Analysis of the regional spectral properties in northwestern South China Sea based on an empirical orthogonal function

This study presents an analysis of the spectral characteristics of remote sensing reflectance(Rrs)in northwestern South China Sea based on the in situ optical and water quality data for August 2018.Rrswas initially divided into four classes,classes A to D,using the max-classification algorithm,and the spectral properties of whole Rrs were characterized using the empirical orthogonal function(EOF)analysis.Subsequently,the dominant factors in each EOF mode were determined.The results indicated that more than 95%of the variances of Rrs are partly driven by the back-scattering characteristics of the suspended matter.The initial two EOF modes were well correlated with the total suspended matter and back-scattering coefficient.Furthermore,the first EOF modes of the four classes of Rrs(A-D Rrs-EOF1)significantly contributed to the total variances of each Rrs class.In addition,the correlation coefficients between the amplitude factors of class A-D Rrs-EOF1 and the variances of the relevant water quality and optical parameters were better than those of the unclassified ones.The spectral shape of class ARrs-EOF1 was governed by the absorption characteristic of chlorophyll a and colored dissolved organic matter(CDOM).The spectral shape of class B Rrs-EOF1 was governed by the absorption characteristic of CDOM since it exhibited a high correlation with the absorption coefficient of CDOM(ag(λ)),whereas the spectral shape of class C Rrs-EOF1 was governed by the back-scattering characteristics but not affected by the suspended matter.The spectral shape of class D Rrs-EOF1 exhibited a relatively good correlation with all the water quality parameters,which played a significant role in deciding its spectral shape.

Understanding Human Development Potentials and Demands for Greenhouse Gas Emissions:with Empirical Analysis using time series and cross-sectional data

Based on an investigation of the meaning of development, the neo-classical economic approach to development, and the post-welfarist theory of development, this paper proposes a conceptual framework for understanding human development potentials, while undertaking empirical analysis using cross-sectional and time series data on human development. Human development is associated with basic necessities for subsistence, the quality of life, and political and civil rights, in addition to income indicators. Our analysis suggests that the concept of human development potentials has two dimensions: the rights of development and limits to human development. Both are largely ignored in the neoclassical theory of development. However, human development is not unbounded, which approaches to a relatively fixed constant at given economic, technological and institutional conditions. This conceptual understanding is supported by results from the empirical examination of the relationships between demands for carbon

Empirical Analysis of Agricultural Cultural Resources Value Evaluation under DEA Model

Agricultural culture is a productive activity about education and management.It aims at high efficiency and high quality,uses technology as its means,and takes nature as its carrier.Agricultural cultural resources are the product of the rapid development of modern economy.It promotes the development of the national economy and profoundly affects people's production and life.DEA model,also known as data envelope analysis method,is an algorithm that uses multiple data decision units for input and output training to obtain the final model.This article explains the concept and basic characteristics of agricultural culture.Through questionnaire surveys and expert interviews,we collected development data,screened human,material,and financial data,and calculated information on economic and social resources.On this basis,this paper establishes the evaluation index of agricultural culture based on DEA model.Then,through empirical analysis from a specific perspective,it can be concluded that increasing human,material and financial input can achieve economic and social benefits.Generally speaking,cultural investment can promote the development of the industry.The research results of this paper laid a theoretical foundation for the development of agricultural culture,and put forward a development model focusing on technology development,improving investment efficiency,and investing in material resources.

An Empirical Analysis on Diversity of Regional Economic Growth in Jiangsu Province of China

By using index β * and δ * ,this paper carries out an empirical analysis on diversity of regional economic growth in Jiangsu province. Firstly, the paper, from the point of view of economics, divides diversity theories of economic growth into three categories, i.e. the theory of convergence, the theory of divergence and the theory of constant differentials, and analyses them respectively. Secondly, the paper, using sectional and time series data, compares and studies regional economic growth among southern, middle and northern part of Jiangsu province. Finally, the paper analyses the empirical conclusions. The main conclusion is that the theory of convergence is suit to Jiangsu economic growth.

