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Impedance behavior of excess CaO type non-stoichiometric Ca1-xZrO3-δ perovskite ceramic
Huiyu Li,Xingmin Guo 한국물리학회 2013 Current Applied Physics Vol.13 No.3
Excess CaO type non-stoichiometric Ca1-xZrO3-δ (x = 0.2, 0.23) was prepared to investigate their impedance behavior in 500 Ce1100 C temperature range. It was confirmed that grain plays predominantly role in total resistance and relaxation process. The grain boundary resistance decreases more rapidly than that of grain with the rising of temperature. The relaxation time was found reduces with temperature increases. The activation energies are calculated to be 1.19 eV of C1.2Z and 1.53 eV of C1.23Z. The excess CaO is suggested can enhance the resistance and relaxation process of grain boundary and gives rise to a higher activation energy of C1.23Z. By analyzing dielectric permittivity, polarization effect was verified works more seriously at higher temperatures especially in C1.2Z. The excess CaO was proved can relieve the polarization effect in C1.23Z.
Li Zhao,Jizhou Lv,Fei Li,Kairui Li,Bo He,Luyao Zhang,Xueqing Han,Huiyu Wang,Nicholas Johnson,Xiangmei Lin,Shaoqiang Wu,Yonghong Liu 대한기생충학ㆍ열대의학회 2020 The Korean Journal of Parasitology Vol.58 No.1
Livestock husbandry is vital to economy of the Tarim Basin, Xinjiang Autonomous Region, China. However, there have been few surveys of the distribution of ixodid ticks (Acari: Ixodidae) and tick-borne pathogens affecting domestic animals at these locations. In this study, 3,916 adult ixodid ticks infesting domestic animals were collected from 23 sampling sites during 2012-2016. Ticks were identified to species based on morphology, and the identification was confirmed based on mitochondrial 16S and 12S rRNA sequences. Ten tick species belonging to 4 genera were identified, including Rhipicephalus turanicus, Hyalomma anatolicum, Rh. bursa, H. asiaticum asiaticum, and Rh. sanguineus. DNA sequences of Rickettsia spp. (spotted fever group) and Anaplasma spp. were detected in these ticks. Phylogenetic analyses revealed possible existence of undescribed Babesia spp. and Borrelia spp. This study illustrates potential threat to domestic animals and humans from tick-borne pathogens.
Huiyu Jiang,Yujiao Wang,Heng Quan,Wei Li 한국섬유공학회 2018 Fibers and polymers Vol.19 No.4
Waterborne polyurethane modified by acrylate/nano-ZnO (PUA/ZnO) was synthesized and used to improve the wet rubbing fastness of reactive dyed cotton fabric. The reaction conditions were optimized and the products were characterized by FT-IR, TG, DSC, SEM, and particle size distribution. The dyed cotton fabrics were finished with PUA/ZnO emulsion and the rubbing fastness, ultraviolet resistant property, and wearability of treated fabrics were measured. The wet rubbing fastness of treated fabrics was increased by about 0.5-1 rate to achieve 3-4 rate, and the ultraviolet protection factor (UPF) achieved 50+ level. The whiteness, air permeability, and elongation at break of treated fabric were not decreased significantly. SEM showed that the smooth and reticular coating on the surface of treated fabric reduced the mechanical friction force between dyed fabric and rubbing cloth, and thus improved the rubbing fastness. The decomposition temperature of finished fabric was increased by 50-80 oC.
Huiyu Zhou,Shingo Mabu,Manoj Kanta Mainali,Xianneng Li,Kaoru Shimada,Kotaro Hirasawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Time Related Association rule mining is a kind of sequence pattern mining for sequential databases. In this paper, a Generalized Class Association Rule Mining is proposed using Genetic Network Programming (GNP) in order to find time related sequential rules more efficiently. GNP has been applied to generate the candidates of the time related association rules as a tool. For fully utilizing the potential ability of GNP structure, the mechanism of Generalized GNP with Multi-Branches· Full-Paths mechanism is proposed for class association data mining. The aim of this algorithm is to better handle association rule extraction from the databases with high efficiency in a variety of time-related applications, especially in the traffic volume prediction problems. The algorithm capable of finding the important time related association rules is described and experimental results are presented using a traffic prediction problem.
Xianeng Li,Shingo Mabu,Huiyu Zhou,Kaoru Shimada,Kotaro Hirasawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, a novel evolutionary paradigm combining Genetic Network Programming(GNP) and Estimation of Distribution Algorithms(EDAs) is proposed and used to find important association rules in time-related applications, especially intraffic prediction. GNP is one of the evolutionary optimization algorithms, which uses directed-graph struc-tures. EDAs is a novel algorithm, where the new population of individuals is produced from aprobabilistic distribution estimated from the selected individuals from the previous genration. This model replaces random cross over and mutation to generate off spring. In stead of generating the can didate association rules using conventional GNP, the proposed method can obtainalarge number of important association rules more effectively. The purpose of this paper is to compare the proposed method with conventional GNP intraffic prediction systems interms of the number of rules obtained.
