineralien für den Multischichtaufbau durch alternierende Adsorption von Polykation und Polyanion aus der Lösung verwendet werden (Methode von G. Decher). Die Multischichtbildung konnte mittels UV-Spektroskopie, IR-Spektroskopie, Kontaktwinkel-Messungen, Röntgenreflexionsmessungen und Oberflächen Plasmonen-Spektroskopie verfolgt werden. Die Subschichten sind zwischen 25 und 55 Å dick und hängen z.B. von der Polarität des Lösungsmittels ab. Erste cis-trans Isomerisierungen und Photoorientierungs-Versuche wurden durchgeführt.

Betrachtung von chemischen Reaktionen und mesoskopischen Strukturen auf Oberflächen mittels spektroskopischer Photoelektronenmikroskopie

In dieser Arbeit wurden Untersuchungen mit verschiedenenMethoden derMikrospektroskopie unter Verwendung einesPhotoemissions-Elektronenmikroskops(PEEM) durchgeführt. Es wurde ein Energiefilterfür den Einsatzmit dem PEEM aufgebaut und getestet. Dieses Instrument wurdezusammen miteinem Multilayer-Monochromator am Synchrotron eingesetzt.Der Energiefilterwurde unter anderem für Photoelektronenspektroskopie anAu_xCs_1-xund Pb/Si-Schichten, sowie zur Charakterisierung desMonochromators eingesetzt.
Die Transmissionsfunktion eines abbildendenGegenfeldanalysators fürdas PEEM wurde berechnet und mit Messungen verglichen. InÜbereinstimmungmit der Berechnung zeigt sich ein charakteristischesasymmetrisches Profilder mit dem Analysator gemessenen Photoelektronenpeaks. Eswurde eine Verbesserungder Ortsauflösung durch energieselektive Abbildungnachgewiesen.
Mit dem PEEM wurde erstmals Mehr-Photonen Photoemissionzur Abbildungausgenutzt. Es wurde ein Verfahren gezeigt, mit dem sich dieOrdnung dernichtlinearen Photoemission aus zwei mit unterschiedlicherLaserleistungaufgenommenen Bildern lateral abbilden läßt. DiePolarisationsabhängigkeitder Photoemission von glatten Probenstellen läßtsich mit einercos⁴-Funktion anpassen, wie es fürZwei-Photonen Photoemissionzu erwarten ist. Alle Proben wiesen Zentren erhöhterPhotoemissionsintensitätauf, welche durch Anregung lokalisierter Plasmonen auf derOberflächean kleinen Partikeln entstehen. An diesen erstmalig sichtbargemachten'Hot Spots' zeigt sich eine charakteristischePolarisationsabhängigkeitder Photoemission mit bevorzugter Anregung vonPhotoelektronen bei s-polarisiertemLicht.