Empirical Analysis on Dominant Agriculture in Agricultural Districts and Counties of Tianjin

At present,developing the dominant agriculture plays an essential role in promoting the agricultural modernization of Tianjin. Based on the theory of location quotient,this paper made a quantitative analysis of the dominant agriculture in the agricultural districts and counties of Tianjin. According to the analysis,it made a qualitative analysis of the factors. Finally,it determined the dominant agriculture of each agricultural district and county of Tianjin.

An Empirical Study of Downstream Analysis Effects of Model Pre-Processing Choices

This study uses an empirical analysis to quantify the downstream analysis effects of data pre-processing choices. Bootstrap data simulation is used to measure the bias-variance decomposition of an empirical risk function, mean square error (MSE). Results of the risk function decomposition are used to measure the effects of model development choices on model bias, variance, and irreducible error. Measurements of bias and variance are then applied as diagnostic procedures for model pre-processing and development. Best performing model-normalization-data structure combinations were found to illustrate the downstream analysis effects of these model development choices. In additions, results found from simulations were verified and expanded to include additional data characteristics (imbalanced, sparse) by testing on benchmark datasets available from the UCI Machine Learning Library. Normalization results on benchmark data were consistent with those found using simulations, while also illustrating that more complex and/or non-linear models provide better performance on datasets with additional complexities. Finally, applying the findings from simulation experiments to previously tested applications led to equivalent or improved results with less model development overhead and processing time.

Empirical Analysis on Relationship between Apple Futures and Spot Prices in China

Taking a total of 903 apple futures data from Zhengzhou Futures Exchange as research samples, and through unit root test, cointegration test, error correction, Granger causality test and variance decomposition with the aid of Eviews 8.0, this paper made an empirical analysis on the relationship between Zhengzhou apple futures market and Chinese apple website(pingguo7.cn) spot market price. It concluded that the main continuity of apple futures has an absolute advantage over the reference value of the futures index, and apple market participants can achieve hedging through the futures and spot market.

An Empirical Analysis of Factors Affecting Mentoring Relationship between Supervisor and Postgraduate

The mentoring relationship between supervisor and postgraduate is crucially important to ensure the quality of education for postgraduates.In this paper,factors affecting the mentoring relationship were investigated by a binary logit model using data collected from 345 postgraduates.In addition,marginal effects were introduced to quantify the effects of factors on mentoring relationship.A total of 11 factors were found to be significant,and four of them could increase the risk of supervisor-postgraduate conflict,while the remaining seven factors could decrease the risk of supervisor-postgraduate conflict.Findings from this study can help better understand the mechanism of supervisor-postgraduate conflicts and develop effective countermeasures.

Spatio-temporal variability of surface chlorophyll a in the Yellow Sea and the East China Sea based on reconstructions of satellite data of 2001-2020

Chlorophyll-a(Chl-a)concentration is a primary indicator for marine environmental monitoring.The spatio-temporal variations of sea surface Chl-a concentration in the Yellow Sea(YS)and the East China Sea(ECS)in 2001-2020 were investigated by reconstructing the MODIS Level 3 products with the data interpolation empirical orthogonal function(DINEOF)method.The reconstructed results by interpolating the combined MODIS daily+8-day datasets were found better than those merely by interpolating daily or 8-day data.Chl-a concentration in the YS and the ECS reached its maximum in spring,with blooms occurring,decreased in summer and autumn,and increased in late autumn and early winter.By performing empirical orthogonal function(EOF)decomposition of the reconstructed data fields and correlation analysis with several potential environmental factors,we found that the sea surface temperature(SST)plays a significant role in the seasonal variation of Chl a,especially during spring and summer.The increase of SST in spring and the upper-layer nutrients mixed up during the last winter might favor the occurrence of spring blooms.The high sea surface temperature(SST)throughout the summer would strengthen the vertical stratification and prevent nutrients supply from deep water,resulting in low surface Chl-a concentrations.The sea surface Chl-a concentration in the YS was found decreased significantly from 2012 to 2020,which was possibly related to the Pacific Decadal Oscillation(PDO).

