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The Effect of Mixed Amino Acids on Nitrate Uptake and Nitrate Assimilation in Leafy Radish
Liu, Xing-Quan,Kim, Young-Sun,Lee, Kyu-Seung The Korean Society of Environmental Agriculture 2005 한국환경농학회지 Vol.24 No.3
The objective of the present work was to determine the corresponding uptake and assimilation of ${NO_3}^-$ in roots and shoots of leafy radish by applying of mixed amino acids (MAA). The amino acids used in this experiment were alanine (Ala), ${\beta}-alanine\;({\beta}-Ala)$, aspartic acid (Asp), asparagines (Asn), glutamic acid (Glu), glutamine (Gln), and glycine (Gly). Leafy radish was grown by conventional fertilization with macro- and micronutrients under controlled conditions. The 15-day-old seedlings were treated 0, 0.3 and 3.0 mM of MAA containing 5 mM ${NO_3}^-$ in growth medium. Nitrate uptake was determined by following ${NO_3}^-$ depletion from the uptake solution. The activity of the enzymes related to the process of ${NO_3}^-$ reduction (NR: nitrate reductase; NiR: nitrite reductase; GS: glutamine synthetase) and the content of ${NO_2}^-\;and\;{ND_3}^-$ were analyzed in shoots and roots. The results of this study showed that ${NO_3}^-$ uptake was inhibited 38% with treatment of 0.3 mM of MAA. However, there was more than three times increase of N03- uptake in 3.0 mM MAA. In addition, the enzymatic activities were positively affected by the high MAA rate. Finally, the ${NO_3}^-$ content was increased slightly both in shoots and roots of leafy radish by MAA treatments.
A high-efficiency simulation method of wind field and its application on transmission line
Xing Fu,Xing-Heng Zhang,Hong-Nan Li,Gang Li,Hui-Juan Liu 한국풍공학회 2021 Wind and Structures, An International Journal (WAS Vol.33 No.4
Generally, the fluctuating wind is simplified as several independent one-dimensional multivariate stationary Gaussian processes in simulating a natural wind field. The correlation in the lateral, longitudinal and vertical directions should all be considered in the simulation of longitudinal wind field for the large-span spatial structures. In fact, this type of structure has lots of simulation points. The calculation amount of wind field simulation by the harmonic superposition method depends on the scale of cross-spectral density matrix, which is directly related to the number of simulated points, leading to a low efficiency when generating the time-varying wind speed. This paper innovatively proposes a high-efficiency simulation method for the longitudinal wind field based on Taylor’s hypothesis. Subsequently, the effectiveness of the proposed wind field method was verified by the numerical simulation. Finally, the dynamic responses of a transmission tower-line system under the wind loadings generated with the new method and traditional method are calculated and compared. The percentages difference of the mean and maximum axial force at the main tower members are less than 0.02% and 1%, respectively, indicating the effectiveness of the proposed time delay method. The results also show that the proposed simulation method of wind field can not only ensure the simulation accuracy, but also significantly improve the efficiency of wind speed generation, which is suitable for the wind load simulation of large-span spatial structures.
Xing-Yuan Liu 대한화학회 2010 Bulletin of the Korean Chemical Society Vol.31 No.5
A novel poly(safranine)-modified electrode has been constructed for the determination of 4-nitrophenol (4-NP) in natural water sample. The electrochemical behavior of poly(safranine) film electrode and its electrocatalytic activity toward 4-NP were studied in detail by cyclic voltammetry (CV) and adsorptive linear stripping voltammetry (LSV). All experimental parameters were optimized and LSV was proposed for its determination. In optimal working conditions, the reduction current of 4-NP at this poly(safranine)-modified electrode exhibited a good linear relationship with 4-NP concentration in the range of 8.0 × 10‒8 to 4.0 × 10‒5 mol L‒1. The detection limit was 3.0 × 10‒8mol L‒1. The high sensitivity and selectivity of the sensor were demonstrated by its practical application for the determination of trace amounts of 4-NP in natural water and fruit samples.
