Evaluation of the sustainable development level of countries along the Belt and Road and its impact factors:Empirical analysis based on the Super-efficiency slacks-based measure and Tobit measure models

Sustainable development is an important component of the Belt and Road Initiative(BRI)and is of great significance for evaluating the levels of sustainable development of countries along this route(henceforth,BRI countries).Therefore,this study aims to identify the factors that influence the levels of sustainable development of BRI countries in a reasonable and objective manner.Eventually,this study employs the super efficiency slacks-based measure(Super-SBM)model,which considers unexpected outputs to measure the level of sustainable development of BRI countries.The dynamic change and composition of the sustainable development level of these countries are calculated using the global Malmquist-Luenberger index.Furthermore,the Tobit model is used to identify the factors influencing the level of sustainable development of BRI countries in general and in various categories.The empirical results suggest the following points.(a)The overall level of sustainable development of BRI countries is low,whereas those of high-income and middle-and high-income countries are relatively high.(b)The overall sustainable development levels of BRI countries declined to a certain extent in 2008 owing to the effect of the financial crisis,.However,the sustainable development level of other countries,barring low-income countries,has gradually increased since 2011.(c)Since 2008,technological progress has replaced technical efficiency as the main driving force behind the improvement of the sustainable development level of BRI countries.(d)A U-shaped relationship is observed between the economic and sustainable development levels of these countries.(e)The level of science and technology and the proportion of renewable energy consumption can promote the sustainable development of these countries.Moreover,a negative correlation exists between the level of opening to the outside world and that of sustainable development of countries that mainly export resource-based products and are dominated by labor-intensive export industries.Barring low-income countries,the energy structure plays an effective role in improving the level of sustainable development.Finally,the study presents suggestions for China in the process of coping with the sustainable development of relevant countries during its promotion of the BRI.

Multiple Measurement Models of Articulated Arm Coordinate Measuring Machines

The existing articulated arm coordinate measuring machines（AACMM） with one measurement model are easy to cause low measurement accuracy because the whole sampling space is much bigger than the result in the unstable calibration parameters. To compensate for the deficiency of one measurement model, the multiple measurement models are built by the Denavit-Hartenberg＇s notation, the homemade standard rod components are used as a calibration tool and the Levenberg-Marquardt calibration algorithm is applied to solve the structural parameters in the measurement models. During the tests of multiple measurement models, the sample areas are selected in two situations. It is found that the measurement errors＇ sigma value（0.083 4 ram） dealt with one measurement model is nearly two times larger than that of the multiple measurement models（0.043 1 ram） in the same sample area. While in the different sample area, the measurement errors＇ sigma value（0.054 0 ram） dealt with the multiple measurement models is about 40% of one measurement model（0.137 3 mm）. The preliminary results suggest that the measurement accuracy of AACMM dealt with multiple measurement models is superior to the accuracy of the existing machine with one measurement model. This paper proposes the multiple measurement models to improve the measurement accuracy of AACMM without increasing any hardware cost.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

MEASUREMENT METHOD AND PHYSICAL MODEL OF VSC CONDUCTIVITY AND ITS APPLICATIONS IN CONDUCTING POLYMERS

Method of VSC (Voltage Shorted Compaction)can be used to determine the intrinsic temperature dependence ofconductivity ofpolycrystalline compaction. The experimental conditions and technical key for preparation of VSC device and its physical model as well as its applications in conducting polymers are discussed in detail.

ZTE Communications Special Issue on Channel Measurement and Modeling for Heterogeneous 5G

While cellular networks have continuously evolved in recent years, the industry has clearly seen unprecedented challenges to meet the exponentially growing expectations in the near future.

ZTE Communications Special Issue on Channel Measurement and Modeling for Heterogeneous 5G

While cellular networks have continuously evolved in re- cent years, the industry has clearly seen unprecedented chal- lenges to meet the exponentially growing expectations in the near future. The 5G system is facing grand challenges such as the ever-increasing traffic volumes and remarkably diver- sified services connecting humans and machines alike. As a result, the future network has to deliver massively increased capacity, greater flexibility, incorporated computing capabili- ty, support of significantly extended battery lifetime, and ac- commodation of varying payloads with fast setup and low latency, etc. In particular, as 5G requires more spectrum resource, higher frequency bands are desirable. Nowadays, millimeter wave has been widely accepted as one of the main communication bands for 5G.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.

