Avaliação clínico visual de três técnicas de clareamento dental

O objetivo deste estudo in vivo foi avaliar comparativamente três técnicas de clareamento de dentes polpados quanto ao grau de cor final alcançado, sensibilidade dental e satisfação pessoal de operadores e pacientes. Indivíduos jovens de mesma faixa etária e padrão de higiene bucal foram selecionados e divididos aleatoriamente entre os grupos (G1; n=7) caseiro, com regime de uso de 8 h/dia/4 semanas; (G2; n=7) consultório, com regime de clareamento de 4 sessões semanais de 2 aplicações de 15 min cada e; (G3; n=6) associado, com caseiro e consultório combinados. Para as técnicas caseira e de consultório foram utilizados peróxido de carbamida a 16% (WhitegoldHome/Dentsply) e peróxido de hidrogênio a 35% (Whitegold Office/Dentsply), respectivamente. Os registros de cor foram obtidos por um único operador antes e após o emprego da cada técnica utilizando escala de cores Vita Bleachedguide 3D-Master e máquina fotográfica digital profissional (EOS Rebel XT Canon), com ajustes de iluminação, flash e distância focal padronizados. O nível de clareamento foi avaliado por unidades de mudança de cor (luminosidade) na escala de cores, além do número de tons alcançados nas imagens digitais e mudança de cor no sistema CIE L*a*b* por meio do software ScanWhite. Os dados foram tratados estatisticamente pelos testes não paramétricos de Kruskal Wallis e dos sinais (p≤0,05). Os registros de sensibilidade dental trans e pós operatória e da satisfação pessoal dos operadores e pacientes foram preenchidos individualmente em questionário unidimensional ao final de cada sessão. Foram atribuídos escores para a avaliação final da sensibilidade dental, conforme: 0=ausente; 1=leve; 2=moderada e; 3=severa. Os dados foram tratados estatisticamente pelo teste Kruskal Wallis. As médias das variações de unidades de mudança de cor da escala Vita e do software foram, respectivamente: G1) 4,57 (IC1,34), 27,14 (IC12,03); G2) 2,86 (IC0,99), 21,29 (IC14,27); G3) 4 (IC1,82), 25,33 (IC10,70). Na comparação entre os métodos de avaliação de cor, os p-valores do teste dos sinais foram 0,453, 0,453 e 0,687 para os grupos 1, 2 e 3, respectivamente. As médias da variação total de cor (∆E) foram, respectivamente: G1) 8,79(IC4,18), G2) 7,10(IC3,53) e G3) 9,74 (IC4,07). Não foi determinada diferença estatisticamente significante entre os grupos. Os postos médios do nível de sensibilidade foram: G1 = 9,64; G2 = 11,58; e G3 = 10,43, e o p-valor = 0,807. Não houve diferença estatisticamente significante entre grupos. Conclui-se que as técnicas caseiro, consultório e associada foram igualmente eficazes quanto ao nível de cor final, de acordo com os métodos objetivos e subjetivos utilizados. O nível de sensibilidade dental foi o mesmo independentemente da técnica utilizada. Todos os indivíduos registraram satisfação ao final do clareamento.

Learning large-scale spatial relationships in a maze and effects of MK-801 on retrieval in the rhesus monkey

Monkeys have strong abilities to remember the visual properties of potential food sources for survival in the nature. The present study demonstrated the first observations of rhesus monkeys learning to solve complex spatial mazes in which routes were guid

Large Scale Column Detection for Bridge Inspection

Manually inspecting bridges is a time-consuming and costly task. There are over 600,000 bridges in the US, and not all of them can be inspected and maintained within the specified time frame as some state DOTs cannot afford the essential costs and manpower. This paper presents a novel method that can detect bridge concrete columns from visual data for the purpose of eventually creating an automated bridge condition assessment system. The method employs SIFT feature detection and matching to find overlapping areas among images. Affine transformation matrices are then calculated to combine images containing different segments of one column into a single image. Following that, the bridge columns are detected by identifying the boundaries in the stitched image and classifying the material within each boundary. Preliminary test results using real bridge images indicate that most columns in stitched images can be correctly detected and thus, the viability of the application of this research.

Expressive visual text-to-speech using active appearance models

This paper presents a complete system for expressive visual text-to-speech (VTTS), which is capable of producing expressive output, in the form of a 'talking head', given an input text and a set of continuous expression weights. The face is modeled using an active appearance model (AAM), and several extensions are proposed which make it more applicable to the task of VTTS. The model allows for normalization with respect to both pose and blink state which significantly reduces artifacts in the resulting synthesized sequences. We demonstrate quantitative improvements in terms of reconstruction error over a million frames, as well as in large-scale user studies, comparing the output of different systems. © 2013 IEEE.

