Influence of matrix composition on polymerization stress development of experimental composites

Objective. Stress development at the tooth/restoration interface is one of the most important reasons for failure of adhesive restorations. The aim of this study was to evaluate the influence of BisGMA/TEGDMA (B/T) and UDMA/TEGDMA (U/T) ratios on polymerization stress (PS) and on the variables related to its development: degree of conversion (DC), polymerization maximum rate (Rp(max)), volumetric shrinkage (VS), elastic modulus (E), stress relaxation (SR) and viscosity of experimental composites. Method. Composites were formulated containing B/T or U/T in mol% ratios of 2: 8, 3: 7, 4: 6, 5: 5, 6: 4, 7: 3 and 8: 2, and 15 wt% of fumed silica. PS was determined with a universal testing machine. VS was measured with a linometer. E and SR were obtained in three-point bending. DC and Rp(max) were determined by real time NIR spectroscopy and viscosity was measured in viscometer. Data were submitted to one-way ANOVA, Tukey test (alpha = 0.05%) and regression analyses. Results. PS, VS, E and DC decreased and viscosity and Rp(max) increased with base monomer content in both series. PS showed strong correlation with VS, DC and viscosity. PS, VS and DC were higher and viscosity was lower for UDMA-based materials. Significance. Reduced viscosity, kinetics parameters and molecular characteristics led UDMA-based composites to elevated conversion and relatively lower PS at lower TEGDMA contents, compared to B/T composites. (C) 2010 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Bi-directional reflectance of corals

An assessment of the bi-directional reflectance distribution function (BRDF) of corals with different morphologies was undertaken using hyperspectral reflectance measurements. The highest variance in reflectance obtained at different viewing angles was found for the open branching Acropora colony, possibly attributed to branch orientation and internal shadow distribution. Spectral separation within and between features at the nominated sensor-viewing angles was greatest in the near infrared portion of the spectrum. The analysis of coral reef bi-directional reflectance properties and degree of internal shadowing holds potential for future assessment and information extraction relating to coral structural characteristics.

Chemistry, properties, and phylogenetic implications of the methylated carrageenans from red algae of the genus Areschougia (Areschougiaceae, Gigartinales, Rhodophyta)

The three Australian-endemic species comprising the genus Aresehougia have been examined to determine the structure of their nonfibrillar wall components. The polysaccharide extracted from the most widely distributed species, A. congesta (Turner) J. Agardh, was shown by compositional analyses, Fourier transform infrared (FTIR) spectroscopy, linkage analysis, and C-13-NMR spectroscopy to be a carrageenan composed predominantly of the repeating disaccharides 6'-O-methylcarrabiose 2,4'-disulfate, carrabiose 2,4-disulfate (the repeating unit of L-carrageenan), 4',6'-O-(1-carboxyethylidene)carrabiose 2-sulfate, and 6'-O-methylcarrabiose 2-sulfate. The carrageenan also contained small amounts of 4-linked Galp residues, some bearing methyl ether substitution at O-3 and some possibly bearing sulfate ester and/or glycosyl substitutions at O-3. The A. congesta carrageenan had unique rheological properties, its gels having some similarities to those of commercial iota -carrageenan but with the viscosity of commercial lambda -carrageenan. Polysaccharides from A. ligulata Harvey ex J. Agardh and A. stuartii Harvey were shown by constituent sugar and FTIR analyses to be sulfated galactans rich in mono-O-methylgalactose. The carrageenan structures of Areschougia spp. were consistent with those of the genera Rhabdonia, Erythroclonium, and Austroclonium, the other genera constituting the family Areschougiaceae.

The copolymerization of N-vinyl-2-pyrrolidone with 2-hydroxyethyl methacrylate

The bulk free radical copolymerization of 2-hydroxyethyl methacrylate (HEMA) with N-vinyl-2-pyrrolidone (VP) was carried out to low conversions at 50 degreesC, using benzoyl peroxide (BPO) as initiator. The compositions of the copolymers; were determined using C-13 NMR spectroscopy. The conversion of monomers to polymers was studied using FT-NIR spectroscopy in order to predict the extent of conversion of monomer to polymer. From model fits to the composition data, a statistical F-test revealed that die penultimate model describes die copolymerization better than die terminal model. Reactivity ratios were calculated by using a non-linear least squares analysis (NLLS) and r(H) = 8.18 and r(V) = 0.097 were found to be the best fit values of the reactivity ratios for the terminal model and r(HH) = 12.0, r(VH) = 2.20, r(VV) = 0.12 and r(HV) = 0.03 for the penultimate model. Predictions were made for changes in compositions as a function of conversion based upon the terminal and penultimate models.