Singularity of Some Software Reliability Models and Parameter Estimation Method

According to the principle, “The failure data is the basis of software reliability analysis”, we built a software reliability expert system (SRES) by adopting the artificial intelligence technology. By reasoning out the conclusion from the fitting results of failure data of a software project, the SRES can recommend users “the most suitable model” as a software reliability measurement model. We believe that the SRES can overcome the inconsistency in applications of software reliability models well. We report investigation results of singularity and parameter estimation methods of experimental models in SRES.

Experimental and modelling study of the solubility of CO_2 in various CaCl_2 solutions at different temperatures and pressures

Study of the thermodynamic behaviour of CaCl2-H2O-CO2 systems is important in different scientific areas in the chemical and petroleum engineering fields. For example, a system including salt- H20-CO2 is a common system in CO2 geological storage. During carbonate matrix acidizing, this mixture also appears as the spent acid. Hence, study of the behaviour of this system and the solubility of CO2 in CaCl2 brine in different thermodynamic conditions is critical. In this study, CO2 solubility in 0, 1.90 and 4.80 mol/L CaCl2 solutions at 328.15 to 375.15 K and 68.9 to 206.8 bar were measured. These values are normal for oil reservoirs. A popular thermodynamic model is available in the literature for estimating the CO2 solubility in pure water and NaC1 solutions. In this paper, the available model was modified by experimental work to be applicable for CaCl2 as well. Based on the measured data, the component interaction parameters in the base model were adjusted for a CaCl2-H2O-CO2 system. The developed model could predict CO2 solubility in different conditions with remarkable accuracy, particularly for high concentration solutions and at high pressures. This improvement is up to 65% better than in the base model. This model can be used in Darcy scale models for predicting wormhole propagation during carbonate matrix acidizing.

Singularity of Software Reliability Models LVLM and LVQM

According to the principle, “The failure data is the basis of software reliabilityanalysis”, we built a software reliability expert system (SRES) by adopting the artificialtechnology. By reasoning out the conclusion from the fitting results of failure data of asoftware project, the SRES can recommend users “the most suitable model” as a softwarereliability measurement model. We believe that the SRES can overcome the inconsistency inapplications of software reliability models well. We report investigation results of singularity and parameter estimation methods of models, LVLM and LVQM.

Sub-external cavity effect and elimination method in laser self-mixing interference wave plate measurement system

Laser self-mixing interference（SMI） wave plate measurement method is a burgeoning technique for its simplicity and efficiency. But for the non-coated sample, the reflected light from the surface can seriously affect the measurement results.To analyze the reason theoretically, a self-consistent model for laser operation with a sub-external and an external cavity is established, and the sub-external cavity formed by the sample and a cavity mirror is proved to be the main error source.A synchronous tuning method is proposed to eliminate the sub-external cavity effect. Experiments are carried out on the synchronously tuning double external cavities self-mixing interference system, and the error of the system is in the range of -0.435°~0.387° compared with the ellipsometer. The research plays an important role in improving the performance and enlarging the application range of the laser self-mixing interference system.

A FGR Software Model for Measuring the Effect of Technological Progress

The work of quantitative studying the effect of technological progress on economic growth, being of great complexity and far-reaching significance, has become a quite popular research topic in the world. In recent years there are a large number of scientists who are engaged in this research both at home and abroad.

A SYSTEMATIC ARCHITECTURE AND MODELING OF VIRTUAL MANUFACTURING AND MEASURING CELL

The concept of virtual manufacturing and measuring cell (VMMC) is proposed, the systematic architecture of the VMMC is established and two key problems: the error fusion in machining and the reconstructable modeling of workpiece during virtual manufacturing and measuring, are discussed. An actual VMMC is presented as an example and its modularized frame is introduced.

