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.

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.

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.

Evaluating genetic insights into ulcerative colitis and anxiety:Limitations and future directions

We reviewed the study by He et al,which investigates the genetic correlation between ulcerative colitis(UC)and anxiety using bidirectional Mendelian rando-mization.This study reveals a genetic link between UC and anxiety,diverging from prior research associating higher anxiety with Crohn’s disease.While the study's use of large-scale genome-wide association studies data is commendable,it faces limitations such as single nucleotide polymorphism selection biases,lack of multiple testing corrections,and a reliance on European populations.Future research should address these limitations,incorporate diverse populations,and explore psychotherapeutic interventions to improve UC management and patient outcomes.

Impact of air pollution on urbanization:evidence at China’s city level

This paper investigates the effect and transmission mechanism of air pollution on urbanization based on data from China’s 107 cities during 2005–2018.In order to identify the impact of air pollution on China’s urbanization,we utilized night light data to represent the level of urbanization and used temperature inversion as an instrumental variable to mitigate endogeneity within the two-stage least squares framework.The results suggest that air pollution significantly slowed China’s urbanization process with economic growth acting as the transmission mechanism.The heterogeneity analyses revealed that air pollution had a greater negative impact on urbanization in northern regions than that in southern regions,and a greater negative impact in resource-oriented cities than that in non-resource-based cities.We also find that air pollution was to the detriment of urbanization in larger cities,which have more than 3 million residents,while it did not have a significant impact on Type II large cities,which have fewer than 3 million residents.

The effects of population aging on industrial structure upgrading:Empirical analysis of provincial and threshold characteristics in China

Global population aging trends are intensifying,presenting multifaceted economic and social challenges for countries worldwide.As the world’s largest developing country,China has entered a phase of extreme demographic aging,posing significant questions about its impact on the ongoing upgrading of industrial structures.How does this demographic shift influence the upgrading of industrial structures,and does technological innovation mitigate or exacerbate this impact?The empirical results indicate that population aging impedes upgrading the industrial structure,while technological innovation positively affects the relationship between the two.Moreover,using technological innovation as a threshold variable,the impact of population aging on industrial structure upgrading evolves in a“gradient”manner from“impediment”to“insignificant”to“promotion”as the technological innovation levels increase.These findings offer practical guidance for tailoring industrial policies to different stages of technological advancement.

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.

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.

Layoff Factors Analysis:Evidence from 2021 China General Social Survey

This paper analyzes factors that explain company layoffs,given the individual layoff data in 2021,China.Using the Probit regression model,we find that gender inequality exists in layoffs,an employee’s work experience becomes less critical in the company’s layoff decisions,and how an employee’s health reasons affect work affects its probability of being laid off.Since we consider a significant endogeneity issue with education,using parents’education as an instrumental variable suggests that political status cannot be a significant advantage for employees to lower the chance of being laid off.Moreover,evidence implies that policymakers encouraging the pursuit of higher educational degrees can foster stability in the labor market.

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.

Identification algorithm for a kind of fractional order system

The state-space representation of linear time-invariant (LTI) fractional order systems is introduced, and a proof of their stability theory is also given. Then an efficient identification algorithm is proposed for those fractional order systems. The basic idea of the algorithm is to compute fractional derivatives and the filter simultaneously, i.e., the filtered fractional derivatives can be obtained by computing them in one step, and then system identification can be fulfilled by the least square method. The instrumental variable method is also used in the identification of fractional order systems. In this way, even if there is colored noise in the systems, the unbiased estimation of the parameters can still be obtained. Finally an example of identifying a viscoelastic system is given to show the effectiveness of the aforementioned method.

