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This study provides the foundation and insights for future research on the potential use of Hutat2 Fc as a novel gene therapy approach for HAND through utilizing monocytes/macrophages, which naturally cross the blood-brain barrier, for gene delivery.
The common approach for hand posture characterization is based on descriptors like Hu moments [6], Zernike moments [7], and Fourier descriptors [8, 9].
Secondly, we have improved the recognition performances especially for very similar postures by proposing an approach for hand posture characterization, which involves an original signature developed in [3] and improved in [4].
Thus, identifying this novel negative regulatory feedback loop involving RelB could be particularly useful as an adjunctive therapeutic approach for HAND, peripheral HIV infection, or even other neurologic or immune diseases, since overexpression of RelB in microglial cells does not completely block Tat-induced release of TNFα, which would negatively impact TNFα's other endogenous functions.
Brachial plexus block with axillary approach for hand and forearm surgery is commonly used.
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Lim et al. [21] describe an approach for hand-written Chinese character recognition, in which high-level signal features are constructed using the explanation-based learning (EBL) framework.
This article presents an augmented reality home-training system based on the mirror and imagery treatment approaches for hand training.
Many of today's recognition approaches for hand-drawn sketches are feature-based, which is conceptually similar to the recognition of hand-written text.
We propose a novel approach for articulated hand pose estimation from a single depth image using a very deep convolutional network.
Eventually, by introducing a novel design approach for robotic hands, this work will lay the groundwork to improve hand performance across multiple robotic disciplines, pushing the boundaries of robotic hand capabilities.
Eventually, by introducing a novel design approach for robotic hands, this work will lay the necessary groundwork to improve hand performance across multiple robotic disciplines, pushing the boundaries of robotic hand capabilities.
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