Xing Liu,Jifan Hu,Bin Cheng,Hongwei Qin,Minhua Jiang 한국물리학회 2009 Current Applied Physics Vol.9 No.3
Nanoparticulate perovskite-type LnFe0.9Mg0.1O3 (Ln = Nd, Sm, Gd and Dy) oxides were prepared by sol–gel method. X-ray diffraction was used to confirm the phase composition of the compounds. The materials exhibit p-type semiconductor behavior. Their sensitivity and selectivity towards ethanol gas were investigated. It was found that SmFe0.9Mg0.1O3-based sensor had the highest response and selectivity. It is a new potential gas sensing material. The great difference of conductance in air and ethanol gas was found and discussed in detail. Nanoparticulate perovskite-type LnFe0.9Mg0.1O3 (Ln = Nd, Sm, Gd and Dy) oxides were prepared by sol–gel method. X-ray diffraction was used to confirm the phase composition of the compounds. The materials exhibit p-type semiconductor behavior. Their sensitivity and selectivity towards ethanol gas were investigated. It was found that SmFe0.9Mg0.1O3-based sensor had the highest response and selectivity. It is a new potential gas sensing material. The great difference of conductance in air and ethanol gas was found and discussed in detail.
Microstructure Evolution of Inconel 718 Alloy during Ring Rolling Process
Xing-lin Zhu,Dong Liu,Li-juan Xing,Yang Hu,Yan-hui Yang 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.17 No.6
Microstructure determines the comprehensive mechanical properties and service life of ring parts. In this study, ring rolling process is considered as a multi-pass process which is parted into four phases, and the microstructure evolution model is then established based on the characteristics of this multi-pass process by combining with a 3D coupled thermo-mechanical FE model. By contrasting with experiment results, the microstructure evolution model is actually proven can be competently applied to predict the microstructure of the formed ring. Also through comprehensive analysis on distribution of recrystallization fractions based on the microstructure evolution model, conclusions can be summarized as following. (1) It is inaccurate to predict the microstructure by regarding the ring rolling as a single-pass deformation. The ring rolling process should be parted into different phases, and for each phase, the singlepass microstructure evolution model is adapted. (2) Different with single-pass deformation, due to the high temperature dwelling phase during ring rolling process, meta-dynamic recrystallization (MDR) is another important grain refinement mechanism besides dynamic recrystallization (DR). (3) MDR has different distribution trends with DR, which is benefit not only for grains refinement but also for microstructure uniformity. (4) Rolling penetration is obviously improved with feed rate increases, whereas, unduly high feed rate leads to recrystallization fraction decrease in outer layer area, which is adverse to microstructure uniformity.
Xing Liu,이종근,Michael R. Kessler 한국고분자학회 2011 Macromolecular Research Vol.19 No.10
Norbornene-based healing agent candidates, 5-ethylidene-2-norbornene (ENB) and ENB with a custom crosslinker, were prepared into uniform microspheres using a Shirasu porous glass (SPG) emulsification technique,and microencapsulated by in situ polymerization of melamine-urea-formaldehyde (MUF). The resulting microcapsules were observed by optical and scanning electron microscopy for their morphology, outer and inner surface and shell thickness. Particle size analysis revealed a more uniform size distribution with a mean diameter of 40 μm than a conventional method using a mechanical impeller. The thermal and mechanical properties of the microcapsules were also examined by considering fabrication of self-healing composites.
Use of deep learning in nano image processing through the CNN model
Xing, Lumin,Liu, Wenjian,Liu, Xiaoliang,Li, Xin,Wang, Han Techno-Press 2022 Advances in nano research Vol.12 No.2
Deep learning is another field of artificial intelligence (AI) utilized for computer aided diagnosis (CAD) and image processing in scientific research. Considering numerous mechanical repetitive tasks, reading image slices need time and improper with geographical limits, so the counting of image information is hard due to its strong subjectivity that raise the error ratio in misdiagnosis. Regarding the highest mortality rate of Lung cancer, there is a need for biopsy for determining its class for additional treatment. Deep learning has recently given strong tools in diagnose of lung cancer and making therapeutic regimen. However, identifying the pathological lung cancer's class by CT images in beginning phase because of the absence of powerful AI models and public training data set is difficult. Convolutional Neural Network (CNN) was proposed with its essential function in recognizing the pathological CT images. 472 patients subjected to staging FDG-PET/CT were selected in 2 months prior to surgery or biopsy. CNN was developed and showed the accuracy of 87%, 69%, and 69% in training, validation, and test sets, respectively, for T1-T2 and T3-T4 lung cancer classification. Subsequently, CNN (or deep learning) could improve the CT images' data set, indicating that the application of classifiers is adequate to accomplish better exactness in distinguishing pathological CT images that performs better than few deep learning models, such as ResNet-34, Alex Net, and Dense Net with or without Soft max weights.