Color to Gray: Visual Cue Preservation

Both commercial and scientific applications often need to transform color images into gray-scale images, e. g., to reduce the publication cost in printing color images or to help color blind people see visual cues of color images. However, conventional color to gray algorithms are not ready for practical applications because they encounter the following problems: 1) Visual cues are not well defined so it is unclear how to preserve important cues in the transformed gray-scale images; 2) some algorithms have extremely high time cost for computation; and 3) some require human-computer interactions to have a reasonable transformation. To solve or at least reduce these problems, we propose a new algorithm based on a probabilistic graphical model with the assumption that the image is defined over a Markov random field. Thus, color to gray procedure can be regarded as a labeling process to preserve the newly well-defined visual cues of a color image in the transformed gray-scale image. Visual cues are measurements that can be extracted from a color image by a perceiver. They indicate the state of some properties of the image that the perceiver is interested in perceiving. Different people may perceive different cues from the same color image and three cues are defined in this paper, namely, color spatial consistency, image structure information, and color channel perception priority. We cast color to gray as a visual cue preservation procedure based on a probabilistic graphical model and optimize the model based on an integral minimization problem. We apply the new algorithm to both natural color images and artificial pictures, and demonstrate that the proposed approach outperforms representative conventional algorithms in terms of effectiveness and efficiency. In addition, it requires no human-computer interactions.

Sharing visual features for multiclass and multiview object detection

We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifiers to the image, at multiple locations and scales. This can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. In particular, for independently trained detectors, the (run-time) computational complexity, and the (training-time) sample complexity, scales linearly with the number of classes to be detected. It seems unlikely that such an approach will scale up to allow recognition of hundreds or thousands of objects. We present a multi-class boosting procedure (joint boosting) that reduces the computational and sample complexity, by finding common features that can be shared across the classes (and/or views). The detectors for each class are trained jointly, rather than independently. For a given performance level, the total number of features required, and therefore the computational cost, is observed to scale approximately logarithmically with the number of classes. The features selected jointly are closer to edges and generic features typical of many natural structures instead of finding specific object parts. Those generic features generalize better and reduce considerably the computational cost of an algorithm for multi-class object detection.

The Role of Knowledge in Visual Shape Representation

This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.

Learning Shape Descriptions: Generating and Generalizing Models of Visual Objects

We present the results of an implemented system for learning structural prototypes from grey-scale images. We show how to divide an object into subparts and how to encode the properties of these subparts and the relations between them. We discuss the importance of hierarchy and grouping in representing objects and show how a notion of visual similarities can be embedded in the description language. Finally we exhibit a learning algorithm that forms class models from the descriptions produced and uses these models to recognize new members of the class.

Fast Synchronization of Perpetual Grouping in Laminar Visual Cortical Circuits

Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such groupings. Recent psychophysical and neurophysiological evidence have shown that the grouping process can facilitate rapid synchronization of the cells that are bound together by a grouping, even when the grouping must be completed across regions that receive no contrastive inputs. Synchronous grouping can hereby bind together different object parts that may have become desynchronized due to a variety of factors, and can enhance the efficiency of cortical transmission. Neural models of perceptual grouping have clarified how such fast synchronization may occur by using bipole grouping cells, whose predicted properties have been supported by psychophysical, anatomical, and neurophysiological experiments. These models have not, however, incorporated some of the realistic constraints on which groupings in the brain are conditioned, notably the measured spatial extent of long-range interactions in layer 2/3 of a grouping network, and realistic synaptic and axonal signaling delays within and across cells in different cortical layers. This work addresses the question: Can long-range interactions that obey the bipole constraint achieve fast synchronization under realistic anatomical and neurophysiological constraints that initially desynchronize grouping signals? Can the cells that synchronize retain their analog sensitivity to changing input amplitudes? Can the grouping process complete and synchronize illusory contours across gaps in bottom-up inputs? Our simulations show that the answer to these questions is Yes.

Spiking Dynamics during Perceptual Grouping in the Laminar Circuits of Visual Cortex

Grouping of collinear boundary contours is a fundamental process during visual perception. Illusory contour completion vividly illustrates how stable perceptual boundaries interpolate between pairs of contour inducers, but do not extrapolate from a single inducer. Neural models have simulated how perceptual grouping occurs in laminar visual cortical circuits. These models predicted the existence of grouping cells that obey a bipole property whereby grouping can occur inwardly between pairs or greater numbers of similarly oriented and co-axial inducers, but not outwardly from individual inducers. These models have not, however, incorporated spiking dynamics. Perceptual grouping is a challenge for spiking cells because its properties of collinear facilitation and analog sensitivity to inducer configurations occur despite irregularities in spike timing across all the interacting cells. Other models have demonstrated spiking dynamics in laminar neocortical circuits, but not how perceptual grouping occurs. The current model begins to unify these two modeling streams by implementing a laminar cortical network of spiking cells whose intracellular temporal dynamics interact with recurrent intercellular spiking interactions to quantitatively simulate data from neurophysiological experiments about perceptual grouping, the structure of non-classical visual receptive fields, and gamma oscillations.

