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5. A Drive-by Bridge Damage Localisation Method with an Instrumented Vehicle

Author

Lu, Xuzhao, Sun, Limin, Kim, Chul-Woo, Chang, Kai-Chun, Han, Zhuoran, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Limongelli, Maria Pina, editor, Giordano, Pier Francesco, editor, Quqa, Said, editor, Gentile, Carmelo, editor, and Cigada, Alfredo, editor

Published
2023
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9. Research on Machine Translation Model Based on Neural Network

Author

Han, Zhuoran, Li, Shenghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Liu, Xin, editor, Na, Zhenyu, editor, Wang, Wei, editor, Mu, Jiasong, editor, and Zhang, Baoju, editor

Published
2020
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11. Opportunistic Routing Algorithm Based on Estimator Learning Automata

Author

Han, Zhuoran, Li, Shenghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Mu, Jiasong, editor, Jia, Min, editor, Wang, Wei, editor, Feng, Xuhong, editor, and Zhang, Baoju, editor

Published
2019
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12. Learning Automata Based SVM for Intrusion Detection

Author

Di, Chong, Su, Yu, Han, Zhuoran, Li, Shenghong, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Mu, Jiasong, editor, Jia, Min, editor, Wang, Wei, editor, Feng, Xuhong, editor, and Zhang, Baoju, editor

Published
2019
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18. HISTOCHEMICAL DISTRIBUTION OF THREE TYPES OF ENZYMES AND MUCOUS CELLS IN THE GILL, MANTLE AND HEPATOPANCREAS OF THE ARK SHELL SCAPHARCA SUBCRENATA

Author

Mao, Qing, Han, Zhuoran, Li, Yinglan, Sun, Jingfeng, Guo, Yongjun, Sun, Xueliang, Chen, Limei, and Xing, Kezhi

Subjects
Esterases -- Observations, Peroxidase -- Observations, Pteriomorphia -- Observations, Zoological research, Alkaline phosphatase -- Observations, pH, Phosphatases, Enzymes, Methylene blue, Biological sciences, Zoology and wildlife conservation
Abstract

The present study was aimed at evaluating the histochemical distribution of alkaline phosphatase (ALP), nonspecific esterase (NSE), peroxidase (POD) and various types of mucous cells in the gill, mantle and hepatopancreas of the ark shell Scapharca subcrenata. The ALP activity was found in the epithelial cells (EP) of the gill filament and the mantle as well as in the basal lamina of the glandular duct in the hepatopancreas. The staining intensity of ALP in the mantle and hepatopancreas was stronger than that in the gill. The NSE activity was detected in the EP in the gill filament, mantle and hepatopancreas, with the hepatopancreas showing a stronger intensity than the gill. The POD activity was located in the EP of the mantle and glandular duct of the hepatopancreas as well as in the connective tissue of the gill. The mantle showed stronger staining intensity of POD than the hepatopancreas. The Alcian blue (pH 2.5) periodic acid Schiff (AB-PAS) histochemical results revealed four types of mucous cells in the gill, mantle and hepatopancreas. Type III cells (nPAS+AB+) and type IV cells (aPAS+AB+) were observed in the gill, mantle and hepatopancreas. Type I cells (PAS+AB-) were not detected in the hepatopancreas but were distributed ubiquitously throughout the gill filament and mantle. Type II cells (PAS--AB+) were not detected in the gill but were distributed ubiquitously in the digestive ducts of the hepatopancreas. KEY WORDS: enzyme activity, mucous cells, histochemical techniques, ark shell, Scapharca subcrenata, INTRODUCTION The bivalve mollusc has various enzymes and mucous cells distributing widely in the host tissues. They play an important role in the growth, development and immune defense of the [...]

Published
2019
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20. Changes in the intestinal microbiota of farmed northern sheatfish (Silurus soldatovi) associated with natural bacterial infection.