Iterative identification of discrete-time output-error model with time delay

The problem of discrete-time model identification of industrial processes with time delay was investigated.An iterative and separable method is proposed to solve this problem,that is,the rational transfer function model parameters and time delay are alternately fixed to estimate each other.The instrumental variable technique is applied to guarantee consistent estimation against measurement noise.A noteworthy merit of the proposed method is that it can handle fractional time delay estimation,compared to existing methods commonly assuming that the time delay is an integer multiple of the sampling interval.The identifiability analysis for time delay is addressed and correspondingly,some guidelines are provided for practical implementation of the proposed method.Numerical and experimental examples are presented to illustrate the effectiveness of the proposed method.

Closed-loop identification of systems using hybrid Box–Jenkins structure and its application to PID tuning

The paper describes a closed-loop system identification procedure for hybrid continuous-time Box–Jenkins models and demonstrates how it can be used for IMC based PID controller tuning. An instrumental variable algorithm is used to identify hybrid continuous-time transfer function models of the Box–Jenkins form from discretetime prefiltered data, where the process model is a continuous-time transfer function, while the noise is represented as a discrete-time ARMA process. A novel penalized maximum-likelihood approach is used for estimating the discrete-time ARMA process and a circulatory noise elimination identification method is employed to estimate process model. The input–output data of a process are affected by additive circulatory noise in a closedloop. The noise-free input–output data of the process are obtained using the proposed method by removing these circulatory noise components. The process model can be achieved by using instrumental variable estimation method with prefiltered noise-free input–output data. The performance of the proposed hybrid parameter estimation scheme is evaluated by the Monte Carlo simulation analysis. Simulation results illustrate the efficacy of the proposed procedure. The methodology has been successfully applied in tuning of IMC based flow controller and a practical application demonstrates the applicability of the algorithm.

Iterative identification of output error model for industrial processes with time delay subject to colored noise

To deal with colored noise and unexpected load disturbance in identification of industrial processes with time delay, a bias-eliminated iterative least-squares(ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover, a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation, an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.

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.

Institutional Distance and CrossNational Income Gaps

ihis paper examines the root causes of current cross-national institutional difference from the perspective of national hetereogeneity and provides detailed explanations on the justification and effectiveness of using cross-national genetic distance as the instrumental variable （IV） of institutional difference. We combined 10,585 samples by pairing 146 countries and regions, created a cross-national institutional distance variable composed of 14 indicators from the World Bank and the Heritage Foundation in three aspects including differences of political system, economic system and institutional implementation attributes, and conducted a cross-section IV estimation for the long-term effect of institutional differences on cross-national income gaps using data between 1996 and 2010. Empirical results indicate that institutional difference has a long-term significant positive effect on cross-national income gaps and such an effect has a tendency to increase during sample period. With factors like human capital, geographical factor, language and religion under control, we still arrived at similar conclusions. The empirical results are demonstrated to be robust using different genetic distance measurement indicators and estimation methods.

Intergenerational Transmission of Income Gap for Chinese Urban and Rural Households

An accurate understanding of the intergenerational transmission of income gap is the foundation for theoretical research and policy formulation to address this issue. This paper has employed the method of two sample instrumental variables to effectively integrate CHIP data and CFPS data and correct the temporal income bias, life-cycle bias and coresidence bias, which are common problems in existing studies, and investigated the tendencies of intergenerational transmission of income gap for China's urban and rural households between 2002 and 2012. Results of empirical study indicate that the intergenerational transmission of income gap for China's urban and rural households has been on the decline yet the level of intergenerational transmission is greater for urban residents than for rural residents. This level of intergenerational transmission of income gap in China is at a medium international level lower than that of countries like the United States, Brazil and Japan and higher than that of Sweden and Chinese Taiwan. Further analysis of the intergenerational mobility of various income groups suggests the following: the intergenerational solidification of the bottom and top income groups of urban residents has significantly improved, which is the source for the reduction of intergenerational transmission of income gap. Rural residents of bottom income group are vulnerable to falling into the trap of intergenerational transmission of low income. In order to mitigate the intergenerational transmission of income gap, efforts must be made to improve educational allowance policy and increase the opportunities for children from poor and underprivileged families to receive education and to eliminate the divide of labor markets to create equal job opportunities for each and every worker.

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.

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.