10,392 research outputs found

    Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis

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    The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing progress over the last few decades and has generated considerable interest in the autonomous driving community. With its conceptual roots in navigation and mapping, SLAM outperforms some traditional positioning and localization techniques since it can support more reliable and robust localization, planning, and controlling to meet some key criteria for autonomous driving. In this study the authors first give an overview of the different SLAM implementation approaches and then discuss the applications of SLAM for autonomous driving with respect to different driving scenarios, vehicle system components and the characteristics of the SLAM approaches. The authors then discuss some challenging issues and current solutions when applying SLAM for autonomous driving. Some quantitative quality analysis means to evaluate the characteristics and performance of SLAM systems and to monitor the risk in SLAM estimation are reviewed. In addition, this study describes a real-world road test to demonstrate a multi-sensor-based modernized SLAM procedure for autonomous driving. The numerical results show that a high-precision 3D point cloud map can be generated by the SLAM procedure with the integration of Lidar and GNSS/INS. Online four–five cm accuracy localization solution can be achieved based on this pre-generated map and online Lidar scan matching with a tightly fused inertial system

    Efficient algorithms to solve atom reconfiguration problems. II. The assignment-rerouting-ordering (aro) algorithm

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    Programmable arrays of optical traps enable the assembly of configurations of single atoms to perform controlled experiments on quantum many-body systems. Finding the sequence of control operations to transform an arbitrary configuration of atoms into a predetermined one requires solving an atom reconfiguration problem quickly and efficiently. A typical approach to solve atom reconfiguration problems is to use an assignment algorithm to determine which atoms to move to which traps. This approach results in control protocols that exactly minimize the number of displacement operations; however, this approach does not optimize for the number of displaced atoms nor the number of times each atom is displaced, resulting in unnecessary control operations that increase the execution time and failure rate of the control protocol. In this work, we propose the assignment-rerouting-ordering (aro) algorithm to improve the performance of assignment-based algorithms in solving atom reconfiguration problems. The aro algorithm uses an assignment subroutine to minimize the total distance traveled by all atoms, a rerouting subroutine to reduce the number of displaced atoms, and an ordering subroutine to guarantee that each atom is displaced at most once. The ordering subroutine relies on the existence of a partial ordering of moves that can be obtained using a polynomial-time algorithm that we introduce within the formal framework of graph theory. We numerically quantify the performance of the aro algorithm in the presence and in the absence of loss, and show that it outperforms the exact, approximation, and heuristic algorithms that we use as benchmarks. Our results are useful for assembling large configurations of atoms with high success probability and fast preparation time, as well as for designing and benchmarking novel atom reconfiguration algorithms.Comment: 26 pages, 10 figure

    Energy properness and Sasakian-Einstein metrics

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    In this paper, we show that the existence of Sasakian-Einstein metrics is closely related to the properness of corresponding energy functionals. Under the condition that admitting no nontrivial Hamiltonian holomorphic vector field, we prove that the existence of Sasakian-Einstein metric implies a Moser-Trudinger type inequality. At the end of this paper, we also obtain a Miyaoka-Yau type inequality in Sasakian geometry.Comment: 27 page

    Interleukin-17A promotes parietal cell atrophy by inducing apoptosis

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    Background & Aims: Atrophic gastritis caused by chronic inflammation in the gastric mucosa leads to the loss of gastric glandular cells, including acid-secreting parietal cells. Parietal cell atrophy in a setting of chronic inflammation induces spasmolytic polypeptide expressing metaplasia, a critical step in gastric carcinogenesis. However, the mechanisms by which inflammation causes parietal cell atrophy and spasmolytic polypeptide expressing metaplasia are not well defined. We investigated the role of interleukin-17A (IL-17A) in causing parietal cell atrophy. Methods: A mouse model of autoimmune atrophic gastritis was used to examine IL-17A production during early and late stages of disease. Organoids derived from corpus glands were used to determine the direct effects of IL-17A on gastric epithelial cells. Immunofluorescent staining was used to examine IL-17A receptors and the direct effect of signaling on parietal cells. Mice were infected with an IL-17A-producing adenovirus to determine the effects of IL-17A on parietal cells in vivo. Finally, IL-17A neutralizing antibodies were administered to mice with active atrophic gastritis to evaluate the effects on parietal cell atrophy and metaplasia. Results: Increased IL-17A correlated with disease severity in mice with chronic atrophic gastritis. IL-17A caused caspase-dependent gastric organoid degeneration, which could not be rescued with a necroptosis inhibitor. Parietal cells expressed IL-17A receptors and IL-17A treatment induced apoptosis in parietal cells. Overexpressing IL-17A in vivo induced caspase-3 activation and terminal deoxynucleotidyl transferase–mediated deoxyuridine triphosphate nick-end labeling staining in parietal cells. Finally, IL-17A neutralizing antibody decreased parietal cell atrophy and metaplasia in mice with chronic atrophic gastritis. Conclusions: These data identify IL-17A as a cytokine that promotes parietal cell apoptosis during atrophic gastritis, a precursor lesion for gastric cancer. Keywords: IL-17A, Atrophy, Metaplasia, Apoptosi

    rac-(3S,4S)-3-Hy­droxy-4-phenyl-1-[(S)-(3-phenyl-4,5-dihydro-1,2-oxazol-5-yl)meth­yl]-4,5-dihydro-1H-1,5-benzo­diazepin-2(3H)-one

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    In the title compound, C25H23N3O3, the seven-membered diazepine ring adopts a boat conformation with the hydroxy-substituted C atom at the prow and fused-ring C atoms at the stern. The crystal packing features C—H⋯O, C—H⋯π and N—H ⋯π inter­action

    Fatigue evaluation in maintenance and assembly operations by digital human simulation

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    Virtual human techniques have been used a lot in industrial design in order to consider human factors and ergonomics as early as possible. The physical status (the physical capacity of virtual human) has been mostly treated as invariable in the current available human simulation tools, while indeed the physical capacity varies along time in an operation and the change of the physical capacity depends on the history of the work as well. Virtual Human Status is proposed in this paper in order to assess the difficulty of manual handling operations, especially from the physical perspective. The decrease of the physical capacity before and after an operation is used as an index to indicate the work difficulty. The reduction of physical strength is simulated in a theoretical approach on the basis of a fatigue model in which fatigue resistances of different muscle groups were regressed from 24 existing maximum endurance time (MET) models. A framework based on digital human modeling technique is established to realize the comparison of physical status. An assembly case in airplane assembly is simulated and analyzed under the framework. The endurance time and the decrease of the joint moment strengths are simulated. The experimental result in simulated operations under laboratory conditions confirms the feasibility of the theoretical approach
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