A systematic study of the microwave and thermal cure kinetics of the DGEBA/DDS and DGEBA/DDM epoxy-amine resin systems

The microwave and thermal cure processes for the epoxy-amine systems (epoxy resin diglycidyl ether of bisphenol A, DGEBA) with 4,4'-diaminodiphenyl sulphone (DDS) and 4,4'-diaminodiphenyl methane (DDM) have been investigated for 1:1 stoichiometries by using fiber-optic FT-NIR spectroscopy. The DGEBA used was in the form of Ciba-Geigy GY260 resin. The DDM system was studied at a single cure temperature of 373 K and a single stoichiometry of 20.94 wt% and the DDS system was studied at a stoichiometry of 24.9 wt% and a range of temperatures between 393 and 443 K. The best values of the kinetic rate parameters for the consumption of amines have been determined by a least squares curve fit to a model for epoxy/amine cure. The activation energies for the polymerization of the DGEBA/DDS system were determined for both cure processes and found to be 66 and 69 kJ mol(-1) for the microwave and thermal cure processes, respectively. No evidence was found for any specific effect of the microwave radiation on the rate parameters, and the systems were both found to be characterized by a negative substitution effect. Copyright (C) 2002 John Wiley Sons, Ltd.

Genotypic variation in proanthocyanidin status in the Leucaena genus

The proanthocyanidin (PA) status of 116 accessions from the Leucaena genus representing 21 species, 6 subspecies, 3 varieties and 4 interspecific hybrids was evaluated under uniform environmental and experimental conditions at Redland Bay, Queensland, Australia in October 1997. The PA content of lyophilized youngest fully expanded leaves was measured spectrophotometrically by the butanol/HCl assay referenced to L. leucocephala ssp. glabrata standard PA and expressed as L. leucocephala ssp. glabrata PA equivalents (LLPAE). Considerable interspecific variation in PA concentration existed within the genus, ranging from 0-339 g LLPAE/kg dry matter (DM). Taxa including L. confertiflora, L. cuspidata, L. esculenta and L. greggii contained very high (> 180 g LLPAE/kg DM) PA concentrations. Similarly, many agronomically superior accessions from L. diversifolia, L. pallida and L. trichandra contained extremely high (up to 250 g LLPAE/kg DM) PA concentrations, although these taxa exhibited wide intraspecific variation in PA content offering the potential to select accessions with lower (120-160 g LLPAE/kg DM) PA content. Commercial cultivars of L. leucocephala ssp. glabrata, known to produce forage of superior quality, contained low amounts of PA (33-39 g LLPAE/kg DM). Artificial interspecific hybrids had PA contents intermediate to those of both parents, Lesser-known taxa. including L. collinsii, L. lanceolata, L. lempirana, L. macrophylla, L. magnifica, L. multicapitula, L. salvadorensis and L. trichodes, contained undetectable to low (0-36 g LLPAE/kg DM) quantities of PA and have potential as parents to breed interspecific hybrids of low PA status and superior forage quality. Extractable PA was the dominant PA component, accounting for 91% of total PA within the genus. Regression analysis of accession ranks from different experiments compared to these results indicated that genetic regulation of Leucaena spp. PA content was consistent (P < 0.01) under different edapho-climatic environments. The distribution of PA within the Leucaena genus did not concur with the predictions of various evolutionary and phylogenetic plant defence theories.

ITO/SiOx/Si optical sensor with internal gain

A visible/near-infrared optical sensor based on an ITO/SiOx/n-Si structure with internal gain is presented. This surface-barrier structure was fabricated by a low-temperature processing technique. The interface properties and carder transport were investigated from dark current-voltage and capacitance-voltage characteristics. Examination of the multiplication properties was performed under different light excitation and reverse bias conditions. The spectral and pulse response characteristics are analysed. The current amplification mechanism is interpreted by the control of electron current by the space charge of photogenerated holes near the SiOx/Si interface. The optical sensor output characteristics and some possible device applications are presented.

Photodiode with nanocrystalline Si/amorphous Si absorber bilayer

This letter reports a near-ultraviolet/visible/near-infrared n(+)-n-i-delta(i)-p photodiode with an absorber comprising a nanocrystalline silicon n layer and a hydrogenated amorphous silicon i layer. Device modeling reveals that the dominant source of reverse dark current is deep defect states in the n layer, and its magnitude is controlled by the i layer thickness. The photodiode with the 900/400 nm thick n-i layers exhibits a reverse dark current density of 3nA/cm(2) at -1V. Donor concentration and diffusion length of holes in the n layer are estimated from the capacitance-voltage characteristics and from the bias dependence of long-wavelength response, respectively. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3660725]

Detecção e seguimento de objectos em imagens termográficas: análise experimental de modelos de descrição