Study on the Influence of Lanzhou-Urumqi High-Speed Railway on Regional Accessibility and Economic Development

The Lanzhou-Urumqi high-speed railway is an important part of the railway network connecting Gansu,Qinghai,and Xinjiang,and it is of far-reaching significance in facilitating China’s western development.An accessibility model and a double difference model were built to analyze the impact of the Lanzhou-Urumqi high-speed railway on regional accessibility and economic development of the areas along the line before(2012-2014)and after(2017-2019)its opening.The results show that the regional accessibility remains unchanged before and after the operation of this railway line.However,there is a spatial difference in improvement,that of central cities being better.The opening of the high-speed railway is conducive to driving the overall economic development of the region and promoting the comprehensive and coordinated development of regional economies.

Are“Internet+”tactics the key to poverty alleviation in China’s rural ethnic minority areas? Empirical evidence from Sichuan Province

China has made great efforts to alleviate poverty in rural ethnic minority areas and targeted achieving the poverty-alleviation task by the end of 2020.Aba,Ganzi,and Liangshan,three of the poorest ethnic prefectures in Sichuan Province,Southwest China,have all implemented“Internet+”tactics since 2013,which have had the positive effect of increasing family revenues by improving communication infrastructure and encouraging the large-scale use of e-commerce.This paper aims to comprehensively investigate whether“Internet+”tactics play a key role in poverty alleviation in Sichuan’s rural ethnic minority areas and to propose further measures to enhance the efficiency of e-commerce practice.To this end,we conduct an analysis using the framework of classic growth theory and use panel data from 2000 to 2018 to examine the relationship between Communication Infrastructure Investment(CII)and a set of poverty-alleviation indicators,including local GDP growth rate(LGGR),local government revenue(LGR),and per-capita income of residents(PCIR).The results indicate that strengthening CII improves the PCIR and local economic growth,playing a key role in poverty alleviation.However,the stimulation of CII on LGGR and LGR wanes as time passes.More financial and technical actions will be needed to improve the efficiency and quality of current strategies for sustainable development in those areas.

An Empirical Study on the Influence of Agricultural Public Infrastructure on Total Factor Productivity of China’s Grain Production

A critical method of ensuring grain production is to increase the total factor productivity(TFP),and the key measure to increase the TFP of grain production lies in the construction of agricultural public infrastructure.For this topic,existing literature lacks systematic and empirical analysis.Therefore,research on the influence of agricultural public infrastructure on the TFP of China’s grain production has relatively strong policy implications and theoretical value.For this study,we collected panel data for grain inputs and outputs as well as for agricultural public infrastructure in China’s provinces(autonomous regions/municipalities)from 1990 to 2017,and adopted the stochastic frontier function(SFF)approach to measure the TFP of provincial-level grain production.Through this empirical study,we analyzed the influence of agricultural public infrastructures,such as irrigation,roads,and electric power facilities on the TFP of China’s agriculture.We found that such facilities have a positive influence on the TFP of grain production.Specifically,when the input for irrigation facilities is increased by 1 percent,the TFP of grain production will rise by 5.74 percent.Based on this finding,policy recommendations are proposed for enhancing grain TFP through agricultural public infrastructure construction.

Research on Accounting Issues of the Pension Insurance Fund for Urban Employees

Pension insurance is a vital component of China's social security system,ensuring the welfare of the general publie.This study centers on the revenue and expenses of City S's urban employee basic pension insurance fund.It introduces and analyzes the fund's accounting status from four key perspectives:fund raising.expenditure,financial statement system,and accounting information disclosure.The research identifes existing problems in City S's accounting system and conducts in-depth research on these issues.Furthermore,an empirical analysis is conducted on the management of the pension insurance fund.Through this empirical study,the paper aims to offer insights and recommendations for promoting stable and healthy development measures for City S'8 urban employee basic pension insurance fund.

