A review of the immunomodulatory activities of polysaccharides isolated from Panax species

Yeye Hu,Yang He,Zhiqiang Niu,Ting Shen,Ji Zhang,Xinfeng Wang,Weicheng Hu a,Jae Youl Cho 고려인삼학회 2022 Journal of Ginseng Research Vol.46 No.1

Panax polysaccharides are biopolymers that are isolated and purified from the roots, stems, leaves, flowers, and fruits of Panax L. plants, which have attracted considerable attention because of their immunomodulatory activities. In this paper, the composition and structural characteristics of purified polysaccharides are reviewed. Moreover, the immunomodulatory activities of polysaccharides are described both in vivo and in vitro. In vitro, Panax polysaccharides exert immunomodulatory functions mainly by activating macrophages, dendritic cells, and the complement system. In vivo, Panax polysaccharides can increase the immune organ indices and stimulate lymphocytes. In addition, this paper also discusses the membrane receptors and various signalling pathways of immune cells. Panax polysaccharides have many beneficial therapeutic effects, including enhancing or activating the immune response, and may be helpful in treating cancer, sepsis, osteoporosis, and other conditions. Panax polysaccharides have the potential for use in the development of novel therapeutic agents or adjuvants with beneficial immunomodulatory properties.

Frequency Response Analysis on Modified Plant of Extended State Observer

Yuqiong Zhang,Yali Xue,Donghai Li,Zhiqiang Gao,Haiming Niu,Huanpao Huang 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10

The active disturbance rejection control (ADRC) framework gives birth to a new concept, the modified plant (MP), describing the dynamics after the total disturbance is estimated and cancelled approximately. Ideally the modified plant is in integral form, to greatly simplify and fix the controller design, even though actual plant contains higher-order dynamics or dead time. This paper investigates that when such processes are modified into the integral, how the parameters of the extended state observer (ESO) impact on the dynamic characteristics and stability of the MP. Frequency-domain analyses show that the MP can gradually approach the integral form through parameters tuning. However, it should be cautious that an aggressive set of parameters may lead to an unstable modified plant in the presence of order mismatch.

The potential of Panax notoginseng against COVID-19 infection

Yeye Hu,Ziliang He,Wei Zhang,Zhiqiang Niu,Yanting Wang,Ji Zhang,Ting Shen,Hong Cheng,Weicheng Hu 고려인삼학회 2023 Journal of Ginseng Research Vol.47 No.5

The COVID-19 pandemic has changed the world and has presented the scientific community with unprecedentedchallenges. Infection is associated with overproduction of proinflammatory cytokines secondaryto hyperactivation of the innate immune response, inducing a cytokine storm and triggeringmultiorgan failure and significant morbidity/mortality. No specific treatment is yet available. For thousandsof years, Panax notoginseng has been used to treat various infectious diseases. Experimental evidenceof P. notoginseng utility in terms of alleviating the cytokine storm, especially the cascade, andimproving post-COVID-19 symptoms, suggests that P. notoginseng may serve as a valuable adjuncttreatment for COVID-19 infection.

Uncertainty Analysis of Dynamic Thermal Rating of Overhead Transmission Line

Zhou, Xing,Wang, Yanling,Zhou, Xiaofeng,Tao, Weihua,Niu, Zhiqiang,Qu, Ailing Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.2

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambient temperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty is an important parameter to evaluate the reliability of measurement results. This paper presents the uncertainty analysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probability density function of the input parameter value, the probability density function of the output value is determined by probability distribution random sampling. Through the calculation and analysis of the transient thermal balance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, the transient current carrying capacity, the standard uncertainty and the probability distribution of the minimum and maximum values of the conductor under 95% confidence interval are obtained. The simulation results indicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, and increase the validity and reliability of the uncertainty evaluation.

Short-Term Wind Speed Forecast Based on Least Squares Support Vector Machine

Wang, Yanling,Zhou, Xing,Liang, Likai,Zhang, Mingjun,Zhang, Qiang,Niu, Zhiqiang Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.6

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to low prediction accuracy for wind speed. According to this situation, this paper constructs the short-time forecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate the regression relationships between the historical data and forecasting data of wind speed. In order to improve the forecast precision, historical data is clustered by cluster analysis so that the historical data whose changing trend is similar with the forecasting data can be filtered out. The filtered historical data is used as the training samples for SVR and the parameters would be optimized by particle swarm optimization (PSO). The forecasting model is tested by actual data and the forecast precision is more accurate than the industry standards. The results prove the feasibility and reliability of the model.

Short-Term Wind Speed Forecast Based on Least Squares Support Vector Machine

Yanling Wang,Xing Zhou,Likai Liang,Mingjun Zhang,Qiang Zhang,Zhiqiang Niu 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.6

There are many factors that affect the wind speed. In addition, the randomness of wind speed also leads to lowprediction accuracy for wind speed. According to this situation, this paper constructs the short-timeforecasting model based on the least squares support vector machines (LSSVM) to forecast the wind speed. The basis of the model used in this paper is support vector regression (SVR), which is used to calculate theregression relationships between the historical data and forecasting data of wind speed. In order to improvethe forecast precision, historical data is clustered by cluster analysis so that the historical data whose changingtrend is similar with the forecasting data can be filtered out. The filtered historical data is used as the trainingsamples for SVR and the parameters would be optimized by particle swarm optimization (PSO). Theforecasting model is tested by actual data and the forecast precision is more accurate than the industrystandards. The results prove the feasibility and reliability of the model.

Uncertainty Analysis of Dynamic Thermal Rating of Overhead Transmission Line

Xing Zhou,Yanling Wang,Xiaofeng Zhou,Weihua Tao,Zhiqiang Niu,Ailing Qu 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.2

Dynamic thermal rating of the overhead transmission lines is affected by many uncertain factors. The ambienttemperature, wind speed and wind direction are the main sources of uncertainty. Measurement uncertainty isan important parameter to evaluate the reliability of measurement results. This paper presents the uncertaintyanalysis based on Monte Carlo. On the basis of establishing the mathematical model and setting the probabilitydensity function of the input parameter value, the probability density function of the output value is determinedby probability distribution random sampling. Through the calculation and analysis of the transient thermalbalance equation and the steady- state thermal balance equation, the steady-state current carrying capacity, thetransient current carrying capacity, the standard uncertainty and the probability distribution of the minimumand maximum values of the conductor under 95% confidence interval are obtained. The simulation resultsindicate that Monte Carlo method can decrease the computational complexity, speed up the calculation, andincrease the validity and reliability of the uncertainty evaluation.