Fatigue Behavior of High Performance Fiber Yarns

Yuan Qiao Rao,Mistuhiro Sakuda,Richard J. Farris 한국고분자학회 1997 한국고분자학회 학술대회 연구논문 초록집 Vol.1997 No.10

Privet golden leaves adapt unexpectedly well to light changes

Ming Yuan,Bo Huang,Li-Hua Dong,Qiao-Hong Han,Yong Yang,Chun-Bang Ding,Chao Hu,Yang-Er Chen,Zhong-Wei Zhang,Shu Yuan 한국원예학회 2020 Horticulture, Environment, and Biotechnology Vol.61 No.4

Golden-leaf privet ( Ligustrum × vicaryi ) is widely used as a horticultural shrub because of its upper golden leaves, butits lower leaves are green. However, the putative mechanisms of its upper golden leaves and the leaf color changes inresponse to light shifts have not been well studied so far. Here, chlorophylls (Chl), carotenoids, and Chl precursors from bothgolden and green leaves grown in full sunlight (approximately 1200 μmol photons m −2 s −1 at noon) or low-light conditions(180 μmol m −2 s −1 ) were determined spectrophotometrically. In addition, their gas exchange parameters and Chl fl uorescencewere measured in situ. Metabolic fl ux analysis of chlorophyll intermediates indicated that the conversion of prochlorophyllideto chlorophyllide was signifi cantly blocked in golden leaves when compared with green leaves. Green leaves showed higherphotosynthetic capacity in low light than golden leaves, but golden leaves presented unexpectedly stronger photosyntheticcapacity and lower reactive oxygen species accumulation under the high-light condition. Furthermore, golden leaves showeda higher level of nonphotochemical quenching (NPQ) after the light-to-dark shift and presented a stronger adaptive abilityto a broad range of light environments. Higher NPQ values and less oxidative damage in golden leaves may be correlatedwith their higher carotenoid levels. The results imply that lower chlorophyll levels and higher carotenoid levels in canopyleaves may help privet plants acclimate better to illumination changes. This study demonstrates the key role of irradiance ingenerating the two types of Ligustrum × vicaryi leaves and sheds a light on cultivation of other ornamental foliage plants.

STUDY ON CHINESE TOURISTS' MOTIVATION AND SATISFACTION TO VISIT SOUTH KOREA

Guang-Hui Qiao,Nan Chen,Yuan-Yuan Guan,Seok-Chool Kim 한국관광학회 2008 International Journal of Tourism Sciences Vol.8 No.1

The purposes of this study are to identify the Chinese tourists' profiles, motivation factors, satisfaction levels and to assess the important detenninants and the likelihood of Chinese tourists revisiting Korea. A structured personal interview was conducted and a systematic sampling approach was used to select 240 respondents who were traveling by air. This study identified the major tourism motivations of Chinese tourists; the relationship between tourists' demographic characteristics and motivation factors; the relationship between demographic characteristics and satisfaction levels; motivation has a positive effect on satisfaction; satisfaction has a positive effect on revisit and motivation has a positive effect on revisit. In the end the limitations of this study are discussed and recommendations for future study are made.

Research on data augmentation algorithm for time series based on deep learning

Shiyu Liu,Hongyan Qiao,Lianhong Yuan,Yuan Yuan,Jun Liu 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.6

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

Effect of Different Preharvest and Postharvest Treatments on Glucoraphanin Content and Quinone Reductase Inducer Activity in Broccoli Florets

Qiao-Mei Wang,Chao-Jiong Xu,Jing Yuan,De-Ping Guo 한국원예학회 2006 한국원예학회 기타간행물 Vol.- No.-

Method of local characteristics for calculating electric field and ion current of HVDC transmission lines with transverse wind

Qiao, Ji,Zou, Jun,Yuan, Jiansheng,Lee, Jaebok,Ju, Mun-no THE INSTITUTION OF ENGINEERING AND TECHNOLOGY 2017 IET GENERATION TRANSMISSION AND DISTRIBUTION Vol.11 No.4

<P>The electric field and ion flow are significantly influenced by the transverse wind around the high-voltage direct current (HVDC) transmission lines. In this study, a new method using local characteristics is proposed to analyse the effect of wind. The present method, called method of local characteristic, updates the ion density based on the local characteristic curve in each second-order finite element method (FEM) element without Deutsch assumption. The defining equation of the characteristics is able to take into account the directional character of the information propagation in convective transport and has a better performance to satisfy the conservation law. The present approach is stable and efficient even in the presence of high-speed transverse wind. Calculations show good agreement with the measurement values of the reduced-scale unipolar model and the full-scale bipolar test line. Finally, the influence of wind on the electric field and ion current is discussed.</P>