Author

Zan, Zhongjie, Mao, Qing, Han, Zhuoran, and Sun, Jingfeng

Subjects
GUT microbiome, BACTERIAL diseases, FISHER discriminant analysis, VIBRIO cholerae, POULTRY farms, BACTERIAL population, BACTEROIDES fragilis
Abstract

An acute infectious disease of northern sheatfish (Silurus soldatovi) was found in a commercial aquaculture pond in Tianjin, China. Herein, two dominant bacterial strains were isolated from naturally diseased northern sheatfish and identified as Aeromonas veronii and Vibrio cholerae. Seven healthy and seven naturally diseased fish that were collected from the pond were used for the gut microbiota analysis by high‐throughput 16S rRNA gene sequencing. The α‐diversity indices (ACE, Chao 1, and Shannon) did not differ significantly between diseased and healthy fish (p > 0.05), but a significant separation was observed between them when β‐diversity analysis of the bacterial population was performed. The diseased fish demonstrated a significant elevation in the relative abundances of Aeromonas, Vibrio, Blautia, and Megamonas and a decrease in Cetobacterium, Bacteroides, Chryseolinea, Ralstonia, and Pseudomonas compared with healthy fish (p < 0.05). Linear discriminant analysis effect size showed that microbial marker species in the diseased fish were in the order Aeromonadales, the family Aeromonadaceae, and the genus Aeromonas. The functional profiles of the microbial community that were predicted using the PICRUSt2 indicated that the disturbance of gut microbiota caused the alteration of its functional profiles in the diseased fish. [ABSTRACT FROM AUTHOR]

Published
2023
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32. Using Generalized Basis for Functional Expansion

Author

Han, Zhuoran, Forget, Benoit, Smith, Kord, Han, Zhuoran, Forget, Benoit, and Smith, Kord

Abstract

Functional expansion has been rigorously studied as a promising method in stochastic neutron transport and multi-physics coupling. It is a method to represent data specified on a desired domain as an expansion of basis set in a continuous manner. For convenience, the basis set for functional expansion is typically chosen to be orthogonal. In cylindrical PWR pin-cell simulations, the orthogonal Zernike polynomials have been used. The main advantage of using functional expansion in nuclear modeling is that it requires less memory to represent temperature and nuclide variations in fuel then using a fine discretization. Fewer variables are involved in the data storage and transfer process. Each nuclide can have its unique expansion order, which becomes very important for depletion problems. In a recent study, performance analysis was conducted on Zernike-based FETs on a 2D PWR geometry. For reaction rates like the absorption rate of U-238, however, many orders are needed with Zernike-based FETs to achieve a reasonable accuracy. This gap inspires the study in this paper on alternative basis set that can better capture the steep gradient with fewer orders. In this paper, a generalized functional expansion method is established. The basis set can be an arbitrary series of independent functions. To capture the self-shielding effect of U-238 absorption rate, an exponential basis set is chosen. The results show that the expansion order utilizing exponential basis can reduce by half of that from using orthogonal Zernike polynomials while achieving the same accuracy. The integrated reaction rate is also demonstrated to be preserved. This paper also shows that the generalized functional expansion could be a heuristic method for further investigation on continuous depletion problems.

Published
2021

33. Using Generalized Basis for Functional Expansion

Author

Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Han, Zhuoran, Forget, Benoit Robert Yves, Smith, Kord S., Massachusetts Institute of Technology. Department of Nuclear Science and Engineering, Han, Zhuoran, Forget, Benoit Robert Yves, and Smith, Kord S.

Abstract

Functional expansion has been rigorously studied as a promising method in stochastic neutron transport and multi-physics coupling. It is a method to represent data specified on a desired domain as an expansion of basis set in a continuous manner. For convenience, the basis set for functional expansion is typically chosen to be orthogonal. In cylindrical PWR pin-cell simulations, the orthogonal Zernike polynomials have been used. The main advantage of using functional expansion in nuclear modeling is that it requires less memory to represent temperature and nuclide variations in fuel then using a fine discretization. Fewer variables are involved in the data storage and transfer process. Each nuclide can have its unique expansion order, which becomes very important for depletion problems. In a recent study, performance analysis was conducted on Zernike-based FETs on a 2D PWR geometry. For reaction rates like the absorption rate of U-238, however, many orders are needed with Zernike-based FETs to achieve a reasonable accuracy. This gap inspires the study in this paper on alternative basis set that can better capture the steep gradient with fewer orders. In this paper, a generalized functional expansion method is established. The basis set can be an arbitrary series of independent functions. To capture the self-shielding effect of U-238 absorption rate, an exponential basis set is chosen. The results show that the expansion order utilizing exponential basis can reduce by half of that from using orthogonal Zernike polynomials while achieving the same accuracy. The integrated reaction rate is also demonstrated to be preserved. This paper also shows that the generalized functional expansion could be a heuristic method for further investigation on continuous depletion problems., U.S. Department of Energy’s Office of Science/National Nuclear Security Administration (Award 17-SC-20-SC)

