Modelling of an hydraulic excavator using simplifiedrefined instrumental variable(SRIV)algorithm

Instead of establishing mathematical hydraulic system models from physical laws usually done with the problems of complex modelling processes, low reliability and practicality caused by large uncertainties, a novel modelling method for a highly nonlinear system of a hydraulic excavator is presented. Based on the data collected in the excavator＇s arms driving experiments, a data-based excavator dynamic model using Simplified Refined Instrumental Variable （SRIV） identification and estimation algorithms is established. The validity of the proposed data-based model is indirectly demonstrated by the performance of computer simulation and the.real machine motion control exoeriments.

Causal roles of gut microbiota in cholangiocarcinoma etiology suggested by genetic study

BACKGROUND Cholangiocarcinoma(CCA)is a highly malignant biliary tract cancer with poor prognosis.Previous studies have implicated the gut microbiota in CCA,but evidence for causal mechanisms is lacking.AIM To investigate the causal relationship between gut microbiota and CCA risk.METHODS We performed a two-sample mendelian randomization study to evaluate potential causal associations between gut microbiota and CCA risk using genome-wide association study summary statistics for 196 gut microbial taxa and CCA.Genetic variants were used as instrumental variables.Multiple sensitivity analyses assessed result robustness.RESULTS Fifteen gut microbial taxa showed significant causal associations with CCA risk.Higher genetically predicted abundance of genus Eubacteriumnodatum group,genus Ruminococcustorques group,genus Coprococcus,genus Dorea,and phylum Actinobacteria were associated with reduced risk of gallbladder cancer and extrahepatic CCA.Increased intrahepatic CCA risk was associated with higher abundance of family Veillonellaceae,genus Alistipes,order Enterobacteriales,and phylum Firmicutes.Protective effects against CCA were suggested for genus Collinsella,genus Eisenbergiella,genus Anaerostipes,genus Paraprevotella,genus Parasutterella,and phylum Verrucomicrobia.Sensitivity analyses indicated these findings were reliable without pleiotropy.CONCLUSION This pioneering study provides novel evidence that specific gut microbiota may play causal roles in CCA risk.Further experimental validation of these candidate microbes is warranted to consolidate causality and mechanisms.

Has China-ASEAN Trade opening increased China’ s carbon emissions?

This study uses carbon emission data at the provincial level in China between 1998-2018 and the proportion of the total import and export trade between provinces and the Association of Southeast Asian Nations(ASEAN)in GDP to measure the level of China-ASEAN trade openness.It examines the impact of China ASEAN trade openness on carbon emissions and its transmission mechanism,and selects the RMB/USD exchange rate as an instrumental variable to address the endogeneity of China-ASEAN trade openness variables.The impact of China-ASEAN trade openness on China’s environment is estimated within a two-stage least squares framework.The results show that trade openness between China and ASEAN positively impacts China’s environment and can facilitate carbon emission reduction.The scale,structural,and technology effects brought by China-ASEAN trade liberalization jointly promote China’s carbon dioxide emission reduction.An inverted“U”relationship is found between economic growth and environmental quality in China,and some provinces and municipalities have now crossed the inflection point of the curve,in which carbon emi ssions decrease with an increase in per capita wealth.

Instrumental Variable Type Estimation for Generalized Varying Coefficient Models with Error-Prone Covariates

In this paper,the estimation for a class of generalized varying coefficient models with error-prone covariates is considered.By combining basis function approximations with some auxiliary variables,an instrumental variable type estimation procedure is proposed.The asymptotic results of the estimator,such as the consistency and the weak convergence rate,are obtained.The proposed procedure can attenuate the effect of measurement errors and have proved workable for finite samples.

Testing and data reduction of the Chinese Small Telescope Array(CSTAR) for Dome A,Antarctica

The Chinese Small Telescope Array （CSTAR） is the first Chinese astronomical instrument on the Antarctic ice cap. The low temperature and low pressure testing of the data acquisition system was carried out in a laboratory refrigerator and on the 4500 m Pamirs high plateau, respectively. The results from the final four nights of test observations demonstrated that CSTAR was ready for operation at Dome A, Antarctica. In this paper, we present a description of CSTAR and the performance derived from the test observations.