Optimizing Service Stipulation Uncertainty with Deep Reinforcement Learning for Internet Vehicle Systems

Fog computing brings computational services near the network edge to meet the latency constraints of cyber-physical System(CPS)applications.Edge devices enable limited computational capacity and energy availability that hamper end user performance.We designed a novel performance measurement index to gauge a device’s resource capacity.This examination addresses the offloading mechanism issues,where the end user(EU)offloads a part of its workload to a nearby edge server(ES).Sometimes,the ES further offloads the workload to another ES or cloud server to achieve reliable performance because of limited resources(such as storage and computation).The manuscript aims to reduce the service offloading rate by selecting a potential device or server to accomplish a low average latency and service completion time to meet the deadline constraints of sub-divided services.In this regard,an adaptive online status predictive model design is significant for prognosticating the asset requirement of arrived services to make float decisions.Consequently,the development of a reinforcement learning-based flexible x-scheduling(RFXS)approach resolves the service offloading issues,where x=service/resource for producing the low latency and high performance of the network.Our approach to the theoretical bound and computational complexity is derived by formulating the system efficiency.A quadratic restraint mechanism is employed to formulate the service optimization issue according to a set ofmeasurements,as well as the behavioural association rate and adulation factor.Our system managed an average 0.89%of the service offloading rate,with 39 ms of delay over complex scenarios(using three servers with a 50%service arrival rate).The simulation outcomes confirm that the proposed scheme attained a low offloading uncertainty,and is suitable for simulating heterogeneous CPS frameworks.

Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?

There are eight provinces and autonomous regions(Gansu Province,Ningxia Hui Autonomous Region,Xinjiang Uygur Autonomous Region,Inner Mongolia Autonomous Region,Tibet Autonomous Region,Qinghai Province,Shanxi Province,and Shaanxi Province)in Northwest China,most areas of which are located in arid and semi-arid regions(northwest of the 400 mm precipitation line),accounting for 58.74%of the country's land area and sustaining approximately 7.84×10^6 people.Because of drought conditions and fragile ecology,these regions cannot develop agriculture at the expense of the environment.Given the challenges of global warming,the green total factor productivity(GTFP),taking CO2 emissions as an undesirable output,is an effective index for measuring the sustainability of agricultural development.Agricultural GTFP can be influenced by both internal production factors(labor force,machinery,land,agricultural plastic film,diesel,pesticide,and fertilizer)and external climate factors(temperature,precipitation,and sunshine duration).In this study,we used the Super-slacks-based measure(Super-SBM)model to measure agricultural GTFP during the period 2000-2016 at the regional level.Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period(2000-2016),and the fluctuation was caused by the production factors(input and output factors).To improve agricultural GTFP,Shaanxi,Shanxi,and Gansu should reduce agricultural labor force input;Shaanxi,Inner Mongolia,Gansu,and Shanxi should decrease machinery input;Shaanxi,Inner Mongolia,Xinjiang,and Shanxi should reduce fertilizer input;Shaanxi,Xinjiang,Gansu,and Ningxia should reduce diesel input;Xinjiang and Gansu should decrease plastic film input;and Gansu,Shanxi,and Inner Mongolia should cut pesticide input.Desirable output agricultural earnings should be increased in Qinghai and Tibet,and undesirable output(CO2 emissions)should be reduced in Inner Mongolia,Xinjiang,Gansu,and Shaanxi.Agricultural GTFP is influenced not only by internal production factors but also by external climate factors.To determine the influence of climate factors on GTFP in these provinces and autonomous regions,we used a Geographical Detector(Geodetector)model to analyze the influence of climate factors(temperature,precipitation,and sunshine duration)and identify the relationships between different climate factors and GTFP.We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions.For Xinjiang,Inner Mongolia,and Tibet,a suitable average annual temperature would be in the range of 7℃-9℃;for Gansu,Shanxi,and Ningxia,it would be 11℃-13℃;and for Shaanxi,it would be 15℃-17℃.Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture.Hence,in the agricultural production process,reducing the redundancy of input factors is the best way to reduce CO2 emissions and to maintain temperatures,thereby improving the agricultural GTFP.The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions,identifying an effective way forward for the arid and semi-arid regions of Northwest China.

A polynomial hybrid reflection model and measurement of its parameters based on images of sample

Reflectance model is a basic concept in computer vision. Some existing models combining the classical diffuse reflectance model and those for surfaces containing specular components can approximately describe real reflectance. But the ratio of diffuse and specular reflection decided manually has no clear meaning. We propose a new polynomial hybrid reflectance model. The reflectance map equation with a known shape （for example cylinder） as a sample is used to estimate parameters of the proposed reflectance model by least square regression algorithm. Then the reflectance parameters for surfaces of the same class of materials can be determined. Experiments are performed for a metal surface. The synthesis images produced by the proposed method and existing ones are compared with the real acquired image, and the results show that the proposed reflectance model is suitable for describing real reflectance.

