Duck viral hepatitis (DVH) is an acute and fatal disease of young ducklings characterized by rapid transmission and damages. The most important agent of DVH is duck hepatitis virus 1 (DHV-1). The effective control of DVH was achieved by active immunization of 1-day-old duck- lings with an attenuated DHV-1 virus vaccine. However, the attenuated virus might reverse to virulence. In this study, a DHV-1 strain, Du/CH/LBJ/090809, was identified and its genomic se- quences were determined. The genome of Du/CH/LBJ/090809 is composed of 7,692 nt excluding poly A and the virus was clustered into genotype A by comparing with other referenced DHV-1 strains. Du/CH/LBJ/090809 could lead to 30% mortality of 10-day-old specific pathogen free (SPF) ducklings. The virus was passaged serially in SPF chicken embryonated eggs and three vi- ruses, passage 16 (P16), P29 and P40, were selected for genomic analysis. P29 and P40 were used to evaluate the attenuation in duckling by inoculating the virus to 10-day-old SPF ducklings. Re- sults of vaccination-challenge assay showed that the inactivated virus P40 could evoke protection against the pathogenic parent virus. Nucleotide and amino acid sequences of the genomes of Du/ CH/LBJ/090809, P16, P29 and P40 were compared. Changes both in nucleotides and amino acids, which might be contributed to the decreasing in virulence by chicken embryo-passaging of DHV- 1, were observed. We speculated that these changes might be important in the adaption and at- tenuation of the virulent virus. Additionally, strains obtained in this study will provide potential candidate in the development of vaccines against DHV-1.

As the dynamic behavior of the concrete is different from that under static load, this research focuses on the study of dynamic responses of concrete by simulating the split Hopkinson pressure bar (SHPB) test. Finite element code LS-DYNA is used for modeling the dynamic behaviors of concrete. Three continuous models are reviewed and the Holmquist-Johnson-Cook model (HJC) is introduced in detail. The HJC model which has been implemented in LS-DYNA is used to represent the concrete properties. The SHPB test model is established and a few stress waves are applied to the incident bar to simulate the dynamic concrete behaviors. The stress-strain curves are obtained. The stress distributions are analyzed. The crack initiation and propagation process are described. It is concluded that: the HJC model can modeling the entire process of the fracture initiation and fragmentation; the compressive of the concrete is significantly influenced by the strain rates.

In this study, X-ray diffraction, thermogravimetric analysis and differential scanning calorimetry (DSC) method were used to analyze the main characteristics of sweet potato starch, and to analyze the thermal degradation process of sweet potato starch. Specifically, X-ray diffraction to study its structure, thermogravimetric analysis to study the thermal degradation kinetics, and differential scanning calorimetry to study the thermogram of sweet potato starch. The thermal decomposition kinetics of sweet potato starch was examined within different heating rates in nitrogen atmosphere. Different models of kinetic analysis were used to calculate the activation energies using thermogravimetric data of the thermal degradation process. Activation energies obtained from Kissinger, Flynn-Wall- Ozawa, and Šatava-Šesták models were 173.85, 174.87 and 174.34 kJ/mol, respectively. The values of activation energy indicated that the thermal degradation of the sweet potato starch was a single reaction mechanism or the combination of multi-reaction mechanisms. The differential scanning calorimetry analysis show that two decomposition stages were presented: the first at a low temperature involves the decomposition of long chain; and the second at a high temperature represents the scission of glucose ring. This information was helpful to design the processing process of many natural polymers. Thermogravimetric Fourier transform-infrared (TG–FTIR) analysis showed that the main pyrolysis products included water, methane, carbon dioxide, ammonia, and others.

An intelligent boundary switch is a three-phase outdoor power distribution device equipped with a controller. It is installed at the boundary point on the medium voltage overhead distribution lines. It can automatically remove the single-phase-to-ground fault and isolation phase-to-phase short-circuit fault. Firstly, the structure of an intelligent boundary switch is studied, and then the fault detection principle is also investigated. The single-phase-to-ground fault and phase-to-phase short-circuit fault are studied respectively. A method using overcurrent to judge the short-circuit fault is presented. The characteristics of the single-phase-to-ground fault on an ungrounded distribution system and compositional grounded distribution system are analyzed. Based on these characteristics, a method using zero sequence current to detect the single-phase-to-ground fault is proposed. The research results of this paper give a reference for the specification and use of intelligent boundary switches.

When a single line-to-ground fault occurs in the ungrounded distribution system, the steady-state fault current is relatively small for fault analysis and the transient fault current is observable, which can be used for faulted feeder identification and location. The principal frequency component retains most of the characteristics of the transient current. The principal frequency is related to the distance from the fault point to the substation and can be used for fault location. This paper analyzes the sequence network model of a single line-to-ground fault in the distribution network, and gives a method for principal frequency calculation. Depending on the characteristics of the maximum amplitude of the principal frequency component of the faulted feeder, the method of faulted feeder identification is given. Based on the complementary characteristics of the phase angle of the principal frequency component of the fault current and the phase angle at the substation bus, the faulted section location is carried out. MATLAB simulation is used to verify the effectiveness of the faulted feeder identification and location method.

