87 resultados para reinforcement classes


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We determine the relation amongst the global Lê cycles and the Milnor classes of analytic hypersurfaces defined by a section of a very ample line bundle over a compact complex manifold. The key point is finding appropriate expressions for the global Lê cycles and for the Milnor classes in terms of polar varieties. Our starting points are an interpretation of the Lê cycles given by T. Gaffney and R. Gassler, a formula by A. Parusinski and P. Pragacz for the Milnor classes via McPherson’s functor, and a conjecture of J.-P. Brasselet, that we prove, stating that Milnor classes can be expressed in terms of polar varieties. We then use the work by R. Piegne for Mather classes, by J. Schürmann and M. Tibăr for MacPherson’s classes for constructible functions, and by D. Massey for an extension of the local Lê cycles for constructible sheaves.

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This article is focused in the understanding of how can social classes influence in prenatal, throughout the patient medical relationship as well as the many aspects surrounding. In the first chapter, reflected about the adherence to prenatal and considerations in gestational period when dealing with public health treatment offer by SUS. Next chapter, patient medical relationship is addressed as a relationship classes, over questioning how this relationship use to be in front of disadvantaged extracts, focused in prenatal. In the third chapter, the patient medical relationship is analyzed throughout the patient vision, pointing the many factors that can induce the success of a therapeutic. In the last chapter, there are reflections about whereby health professionals upgrading, as well as the improve of basic health care networks are necessary to a larger prenatal adherence.

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Within a broader study of the apparatus governing the establishment of word classes in grammatical tradition, this study is centered on examining the treatment of the (sub)class of pronouns in two grammar guide groups from different periods. The collation was especially oriented by the existing general notion of a very strong link of the first grammarians with logic and, as a counterpart, of an insertion of the most recent works in the universe of a linguistic science and, at the same time, in the universe of a parameterization limiting actions and decisions.

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The aims of this study were (1) to synthesize and characterize random and aligned nanocomposite fibers of multi-walled carbon nanotubes (MWCNT)/nylon-6 and (2) to determine their reinforcing effects on the flexural strength of a dental resin composite.Nylon-6 was dissolved in hexafluoropropanol (10 wt%), followed by the addition of MWCNT (hereafter referred to as nanotubes) at two distinct concentrations (i.e., 0.5 or 1.5 wt%). Neat nylon-6 fibers (without nanotubes) were also prepared. The solutions were electrospun using parameters under low- (120 rpm) or high-speed (6000 rpm) mandrel rotation to collect random and aligned fibers, respectively. The processed fiber mats were characterized by scanning (SEM) and transmission (TEM) electron microscopies, as well as by uni-axial tensile testing. To determine the reinforcing effects on the flexural strength of a dental resin composite, bar-shaped (20 x 2 x 2 mm(3)) resin composite specimens were prepared by first placing one increment of the composite, followed by one strip of the mat, and one last increment of composite. Non-reinforced composite specimens were used as the control. The specimens were then evaluated using flexural strength testing. SEM was done on the fractured surfaces. The data were analyzed using ANOVA and the Tukey's test (alpha=5%).Nanotubes were successfully incorporated into the nylon-6 fibers. Aligned and random fibers were obtained using high- and low-speed electrospinning, respectively, where the former were significantly (p<0.001) stronger than the latter, regardless of the nanotubes'presence. Indeed, the dental resin composite tested was significantly reinforced when combined with nylon-6 fibrous mats composed of aligned fibers (with or without nanotubes) or random fibers incorporated with nanotubes at 0.5 wt%. (C) 2015 Elsevier Ltd. All rights reserved.

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The focus of this research was to study the utilization of residues from bamboo (Dendrocalamus giganteus) lamination in the manufacturing of panels for structural purposes. Bamboo particleboards were produced under three conditions: pure boards, reinforced with bamboo laminas, and with treated particles. Castor oil-based polyurethane was the resin binder, in view of using lower toxicity materials. The mechanical tests were performed according to Brazilian Standard (NBR) 14810-3 (2006) and European Standard (EN) 310 (2000). The results were superior to those recommended by these and other standards for internal adhesion resistance, modulus of rupture, and elasticity in static bending, as well as to the results of other studies. Starch treatment was an unnecessary stage. According to the conditions of this process, the studied panels showed a good potential for construction use. Moreover, the bamboo particleboards are an economically viable, environmentally friendly, and sustainable alternative for the use of waste generated during the processing of Dendrocalamus giganteus bamboo species, allied with castor oil-based polyurethane resin. The reinforced particleboard and its production process are being licensed as an Innovation Patent in Brazil, (BR 1020130133919-1-2013).