Wang, Huiyu,Qiao, Jian,Gao, Mingyu,Yang, Ying,Li, Kai,Wang, Jianlin,Tian, Yong,Xu, Tong Asian Australasian Association of Animal Productio 2007 Animal Bioscience Vol.20 No.10
Endothelin-1 (ET-1) is an important factor in regulation of cardiovascular tone in humans and mammals, but the biological function of ET-1 in the avian vascular system has not been determined. The purpose of this study was to characterize the role of endogenous ET-1 in the vascular system of poultry by investigating the effect of endothelin A receptor ($ET_AR$) antagonist BQ123 on the femoral artery pressure (FAP) and the pulmonary artery pressure (PAP) in broiler chickens. First, we found that plasma and lung homogenate ET-1 levels were both increased with age over the seven weeks life cyccle of broiler chickens. Second, 60 min after intravenous injection, BQ123 ($0.4{\mu}g\;kg^{-1}$ and $2.0{\mu}g\;kg^{-1}$, respectively) induced a significant reduction in FAP and PAP (p<0.05). Third, chronic infusion of BQ123 ($2.0{\mu}g\;kg^{-1}$ each time, two times a day) into abdominal cavities led to significant decrease in systolic pressure of the femoral (p<0.05) and pulmonary arteries (p<0.01) in broiler chickens at 7 and 14 days after treatment. Taken together, the $ET_AR$ antagonist BQ123 lead to a significant reduction of FAP and PAP, which suggests that endogenous ET-1 may be involved in the maintenance and regulation of systemic and pulmonary pressure in broiler chickens.
The Noise Monitoring System and Automatic Correction Algorithm
Zeng Huapu,Li Yuting,Xu Huiyu,Pu Yunming,Qiao feng,Liang jun 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.9
For the improvement of living environment, there are more needs of the real time and online automatic noise monitoring system installed in many urban areas. In this project, the principle of noise audio frequency processing and coding algorithm was researched, including Discrete Cosine Transform and Wavelet Transform. The noise monitoring system solved the synchronous problem between the audio data and noise decibel, the special storage format separated the audio data which can be located in probability, and the audio data across segments to be played continually. The design of double-layer structure and isolating solved the problem of heat dissipating, waterproof and dustproof. In the experimental testing of the noise monitoring system, the noise decibel was affected by temperature and differential pressure, for improving its precision, the linear regression model is applied in the calculation of noise decibel. The least estimate method was used to calculate the residual for the automatic correction of the noise monitoring, and increase the accuracy of noise monitoring.
Yahan Cui,Liyan Jiang,Huiyu Li,Di Meng,Yanhua Chen,Lan Ding,Yang Xu 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.96 No.-
The widespread addition of sulfa antibiotics in feeds has long been an environment safety issue. Therefore, it is quite meaningful to constantly propose better solutions for determining the sulfaantibiotics in the environment. Herein, molecularly imprinted electrospun nanofibre membrane (MIM)assisted stir bar sorptive extraction method for the determination sulfonamides (SAs) in feed wasdeveloped. In this study, molecularly imprinted polymers (MIPs) werefirstly prepared via emulsionpolymerization using sulfamonomethoxine as template. Then, the morphology-controllable MIM wasobtained with MIPs-doping electro-spinning solution using electro-spinning technique. Next, MIM arecoated on the magnetic stir bar by heat-sealing. Finally, MIM coated stir bar was used for selectiveenrichment of SAs. The obtained MIM exhibited excellent class selectivity towards SAs (the selectivityfactor β is 2.3–2.7). The MIM coated stir bar can be directly applied to extract SAs from feed samples. Under the optimum extraction conditions, the detection limit of the method could reach 1.5 3.4 ng/g. And satisfactory recoveries ranging from 80 6% to 89 7% were achieved under all three spiked levelsfor determination of four SAs infive different feed samples. The present work not only offers insights todevelop magnetic stir bar using imprinted membrane, but also provides a new method for SAs extraction.
Yang Wang,Shingo Mabu,Huiyu Zhou,Xianneng Li,Kaoru Shimada,Bofeng Zhang,Kotaro Hirasawa 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, a method of time-related classas sociation rule mining is proposed based on Genetic Network Programming(GNP) combined with Estimation of Distribution Algorithms(EDAs). The reare two important points in this paper: The first important point is to combine GNP with Estimation of Distribution Algorithms which are a novel evolution strategy. The second important point is that three kinds of probability models have been put for ward for generating new individuals. The aim of this paper is to extract more interesting association rules and to improve the traffic prediction accuracy by combining Genetic Network Proramming with Estimation of Distribution Algorithms. We applied the proposed data mining algorithm to traffic system sin order to predict the traffic volume in future. The simulation results show that our proposed method is effective compared with the conventional method based on GNP.