Simulation of the Temperature and Salinity Along $36^{\circ}N$ in the Yellow Sea with a Wave-Current Coupled Model

Qiao, Fangli,Ma, Ji-An,Yang, Yong-Zeng,Yuan, Yeli The Korean Society of Oceanography 2004 Journal of the Korean Society of Oceanography Vol.39 No.1

Based on the MASNUM wave-current coupled model, the temperature and salinity structures along $36^{\circ}N$ in the Yellow Sea are simulated and compared with observations. Both the position and strength of the simulated thermocline are similar to data analysis. The wave-induced mixing is strongest in winter and plays a key role in the formation of the upper mixed layer in spring and summer. Numerical experiments suggest that in the coastal area, wave-induced mixing and tidal mixing control the vertical structure of temperature and salinity.

Gut Microbiota Alteration Influences Colorectal Cancer Metastasis to the Liver by Remodeling the Liver Immune Microenvironment

Yuan Na,Li Xiaoyan,Wang Meng,Zhang Zhilin,Qiao Lu,Gao Yamei,Xu Xinjian,Zhi Jie,Li Yang,Li Zhongxin,Jia Yitao 거트앤리버 소화기연관학회협의회 2022 Gut and Liver Vol.16 No.4

Background/Aims:This study aimed to explore the effect of gut microbiota-regulated Kupffer cells (KCs) on colorectal cancer (CRC) liver metastasis. Methods: A series of in vivo and in vitro researches were showed to demonstrate the gut microbiota and its possible mechanism in CRC liver metastasis. Results: Fewer liver metastases were identified in the ampicillin-streptomycin-colistin and colistin groups. Increased proportions of Parabacteroides goldsteinii, Bacteroides vulgatus, Bacteroides thetaiotaomicron, and Bacteroides uniformis were observed in the colistin group. The significant expansion of KCs was identified in the ampicillin-streptomycin-colistin and colistin groups. B. vulgatus levels were positively correlated with KC levels. More liver metastases were observed in the vancomycin group. An increased abundance of Parabacteroides distasonis and Proteus mirabilis and an obvious reduction of KCs were noted in the vancomycin group. P. mirabilis levels were negatively related to KC levels. The number of liver metastatic nodules was increased in the P. mirabilis group and decreased in the B. vulgatus group. The number of KCs decreased in the P. mirabilis group and increased in the B. vulgatus group. In vitro, as P. mirabilis or B. vulgatus doses increased, there was an opposite effect on KC proliferation in dose- and time-dependent manners. P. mirabilis induced CT26 cell migration by controlling KC proliferation, whereas B. vulgatus prevented this migration. Conclusions: An increased abundance of P. mirabilis and decreased amount of B. vulgatus play key roles in CRC liver metastasis, which might be related to KC reductions in the liver.

An Age- and Condition-Dependent Variable Weight Model for Performance Evaluation of Bridge Systems

Yuan Ren,Xiang Xu,Bin Liu,Qiao Huang 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.5

To address the balance problem between indexes within the performance evaluation of bridge systems, this paper develops an age- and condition-based variable weight model (ACVWM). First, the limitations of existing models used for the multi-layer weighted sum method, i.e., constant weight model (CWM) and condition-based variable weight model (CVWM), are presented through case studies, indicating that the weight variation is insufficient to characterize the deterioration law of components. Then, the definition of age-based variable weight is established following the existing concept of condition-based variable weight, which makes weights vary with service ages. Considering the characteristics of bridge assessment, an age-based variable weight model is built up to depict the time-variant trends of index weights with the service age. The variation law of age-based variable weight is discussed by using indexes in the superstructure of suspension bridges. As a result, the weights of replaceable and permanent components behave differently within the bridge service life. Finally, the ACVWM is built up and its effectiveness is verified through the same case studies applied to the CWM and CVWM. Compared with the evaluation results from the CWM and CVWM, the evaluation result of the ACVWM is more in line with the real maintenance strategy. Considering the CVWM in which low initial weights may lead to unsatisfactory weight assignment, the advantage of the proposed ACVWM lies in its capability to adjust initial weights over the service age.

Cointegration based modeling and anomaly detection approaches using monitoring data of a suspension bridge

Yuan Ren,Ziyuan Fan,Qiao Huang,Qiaowei Ye,Weijie Chang,Yichao Wang 국제구조공학회 2023 Smart Structures and Systems, An International Jou Vol.31 No.2

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.