Modelling the performance of EPB shield tunnelling using machine and deep learning algorithms

This paper introduces an intelligent framework for predicting the advancing speed during earth pressure balance(EPB)shield tunnelling.Five artificial intelligence(AI)models based on machine and deep learning techniques-back-propagation neural network(BPNN),extreme learning machine(ELM),support vector machine(SVM),long-short term memory(LSTM),and gated recurrent unit(GRU)-are used.Five geological and nine operational parameters that influence the advancing speed are considered.A field case of shield tunnelling in Shenzhen City,China is analyzed using the developed models.A total of 1000 field datasets are adopted to establish intelligent models.The prediction performance of the five models is ranked as GRU>LSTM>SVM>ELM>BPNN.Moreover,the Pearson correlation coefficient(PCC)is adopted for sensitivity analysis.The results reveal that the main thrust(MT),penetration(P),foam volume(FV),and grouting volume(GV)have strong correlations with advancing speed(AS).An empirical formula is constructed based on the high-correlation influential factors and their corresponding field datasets.Finally,the prediction performances of the intelligent models and the empirical method are compared.The results reveal that all the intelligent models perform better than the empirical method.

The Interannual Variability of Summer Rainfall in the Arid and Semiarid Regions of Northern China and Its Association with the Northern Hemisphere Circumglobal Teleconnection

Using the latest daily observational rainfall datasets for the period 1961–2008, the present study investigates the interannual variability of June–September （JJAS） mean rainfall in northern China. The regional characteristics of JJAS mean rainfall are revealed by a rotated empirical orthogonal function （REOF） analysis. The analysis identifies three regions of large interannual variability of JJAS rainfall： North China （NC）, Northeast China （NEC）, and the Taklimakan Desert in Northwest China （TDNWC）. Summer rainfall over NC is shown to have displayed a remarkable dry period from the late 1990s; while over NEC, decadal-scale variation with a significant decreasing trend in the last two decades is found, and over TDNWC, evidence of large interannual variability is revealed. Results also show that the interannual variability of JJAS rainfall in northern China is closely associated with the Northern Hemisphere circumglobal teleconnection （CGT）. Correlation coefficients between the CGT index and regional-averaged JJAS mean rainfall over NC and NEC were calculated, revealing values of up to 0.50 and 0.53, respectively, both of which exceeded the 99% confidence level.

Developing a quantitative index system for assessing sustainable forestry management in Heilongjiang Province,China： a case study

In this study, we developed a comprehensive index system for forestry sustainability of Heilongjiang Province, which includes forest resources sustainability,sustainable economic development, sustainable social development and sustainable advancement in science and technology. Based on this system and the regional forest development, we further evaluated the sustainability of Heilongjiang Province for year 2008-2013. The results show that even though the regional forestry has been preliminarily on the track of sustainable development, it is fragile. Four indicators, e.g. soil and water retention rate,forest stand growth（per unit area）, the proportion of national investment and the annual carbon sequestration have important impact on the sustainability, with a weight of 39.0 % in all the indicators. We also analyzed the factors hindering the sustainable development. It turns out that soil and water retention rate, forest stand growth（per unit area）,the proportion of science and technology funds, per capita GDP and the proportion of the tertiary industry production are the main factors hindering regional sustainable development, which accounts for 50.94 % of the total obstacle degrees in the system. At last, we discussed how to promote the regional sustainable development from the perspectives of forest resources sustainability, economic development sustainability, society development sustainability and the sustainable advancement of science and technology.

