The impact of Internet access on household dietary quality:Evidence from rural China

Over the past few decades,the Internet has rapidly diffused across China.The spread of the Internet has had a profound economic and social impact on Chinese rural areas.Existing research shows that Internet access significantly impacts agricultural production and improves smallholder farmers’income.Beyond these,the Internet can affect other dimensions of social welfare.However,research about the impact of Internet access on dietary quality in rural China remains scarce.This study utilizes multi-period panel data from Fixed Observation Point in rural China from 2009 to 2015 to estimate the impact of Internet access on dietary quality and food consumption of rural households and conducts a causal analysis.Regression models with time and household fixed effects allow robust estimation while reducing potential issues of unobserved heterogeneity.The estimates show that Internet access has significantly increased rural household dietary quality(measured by the Chinese Diet Balance Index).Further research finds that Internet access has increased the consumption of animal products,such as aquatic and dairy products.We also examine the underlying mechanisms.Internet access improves dietary quality and food consumption mainly through increasing household income and food expenditure.These results encourage the promotion of Internet access as a valuable tool for nutritional improvements,especially in rural areas.

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.

INTERACTION MODELS FOR EFFECTIVE THERMAL AND ELECTRIC CONDUCTIVITIES OF CARBON NANOTUBE COMPOSITES

The present article provides supplementary information of previous works of analytic models for predicting conductivity enhancements of carbon nanotube composites. The models, though fairly simple, are able to take account of the effects of conductivity anisotropy, nonstraightness, and aspect ratio of the CNT additives on the conductivity enhancement of the composite and to give predictions agreeing well with existing experimental data. The omitted detailed derivation of this model is demonstrated in the present article with a more systematical analysis, which may help with further development in this direction. Furthermore, the effects of various orientation distributions of CNTs are reported here for the first time. The information may be useful in design or fabrication technology of CNT composites for better or specified conductivities.

INFLUENCE ANALYSIS IN NONLINEAR MODELS WITH RANDOM EFFECTS

In this paper,a unified diagnostic method for the nonlinear models with random effects based upon the joint likelihood given by Robinson in 1991 is presented.It is shown that the case deletion model is equivalent to the mean shift outlier model.From this point of view,several diagnostic measures,such as Cook distance,score statistics are derived.The local influence measure of Cook is also presented. A numerical example illustrates that the method is available.

Effects of Three Typical Resistivity Models on Pulsed Inductive Plasma Acceleration Modeling

The effects of three different typical resistivity models（Spitzer, Z＆L and M＆G） on the performance of pulsed inductive acceleration plasma are studied. Numerical results show that their influences decrease with the increase of the plasma temperature. The significant discriminations among them appear at the plasma temperature lower than 2.5 eV, and the maximum gap of the pulsed inductive plasma accelerated efficiency is approximately 2.5%.Moreover, the pulsed inductive plasma accelerated efficiency is absolutely related to the dynamic impedance parameters, such as voltage, inductance, capacitance and flow rate. However, the distribution of the efficiency as a function of plasma temperature with three resistivity models has nothing to do with the dynamic impedance parameter.

Bias and Mean Square Error of Reliability Estimators under the One and Two Random Effects Models: The Effect of Non-Normality

The coefficient of reliability is often estimated from a sample that includes few subjects. It is therefore expected that the precision of this estimate would be low. Measures of precision such as bias and variance depend heavily on the assumption of normality, which may not be tenable in practice. Expressions for the bias and variance of the reliability coefficient in the one and two way random effects models using the multivariate Taylor’s expansion have been obtained under the assumption of normality of the score (Atenafu et al. [1]). In the present paper we derive analytic expressions for the bias and variance, hence the mean square error when the measured responses are not normal under the one-way data layout. Similar expressions are derived in the case of the two-way data layout. We assess the effect of departure from normality on the sample size requirements and on the power of Wald’s test on specified hypotheses. We analyze two data sets, and draw comparisons with results obtained via the Bootstrap methods. It was found that the estimated bias and variance based on the bootstrap method are quite close to those obtained by the first order approximation using the Taylor’s expansion. This is an indication that for the given data sets the approximations are quite adequate.

