Modelo petrofísico 3D do Arenito Namorado no Campo de Namorado - Bacia de Campos, RJ

The Namorado Oil Field represents the beginning of the oil exploration in Brazil, in the 70s, and it is still a subject of researches because the importance of this turbidite sandstone in the brazilian oil production. The Namorado’s production level was denominated “Namorado sandstone”, it is composed by turbidite sandstone deposited during the Albian-Cenomanian. In order to define the structural geometry of the main reservoir, geological and geophysical tools like RECON and Geographix (Prizm – Seisvision) softwares were used, and its application was focused on geological facies analysis, for that propose well logs, seismic interpretation and petrophysical calculations were applied. Along this work 15 vertical wells were used and the facies reservoirs were mapped of along the oil field; it is important to mentioned that the all the facies were calibrated by the correlation rock vs log profile, and 12 reservoir-levels (NA-1, NA-2, NA-3, NA-4, NA-5, NA-6, NA-7, NA-8, NA-9, NA-10, NA-11 e NA-12) were recognized and interpreted. Stratigraphic sections (NE-SW and NW-SE) were also built based on stratigraphic well correlation of each interpreted level, and seismic interpretation (pseudo-3D seismic data) on the southeastern portion of the oil field. As results it was interpreted on two- and three-dimensional maps that the deposition reservoir’s levels are hight controlled by normal faults systems. This research also shows attribute maps interpretation and its relationship with the selection of the reservoir attribute represented on it. Finally the data integration of stratigraphic, geophysical and petrophysical calculations lets us the possibility of obtain a detail geological/petrophysical 3D model of the main reservoir levels of “Namorado sandstone” inside the oil/gás field

Expansão ex vivo de células uroteliais em scaffolds 3D

Malformations and possible damages to the urogenital system can be originated in the embryonic period. Moreover, fire guns, knives and accidents, where there is the disruption of the urethra, also cause these lesions. The objective was to analyze the contribution of tissue engineering in the construction of neo-urethra, developed by bioengineering. We performed an urothelial ex vivo expansion of cells in 3D scaffolds (platelet gel matrix and acellular porcine aorta) to assess the contribution of this technique in the construction of a neo-urethra. Mechanical dissociation was made of the inner wall of 10 North Folk rabbit’s bladder, weighing 2.5 to 3.0 kg. After dissociation the cell content was centrifuged and obtained a pellet of urothelial cells. The pellet was ressuspended in culture medium DMEM F12 and cells were maintained in culture for 15 days. Immunohistochemical analysis characterized the urothelial culture. The cells were then implanted in the scaffold - platelet gel. In a second experiment using aortic porcine acellular matrix were implanted urothelial cells alone and urothelial cells on platelet gel, on the inner wall of the scaffold - aorta, with space for setting bordered by a urethral probe. The complex probe - cells - aorta and probe - cells in platelet gel - aorta, were sealed with suture material and culture were maintained in a humidified 37ºC incubator with 5% CO2 in air for 12 days to subsequent histological analysis of urothelium cell adhesion to the scaffolds. By observation under an optical microscope, we could see the growth of cells in the scaffold platelet gel, from a monolayer in to a three-dimensional structure. In the acellular porcine aortic matrix containing the platelet gel, we could observe a few quantity of urothelial cells adhered. However with the acellular porcine aortic matrix in which was implanted only the urothelial cells, we have obtained adhesion to the wall

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Tailoring the refractive index of Ge-S based glass for 3D embedded waveguides operating in the mid-IR region

The photosensitivity of GeSx binary glasses in response to irradiation to femtosecond pulses at 800 nm is investigated. Samples with three different molecular compositions were irradiated under different exposure conditions. The material response to laser exposure was characterized by both refractometry and micro-Raman spectroscopy. It is shown that the relative content of sulfur in the glass matrix influences the photo-induced refractive index modification. At low sulfur content, both positive and negative index changes can be obtained while at high sulfur content, only a positive index change can be reached. These changes were correlated with variations in the Raman response of exposed glass which were interpreted in terms of structural modifications of the glass network. Under optimized exposure conditions, waveguides with positive index changes of up to 7.8x10−3 and a controllable diameter from 14 to 25 μm can be obtained. Direct inscription of low insertion losses (IL = 3.1 – 3.9 dB) waveguides is demonstrated in a sample characterized by a S/Ge ratio of 4. The current results open a pathway towards the use of Ge-S binary glasses for the fabrication of integrated mid-infrared photonic components.