A Neural Model of 3D Shape-From-Texture: Multiple-Scale Filtering, Boundary Grouping, and Surface Filling-In

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids (Todd and Akerstrom, 1987, J. Exp. Psych., 13, 242). In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.

Decadal basin-scale changes in diatoms, dinoflagellates, and phytoplankton color across the North Atlantic

The Continuous Plankton Recorder (CPR) survey has been used to characterize phytoplankton and zooplankton space-time dynamics in the North Sea since 1931 and in the North Atlantic since 1939. Phytoplankton biomass is assessed from these samples by visual assessment of the green color of the silk mesh, the Phytoplankton Color Index (PCI), and the total count of diatoms and dinoflagellates. Species with a frequency of occurrence greater than 1% in the samples are used as indicator species of the community. We investigated (1) long-term fluctuations of phytoplankton biomass, total diatoms, and total dinoflagellates; (2) geographical variation of patterns; (3) the relationship between phytoplankton and climate forcing in the North Atlantic CPR samples; (4) the relative contribution of diatoms and dinoflagellates to the PCI; and (5) the fluctuations of the dominant species over the period of survey to provide more information on the processes linking climate to changes in the phytoplankton community. As a result of the differences in microscopic analysis methods prior to 1958, our analyses were conducted for the period ranging from 1958 to 2002. The North Atlantic was divided into six regions identified through bathymetric criteria and separated along a North-South axis. Based on 12 monthly time series, we demonstrate increasing trends in PCI and total dinoflagellates and a decrease in total diatoms.

Ten Year Performance Evaluation of a Field-Scale Zero-Valent Iron Permeable Reactive Barrier Installed to Remediate Trichloroethene Contaminated Groundwater

The Monkstown Fe0 PRB, Europe’s oldest commercially installed PRB, had been treating trichloroethene (TCE) contaminated groundwater for about 10 years on the Nortel Network site in Northern Ireland when cores were collected in December, 2006. Groundwater data from 2001-2006 indicated that TCE is being remediated to below detection limits as the contaminated groundwater flows through the PRB, Ca and Fe carbonates, crystalline and amorphous FeS, and Fe (oxy)hydroxides precipitates are present in the Fe0 filing material within the PRB. A greater variety of minerals are associated with a 1 cm thick slightly cemented crust at the entrance of the Fe0 section of the reactive vessel and the discontinuous cemented Fe0 material directly below it. Also, a greater presence of microbial communities occurred in the upper portion of the PRB compared to the lower section which might be due to less favourable conditions (i.e. high pH, low oxygen) for microbial growth in the lower section of the PRB. Visual estimation suggests that the Fe0 filings in the effluent section of the PRB have life-span of 10+ years compared to the Fe0 filings in the thin influent section of the PRB which may have a life span of only ~2-5 more years. Multi-tracer tests indicated that preferential pathways have formed in this PRB over the 10 years of operation.

Help needed in medication self-management for people with visual impairment: case-control study

Background: Visual impairment (VI) is rising in prevalence and contributing to increasing morbidity, particularly among older people. Understanding patients' problems is fundamental to achieving optimal health outcomes but little is known about how VI impacts on self-management of medication.

Aim: To compare issues relating to medication self-management between older people with and without VI.

Design and setting: Case-control study with participants aged =65 years, prescribed at least two long-term oral medications daily, living within the community.

Method: The study recruited 156 patients with VI (best corrected visual acuity [BCVA] 6/18 to 3/60) at low-vision clinics; community optometrists identified 158 controls (BCVA 6/9 or better). Researchers visited participants in their homes, administered two validated questionnaires to assess medication adherence (Morisky; Medication Adherence Report Scale [MARS]), and asked questions about medication self-management, beliefs, and support.

Results: Approximately half of the participants in both groups reported perfect adherence on both questionnaires (52.5% Morisky; 43.3%, MARS). Despite using optical aids, few (3%) with VI could read medication information clearly; 24% had difficulty distinguishing different tablets. More people with VI (29%) than controls (13%) (odds ratio [OR] = 2.8; 95% confidence interval [CI] = 1.6 to 5.0) needed help managing their medication, from friends (19% versus 10%) or pharmacists (10% versus 2.5%; OR = 4.4, 95% CI = 1.4 to 13.5); more received social service support (OR = 7.1; 95% CI = 3.9 to 12.9).

Conclusion: Compared to their peers without VI, older people with VI are more than twice as likely to need help in managing medication. In clinical practice in primary care, patients' needs for practical support in taking prescribed treatment must be recognised. Strategies for effective medication self-management should be explored.