Predicting China's CPI by Scanner Big Data

Scanner big data has potential to construct Consumer Price Index (CPI). This work utilizes the scanner data of supermarket retail sales, which are provided by China Ant Business Alliance (CAA), to construct the Scanner-data Food Consumer Price Index (S-FCPI) in China, and the index reliability is verified by other macro indicators, especially by China's CPI. And not only that, we build multiple machine learning models based on S-FCPI to quantitatively predict the CPI growth rate in months, and qualitatively predict those directions and levels. The prediction models achieve much better performance than the traditional time series models in existing research. This work paves the way to construct and predict price indexes through using scanner big data in China. S-FCPI can not only reflect the changes of goods prices in higher frequency and wider geographic dimension than CPI, but also provide a new perspective for monitoring macroeconomic operation, predicting inflation and understanding other economic issues, which is beneficial supplement to China's CPI

Size-dependent vibration of nickel cantilever microbeams: Experiment and gradient elasticity

The size-dependent elasticity of a series of nickel cantilever microbeams was investigated experimentally for the first time. The experimental results revealed that the dimensionless natural frequencies of the cantilever microbeams increase to about 2.1 times with the beam thickness decreasing from 15 to 2.1 μm. Furthermore, based on the strain gradient elasticity theory (SGT) and by using the differential quadrature method (DQM) and the least square method (LSM), the experimental results were interpreted and the material length scale parameters in the scale of micron in elastic range were obtained. This investigation will be useful and helpful for the theoretical and numerical simulation of micro-structures and important for the design of the MEMS/NEMS

Parameter Adaptive Sliding Mode Force Control for Aerospace Electro-Hydraulic Load Simulator

The aerospace electro-hydraulic servo simulator is used to simulate the air load received during flight, and is used for the performance test and acceptance test of aerospace servo actuators on the ground. The force loading accuracy of the load simulator is an important assessment index. Because the loading system and the actuator system to be tested are coupled together, the free displacement of the system to be tested during loading will bring huge disturbance to the loading system, thus how to suppress external interference has always been a hot issue in the control field. This paper addresses this issue under the influence of nonlinear friction and uncertain external disturbance. First, the exact mathematical model of the system is derived, and the characteristics of the system are described by the state equations. Second, in order to obtain the relevant parameters in the controller, the system parameters are identified. Third, the parameter adaptive sliding mode force control based on the reaching law is proposed, and the performance of the control algorithm is analyzed theoretically. Finally, the new control method is applied in the aerospace electro-hydraulic servo simulator, and the results show that the new control algorithm can suppress the external interference by 95% or more, and the control accuracy is more than 97%, which fully demonstrates the effectiveness of the control method

A spatial error-based cellular automata approach to reproducing and projecting dynamic urban expansion

Urban systems are featured by spatial autocorrelation, which may produce clustering of model residuals when simulating urban expansion using cellular automata (CA). Accurate identification of spatial autocorrelation and reduction of residual clustering are essential to accurate CA modeling of urban expansion. We developed a new CA approach (CASEM) using a spatial error model (SEM) that incorporates spatial autocorrelation. Using Zhengzhou City as a case study, we calibrated three types of CA models [e.g., logistic regression (Logit), spatial lag model (SLM) and SEM] from 2000 to 2010. Here, two important issues are the choice of the appropriate method (SLM vs. SEM) for urban expansion modeling and the applicability of CASEM for projecting urban scenarios. We validated the CASEM model from 2010 to 2017 and projected urban scenarios out to the year 2030 using this model. End-state assessment reveals that CASEM yields a higher overall accuracy (91.4%) in the calibration, but lower overall accuracy (83.8%) in the validation. For change assessment, CASEM yields a lower figure-of-merit (FOM; 31.8%) in the calibration but a higher FOM (35.2%) in the validation. We conclude that CASEM can accurately simulate urban expansion at Zhengzhou considering the fit performance of urban land transition rules, and the accuracy assessment of urban patterns and expansion. Scenario prediction using CASEM is therefore valuable for formulating useful urban planning regulations and in supporting sustainable urban development

