151,095 research outputs found

    Evolution of a Monomer Concentration Field in a Micro-Fluidic Channel

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    The purpose of this research is to determine how long a micro-channel could be in the production of Non-Linear Optical Thin Film Wave-Guides. In determining this length, it is necessary to compute the monomer diffusion process between two solutions of monomers in a micro channel flow. Two models of this flow were created, the first with no flow in a one dimensional channel making diffusion a function of time and position and the second of flow in a two dimensional channel with an imposed velocity profile. Using these models it was determined that the micro channel could be the longest if there was an imposed velocity profile. This velocity caused the forced convection process to dominate over pure diffusion. The simple model can be easily computed and plotted. Unfortunately the complex model requires the solution of a partial differential equation that is not easily solvable using the technique of separation of variables. This technique requires the numerical solution of an eigenfunction problem through the method of Finite Elements and the determination of the coefficients in a Fourier series. The numerical solution is found using the computer programs Mathematica and MatLab. Using these techniques the concentration of monomers was determined throughout the micro channel for both models

    Spontaneous Subtle Expression Detection and Recognition based on Facial Strain

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    Optical strain is an extension of optical flow that is capable of quantifying subtle changes on faces and representing the minute facial motion intensities at the pixel level. This is computationally essential for the relatively new field of spontaneous micro-expression, where subtle expressions can be technically challenging to pinpoint. In this paper, we present a novel method for detecting and recognizing micro-expressions by utilizing facial optical strain magnitudes to construct optical strain features and optical strain weighted features. The two sets of features are then concatenated to form the resultant feature histogram. Experiments were performed on the CASME II and SMIC databases. We demonstrate on both databases, the usefulness of optical strain information and more importantly, that our best approaches are able to outperform the original baseline results for both detection and recognition tasks. A comparison of the proposed method with other existing spatio-temporal feature extraction approaches is also presented.Comment: 21 pages (including references), single column format, accepted to Signal Processing: Image Communication journa

    Label-free high-throughput photoacoustic tomography of suspected circulating melanoma tumor cells in patients in vivo

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    Significance: Detection and characterization of circulating tumor cells (CTCs), a key determinant of metastasis, are critical for determining risk of disease progression, understanding metastatic pathways, and facilitating early clinical intervention. Aim: We aim to demonstrate label-free imaging of suspected melanoma CTCs. Approach: We use a linear-array-based photoacoustic tomography system (LA-PAT) to detect melanoma CTCs, quantify their contrast-to-noise ratios (CNRs), and measure their flow velocities in most of the superficial veins in humans. Results: With LA-PAT, we successfully imaged suspected melanoma CTCs in patients in vivo, with a CNR >9. CTCs were detected in 3 of 16 patients with stage III or IV melanoma. Among the three CTC-positive patients, two had disease progression; among the 13 CTC-negative patients, 4 showed disease progression. Conclusions: We suggest that LA-PAT can detect suspected melanoma CTCs in patients in vivo and has potential clinical applications for disease monitoring in melanoma

    A Neural Model of How the Brain Computes Heading from Optic Flow in Realistic Scenes

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    Animals avoid obstacles and approach goals in novel cluttered environments using visual information, notably optic flow, to compute heading, or direction of travel, with respect to objects in the environment. We present a neural model of how heading is computed that describes interactions among neurons in several visual areas of the primate magnocellular pathway, from retina through V1, MT+, and MSTd. The model produces outputs which are qualitatively and quantitatively similar to human heading estimation data in response to complex natural scenes. The model estimates heading to within 1.5° in random dot or photo-realistically rendered scenes and within 3° in video streams from driving in real-world environments. Simulated rotations of less than 1 degree per second do not affect model performance, but faster simulated rotation rates deteriorate performance, as in humans. The model is part of a larger navigational system that identifies and tracks objects while navigating in cluttered environments.National Science Foundation (SBE-0354378, BCS-0235398); Office of Naval Research (N00014-01-1-0624); National-Geospatial Intelligence Agency (NMA201-01-1-2016

    A spectral optical flow method for determining velocities from digital imagery

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    We present a method for determining surface flows from solar images based upon optical flow techniques. We apply the method to sets of images obtained by a variety of solar imagers to assess its performance. The {\tt opflow3d} procedure is shown to extract accurate velocity estimates when provided perfect test data and quickly generates results consistent with completely distinct methods when applied on global scales. We also validate it in detail by comparing it to an established method when applied to high-resolution datasets and find that it provides comparable results without the need to tune, filter or otherwise preprocess the images before its application.Comment: 12 pages, 5 figures. Submitted to Earth Science Informatic

    Quasi full-disk maps of solar horizontal velocities using SDO/HMI data

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    For the first time, the motion of granules (solar plasma on the surface on scales larger than 2.5 Mm) has been followed over the entire visible surface of the Sun, using SDO/HMI white-light data. Horizontal velocity fields are derived from image correlation tracking using a new version of the coherent structure tracking algorithm.The spatial and temporal resolutions of the horizontal velocity map are 2.5 Mm and 30 min respectively . From this reconstruction, using the multi-resolution analysis, one can obtain to the velocity field at different scales with its derivatives such as the horizontal divergence or the vertical component of the vorticity. The intrinsic error on the velocity is ~0.25 km/s for a time sequence of 30 minutes and a mesh size of 2.5 Mm.This is acceptable compared to the granule velocities, which range between 0.3 km/s and 1.8 km/s. A high correlation between velocities computed from Hinode and SDO/HMI has been found (85%). From the data we derive the power spectrum of the supergranulation horizontal velocity field, the solar differential rotation, and the meridional velocity.Comment: 8 pages, 11 figures, accepted in Astronomy and Astrophysic
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