An Empirical Study on the Effectiveness of Technology Market Promoting Technological Innovation Capability—Based on panel data in the Yangtze River Delta

Based on panel data such as 2009-2018 R&D expenditures,full-time equivalent of R&D personnel,Number of valid invention patents,and technology market turnover in China's Shanghai,Jiangsu,Zhejiang,and Anhui provinces(cities),using Griliches-Jaffe knowledge to produce Function,construct Time fixed effects model,conduct empirical research on the main factors affecting the technological innovation capability of the Yangtze River Delta,focusing on the relationship between the technological market and technological innovation capability.The results show that human capital and R&D expenditures have a significant and positive impact on the technological innovation capacity of the Yangtze River Delta.Although the technology market has a positive effect on the scientific and technological innovation capacity of the Yangtze River Delta,the effect is not significant.Propose countermeasures and suggestions to strengthen the influence of the technology market on technological innovation.

TESTING FOR VARYING DISPERSION IN DISCRETE EXPONENTIAL FAMILY NONLINEAR MODELS

It is necessary to test for varying dispersion in generalized nonlinear models.Wei,et al(1998) developed a likelihood ratio test,a score test and their adjustments to test for varying dispersion in continuous exponential family nonlinear models.This type of problem in the framework of general discrete exponential family nonlinear models is discussed.Two types of varying dispersion,which are random coefficients model and random effects model,are proposed,and corresponding score test statistics are constructed and expressed in simple,easy to use,matrix formulas.

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Can a multistage approach improve individual tree mortality predictions across the complex mixed-species and managed forests of eastern North America?

Tree mortality plays a fundamental role in the dynamics of forest ecosystems,yet it is one of the most difficult phenomena to accurately predict.Various modeling strategies have been developed to improve individual tree mortality predictions.One less explored strategy is the use of a multistage modeling approach.Potential improvements from this approach have remained largely unknown.In this study,we developed a novel multistage approach and compared its performance in individual tree mortality predictions with a more conventional approach using an identical individual tree mortality model formulation.Extensive permanent plot data(n=9442)covering the Acadian Region of North America and over multiple decades(1965–2014)were used in this study.Our results indicated that the model behavior with the multistage approach better depicted the observed mortality and showed a notable improvement over the conventional approach.The difference between the observed and predicted numbers of dead trees using the multistage approach was much smaller when compared with the conventional approach.In addition,tree survival probabilities predicted by the multistage approach generally were not significantly different from the observations,whereas the conventional approach consistently underestimated mortality across species and overestimated tree survival probabilities over the large range of DBH in the data.The new multistage approach also predictions of zero mortality in individual plots,a result not possible in conventional models.Finally,the new approach was more tolerant of modeling errors because it based estimates on ranked tree mortality rather than error-prone predicted values.Overall,this new multistage approach deserves to be considered and tested in future studies.

基于卫星遥感AOD的华北地区2003—2014年PM2.5浓度时空分布特征

华北及周边地区PM2.5造成的污染,近十年来引起了社会的广泛关注,也是科学研究的重要领域。利用2003—2014年的卫星遥感MODIS AOD数据和2014—2015年的地面观测PM2.5浓度数据,采用聚类分析、混合效应模型、EOF分解等统计分析方法,反演了2003—2014年华北及周边地区PM2.5浓度,分析其时空分布特征。主要结论如下:(1)卫星遥感MODIS AOD与地面观测PM2.5值有较高的相关系数,可利用MODIS卫星遥感AOD对地面观测的PM2.5浓度进行反演;(2)华北地区PM2.5浓度呈现出明显的空间分布特征:太行山脉是污染强弱明确的分界线,山脉东南部的污染显著高于西部,且在地势变化的地方出现明显的突变;河北南部、河南北部和山东西北部分区域是污染最严重的地区;(3)2004年、2009年以及2013年后都是污染浓度比较低的年份。

EMPIRICAL BAYES TEST PROBLEMS OF VARIANCE COMPONENTS IN RANDOM EFFECTS MODEL

Bayes decision rule of variance components for one-way random effects model is derived and empirical Bayes (EB) decision rules are constructed by kernel estimation method. Under suitable conditions, it is shown that the proposed EB decision rules are asymptotically optimal with convergence rates near O(n-1/2). Finally, an example concerning the main result is given.