Identification of delayed system using instrumental variable method

System identification uses system inputs and outputs to raise mathematical models. Various techniques of system identification exist that offer a nominal model and an uncertainty bound. Many practical systems such as thermal processes ＆ chemical processes have inbuilt time delay. If the time delay used in the system model for controller design does not concur with the actual process time delay, a closed-loop system may be unstable or demonstrate unacceptable transient response characteristics so here the time delay is assumed to be time-invariant. This paper proposes on-line identification of delayed complex/uncertain systems using instrumental variable （IV） method. Parametric uncertainty has been considered which may be represented by variations of certain system parameters over some possible range. This method allows consistent estimation when the system parameters are associated with the noise terms, as the IV methods （IVM＇s） usually make no assumption on the noise correlation configuration. The faster convergence of the parameters including noise terms has been proved in this paper. Iterative prefiltering （IP） method has also been used for the identification of the delayed uncertain system and the graphical results given in this paper demonstrate that the convergence results are inferior to the instrumental variable method.

An instrumental variable approach to unveiling the determinants of flatted factory rent in Hong Kong

The early period of industrialisation in the Hong Kong SAR occurred during the 1950s–1970s.Manufacturers were engaged in labour-intensive manufacturing processes with the assistance of machines in factory buildings.Since the 1980s,manufacturers in Hong Kong have faced keen competition from neighbouring economies,amidst the rising costs of land and labour.Moreover,since the adoption of an opening-up policy by the Chinese mainland since 1978,more and more local manufacturers in Hong Kong have relocated their production processes to the mainland so as to take advantage of the lower factor costs.As a result,the contribution of the manufacturing sector to GDP declined from around 20%in 1986 to 2.7%in 2006 and further decreased to merely 1.1%in 2016.Interestingly,there has been a general upward trend of real flatted factory1 rent in Hong Kong in the past decade.This study,via a threshold regression,demonstrates that not only demand from the retail property rental market has been a factor in the increase of factory rent,but demands from the office rental market and local households have also contributed to the recent rise in real factory rent since 2006 Q1.

Premature Boarding and Human Capital Accumulation for Rural Pupils: Evidence from School Consolidations

From 2001 to 2012,many local governments in China closed down village teaching sites for primary school students in the first and second grades,consolidating them into larger township schools more distant from village students’homes.School closure and consolidation are particularly striking in China’s central and western regions,where swathes of rural labor migrated to cities for jobs.As a result,numerous primary school pupils are forced to study at boarding schools in the first and second grades,which is considered as too early for pupils to live without parental care.This paper employs survey data from 137 township schools with boarding qualifications collected by a project team consisting of researchers from the China Institute for Educational Finance Research(CIEFR)of Peking University,the Institute of Population and Labor Economics of the Chinese Academy of Social Sciences(IPLE-CASS)and the Capital University of Economics and Business(CUEB).By matching the home-school distance with village teaching site information as the proxy variable for the school consolidation policy,this paper evaluates the policy's impact on the likelyhood of premature boarding for primary school pupils,as well as the impact on their human capital accumulation.Our study finds that the creation of teaching sites makes it less likely for primary school pupils to board at school.Premature boarding impedes children’s human capital accumulation,and the harmful effect is particularly striking for children lacking pastoral teachers,raised by grandparents and from families above average income levels,as well as girls.