Study of Dynamic Viscoelasticity of a Mineral Oil-Based Magnetic Fluid

Magnetic fluid is a field-responsive intelligent fluid, which has the flow characteristics of liquid and the elastic properties of solid. Because of its unique properties, it has a strong application prospect in the fields of magnetic soft robot, intelligent sensor, and so on. Dynamic viscoelasticity is a significant index to investigate the performance of magnetic fluid in the application process. In this paper, the dynamic viscoelasticity of a homemade mineral oil-based magnetic fluid was investigated under oscillatory shear experimental conditions using an MCR302 rheometer, and the effects of different temperatures and magnetic fields on the dynamic viscoelasticity were examined. Amplitude sweeps tests showed that the value of the storage modulus remained constant within the linear viscoelastic region (LVE) and the stable structure was not destroyed. As the magnetic field strength increased or the temperature increased, the range of the linear viscoelastic zone decreased. At large amplitude, the loss modulus will first appear as a peak and then decrease. The frequency sweep experiment showed that the storage modulus and loss modulus increased with the increase in angular frequency, and the greater the magnetic field intensity, the longer the internal structure relaxation time. When the magnetic field was constant, the higher the temperature, the smaller the storage modulus and loss modulus of the magnetic fluid. At high temperature, the loss coefficient of mesmeric fluid was large, and the magnetic fluid was more viscous. The lower the temperature is, the smaller the loss coefficient of the magnetic fluid is, and the magnetic fluid is more pliant. The study of dynamic viscoelasticity of magnetic fluids lays the foundation for establishing the complete structure intrinsic relationship of magnetic fluids and provides guidance for the application of magnetic fluids in magnetic 3D printing, droplet robot, and smart wear

Multifunctional Perovskite Photodetectors: From Molecular-Scale Crystal Structure Design to Micro/Nano-scale Morphology Manipulation

Highlights Multidimensional detection of intensity, wavelength, polarization, and angle of the incidence light significantly accelerates the development of optical information technology and artificial intelligence fields. The first comprehensive overview of the advancement of multifunctional photodetectors for perovskite semiconductors ranging from polarized light detection, spectral detection, and angle-sensing detection to self-powered detection is summarized. The existing problems and perspectives are discussed which can inspire more researchers to rationally design new perovskite materials and micro/nano-structure for high-performance multifunctional photodetectors

A Novel Method of Flow Curve Measurement for Magnetic Fluid Based on Plane Poiseuille Flow

Accurate measurement of the flow curves of magnetic fluid under a uniform field has always been a challenge. In this article, a novel method is proposed to measure the flow curve of magnetic fluids based on plane Poiseuille flow. The measuring system was built and its performance was compared with that of a commercial rheometer. Flow curves of magnetic fluid with different zero-field viscosity were tested under various field strengths. This novel method facilitates direct observation of the flowing behaviors of magnetic fluid under different stresses. By examining the variation trend of viscosity under certain constant stress, a more reliable method to determine the dynamic yield stress of magnetic fluid was used. The dynamic yield stress of the magnetic fluid measured by the new method was larger than the value obtained by the fitting, which is more reliable from an engineering point of view

Simulating the effect of urban light rail transit on urban development by coupling cellular automata and conjugate gradients

Urban light rail transit systems have a significant potential to alter future urban development. We developed a new cellular automata model (CACG) based on conjugate gradients, and applied it to 1) simulate historical urban development at Jinhua of China, and 2) project future development scenarios incorporating the effect of future light rail transit stations (LRTS). The model produced a realistic urban pattern for 2018 with overall accuracy exceeding 95%, Kappa coefficient exceeding 70% and figure-of-merit exceeding 32%, indicating the model’s ability to accurately capture urban dynamics. We predicted three different scenarios: a benchmark scenario of business as usual (BAU), a scenario focusing on LRTS, and an individual-factor-based scenario (ILRTS). The results show that the annual urban development intensity has the strongest correlation with LRT stations for LRTS-scenario, followed by ILRTS-scenario and BAU-scenario. The model can be readily applied elsewhere to assess the impact of urban infrastructure on future development