Journal of Inorganic and Organometallic Polymers and Materials - Due to their excellent properties, polymides (PIs) result promising as high-performance materials in different technological fields.... 相似文献
Food Science and Biotechnology - The anti-inflammatory effects of mung bean protein hydrolysate (MBPH) on the lipopolysaccharide (LPS)-induced macrophages were investigated herein. MBPH was shown... 相似文献
Catalysis Letters - It is crucial to explore a facile synthesis of rutile TiO2 nanorods anchored at carbon cloth at low temperature for applicable air purifier. Herein, antler-like TiO2 rectangular... 相似文献
This paper aims to find a reliable, collision-free path in a dynamic environment for highly maneuverable unmanned combat air vehicles (UCAVs). Given the real-time nature of the operational scenario, quick and adaptable reactions of UCAVs are necessary for updates in situational awareness. Therefore, we propose a three dimensional (3D) path planning approach based on the situational space to provide the tactical requirements of UCAVs for tracking targets and avoiding collisions. First, to ensure reliable nonlinear measurements, the interacting multiple model (IMM) algorithm based on a cubature Kalman filter (CKF) is chosen for the tracking and prediction algorithm. A constraint reference frame combining the kinematic model of constant acceleration (CA) is developed to solve the problem of arrival point generation. Second, by analyzing the relative motion between the UCAV and the moving objects, we define the situation space and give the corresponding calculation method. In tracking the moving target, the guidance vector contains the fusion information of displacement and velocity. At the same time, taking advantage of the one-step situation space as the judgment of the threat, we further plan the collision avoidance strategy. Third, as the safety in a practically reachable trajectory of the UCAV possesses the absolute priority, the collision avoidance acceleration accounts for this dominant factor in path planning. Simulations and experimental results prove that the proposed approach can plan a smooth and flyable path in 0.008 s under the premise of soft-landing target tracking. 相似文献
Because of its ability to change optical absorption dynamically by applied electric field, nickel oxide (NiO) is a promising anodic material in smart windows, which can improve energy conversion efficiency in construction buildings. Although many works have achieved high electrochromic performance with different method. The underlying mechanism is still not fully investigated. In this article, we prepared the NiO films with large specific surface area and high stability by electron beam evaporation. X-ray diffraction (XRD), scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) were employed to figure out the surface morphology and composition of as-deposited films. Afterwards, the electrochemical properties and optical performance of the prepared NiO films were investigated. On this basis, the origin of surface charge was fully analyzed by cyclic voltammetry and diffusion coefficient test. These experimental and theoretical results firmly confirm that both the surface reaction and capacitive effect bring about the excellent EC performance in NiO films. These results not only provide clear evidence about electrochemical kinetics in NiO films, but also offer some useful guidelines for the design of EC materials with higher performance and longer stability. 相似文献
Recently, deep learning, especially convolutional neural networks, has achieved the remarkable results in natural image classification and segmentation. At the same time, in the field of medical image segmentation, researchers use deep learning techniques for tasks such as tumor segmentation, cell segmentation, and organ segmentation. Automatic tumor segmentation plays an important role in radiotherapy and clinical practice and is the basis for the implementation of follow-up treatment programs. This paper reviews the tumor segmentation methods based on deep learning in recent years. We first introduce the common medical image types and the evaluation criteria of segmentation results in tumor segmentation. Then, we review the tumor segmentation methods based on deep learning from technique view and tumor view, respectively. The technique view reviews the researches from the architecture of the deep learning and the tumor view reviews from the type of tumors.