18,381 research outputs found

    Wavelength scaling of high-order harmonic yield from an optically prepared excited state atom

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    Wavelength scaling law for the yield of high-order harmonic emission is theoretically examined for excited state atoms which are optically prepared by simultaneously exposing to an extreme ultraviolet pulse at the resonant wavelength and an infrared pulse at a variable wavelength in the range of 0.8\mum-2.4\mum. Numerical simulations are performed based on the three-dimensional time-dependent Schrodinger equation (3D TDSE) for Ne and H. We confirm that the harmonic yield follows a \lambda^-{4-6} scaling with the single fundamental driving laser pulse; whereas for the optically prepared excited state atoms, a \lambda^-{2-3} scaling for the harmonic yield is revealed.Comment: 20 pages, 3 figure

    Magnetic-field induced resistivity minimum with in-plane linear magnetoresistance of the Fermi liquid in SrTiO3-x single crystals

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    We report novel magnetotransport properties of the low temperature Fermi liquid in SrTiO3-x single crystals. The classical limit dominates the magnetotransport properties for a magnetic field perpendicular to the sample surface and consequently a magnetic-field induced resistivity minimum emerges. While for the field applied in plane and normal to the current, the linear magnetoresistance (MR) starting from small fields (< 0.5 T) appears. The large anisotropy in the transverse MRs reveals the strong surface interlayer scattering due to the large gradient of oxygen vacancy concentration from the surface to the interior of SrTiO3-x single crystals. Moreover, the linear MR in our case was likely due to the inhomogeneity of oxygen vacancies and oxygen vacancy clusters, which could provide experimental evidences for the unusual quantum linear MR proposed by Abrikosov [A. A. Abrikosov, Phys. Rev. B 58, 2788 (1998)].Comment: 5 pages, 4 figure

    Metallic state in La-doped YBa2_2Cu3_3Oy_y thin films with nn-type charge carriers

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    We report hole and electron doping in La-doped YBa2_2Cu3_3Oy_y(YBCO) thin films synthesized by pulsed laser deposition technique and subsequent \emph{in-situ} postannealing in oxygen ambient and vaccum. The nn-type samples show a metallic behavior below the Mott limit and a high carrier density of 2.8\sim2.8 ×\times 1021^{21} cm3^{-3} at room temperature (\emph{T}) at the optimally reduced condition. The in-plane resistivity (ρ\rhoab_{ab}) of the nn-type samples exhibits a quadratic \emph{T} dependence in the moderate-\emph{T} range and shows an anomaly at a relatively higher \emph{T} probably related to pseudogap formation analogous to underdoped Nd2x_{2-x}Cex_xCuO4_4 (NCCO). Furthermore, ρ\rhoab_{ab}(T), \emph{T}c_c and \emph{T} with minimum resistivity (\emph{T}min_{min}) were investigated in both pp- and nn-side. The present results reveal the nn-pp asymmetry (symmetry) within the metallic-state region in an underdoped cuprate and suggest the potential toward ambipolar superconductivity in a single YBCO system.Comment: 4 pages, 5 figure

    Intelligent Tennis Robot Based on a Deep Neural Network

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    In this paper, an improved you only look once (YOLOv3) algorithm is proposed to make the detection effect better and improve the performance of a tennis ball detection robot. The depth-separable convolution network is combined with the original YOLOv3 and the residual block is added to extract the features of the object. The feature map output by the residual block is merged with the target detection layer through the shortcut layer to improve the network structure of YOLOv3. Both the original model and the improved model are trained by the same tennis ball data set. The results show that the recall is improved from 67.70% to 75.41% and the precision is 88.33%, which outperforms the original 77.18%. The recognition speed of the model is increased by half and the weight is reduced by half after training. All these features provide a great convenience for the application of the deep neural network in embedded devices. Our goal is that the robot is capable of picking up more tennis balls as soon as possible. Inspired by the maximum clique problem (MCP), the pointer network (Ptr-Net) and backtracking algorithm (BA) are utilized to make the robot find the place with the highest concentration of tennis balls. According to the training results, when the number of tennis balls is less than 45, the accuracy of determining the concentration of tennis balls can be as high as 80%.</jats:p

    Study on the insecticidal activity compounds of the essential oil from Syzygium aromaticum against stored grain insect pests

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    Insect pests are a major cause of damage in stored grain around the world. To control the stored grain insects, synthetic insecticides have been used extensively for many years, resulting in insect populations that are resistant to insecticides. Consequently there is an interest to find alternatives to chemical pesticides. The essential oil from Syzygium aromaticum (clove oil) has a number of bioactive compounds. The chemical constituents of the clove oil were analyzed by GC-MS, and 9 of 18 compounds were identified. The main compound (83%) was 2-methoxy-4-(2-propenyl)-phenol the second most common compound (12%) was trans-caryophyllene. These two pure compounds and clove oil were tested for toxicity and repellency against Rhyzopertha dominica, Sitophilus oryzae and Tribolium castaneum. The pure compounds were tested at the dosages found in clove oil. The mortality from 2-methoxy-4-(2-propenyl)-phenol was not significantly different from clove oil, suggesting that the activity of clove oil was solely due to this major compound. The repellency results were more complex. 2-methoxy-4-(2-propenyl)-phenol was more repellant than clove oil. Trans-caryophyllene was less toxic and less repellant than both clove oil and 2-methoxy-4-(2-propenyl)- phenol. The potential for these compounds to be used to control stored product insects is discussed. Keywords: Essential oils, Syzygium aromaticum, Clove oil, Insecticidal activity compounds, Stored grain insect
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