Central to the humoral theory of transplantation is production of antibodies by the recipient against mismatched HLA antigens in the donor organ. Not all mismatches result in antibody production, however, and not all ...
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Central to the humoral theory of transplantation is production of antibodies by the recipient against mismatched HLA antigens in the donor organ. Not all mismatches result in antibody production, however, and not all antibodies are pathogenic. Serologic HLA matching has been the standard for solid organ allocation algorithms in current use. Antibodies do not recognize whole HLA molecules but rather polymorphic residues on the surface, called epitopes, which may be shared by multiple serologic HLA antigens. Data are accumulating that epitope analysis may be a better way to determine organ compatibility as well as the potential immunogenicity of given HLA mismatches. Determination of the pathogenicity of alloantibodies is evolving. Potential features include antibody strength (as assessed by antibody titer or, more commonly and inappropriately, mean fluorescence intensity) and ability to fix complement (in vitro by C1q or C3d assay or by IgG subclass analysis). Technical issues with the use of solid phase assays are also of prime importance, such as denaturation of HLA antigens and manufacturing and laboratory variability. Questions and controversies remain, and here we review new relevant data.
The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variati...
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The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use.
Objective: To demonstrate the feasibility of using X-ray phase-contrast tomography to assess internal organs in a post-mortem piglet model, as a possible non-invasive imaging autopsy technique. Methods: Tomographic im...
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Objective: To demonstrate the feasibility of using X-ray phase-contrast tomography to assess internal organs in a post-mortem piglet model, as a possible non-invasive imaging autopsy technique. Methods: Tomographic images of a new-born piglet were obtained using a free-space propagation X-ray phase-contrast imaging setup at a synchrotron (European Synchrotron Radiation Facility, Grenoble, France). A monochromatic X-ray beam (52 keV) was used in combination with a detector pixel size of 46 x 46 mm(2). A phase-retrieval algorithm was applied to all projections, which were then reconstructed into tomograms using the filtered-back projection algorithm. Images were assessed for diagnostic quality. Results: Images obtained with the free-space propagation setup presented high soft-tissue contrast and sufficient resolution for resolving organ structure. All of the main body organs (heart, lungs, kidneys, liver and intestines) were easily identified and adequately visualized. In addition, grey/white matter differentiation in the cerebellum while still contained within the skull was shown. Conclusion: The feasibility of using X-ray phase-contrast tomography as a post-mortem imaging technique in an animal model has been demonstrated. Future studies will focus on translating this experiment to a laboratory-based setup. Advances in knowledge: Appropriate image processing and analysis enable the simultaneous visualization of both soft-and hard-tissue structures in X-ray phase-contrast images of a complex, thick sample.
A new restoration algorithm for partial blurred image which is based on blur detection and classification is proposed in this paper. Firstly, a new blur detection algorithm is proposed to detect the blurred regions in...
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A new restoration algorithm for partial blurred image which is based on blur detection and classification is proposed in this paper. Firstly, a new blur detection algorithm is proposed to detect the blurred regions in the partial blurred image. Then, a new blur classification algorithm is proposed to classify the blurred regions. Once the blur class of the blurred regions is confirmed, the structure of the blur kernels of the blurred regions is confirmed. Then, the blur kernel estimation methods are adopted to estimate the blur kernels. In the end, the blurred regions are restored using nonblind image deblurring algorithm and replace the blurred regions in the partial blurred image with the restored regions. The simulated experiment shows that the proposed algorithm performs well.
This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of pa...
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This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of parameters and unmodeled dynamics, the quadruped robot always faces some disturbances. The uncertainties and disturbances contribute significant perturbation to the dynamic gait motion control of the quadruped robot. Failing to track the gait pattern properly propagates instability to the whole system and can cause the robot to fall. To overcome the uncertainties and disturbances, structured specified mixed sensitivity H-infinity robust controller was proposed to control the quadruped robot legs' joint angle positions. Before application to the real hardware, the proposed controller was tested on the quadruped robot's leg planar dynamic model using MATLAB. The proposed controller can control the robot's legs efficiently even under uncertainties from a set of model parameter variations. The robot was also able to maintain its stability even when it was tested under several terrain disturbances.
Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images...
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Modern instrumentation provides us with massive repositories of digital images that will likely only increase in the future. Therefore, it has become increasingly important to automatize the analysis of digital images, e.g., with methods from pattern recognition. These methods aim to quantify the visual appearance of captured textures with quantitative measures. As such, lacunarity is a useful multi-scale measure of texture's heterogeneity but demands high computational efforts. Here we investigate a novel approach based on the tug-of-war algorithm, which estimates lacunarity in a single pass over the image. We computed lacunarity for theoretical and real world sample images, and found that the investigated approach is able to estimate lacunarity with low uncertainties. We conclude that the proposed method combines low computational efforts with high accuracy, and that its application may have utility in the analysis of high-resolution images. (C) 2016 Author(s).
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