Against the background of increasing installed capacity of wind power in the power generation system, high-precision ultra-short-term wind power prediction is significant for safe and reliable operation of the power generation system. We present a method for ultra-short-term wind power prediction based on a copula function, bivariate empirical mode decomposition (BEMD) algorithm and gated recurrent unit (GRU) neural network. First we use the copula function to analyze the nonlinear correlation between wind power and external factors to extract the key factors influencing wind power generation. Then the joint data composed of the key factors and wind power are decomposed into a series of stationary subsequence data by a BEMD algorithm which can decompose the bivariate data jointly. Finally, the prediction model based on a GRU network uses the decomposed data as the input to predict the power output in the next four hours. The experimental results show that the proposed method can effectively improve the accuracy of ultra-short-term wind power prediction.

Optical sampling based on ultrafast optical nonlinearities is a useful technique to monitor the waveforms of ultrashort optical pulses. In this paper, we present a new implementation of optical waveform sampling systems by employing our newly constructed free-running mode-locked fibre laser with a tunable repetition rate and a low timing jitter, an all-optical waveform sampler with a highly nonlinear fibre (HNLF), and our developed computer algorithm for optical waveform display and measurement, respectively. Using a femtosecond fibre laser to generate the highly stable optical sampling pulses and exploiting the four-wave mixing effect in a 100 m-long HNLF, we successfully demonstrate the all-optical waveform sampling of a 10 GHz optical clock pulse sequence with a pulse width of 1.8 ps and a 80 Gbit/s optical data signal, respectively. The experimental results show that waveforms of the tested optical pulse signals are accurately reproduced with a pulse width of 2.0 ps. This corresponds to a temporal resolution of 0.87 ps for optical waveform measurement. Moreover, the optical eye diagram of a 10Gbit/s optical data signal with a 1.8 ps pulse width is also accurately measured by employing our developed optical sampling system.

Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods.

Due to the characteristics of color vegetation canopy images which have multiple details and Gaussion noise interference, the adaptive mean filtering (AMF) algorithm is used to perform the denoising experiments on noised images in RGB and YUV color space. Based on the single color characteristics of color vegetation canopy images, a simplified AMF algorithm is proposed in this paper to shorten the overall running time of the denoising algorithm by simplifying the adaptive denoising processing of the component V, which contains less image details. Experimental results show that this method can effectively reduce the running time of the algorithm while maintaining a good denoising effect.

Micro-defects detection in solidified castings of aluminum alloy has always been a hot topic, and the method employed is mainly depends upon the size and shape of the specimens. In present paper, the amount and distribution characters of micro-defects in a series of 2219 aluminum alloy ingot, with diameters of φ1380 mm, φ1250 mm, φ1000 mm, φ850 mm and φ630 mm, prepared by direct chill casting were investigated by means of metallographic, respectively. Samples were cut along the radius direction from slices in the steady casting stage. The result reveals that typical micro-defects are consist of inclusions, porosity and shrinkage under optical microscope, and the total amount of micro-defect per unit area in an ingot slightly decreased with the increase of its diameter. Meanwhile, defects were classified into 2 types according to its size, the results suggesting that defects greater than 40 μm account for the largest proportion among the counted two kinds of defects. Moreover, the distribution of defects greater than 40 μm along the radial direction was detected, its amount increases as its distance from the side, indicating that the micro-defects greater than 40 μm distributed the most in the center zone of ingots and the larger the ingot diameter, the more obvious the tendency was.

The fracture and fragmentation of concrete under static and dynamic loads are studied. The uniaxial compressive strength test is employed to study the concrete behavior under static loads while the split Hopkinson pressure bar is used to study the dynamic behavior of the concrete under static loads. The theories for acquiring the stress, strain and strain rate of the concrete in the dynamic test by Hopkinson pressure bar has been introduced. The fracture patterns of the concrete in the uniaxial compressive test have been obtained and the static concrete compressive strengths have been calculated. The fracture patterns of the concrete in the uniaxial compressive test have been obtained and the static concrete compressive strengths have been calculated. The fracture and fragmentation of the specimen under dynamic loads have been acquired and the stress-strain curves of concrete under various impact loads are obtained. The stress-strain curve indicates a typical brittle material failure process which includes existing micro-fracture closure stage, linear-elastic stage, nonlinear-elastic stage, and post-failure stages. The influence of the loading rate for the compressive strength of the concrete has compared. Compared with the concrete under static loads, the dynamic loads can produce more fractures and fragments. The concrete strength is influenced by the strain rate and the strength increases almost linearly with the increase of the strain rate.

Fe-based PM alloy powder of Fe-2.5Ni-0.5Mo-2Cu-0.4C was pressed by high velocity compaction combined with die wall lubrication, and the effect of die wall lubrication on high velocity compaction behavior and sintering properties of the Fe-based PM alloy were studied. The results indicate that the impact force, green density, sintered density of samples increase with the augment of the impact velocity and die wall lubrication. Compared with that without die wall lubrication, the green density and sintered density of the sample with die wall lubrication are about 0.07-0.12 g/cm3 and 0.08~0.11 g/cm3 higher at the same impact velocity, respectively, while the ejection force of the die wall lubricated sample is much smaller, and reduced about 26%~36%. The green compact with die wall lubrication has much fewer porosity than that without die wall lubrication, and more mechanical bonding and cold welding regions are observed. The sintered samples mainly consists of gray pearlite and white ferrite, and more pearlite is observed in the sintered sample with die wall lubrication.