A instalação de sistemas de videovigilância, no interior ou exterior, em locais como aeroportos, centros comerciais, escritórios, edifícios estatais, bases militares ou casas privadas tem o intuito de auxiliar na tarefa de monitorização do local contra eventuais intrusos. Com estes sistemas é possível realizar a detecção e o seguimento das pessoas que se encontram no ambiente local, tornando a monitorização mais eficiente. Neste contexto, as imagens típicas (imagem natural e imagem infravermelha) são utilizadas para extrair informação dos objectos detectados e que irão ser seguidos. Contudo, as imagens convencionais são afectadas por condições ambientais adversas como o nível de luminosidade existente no local (luzes muito fortes ou escuridão total), a presença de chuva, de nevoeiro ou de fumo que dificultam a tarefa de monitorização das pessoas. Deste modo, tornou‐se necessário realizar estudos e apresentar soluções que aumentem a eficácia dos sistemas de videovigilância quando sujeitos a condições ambientais adversas, ou seja, em ambientes não controlados, sendo uma das soluções a utilização de imagens termográficas nos sistemas de videovigilância. Neste documento são apresentadas algumas das características das câmaras e imagens termográficas, assim como uma caracterização de cenários de vigilância. Em seguida, são apresentados resultados provenientes de um algoritmo que permite realizar a segmentação de pessoas utilizando imagens termográficas. O maior foco desta dissertação foi na análise dos modelos de descrição (Histograma de Cor, HOG, SIFT, SURF) para determinar o desempenho dos modelos em três casos: distinguir entre uma pessoa e um carro; distinguir entre duas pessoas distintas e determinar que é a mesma pessoa ao longo de uma sequência. De uma forma sucinta pretendeu‐se, com este estudo, contribuir para uma melhoria dos algoritmos de detecção e seguimento de objectos em sequências de vídeo de imagens termográficas. No final, através de uma análise dos resultados provenientes dos modelos de descrição, serão retiradas conclusões que servirão de indicação sobre qual o modelo que melhor permite discriminar entre objectos nas imagens termográficas.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Forest fire detection with a small fixed wing autonomous aerial vehicle

In this work a forest fire detection solution using small autonomous aerial vehicles is proposed. The FALCOS unmanned aerial vehicle developed for remote-monitoring purposes is described. This is a small size UAV with onboard vision processing and autonomous flight capabilities. A set of custom developed navigation sensors was developed for the vehicle. Fire detection is performed through the use of low cost digital cameras and near-infrared sensors. Test results for navigation and ignition detection in real scenario are presented.

Planning, operations and data handling of planetary science missions

Dissertação para obtenção do Grau de Mestre em Engenharia Física

Reconfigurable photonic logic architecture

The amorphous silicon photo-sensor studied in this thesis, is a double pin structure (p(a-SiC:H)-i’(a-SiC:H)-n(a-SiC:H)-p(a-SiC:H)-i(a-Si:H)-n(a-Si:H)) sandwiched between two transparent contacts deposited over transparent glass thus with the possibility of illumination on both sides, responding to wave-lengths from the ultra-violet, visible to the near infrared range. The frontal il-lumination surface, glass side, is used for light signal inputs. Both surfaces are used for optical bias, which changes the dynamic characteristics of the photo-sensor resulting in different outputs for the same input. Experimental studies were made with the photo-sensor to evaluate its applicability in multiplexing and demultiplexing several data communication channels. The digital light sig-nal was defined to implement simple logical operations like the NOT, AND, OR, and complex like the XOR, MAJ, full-adder and memory effect. A pro-grammable pattern emission system was built and also those for the validation and recovery of the obtained signals. This photo-sensor has applications in op-tical communications with several wavelengths, as a wavelength detector and to execute directly logical operations over digital light input signals.

Microencapsulation of ellagic acid from pomegranate husk and karaya gum by spray drying

Objective: The aim of this study was to obtain and characterize microcapsules with Ellagic Acid (EA) from pomegranate as core material and Karaya Gum (KG) as wall material. Methods: EA was obtained from dry pomegranate peel powder via methanolysis and quantified by HPLC. Microcapsules were obtained preparing a dispersion containing KG and EA in phosphate buffer pH 8. The dispersion was processed in a spray dryer under specific conditions (inlet temperature at 150 °C, feed flow at 30% and aspirator at 100 %) for obtaining of microcapsules. Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC) and scanning electron microscopy (SEM) were used for characterization. Results: Obtained material contains 98.03±2.82 mg EA/g of pomegranate peel. FTIR showed that there were changes in the molecular structure of microcapsules referred to raw materials. SEM confirmed that particles obtained had micron-size (1-5 µm). DSC analysis showed that raw materials had glass transition temperatures of 79.58 and 83.41 °C and for microcapsules the value was67.25 °C. Conclusion: Methanolysis is a viable technique for the obtaining of EA from the peel of pomegranate. KG shows good potential for be used as wall material for EA microencapsulation.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.