155 research outputs found

    Study on the Development Strategy of China’s Health Care Industry from the Perspective of Active Ageing: Based on Public Cognition Survey

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    With an aging population currently posing a challenge, China must accelerate the construction of a health development model with "prevention as the main focus" from the perspective of active aging. This development requirement is exactly met by the growth of health care industry, which is highly significant strategically to cope with the dual challenges of aging populations and public health issues. The study construct an evaluation index system of influencing factors for the development of health care industry, and further empirically analyse the influencing factors of China’s health care industry by using Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM), and calculate the relative importance weights of 18 influencing factors of perceptual indicators under the four levels of economy, environment, products and individuals. Lastly, countermeasures are made for the superior growth of China’s health care industry based on the results of the weighing analysis

    Top-Down Structure and Device Fabrication using \u3ci\u3eIn Situ\u3c/i\u3e Nanomachining

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    We demonstrate the potential of an alternative tool for the fabrication of nanoscale structures and devices. A nanoindenter integrated with an atomic force microscope is shown to be a powerful machine tool for cutting precise length nanowires or nanobelts and for manipulating the shortened wires. We also demonstrate its utility in cutting grooves and fabricating dents (or periodic arrays of dents) in ZnSnanobelts. This approach permits the direct mechanical machining of nanodevices that are supported on a substrate without the inherent complications of e beam or photolithography

    Tobacco Mosaic Virus Templated Synthesis of One Dimensional Inorganic-Polymer Hybrid Fibres

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    Inorganic–polymer hybrid nanofibres were prepared by using a rod-like tobacco mosaic virus (TMV) as a template. With tetraethylorthosilicate (TEOS) as a precursor, long silica-coated TMVfibres were formed via a head-to-tail assembly, which showed a substantial increase of the elastic modulus. Furthermore, homogenous titania–TMV hybrid fibres could be prepared using polyaniline-coated TMV fibres as a template, which were used to form a composite film that was able to sense liquefied petroleum gases

    Tobacco Mosaic Virus Templated Synthesis of One Dimensional Inorganic–Polymer Hybrid Fibres

    Get PDF
    Inorganic–polymer hybrid nanofibres were prepared by using a rod-like tobacco mosaic virus (TMV) as a template. With tetraethylorthosilicate (TEOS) as a precursor, long silica-coated TMVfibres were formed via a head-to-tail assembly, which showed a substantial increase of the elastic modulus. Furthermore, homogenous titania–TMV hybrid fibres could be prepared using polyaniline-coated TMV fibres as a template, which were used to form a composite film that was able to sense liquefied petroleum gases

    Effect of Tensile Offset Angles on Micro/Nanoscale Tensile Testing

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    For one-dimensional (1D) structures such as tubes, wires, and beams, tensile testing is a simple and reliable methodology for measuring their mechanical properties. The tensile offset angle effect on mechanical property measurement has long been ignored. In this study, theoretical and finite-element analysis(FEA) models for analyzing the tensile offset angle effect have been established. It is found that longitudinal stress decreases with increasing offset angles. The theoretically calculated elastic modulus relative errors reach 4.45% at the offset angle of 10°, whereas the experimentally measured elastic modulus relative errors are 45.4% at the offset angle of 15°. The difference in elastic modulus relative errors between the theoreticalanalysis and the experimental results is discussed with reference to the sensing system in the experimental instrumentation. To accurately measure the mechanical properties using the tensile testing technique, perfect alignment with a zero or small offset angle less than 5° is needed. A calibration methodology for aligning specimens has been developed

    SkyLens: Visual analysis of skyline on multi-dimensional data

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    Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.Comment: 10 pages. Accepted for publication at IEEE VIS 2017 (in proceedings of VAST

    A Bioinspired Neural Model Based Extended Kalman Filter for Robot SLAM

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    Robot simultaneous localization and mapping (SLAM) problem is a very important and challenging issue in the robotic field. The main tasks of SLAM include how to reduce the localization error and the estimated error of the landmarks and improve the robustness and accuracy of the algorithms. The extended Kalman filter (EKF) based method is one of the most popular methods for SLAM. However, the accuracy of the EKF based SLAM algorithm will be reduced when the noise model is inaccurate. To solve this problem, a novel bioinspired neural model based SLAM approach is proposed in this paper. In the proposed approach, an adaptive EKF based SLAM structure is proposed, and a bioinspired neural model is used to adjust the weights of system noise and observation noise adaptively, which can guarantee the stability of the filter and the accuracy of the SLAM algorithm. The proposed approach can deal with the SLAM problem in various situations, for example, the noise is in abnormal conditions. Finally, some simulation experiments are carried out to validate and demonstrate the efficiency of the proposed approach
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