3,118 research outputs found

    α-Tocopheryl succinate inhibits angiogenesis by disrupting paracrine FGF2 signalling

    Get PDF
    AbstractMalignant mesothelioma (MM) cells enhanced proliferation of endothelial cells (ECs) as well as their angiogenesis in vitro by secretion of fibroblast growth factor-2 (FGF2). This effect was suppressed by pre-treating MM cells with α-tocopheryl succinate (α-TOS), which inhibited FGF2 secretion by inducing mitochondria-dependent generation of reactive oxygen species. The role of FGF2 was confirmed by its down-regulation by treating MM cells with siRNA, abolishing EC proliferation and wound healing enhancement afforded by MM cells. We conclude that α-TOS disrupts angiogenesis mediated by MM cells by inhibiting FGF2 paracrine signalling

    Gravitation Field Algorithm with Optimal Detection for Unconstrained Optimization

    Get PDF
    This work is supported by the National Natural Science Foundation of China (Grant Nos. 61472159, 61572227), Development Project of Jilin Province of China (Nos. 20160204022GX, 20160414009GH, 2017C033).Postprin

    Integrated WiFi/PDR/Smartphone using an unscented Kalman filter algorithm for 3D indoor localization

    Get PDF
    Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone’s acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals

    Linkage between surface energy balance non‐closure and horizontal asymmetric turbulent transport

    Get PDF
    A number of studies have reported that the traditional eddy covariance (EC) method generally underestimated vertical turbulent fluxes, leading to an outstanding non-closure problem of the surface energy balance (SEB). Although it is recognized that the enlarged surface energy imbalance frequently coincides with the increasing wind shear, the role of large eddies in affecting the SEB remains unclear. On analyzing data collected by an EC array, considerable horizontal inhomogeneity of kinematic heat flux is observed. The results show that the combined EC method that incorporates the spatial flux contribution increases the kinematic heat flux by 21% relative to the traditional EC method, improving the SEB closure. Additionally, spectral analysis indicates that large eddies with scales ranging from 0.0005 to 0.01 (in the normalized frequency) mainly account for the horizontal inhomogeneity of kinematic heat flux. Under unstable conditions, this process is operating upon large eddies characterized by enlarged asymmetric turbulent flux transport. With enhanced wind shear, the increment of flux contribution associated with sweeps and ejections becomes disproportionate, contributing to the horizontal inhomogeneity of kinematic heat flux, and thus may explain the increased SEB non-closure

    Bridging Trustworthiness and Open-World Learning: An Exploratory Neural Approach for Enhancing Interpretability, Generalization, and Robustness

    Full text link
    As researchers strive to narrow the gap between machine intelligence and human through the development of artificial intelligence technologies, it is imperative that we recognize the critical importance of trustworthiness in open-world, which has become ubiquitous in all aspects of daily life for everyone. However, several challenges may create a crisis of trust in current artificial intelligence systems that need to be bridged: 1) Insufficient explanation of predictive results; 2) Inadequate generalization for learning models; 3) Poor adaptability to uncertain environments. Consequently, we explore a neural program to bridge trustworthiness and open-world learning, extending from single-modal to multi-modal scenarios for readers. 1) To enhance design-level interpretability, we first customize trustworthy networks with specific physical meanings; 2) We then design environmental well-being task-interfaces via flexible learning regularizers for improving the generalization of trustworthy learning; 3) We propose to increase the robustness of trustworthy learning by integrating open-world recognition losses with agent mechanisms. Eventually, we enhance various trustworthy properties through the establishment of design-level explainability, environmental well-being task-interfaces and open-world recognition programs. These designed open-world protocols are applicable across a wide range of surroundings, under open-world multimedia recognition scenarios with significant performance improvements observed
    corecore