Anomaly feature of seasonal frozen soil variationson the Qinghai-Tibet Plateau

The seasonal frozen soil on the Qinghai-Tibet Plateau has strong response to climate change, and its freezing-thawing process also affects East Asia climate. In this paper, the freezing soil maximum depth of 46 stations covering 1961–1999 on the plateau is analyzed by rotated experience orthogonal function (REOF). The results show that there are four main frozen anomaly regions on the plateau, i.e., the northeastern, southeastern and southern parts of the plateau and Qaidam Basin. The freezing soil depths of the annual anomaly regions in the above representative stations show that there are different changing trends. The main trend, except for the Qaidam Basin, has been decreasing since the 1980s, a sign of the climate warming. Compared with the 1980s, on the average, the maximum soil depth decreased by about 0.02 m, 0.05 m and 0.14 m in the northeastern, southeastern and southern parts of the plateau, but increased by about 0.57 m in the Qaidam Basin during the 1990s. It means there are different responses to climate system in the above areas. The spectrum analysis reveals different change cycles: in higher frequency there is an about 2-year long cycle in Qaidam Basin and southern part of the plateau in the four representative areas whereas in lower frequency there is an about 14-year long cycle in all the four representative areas due to the combined influence of different soil textures and solutes in four areas.

Determination of the ground vibration attenuation law from a singleblast: A particular case of trench blasting

The general transmissivity law of ground vibrations was studied,and a user-friendly methodology for determining the behavior of vibrations generated in any rock mass is proposed.The study was based on a single blast in a trench excavation,analyzing the vibration components recorded from two fixed locations.The attenuation law and the main variables according to the legal requirements,frequency and peak particle velocity(PPV),are defined with this novel method,achieving a high confidence level in a simple manner.The proposed approach can also have an important impact in terms of reducing the potential consequences of vibrations for the surrounding construction and achieving the required definition of rock mass.Reducing the cost and time in many projects where blasting techniques are applied is particularly useful for the design of future blasts.

Bias correction of sea surface temperature retrospective forecasts in the South China Sea

Offline bias correction of numerical marine forecast products is an effective post-processing means to improve forecast accuracy. Two offline bias correction methods for sea surface temperature(SST) forecasts have been developed in this study: a backpropagation neural network(BPNN) algorithm, and a hybrid algorithm of empirical orthogonal function(EOF) analysis and BPNN(named EOF-BPNN). The performances of these two methods are validated using bias correction experiments implemented in the South China Sea(SCS), in which the target dataset is a six-year(2003–2008) daily mean time series of SST retrospective forecasts for one-day in advance, obtained from a regional ocean forecast and analysis system called the China Ocean Reanalysis(CORA),and the reference time series is the gridded satellite-based SST. The bias-correction results show that the two methods have similar good skills;however, the EOF-BPNN method is more than five times faster than the BPNN method. Before applying the bias correction, the basin-wide climatological error of the daily mean CORA SST retrospective forecasts in the SCS is up to-3°C;now, it is minimized substantially, falling within the error range(±0.5°C) of the satellite SST data.

Temporal-spatial oceanic variation in relation with the three typical Kuroshio paths south of Japan

Empirical orthogonal function(EOF)analysis was applied to a 50-year long time series of monthly mean positions of the Kuroshio path south of Japan from a regional reanalysis.Three leading EOF modes characterize the contributions from three typical paths of the Kuroshio meander:the typical large meander path,the offshore nonlarge meander path,and the nearshore non-large meander path,respectively.Accordingly,the spatial variation characteristics of oceanic anomaly fields can be depicted by their regression fields upon the associated three leading principal components(PCs),which are well-matched with the results of composite analysis corresponding to each period of the three typical Kuroshio paths.A new index for the typical large meander is defined by using the second leading PC,which is highly correlated with the Kushimoto-Uragami index.Spectral analysis of this new index series shows variability of the Kuroshio path south of Japan at time scales of about 7–8 years and 20 years.