The electrochemistry of Pb(II)/Pb on a stainless steel electrode during the preparation of lead wires from PbO in choline chloride (ChCl)-urea deep eutectic solvent (DES) was investigated by means of cyclic voltammetry, cathodic polarization and chronoamperometry. The experimental results indicated that the reduction of Pb(II) to Pb is a quasi-reversible process controlled by diffusion at temperature varying from 323 to 343 K, and the corresponding apparent activation energy E a is 52.37 kJ mol -1 . The analysis of chro noamperometry measurements suggested that the initial stage of nucleation of lead on stainless steel electrode is a three dimensional instantaneous nucleation under diffusion control. The effects of reaction time and temperature on the morphology of lead deposits are also examined. The lead wires obtained at 343 K for 120 min have a mean particle size of 30 μm in length and 2.5 μm in diameter. Based on experimental evi dence, the deposition mechanism of sub micrometer lead wires on stainless steel substrate is proposed by dif fusion controlled growth mechanism.
In this paper, the complete group classification is performed on the generalized short pulse equation, which includes a lot of important nonlinear wave equations as its special cases. In the sense of geometric symmetry, all of the vector fields of the equation are obtained in terms of the arbitrary functions. Then, the symmetry reductions and exact solutions to the equations are investigated. Especially, we develop the analytic power series method for constructing the exact power series solutions to the short pulse types of equations.
The catalytic degradation of lignin was exploited by magnetic core‐shell Fe3O4@SiO2@CuZnAl‐O catalysts in supercritical methanol (sc‐MeOH) over temperature from 260 °C to 360 °C and the reaction time ranging from 0.5 h to 5 h. The magnetic core‐shell‐structured Fe3O4@SiO2@CuZnAl‐O catalysts with different mole ratio of Cu to Zn were prepared by parallel flow co‐precipitating method. Catalyst Fe3O4@SiO2@Cu1.2Zn4.8Al2‐O with the maximum specific surface area (142.8 m2 g−1) exhibited the highest lignin conversion of 66% and high selectivity for phenols, ketones and benzenes. The recyclable Fe3O4@SiO2@CuZnAl‐O catalyst allows high catalytic activity and selectivity for phenols, ketones and benzenes in the catalytic conversion of lignin in supercritical methanol. It is believed that this study can provide a promising strategy to prepare core–shell structured base metal nanocatalysts with metal‐oxide shells.
ABSTRACT:The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.
We proposed frequency-selective carrier coded aperture correlation holography (FSC-COACH). By introducing frequency-selective techniques into randomly encoded aperture correlation holography, a library of virtual point spread functions (PSFs) for image reconstruction is obtained by modulating plane waves with carrier spherical wave and encoded phase mask, and reconstruction of occlusion imaging is achieved using FSPC. This is a new nonvisual imaging technique that can effectively suppress background noise and accurately encode the transverse region of the image plane to achieve fast non-linear reconstruction. The effect of the virtual point diffusion function filter radius on the reconstruction quality is experimentally analysed. The viability of our technique is demonstrated by reconstructing standard particles under mask occlusion.
ABSTRACT:The existing change detection method mainly stays on the pixel-level, which is very susceptible to light, shadow, etc. And the complex calculation and analysis for each pixel reduce the detection efficiency. Moreover, there is no modeling determination method to initialize standard deviation of each element for existing mixed Gaussian background modeling methods. In this paper, an improved mixed Gaussian background modeling method is proposed, with the use of infrared rotation plane radar. The relationship between the corrected standard deviation of distance and the detection intensity is used to establish the curve of standard deviation of distance with detected intensity. For each data point, the standard deviation is initialized by the value estimated by the change curve, and the detected distance is used to establish the Gaussian mixture background model. The detection effect of the method is discussed and compared with the traditional Gauss background modeling in the experiment, the result shows that it has certain advantages in processing speed, adaptability to change background and accuracy of change detection.
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