The Effect of Overseas Educational Experience on Pro-Environmental Practices: Evidence from Cambodian Academic Scholars

This paper revealed that after spending years overseas for learning, Cambodian fellows realized that a clean society more likely results from the adopting of a waste management system. The lack of such is the main barrier for waste separation willingness and practices in Cambodia. Self-transcendence values and volunteerism are empirically found as the fundamental factors for any interventions designed to promote pro-environmental intentions and practices respectively. The fellows engaging in volunteerisms appear to do waste separation, ignoring how inconvenient the waste management system or facilities are. Similarly, the fellows concerning the environmental and social issues appear to spare their valuable time to do waste-separation which they find not difficult. This is not the case in this COVID-19 epidemic though. The study results imply that in a society where an inconvenient waste management system is in place the fellows without past volunteering, no matter how knowledgeable they are, will less likely engage in the waste-sorting practice.

Does China's digital economy contribute to low-carbon transition?

The digital economy,as a new emerging economic form,has become an important power for realizing Chinese-style modernization and promoting green development in China.This paper measures the digital economy and low-carbon transition index based on the data of 30 provinces in China from 2013 to 2020 and analyzes the mechanism and path of the digital economy affecting low-carbon transition using the fixed effect panel data model and the threshold effect model.It is found that,(1)The digital economy and low-carbon transition in China are various in different regions,with characteristics of being unbalanced and insufficient.(2)The digital economy significantly promotes low-carbon transition,with the greatest influence in the Central region,followed by the Eastern region and the Western region.Under different dimensions,the development of informatization and digital transactions promote low-carbon transition,but the development of the internet plays an inhibiting role.(3)The higher the degree of urbanization and environmental regulation,the greater the influence of the digital economy on low-carbon transition.

Statistical Inference of Partially Specified Spatial Autoregressive Model

This paper studies estimation of a partially specified spatial autoregressive model with heteroskedas- ticity error term. Under the assumption of exogenous regressors and exogenous spatial weighting matrix, the unknown parameter is estimated by applying the instrumental variable estimation. Under certain sufficient conditions, the proposed estimator for the finite dimensional parameters is shown to be root-n consistent and asymptotically normally distributed; The proposed estimator for the unknown function is shown to be consis- tent and asymptotically distributed as well, though at a rate slower than root-n. Consistent estimators for the asymptotic variance-covariance matrices of both estimators are provided. Monte Carlo simulations suggest that the proposed procedure has some practical value.

A closed-form solution for moving source localization using LBI changing rate of phase difference only

Due to the deficiencies in the conventional multiple-receiver localization syste,.ns based on direction of arrival （DOA） such as system complexity of interferometer or array and ampli- tude/phase unbalance between multiple receiving channels and constraint on antenna configuration, a new radiated source localization method using the changing rate of phase difference （CRPD） measured by a long baseline interferometer （LBI） only is studied. To solve the strictly nonlinear problem, a two-stage closed-form solution is proposed. In the first stage, the DOA and its changing rate are estimated from the CRPD of each observer by the pseudolinear least square （PLS） method, and then in the second stage, the source position and velocity are found by another PLS minimiza- tion. The bias of the algorithm caused by the correlation between the measurement matrix and the noise in the second stage is analyzed. To reduce this bias, an instrumental variable （IV） method is derived. A weighted IV estimator is given in order to reduce the estimation variance. The proposed method does not need any initial guess and the computation is small. The Cramer-Rao lower bound （CRLB） and mean square error （MSE） are also analyzed. Simulation results show that the proposed method can be close to the CRLB with moderate Gaussian measurement noise.

Impact of China＇s Outward Foreign Direct Investment on Its Regional Economic Growth

This paper investigates the impact of China＇s outward foreign direct investment （OFDI） on its economic growth. By using a provincial-level panel dataset and applying fixed- effects and instrumental variable regression techniques, the study finds that both OFDI from provincial firms and OFDI from state-owned enterprises have a positive impact on China＇s provincial economic growth. The positive impact of OFDI on provincial economic growth may be the result of reverse knowledge spillovers from OFDI to the home provincial economy through demonstration and imitation, labor movement, and backward and forward industrial linkages, thus increasing the productivity and the efficiency of home firms and promoting the growth of the home economy.

