Raman spectroscopy analysis of structural photoinduced changes in GeS(2) + Ga(2)O(3) thin films

Photoexpansion and photobleaching effects have been observed in amorphous GeS(2) + Ga(2)O(3) (GGSO) thin films, when their surfaces were exposed to UV light. The photoinduced changes on the surface of the samples are indications that the structure has been changed as a result of photoexcitation. In this paper, micro-Raman, energy dispersive X-ray analysis (EDX) and backscattering electrons (BSE) microscopy were the techniques used to identify the origin of these effects. Raman spectra revealed that these phenomena are a consequence of the Ge-S bonds` breakdown and the formation of new Ge-O bonds, with an increase of the modes associated with Ge-O-Ge bonds and mixed oxysulphide tetrahedral units (S-Ge-O). The chemical composition measured by EDX and BSE microscopy images indicated that the irradiated area is oxygen rich. So, the present paper provides fundamental insights into the influence of the oxygen within the glass matrix on the considered photoinduced effects. (C) 2010 Elsevier B.V. All rights reserved.

Rhyacian (2.23-2.20 Ga) juvenile accretion in the southern Sao Francisco craton, Brazil: Geochemical and isotopic evidence from the Serrinha magmatic suite, Mineiro belt

The Serrinha magmatic suite (Mineiro belt) crops out in the southern edge of the Sao Francisco craton, comprising the Brito quartz-diorite, Brumado de Cima and Brumado de Baixo granodiorites, granophyres and felsic sub-volcanic and volcanic rocks, part of which intruded into the Nazareno greenstone belt. The suite rocks have petrographic features that are consistent with magma supercooling due to the low water content combined with volatile loss, leading to crystallization of quartz and alkaline feldspar at the rims of plagioclase phenocrysts (granophyric intergrowth). The investigated rocks are sub-alkaline, calc-alkaline and show low content in rare earth elements. The U-Pb zircon crystallization ages for the Brumado de Cima granodiorite [2227 +/- 22 (23) Ma] and a coeval granophyre [2211 +/- 22 (23) Ma], coupled with available single-zircon Pb evaporation ages for the Brito and Brumado de Baixo plutons, are significantly older than the ""Minas orogeny"" (ca. 2100-2050 Ga) of Quadrilatero Ferrifero area, eastward from the Serrinha suite. Our data establish an early Rhyacian event tectonically linked with the evolution of the Mineiro belt. The bulk Nd isotopic signature [low negative to positive epsilon(Nd(t)) values] of the Serrinha samples are consistent with the important role of Paleoproterozoic mantle components in the magma genesis. The integrated geologic, geochemical and isotopic information suggests that Paleoproterozoic evolution of the Mineiro belt initiated in a passive continental margin basin with deposition of the Minas Supergroup at ca. 2500 Ma. This stage was succeeded by outboard rupture of the oceanic lithosphere with development and coalescence of progressively younger magmatic arcs during Rhyacian time. One of the earliest arcs formed the Serrinha suite. The tectonic collage of the Serrinha and Ritapolis (2190-2120 Ma) arcs produced the NE-SW Lenheiro shear zone, resulting in mylonitization and recrystallization of both the granitoid intrusions and host rocks. As a matter of fact juxtaposition of distinct magmatic units in age and origin took place along the Lenheiros structure in this sector of the Mineiro belt. (C) 2009 Elsevier Ltd. All rights reserved.

Geology and geochronology of the Betara region in south-southeastern Brazil: Evidence for possible Statherian (1.80-1.75 Ga) and Calymmian (1.50-1.45 Ga) extension events

The results of geological mapping, chemical analysis and radiometric dating of metabasic rocks of Betara Formation, and mapping and dating of those present in the Betara basement nucleus together with mylonitic granodiorite and syenogranite are reported here. U-Pb analysis of bulk zircon fractions from the metabasic rocks of the basement nucleus yielded a Statherian age of 1790 +/- 22 Ma, while the metabasic rocks from the upper part of the Betara Formation yielded a Calymmian age between 1500 and 1450 Ma. This age is a minimum for the deposition of the Betara Formation. The older metabasic rocks are associated with post-tectonic, possibly anorogenic syenogranite, while the younger ones are gabbro or very porphyritic ankaramite whose REE patterns are consistent with crystallization from an N-MORB parent magma. The observations and data point to the probable events associated with extensional processes of the end of Paleoproterozoic and early Mesoproterozoic. Similar registers of Statherian (1.80-1.75 Ga) and Calymmian (1.50-1.45 Ga) extensional events are recorded in other parts of the South American and African continents. The Neoproterozoic witnessed the formation and junction of the tectonic slices which formed the Apiai domain during the assemblage of western Gondwana. (C) 2010 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

A method for Ca, Fe, Ga, Na, Si and Zn determination in alumina by inductively coupled plasma optical emission spectrometry after aluminum precipitation

In this present work a method for the determination of Ca, Fe, Ga, Na, Si and Zn in alumina (Al(2)O(3)) by inductively coupled plasma optical emission spectrometry (ICP OES) with axial viewing is presented. Preliminary studies revealed intense aluminum spectral interference over the majority of elements and reaction between aluminum and quartz to form aluminosilicate, reducing drastically the lifetime of the torch. To overcome these problems alumina samples (250 mg) were dissolved with 5 mL HCl + 1.5 mLH(2)SO(4) + 1.5 mL H(2)O in a microwave oven. After complete dissolution the volume was completed to 20 mL and aluminum was precipitated as Al(OH)(3) with NH(3) (by bubbling NH(3) into the solution up to a pH similar to 8, for 10 min). The use of internal standards (Fe/Be, Ga/Dy, Zn/In and Na/Sc) was essential to obtain precise and accurate results. The reliability of the proposed method was checked by analysis of alumina certified reference material (Alumina Reduction Grade-699, NIST). The found concentrations (0.037%w(-1) CaO, 0.013% w w(-1) Fe(2)O(3), 0.012%w w(-1)Ga(2)O(3), 0.49% w w(-1) Na(2)O, 0.014% w w(-1) SiO(2) and 0.013% w w(-1) ZnO) presented no statistical differences compared to the certified values at a 95% confidence level. (C) 2011 Elsevier B.V. All rights reserved.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.