Shear strength criteria for rock,rock joints,rockfill and rock masses:Problems and some solutions

Although many intact rock types can be very strong,a critical confining pressure can eventually be reached in triaxial testing,such that the Mohr shear strength envelope becomes horizontal.This critical state has recently been better defined,and correct curvature or correct deviation from linear Mohr-Coulomb（MC） has finally been found.Standard shear testing procedures for rock joints,using multiple testing of the same sample,in case of insufficient samples,can be shown to exaggerate apparent cohesion.Even rough joints do not have any cohesion,but instead have very high friction angles at low stress,due to strong dilation.Rock masses,implying problems of large-scale interaction with engineering structures,may have both cohesive and frictional strength components.However,it is not correct to add these,following linear M-C or nonlinear Hoek-Brown（H-B） standard routines.Cohesion is broken at small strain,while friction is mobilized at larger strain and remains to the end of the shear deformation.The criterion ＇c then σn tan φ＇ should replace ＇c plus σn tan φ＇ for improved fit to reality.Transformation of principal stresses to a shear plane seems to ignore mobilized dilation,and caused great experimental difficulties until understood.There seems to be plenty of room for continued research,so that errors of judgement of the last 50 years can be corrected.

Toward managing mixed-species stands： from parametrization to prescription

A better understanding and a more quantitative design of mixed-species stands will contribute to more integrative and goal-oriented research in mixed-species forests. Much recent work has indicated that the structure and growth of mixed species forests may fundamentally differ from monocultures. Here we suggest how to progress from the present accumulation of phenomenological findings to a design of mixed-species stands and advanced silvicultural prescriptions by means of modelling. First, the knowledge of mixing effects on the structure and growth at the stand, species, and individual tree level is reviewed, with a focus on those findings that are most essential for suitable modelling and silvicultural designs and the regulation of mixed stands as opposed to monocultures. Then, the key role of growth models, stand simulators, and scenario assessments for designing mixed species stands is discussed The next section illustrates that existing forest stand growth models require some fundamental modifications to become suitable for both monocultures and mixed-species stands. We then explore how silvicultural prescriptions derived from scenario runs would need to be both quantified and simplified for transfer to forest management and demonstrated in training plots. Finally, we address the main remaining knowledge gaps that could be remedied through empirical research.

An Evaluation of the Effects of Cloud Parameterization in the R42L9 GCM

Cloud is one of the uncertainty factors influencing the performance of a general circulation model (GCM). Recently, the State Key Laboratory of Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP) has developed a new version of a GCM (R42L9). In this work, roles of cloud parameterization in the R42L9 are evaluated through a comparison between two 20-year simulations using different cloud schemes. One scheme is that the cloud in the model is diagnosed from relative humidity and vertical velocity, and the other one is that diagnostic cloud is replaced by retrieved cloud amount from the International Satellite Cloud Climatology Project (ISCCP), combined with the amounts of high-, middle-, and low-cloud and heights of the cloud base and top from the NCEP. The boreal winter and summer seasonal means, as well as the annual mean, of the simulated top-of-atmosphere shortwave radiative flux, surface energy fluxes, and precipitation are analyzed in comparison with the observational estimates and NCEP reanalysis data. The results show that the scheme of diagnostic cloud parameterization greatly contributes to model biases of radiative budget and precipitation. When our derived cloud fractions are used to replace the diagnostic cloud amount, the top-of-atmosphere and surface radiation fields are better estimated as well as the spatial pattern of precipitation. The simulations of the regional precipitation, especially over the equatorial Indian Ocean in winter and the Asia-western Pacific region in summer, are obviously improved.