Published
2021

42. Identification and characterization of Aeromonas veroniiand Vibrio choleraefrom naturally diseased red swamp crayfish (Procambarus clarkia)

Author

Su, Yufeng, Zheng, Yi, Han, Zhuoran, Liang, Enrui, and Sun, Jingfeng

Abstract

A large number of red swamp crayfish (Procambarus clarkia) died at a crayfish breeding farm in Tianjin. Two dominant bacterial strains were isolated from the hepatopancreas of diseased crayfish and named PCG1 and PCG2, respectively. Based on phenotypic characteristics and sequence analysis of the 16S rRNA and gyrBgenes, PCG1 was identified as Aeromonas veroniiand PCG2 was identified as Vibrio cholerae. An artificial infection experiment showed that both PCG1 and PCG2 were pathogenic to crayfish, with PCG1 having a median lethal dose (LD50) value of 6.25 × 102CFU/g crayfish weight, and PCG2 having a LD50value of 1.26 × 102CFU/g crayfish weight. Crayfish subjected to single infection with PCG1 or PCG2 and co-infection with PCG1 and PCG2 showed obvious histopathological lesions in hepatopancreas and intestines. These findings suggested that both A. veroniiand V. choleraeisolates were involved the disease occurrence in the crayfish.

Published
2023
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43. Development of a loop-mediated isothermal amplification method for detection of Shewanella algaein fish

Author

Zan, Zhongjie, Han, Zhuoran, Hou, Yuting, Zhang, Yanyu, and Sun, Jingfeng

Abstract

Shewanella algaeis an opportunistic pathogen, which is widely distributed in freshwater and marine environments. Diseases caused by S. algaehave resulted in substantial economic losses in aquaculture industry. This study aimed to establish a loop mediated isothermal amplification (LAMP) method for rapid and specific detection of S. algaein aquatic animals. The specific LAMP primers were designed according to the 16 S rRNA gene sequences of S. algaestrains deposited in GenBank. Based on adjustment of the primer concentration and optimization of reaction conditions, the LAMP method for S. algaedetection was established, and specificity and sensitivity tests were carried out. The optimal temperature of this method was 65 °C at constant 1 h. The LAMP amplification reaction was positive for S. algae, but negative for Pseudoalteromonas pisicida, Aeromonas hydrophila, A. veronii, Vibrio parahemolyticus, S. decolorationis, S. xiamenensis, Enterobacter cloacae, Bacillus cereusand Staphylococcus epidermidis.The minimum concentration of template DNA of S. algaefor the LAMP method was 8.15 × 10−5µg/µL. The LAMP method was comparable to the common PCR when they were used for detection of S. algaein koi carp artificially infected with this pathogen. In this study, a rapid, specific and sensitive LAMP method was successfully established for the detection of S. algae, providing great convenience for rapid diagnosis of aquatic animal diseases caused by S. algaeinfection.

Published
2022
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45. First record of isolation and characterization of Vibrio sinaloensis from diseased orange-spotted grouper Epinephelus coioides.

Author

Zhang X, Sun J, Zhu Y, Han Z, Hu X, Lv A, and Guo Y

Subjects
Animals, Cloning, Molecular, Bass, Fish Diseases microbiology, Vibrio, Vibrio Infections veterinary
Abstract

A dominant bacterium, ZYL-12, isolated from the liver of a diseased orange-spotted grouper Epinephelus coioides, was identified as Vibrio sinaloensis, based on phenotypic and molecular analysis. The median lethal dosage of ZYL-12 was calculated as 1.6 × 105 CFU g-1 fish weight. The infection experiment indicated that ZYL-12 caused noticeable histological lesions to the liver, kidney and spleen of the fish. Growth characteristics showed that ZYL-12 possessed strong environmental adaptability. This note is the first report about the pathogenicity of V. sinaloensis isolated from diseased fish.

Published
2022
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