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Biodegradable polymers are starting to be introduced as raw materials in the food-packaging market. Nevertheless, their price is very high. Starch, a fully biodegradable and bioderived polymer is a very interesting alternative due to its very low price. However, the use of starch as the polymer matrix for the production of rigid food packaging, such as trays, is limited due to its poor mechanical properties, high hidrophilicity and high density. This work presents two strategies to overcome the poor mechanical properties of starch. First, the plasticization of starch with several amounts of glycerol to produce thermoplastic starch (TPS) and second, the production of biocomposites by reinforcing TPS with promising fibers, such as barley straw and grape waste. The mechanical properties obtained are compared with the values predicted by models used in the field of composites; law of mixtures, Kerner-Nielsen and Halpin-Tsai. To evaluate if the materials developed are suitable for the production of food-packaging trays, the TPS-based materials with better mechanical properties were compared with commercial grades of oil-based polymers, polypropylene (PP) and polyethylene-terphthalate (PET), and a biodegradable polymer, polylactic acid (PLA).

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The aim of this study was to evaluate the effects of peer tutor teaching strategy, after a re-training, in relation to the inclusion process of a student with physical disability during physical education classes. The participants were: the student with physical disability, eight peer tutors, and a physical education teacher of a public school in Bauru, Brazil. As the students had previously experienced the tutoring training, a re-training was prepared, which enabled the reinforcement of some aspects of the tutoring and assistance strategies, in order to improve the tutor colleague action. To analyze, two observation instruments were used: System for Observing Fitness Instruction Time (SOFIT) and Souza Observation Protocol. Behavioral changes of the involved students were notable, due to the significant action of the re-training process. Thus, we highlight the importance of the periodic reinforcements of the training for the tutor colleagues, in order to preserve, or even improve the autonomy and self-esteem of the student with disability.

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Studies on learning by exclusion have shown that participants tend to select a new object or a new figure when a new word is dictated, rejecting the objects and figures they already know or that were associated with other words. This study aimed at training conditional relations between dictated word-picture and between picture-printed word, by exclusion, and verify whether this training would be a condition for the emergence of relations between dictated word-printed word, printed word-figure, picture naming and reading. We also investigated whether responding to the words dictated with a female voice generalized to other frequencies such as male and child voices. Participants were five children between five and nine years old, with acute neurosensorial bilateral hearing impairment, users of cochlear implant Nucleus 24k®. They were exposed, individually, to tasks that consisted in selecting a comparison stimulus (either picture or printed word) related to the sample (either dictated word or picture). Words with lowest scores on a pre-test were used. The relations between dictated word-figure (AB) and figure-printed word (BC) were taught by exclusion. We assessed the emergence of the relations between dictated and printed words (AC), printed word and picture (CB), male and child voices generalization (A’C and A’’C), naming (BD) and reading (CD). All the children responded by exclusion and learned relations AB and BC, showing receptive vocabulary; AC and CB relations also were learned, consistent with class formation. Responding generalized to male and child voices, but data on naming were not systematic. Learning by exclusion was similar to that of children with typical hearing and these results describe some conditions that can improve receptive verbal repertoire.

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The aim of this work is to discriminate vegetation classes throught remote sensing images from the satellite CBERS-2, related to winter and summer seasons in the Campos Gerais region Paraná State, Brazil. The vegetation cover of the region presents different kinds of vegetations: summer and winter cultures, reforestation areas, natural areas and pasture. Supervised classification techniques like Maximum Likelihood Classifier (MLC) and Decision Tree were evaluated, considering a set of attributes from images, composed by bands of the CCD sensor (1, 2, 3, 4), vegetation indices (CTVI, DVI, GEMI, NDVI, SR, SAVI, TVI), mixture models (soil, shadow, vegetation) and the two first main components. The evaluation of the classifications accuracy was made using the classification error matrix and the kappa coefficient. It was defined a high discriminatory level during the classes definition, in order to allow separation of different kinds of winter and summer crops. The classification accuracy by decision tree was 94.5% and the kappa coefficient was 0.9389 for the scene 157/128. For the scene 158/127, the values were 88% and 0.8667, respectively. The classification accuracy by MLC was 84.86% and the kappa coefficient was 0.8099 for the scene 157/128. For the scene 158/127, the values were 77.90% and 0.7476, respectively. The results showed a better performance of the Decision Tree classifier than MLC, especially to the classes related to cultivated crops, indicating the use of the Decision Tree classifier to the vegetation cover mapping including different kinds of crops.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)