Modelling Study to Compare the Flow and Heat Transfer Characteristics of Low-Power Hydrogen,Nitrogen and Argon Arc-Heated Thrusters

A modelling study is performed to compare the plasma flow and heat transfer characteristics of low-power arc-heated thrusters （arcjets） for three different propellants： hydrogen, nitrogen and argon. The all-speed SIMPLE algorithm is employed to solve the governing equations, which take into account the effects of compressibility, Lorentz force and Joule heating, as well as the temperature- and pressure-dependence of the gas properties. The temperature, velocity and Mach number distributions calculated within the thruster nozzle obtained with different propellant gases are compared for the same thruster structure, dimensions, inlet-gas stagnant pressure and arc currents. The temperature distributions in the solid region of the anode-nozzle wall are also given. It is found that the flow and energy conversion processes in the thruster nozzle show many similar features for all three propellants. For example, the propellant is heated mainly in the near-cathode and constrictor region, with the highest plasma temperature appearing near the cathode tip; the flow transition from the subsonic to supersonic regime occurs within the constrictor region; the highest axial velocity appears inside the nozzle; and most of the input propellant flows towards the thruster exit through the cooler gas region near the anode-nozzle wall. However, since the properties of hydrogen, nitrogen and argon, especially their molecular weights, specific enthMpies and thermal conductivities, are different, there are appreciable differences in arcjet performance. For example, compared to the other two propellants, the hydrogen arcjet thruster shows a higher plasma temperature in the arc region, and higher axial velocity but lower temperature at the thruster exit. Correspondingly, the hydrogen arcjet thruster has the highest specific impulse and arc voltage for the same inlet stagnant pressure and arc current. The predictions of the modelling are compared favourably with available experimental results.

THEORETICAL MODEL OF EFFECTIVE STRESS COEFFICIENT FOR ROCK/SOIL-LIKE POROUS MATERIALS

Physical mechanisms and influencing factors on the effective stress coefficient for rock/soil-like porous materials are investigated, based on which equivalent connectivity index is proposed. The equivalent connectivity index, relying on the meso-scale structure of porous material and the property of liquid, denotes the connectivity of pores in Representative Element Area （REA）. If the conductivity of the porous material is anisotropic, the equivalent connectivity index is a second order tensor. Based on the basic theories of continuous mechanics and tensor analysis, relationship between area porosity and volumetric porosity of porous materials is deduced. Then a generalized expression, describing the relation between effective stress coefficient tensor and equivalent connectivity tensor of pores, is proposed, and the expression can be applied to isotropic media and also to anisotropic materials. Furthermore, evolution of porosity and equivalent connectivity index of the pore are studied in the strain space, and the method to determine the corresponding functions in expressions above is proposed using genetic algorithm and genetic programming. Two applications show that the results obtained by the method in this paper perfectly agree with the test data. This paper provides an important theoretical support to the coupled hydro-mechanical research.

Acupuncture and vitamin B_(12) injection for Bell's palsy:no high-quality evidence exists