Empirical Likelihood Inference for the Semiparametric Varying-Coefficient Spatial Autoregressive Model

In this paper empirical likelihood(EL)-based inference for a semiparametric varyingcoefficient spatial autoregressive model is investigated.The maximum EL estimators for the parametric component and the nonparametric component are established.Furthermore,asymptotic properties of the proposed estimators and EL ratios are derived,and the corresponding confidence regions/bands are constructed.Their finite sample performances are studied via simulation and an example.

Mendelian randomization and pleiotropy analysis

Background:Mendelian randomization(MR)analysis has become popular in inferring and estimating the causality of an exposure on an outcome due to the success of genome wide association studies.Many statistical approaches have been developed and each of these methods require specific assumptions.Results:In this article,we review the pros and cons of these methods.We use an example of high-density lipoprotein cholesterol on coronary artery disease to illuminate the challenges in Mendelian randomization investigation.Conclusion:The current available MR approaches allow us to study causality among risk factors and outcomes.However,novel approaches are desirable for overcoming multiple source confounding of risk factors and an outcome in MR analysis.

The Impact and Spillover Effects of Chinese Ports on Urban Service Industry under De-maritimization:A Perspective for Port Economic Geography Analysis

Will ports become less important in a post-industrial period dominated by service industries?This paper examines the impact and the spillover effects of ports on city economies.The results show that ports contribute to city economies primarily through producer and consumer services.To be specific,ports can drive the development of port-related producer services,and port spillover effects from other cities have a broader impact on producer services;the port contributes to the development of wholesale and retail trades in the local city but the boost to consumer services comes mainly from spillover effects from other ports.This paper concludes that ports are still shaping economic geography by influencing the service sector,and inter-city coordination mechanisms are suggested because of the spillover effects.

Improved algebraic method for linear continuous-time model identification

Recently a novel algebraic method was proposed for linear continuous-time model identification,which has attracted extensive attention in the literature.This work reveals its connection to classic identification methods,discusses a limitation and presents a useful modification of the method.The discussions are supported by analysis and numerical experiments.

On the use of kernel machines for Mendelian randomization

Background： Properly adjusting for unmeasured confounders is critical for health studies in order to achieve valid testing and estimation of the exposure＇s causal effect on outcomes. The instrumental variable （IV） method has long been used in econometrics to estimate causal effects while accommodating the effect of unmeasured confounders. Mendefian randomization （MR）, which uses genetic variants as the instrumental variables, is an application of the instrumental variable method to biomedical research fields, and has become popular in recent years. One often-used estimator of causal effects for instrumental variables and Mendelian randomization is the two-stage least square estimator （TSLS）. The validity of TSLS relies on the accurate prediction of exposure based on IVs in its first stage. Results： In this note, we propose to model the link between exposure and genetic IVs using the least-squares kernel machine （LSKM）. Some simulation studies are used to evaluate the feasibility of LSKM in TSLS setting. Conclusions： Our results show that LSKM based on genotype score or genotype can be used effectively in TSLS. It may provide higher power when the association between exposure and genetic IVs is nonlinear.

Does the Entrepreneurship of the Parents Affect the Opportunities of their Offspring＇s Entrepreneurship？ Empirical Analysis Based on the CGSS 2010-2013 Data

The whole society is paying close attention to ＂entrepreneurship,＂ which urges researchers to find an explanatory perspective relatively independent and with causality on the intergenerational transfer of entrepreneurship. Based on the data of the Chinese General Social Survey （short for CGSS） during the years 2010-2013, this paper analyzes how parents＇ entrepreneurship affects the probability of their offspring＇s entrepreneurship, and the results show that compared with the offspring of parents who did not start their own business, those whose parents did are more likely to choose to start their own business. In view of historical facts such as the ＂lay-off wave＂ during China＇s transformation into a market economy, we use ＂the annual number of unemployed back to work,＂ a provincial-level indicator, in the 1990s as an instrumental variable to correct possible endogenous problems. We find that parents＇ entrepreneurship has significant positive effects on the probability of their offspring＇s entrepreneurship, which may result from the informal transfer of human capital and wealth from parents to their offspring.