Harmony Coefficient and Regional Agricultural Systems

The regional agricultural system （RAS） can be divided into three subsystems： ecological, economic, and social. This article examines the use of the harmony coefficient （HC）, efficacy coefficient, rank of the harmony coefficient （RHC）, and its appraising index system within the RAS. The harmony coefficient function was developed using a variance coefficient and then applied to Ziyang District, Yiyang City in Hunan Province （ZYH）, China, as a test case. From 1995 to 2002, the HC of RAS increased from 0.2982 to 0.4826 and the RHC increased from 3 to 5, although the HC trend was an ＂n＂ type in general. This suggests that the HC was weakly maladjusted and the RAS was not harmonious. The HC of the ecological subsystem decreased from 0.3898 to 0.2850, and its RHC from 4 to 3, with the HC trend following the ＂n＂ type. For the economic subsystem, the HC value increased from 0.5767 to 0.7458 and the RHC from 6 to 8. However, the trend in HC for the economic subsystem was of the ＂U＂ type. The HC of the social subsystem increased slightly from 0.4948 to 0.4663, and the RHC did not change in value. From the HC trends, the HC curve of the economic subsystem is above the HC curve of ZYH and the HC curve of the ecological subsystem is below the HC curve of ZHY. Hence, the ZHY environment has been destroyed by economic development. Environment and social building should be regarded as important issues in the future and promoting RAS harmony development should be considered. The results of the theoretical analysis match fairly closely with reality, and suggest that the harmony theory is feasible in appraising RAS development phases.

基于Logistic回归的古代玻璃制品化学成分分析和研究

文章主要通过研究玻璃含有的不同化学成分,分析和鉴别古代的玻璃制品。首先分析了现有玻璃文物的数据,利用Spearman’s rank correlation coefficient和卡方检验表面分化、纹饰、颜色和玻璃类型之间的联系,采用Logistic回归鉴别未知文物,分析其所属的类型,并分析了分类结果的灵敏度。通过分析可知,文章采用的分类方法,能较好地通过化学成分对玻璃进行分类。

Change Trend of Chinese Urban Residents' Food-nitrogen Consumption

Change trend of Chinese urban residents＇ per capita food-nitrogen annual consumption from 1981 to 2007 was analyzed and predicted by using ARIMA time-series model in order to reveal the change of urban food-nitrogen consumption during the China＇s urbanization process.Results showed that after 1980s,the annual consumption of Chinese urban residents＇ food-nitrogen had a change trend of ＂ increase-decrease-increase＂ and generally presented as a slight increasing trend;With the acceleration of rapid economic development and urbanization process,Chinese urban residents＇ food-nitrogen consumption will still keep a rising trend in future,and also has a large rising space.

Guided Wave Based Damage Detection Method for Aircraft Composite Structures under Varying Temperatures

Guided waves based damage detection methods using base signals offer the advantages of simplicity of signal generation and reception,sensitivity to damage,and large area coverage;however,applications of the technology are limited by the sensitivity to environmental temperature variations.In this paper,a Spearman Damage Index-based damage diagnosis method for structural health condition monitoring under varying temperatures is presented.First,a PZT sensor-based Guided wave propagation model is proposed and employed to analyze the temperature effect.The result of the analysis shows the wave speed of the Guided wave signal has higher temperature sensitivity than the signal fluctuation features.Then,a Spearman rank correlation coefficient-based damage index is presented to identify damage of the structure under varying temperatures.Finally,a damage detection test on a composite plate is conducted to verify the effectiveness of the Spearman Damage Index-based damage diagnosis method.Experimental results show that the proposed damage diagnosis method is capable of detecting the existence of the damage and identify its location under varying temperatures.

Research on Measurable Nonlinear Relationship Between Phytoplankton Biomass and Environmental Factors in Bohai Bay

B ased on the data of phytoplankton and environmental factors in the Bohai Bay, the dependence between the concentration of phytoplankton and environmental factors is analysed by linear correlation coefficient, rank correlation coefficient and Hoeffding test of independence .The result shows that wind-speed, air-pressure, surface temperature, field pH, salinity, DO, silicate and NO3- have a great impact on the concentration of phytoplankton.