OBJECTIVE： To assess the efficacy of acupuncture combined with vitamin B12 acupoint injection versus acupuncture alone to reduce incomplete recovery in patients with Bell＇s palsy. DATA RETRIEVAL： A computer-based online retrieval of Medline, Web of Science, CNKI, CBM databases until April 2014 was performed for relevant trials, using the key words ＂Bell＇s palsy or idiopathic facial palsy or facial palsy＂ and＂acupuncture or vitamin B12 or methylcobalamin＂. STUDY SELECTION： All randomized controlled trials that compared acupuncture with acupuncture combined with vitamin B12 in patients with Bell＇s palsy were included in the me- ta-analysis. The initial treatment lasted for at least 4 weeks. The outcomes of incomplete facial recovery were monitored. The scoring index varied and the definition of healing was consistent. The combined effect size was calculated by using relative risk （RR） with 95% confidence interval （C/） using the fixed effect model of Review Manager. MAIN OUTCOME MEASURES： Incomplete recovery rates were chosen as the primary outcome. RESULTS： Five studies involving 344 patients were included in the final analysis. Results showed that the incomplete recovery rate of Bell＇s palsy patients was 44.50% in the acupuncture combined with vitamin B12 group but 62.57% in the acupuncture alone group. The major acupoints were Taiyang （EX-HN5）, Jiache （ST6）, Dicang （ST4） and Sibai （ST2）. The combined effect size showed that acupuncture combined with vitamin B12 was better than acupuncture alone for the treatment of Belrs palsy （RR = 0.71, 95%CI： 0.58-0.87; P = 0.001）, this result held true when 8 patients lost to follow up in one study were included into the analyses （RR = 0.70, 95%CI： 0.58-0.86; P = 0.0005）. In the subgroup analyses, the therapeutic effect in patients of the electroacupuncture subgroup was better than in the non-electroacupuncture subgroup （P = 0.024）. There was no significant dif- ference in the incomplete recovery rate by subgroup analysis on drug types and treatment period. Most of the included studies were moderate or low quality, and bias existed. CONCLUSION： In patients with Bell＇s palsy, acupuncture combined with vitamin 812 can reduce the risk of incomplete recovery compared with acupuncture alone in our meta-analysis. Because of study bias and methodological limitations, this conclusion is uncertain and the clinical appli- cation of acupuncture combined with vitamin B12 requires further exploration.

Safety Analysis of Riding at Intersection Entrance Using Video Recognition Technology

To study riding safety at intersection entrance,video recognition technology is used to build vehicle-bicycle conflict models based on the Bayesian method.It is analyzed the relationship among the width of nonmotorized lanes at the entrance lane of the intersection,the vehicle-bicycle soft isolation form of the entrance lane of intersection,the traffic volume of right-turning motor vehicles and straight-going non-motor vehicles,the speed of right-turning motor vehicles,and straight-going non-motor vehicles,and the conflict between right-turning motor vehicles and straight-going nonmotor vehicles.Due to the traditional statistical methods,to overcome the discreteness of vehicle-bicycle conflict data and the differences of influencing factors,the Bayesian random effect Poisson-log-normal model and random effect negative binomial regression model are established.The results show that the random effect Poisson-log-normal model is better than the negative binomial distribution of random effects;The width of non-motorized lanes,the form of vehicle-bicycle soft isolation,the traffic volume of right-turning motor vehicles,and the coefficients of straight traffic volume obey a normal distribution.Among them,the type of vehicle-bicycle soft isolation facilities and the vehicle-bicycle traffic volumes are significantly positively correlated with the number of vehicle-bicycle conflicts.The width of non-motorized lanes is significantly negatively correlated with the number of vehicle-bicycle conflicts.Peak periods and flat periods,the average speed of right-turning motor vehicles,and the average speed of straight-going non-motor vehicles have no significant influence on the number of vehicle-bicycle conflicts.

Digital finance and renewable energy consumption:evidence from China

While digital finance and renewable energy consumption(REC)are two timely issues,it remains unclear whether the former affects the latter,especially in developing economies.This paper examines the impact of digital finance on China’s REC between 2011 and 2018 and explores the underlying mechanisms.Results show that digital finance,along with its coverage breadth and usage depth,significantly improved REC in China and that digital finance in the area of credit has had the most significant impact.Additionally,the results show that loan scale and income level are the main mediation variables,through which digital finance affects REC.The findings also suggest that economic growth and technological progress have increased REC in China,while carbon dioxide emissions have had no meaningful effect on this consumption.The results further indicate that policymakers must pay close attention to the role of digital finance when formulating policies on REC.To promote REC and environmental sustainability,developing economies like China should strengthen the breadth and depth of digital finance development,focus on the influence channels of digital finance,and promote economic growth and technological progress.