THE FOURTH INTERNATIONAL SYMPOSIUM ON REFINED FLOW MODELLING AND TURBULENCE MEASUREMENTS

The Fourth International Symposium on Refined Flow Modelling and TurbulenceMeasurements organized by International Association for Hydraulic Research(IAHR),and co-sponsored by a group of Chinese Institutes headed by Wuhan University ofHydraulic & Eiectric Engineering and Chinese Institute of Water Conservancy andHydroelectric Power Research is to be held on September 20-23,1990 at Wuhan City,People’s Republic of China.The Symposium is intended for presentation discussion and exchange of viewsbetween international colleagues on a wide scope of frontier problems regardingrefined flow modelling and turbulence measurements.The main topics are:

Comparison of three measurement models of soil nitrate-nitrogen based on ion-selective electrodes

Ion-selective electrode(ISE)is a quick and low-cost method of soil nitrate nitrogen(N)detection.The measurement models of soil nitrate-N based on ISEs includes the linear regression model,multiple linear regression model and BP neural network model,and so on.Three models were analyzed in theory,measurement experiments of validation samples and soil nitrate-N concentrations were carried out in this study,and the measurement accuracies of the three models were compared.The results showed that,in the measurement experiments of validation samples and soil nitrate-N concentrations,BP neural network model had the highest accuracy(the average relative errors between results of the BP neural network model and the reference values were 5.07%and 8.81%,respectively)among the three models,multiple linear regression model had the second highest accuracy(the average relative errors between results of the multiple linear regression model and the reference values were 7.70%and 10.51%,respectively),linear regression model couldn’t exclude the interference of chloride ions so that it had the lowest accuracy(the average relative errors between results of the linear regression model and the reference values were 11.16%and 12.28%,respectively)among the three models.The BP neural network model can effectively restrain the interference of chloride ions,and it has a high accuracy for the measurement of soil nitrate-N concentration,so that the BP neural network model can be used to measure soil nitrate-N concentration accurately.

Spatio-temporal Evolution of the Agricultural Eco-efficiency Network and Its Multidimensional Proximity Analysis in China

As a traditional agricultural country,China has always prioritized agricultural development,and has increasingly focused on green and sustainable agricultural development.Based on the inter-provincial panel data for China from 1997 to 2019,this study divided these data into five periods according to the Five-Year Plan(FYP)of China,measured the agricultural eco-efficiency(AEE)values using the Super-SBM model,and then determined the spatial association network of the inter-provincial AEE of China using the improved gravity model.Finally,social network analysis(SNA)was used to further analyze the evolution process of AEE,and we de-veloped a framework of how multidimensional proximity,which includes geographical,economic,technological,cognitive,and institutional proximity,made an influence on the formation of AEE spatial relation network.The findings indicated that:1)in 1997−2019,the AEE in China was present in some spatial and temporal differences characteristics at the provincial scale,and we specifically found that national macro-regulation and policy incentives played a positive role in the long-term development of AEE.2)The spatial correlation of AEE development among provincial regions were becoming closer and exhibits obvious spatial correlation and spillover effects.The evolution of the AEE network has clearly observable trends of hierarchization and aggregation,and the complexity of the correlation network continues to increase and exhibits spatial clustering characteristics that are dense in the east and sparse in the west.The network structure has changed from monocentric radiation to a multicentric network,and network nodes select the more advantageous nodes with which to connect.3)Finally,the geographical proximity had a significant negative effect;the economic,technological,and institutional proximities were all observed to contribute to the AEE network formation,and cognitive proximity did not significantly influence this network formation.

Study of Occlusal-maxillo-facial 3-dimentional Structural Change of Orthodontic Therapy of Crossbite Malocclusion by Modified ACTIVATOR Appliance

Summary: Occlusal-maxillo-facial structural change of crossbite malocclusion after orthodontic therapy by modified ACTIVATOR appliance was investigated. Eighty crossbite cases of deciduous dentition and mixed dentition were treated by modified ACTIVATOR. Through pre- and post-treatment analysis of stone model, Schuller's position X-ray and craniofaciometrics, the change in craniofacial length, width and height in early-phase crossbite malocclusion was studied. The results showed that there was no significant change in the width of maxillary and mandibular dental arch. Maxillary length and protrusion was increased significantly, upper incisors slopped labially. The lower incisors slopped lingually, mental angle decreased more severely. The lower and posterior facial height was increased to normal level.