Characteristics of Ambient Air Quality in the Central Urban Area of Western Guizhou in the Past Five Years

Air is an important condition for human activities and survival,and its quality is closely related to the quality of life and level of health for the people.In recent years,the problem caused by air quality has become one of the main problems that endanger human health and restrict economic development,which has been widely concerned.In this paper,the air quality status and its changing trend were analyzed by using the methods of the comprehensive index of ambient air quality and Spearman s rank correlation coefficient,based on the hourly pollutant concentration data of five national ambient air quality monitoring stations in the central urban area of Liupanshui City,Guizhou Province from January 1,2015 to December 31,2019.The results showed that the concentration of air pollutants in the atmosphere in the past five years showed a downward trend in the central urban area of Liupanshui City.During 2018-2019,the air quality has been up to the standard for two consecutive years,and it was developing to a higher quality direction.The air quality was better in summer half year than in winter half year.In one year,the air quality was the best in June and the worst in February.The air quality was the best at 07:00 and the worst at 21:00 every day.The air quality in the east and the west of the city was better than that in the middle.In most years,the activities,making and burning paper to resemble money as an offering sacrifices to gods or ancestors in Zhongyuan Festival,caused serious pollution.

Parameter Sensitivity and Qualitative Analysis of Dynamics of Ovarian Tumor Growth Model with Treatment Strategy

In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling (LHS) method to generate sample points and Partial Rank Correlation Coefficient (PRCC) method, uses those sample points to find out which parameters are important for the model. Based on our findings, we suggest some treatment strategies. We investigate the sensitivity of the parameters for tumor volume, y, cell nutrient density, Q and maximum tumor size, ymax. We also use Scatter Plot method using LHS samples to show the consistency of the results obtained by using PRCC. Moreover, we discuss the qualitative analysis of ovarian tumor growth model investigating the local and global stability.

An Automatic Monitoring and Alarming Method for the Power Supply of Weather Radars

As weather radar stations require headroom environment to operate,they were mostly built on highlands which are usually unattended.The mains supply is relatively poor,and the risk of radar stoppages due to power outage is therefore ever-present.As such,the radar construction program is used to build a complementary security video monitoring system.By collecting monitoring images of the regulated power supply in real-time from power supply auto transfer systems in distribution rooms and radar transceiver rooms,using Spearman’s rank correlation coefficient to analyse pixel variation trends,and supplementing statistical analysis of pixel characteristics difference to eliminate misjudgments resulting from low image contrast in special scenarios,a software can be developed through C#.It has the function of automatically monitoring mains supply and alerting staff on duty to handle the power outage in a timely manner via text message so that any potential risk is neutralised before it can cause damage.This monitoring and auto-alerting approach is generally applicable to unattended rooms with large amounts of electronical equipment.

Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver

The predictive accuracy of mathematical models representing anything ranging from the meteorological to the biological system profoundly depends on the quality of model parameters derived from experimental data.Hence,robust sensitivity analysis(SA)of these critical model parameters aids in sifting the influential from the negligible out of typically vast parameter regimes,thus illuminating key components of the system under study.We here move beyond traditional local sensitivity analysis to the adoption of global SA techniques.Partial rank correlation coefficient(PRCC)based on Latin hypercube sampling is compared with the variance-based Sobol method.We selected for this SA investigation an infection model for the hepatitis-B virus(HBV)that describes infection dynamics and clearance of HBV in the liver[Murray&Goyal,2015].The model tracks viral particles such as the tenacious and nearly ineradicable covalently closed circular DNA(cccDNA)embedded in infected nuclei and an HBV protein known as p36.Our application of these SA methods to the HBV model illuminates,especially over time,the quantitative relationships between cccDNA synthesis rate and p36 synthesis and export.Our results reinforce previous observations that the viral protein,p36,is by far the most influential factor for cccDNA replication.Moreover,both methods are capable of finding crucial parameters of the model.Though the Sobol method is independent of model structure(e.g.,linearity and monotonicity)and well suited for SA,our results ensure that LHS-PRCC suffices for SA of a non-linear model if it is monotonic.