Using 3D Animations in Teaching Chemistry

This paper discuss possibilities of use of 3D animation as a tool for teaching Chemistry support. The research proposes to investigate the conception process and development of educational animations to use in a Blended Learning environment in undergraduate chemistry. Associated with general chemistry teachers, were raised the demands and difficulties on the content transmission, and the most relevant topics, about "Atomic Theory" with propose to create appropriate animations to meeting needs of themes. Thinking about offering more dynamic materials, we elaborate animations in a format of "micro-documentary", with a length between 4 and 7 minutes. We use the narration aloud to the subject-matter understanding, leaving the external text as a complement of the animation. The conclusions are positives, students accepted well the format and they proved are able to remember, organize and systematize several information presented in animations. These skills don't ensure knowledge acquisition, but may be considered prerequisites to learning occur.

Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

Genetic divergence among maize hybrids by morphological descriptors

Two experiments with 25 maize commercial hybrids were carried out in a direct sowing system in Southern Brazil in the harvests of 2009/2010 and 2010/2011. Quantitative descriptors were used with the objective of determining the genetic divergence and the relative contributions of traits among hybrids for extraction of inbred lines. This study was carried out in Oxisol soil using a randomized block design with four replicates. Data were subjected to combined analysis of variance, and based on the multivariate analyses, Tocher and average linkage (UPGMA) cluster analyses, based on generalized distance of Mahalanobis, to quantify divergence in addition to Singh criterion to validate trait with the most contribution. The multivariate methods were consistent with each other, and the weight of 100 grains was the trait that contributed most to the divergence and had similar behavior in grain yield between hybrids in both years. Furthermore, this descriptor representing significant genetic variability for crossings and lines extraction to hybridization between BM 3061, ATL 200 and P 30B39 Y.

Reconhecimento de faces 3D com Kinect

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação de sistemas imunológicos artificiais para biometria facial: Reconhecimento de identidade baseado nas características de padrões binários

Pós-graduação em Engenharia Elétrica - FEIS

Desenvolvimento do cultivo 3D a partir de células primarias de neoplasias mamárias caninas: estudo da apoptose sobre efeito ou não da carboplatina

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

3D superimposition and understanding temporomandibular joint arthritis

Structured AbstractObjectivesTo investigate the 3D morphological variations in 169 temporomandibular ioint (TMJ) condyles, using novel imaging statistical modeling approaches.Setting and sample populationThe Department of Orthodontics and Pediatric Dentistry at the University of Michigan. Cone beam CT scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA, mean age 39.115.7years), 15 subjects at initial consult diagnosis of OA (mean age 44.914.8years), and seven healthy controls (mean age 4312.4years).Materials and methods3D surface models of the condyles were constructed, and homologous correspondent points on each model were established. The statistical framework included Direction-Projection-Permutation (DiProPerm) for testing statistical significance of the differences between healthy controls and the OA groups determined by clinical and radiographic diagnoses.ResultsCondylar morphology in OA and healthy subjects varied widely with categorization from mild to severe bone degeneration or overgrowth. DiProPerm statistics supported a significant difference between the healthy control group and the initial diagnosis of OA group (t=6.6, empirical p-value=0.006) and between healthy and long-term diagnosis of OA group (t=7.2, empirical p-value=0). Compared with healthy controls, the average condyle in OA subjects was significantly smaller in all dimensions, except its anterior surface, even in subjects with initial diagnosis of OA.ConclusionThis new statistical modeling of condylar morphology allows the development of more targeted classifications of this condition than previously possible.

Automatic method to classify images based on multiscale fractal descriptors and paraconsistent logic

In this study is presented an automatic method to classify images from fractal descriptors as decision rules, such as multiscale fractal dimension and lacunarity. The proposed methodology was divided in three steps: quantification of the regions of interest with fractal dimension and lacunarity, techniques under a multiscale approach; definition of reference patterns, which are the limits of each studied group; and, classification of each group, considering the combination of the reference patterns with signals maximization (an approach commonly considered in paraconsistent logic). The proposed method was used to classify histological prostatic images, aiming the diagnostic of prostate cancer. The accuracy levels were important, overcoming those obtained with Support Vector Machine (SVM) and Bestfirst Decicion Tree (BFTree) classifiers. The proposed approach allows recognize and classify patterns, offering the advantage of giving comprehensive results to the specialists.

Superconducting properties of a parallelepiped mesoscopic superconductor: a comparative study between the 2D and 3D Ginzburg-Landau models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Plant identification based on leaf midrib cross-section images using fractal descriptors

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)