Endogenous Explanation for Random Fluctuation of Stock Price and Its Application: Based on the View of Repeated Game with Asymmetric Information

In this paper, we characterize the players’ behavior in the stock market by the repeated game model with asymmetric information. We show that the discount price process of stock is a martingale driven by Brownian motion, and give an endogenous explanation for the random fluctuation of stock price: the randomizations in the market is due to the randomizations in the strategy of the informed player which hopes to avoid revealing his private information. On this basis, through studying the corresponding option pricing problem furtherly, we can give the expression of function φ.

Effect of surface property on mass flux in a variable-section microchannel

For microfluidic systems, interfacial phenomena in micro-reactors are of great importance because they control the transfer and reaction characteristics. This paper dwells on how the surface property and geometry influence the mass flux in a complex microchannel. The lattice Boltzmann method(LBM) with a pseudo potential model and the Shan–Chen model for the interaction between fluid and hydrophobic surface were built up, so a boundary slip effect was added and verified. On this basis, a microchannel with variable-section geometry was simulated. The results indicate that the optimal design and the flow pattern are quite different under hydrophilic and hydrophobic conditions. A microchannel with sequential hydrophilic and hydrophobic surface was also simulated. The numerical results indicate that the hydrophobic wall can improve the mass flux, irrespective of microchannel geometry. Particularly, an empirical correlation with a linearly relationship between length of hydrophobic segment and mass flux was obtained for the straight microchannel.

An Efficient Algorithm for Skyline Queries in Cloud Computing Environments

Skyline query processing has recently received a lot of attention in database and data mining communities. However, most existing algorithms consider how to efficiently process skyline queries from base tables. Obviously, when the data size and the number of skyline queries increase, the time cost of skyline queries will increase exponentially, which will seriously influence the query efficiency. Motivated by the above, in this paper, we consider improving the query efficiency via skyline views and propose a cost-based algorithm(abbr. CA) to efficiently select the optimal set of skyline views for storage. The CA algorithm mainly includes two phases:(i) reduce the skyline views selection to the minimum steiner tree problem and obtain the approximate optimal set AOS of skyline views, and(ii) adjust AOS and produce the final optimal set FOS of skyline views based on the simulated annealing. Moreover, in order to improve the extendibility of the CA algorithm, we implement it based on the map/reduce distributed computation model in cloud computing environments. The detailed theoretical analyses and extensive experiments demonstrate that the CA algorithm is both efficient and effective.

GEE-Based monitoring method of key management nodes in cotton production

The high-temporal-resolution monitoring of key management nodes in cotton management via agricultural remote sensing is vital forfield cotton macro-statistics,particularly for predicting cotton production and obtaining comprehensive data.This study examines Shihezi,Xinjiang as a case study,utilizing Sentinel-1 and Sentinel-2 data from 2019 to 2021.Three machine learning models(RF,SVM,and CART)were employed to extract annual crop classification area rasters,monitor weekly cultivation progress,and monitor abandoned cropland during the cultivation period.The results demonstrate that the random forest model has produced satisfactory results in gridded extraction for cotton classification areas,achieving the producer’s accuracy of the cotton category reached 98.5%,and the kappa coefficient is 0.947.Cotton cultivated in 2021 began is a week later than in 2020,yet exhibited a faster cultivate speed.The proportion of abandoned cottonfields in the study area rose in 2020 compared to 2019.The methodology presented in this study has a certain reference value for exploring the monitoring of continuous changes in crops over the years and macro-monitoring of important activities in the entire growth cycle.

互联网技术进步与中国产业结构优化升级:理论与实证

本文构建了互联网技术驱动下的产业结构优化升级模型,利用信息化发展指数测算出互联网技术进步率,并推导出全国31个地区互联网技术进步对三大产业生产率贡献的序关系,从而在理论层面考察了互联网技术进步对各地产业结构调整的异质性影响,然后利用2000~2017年全国省际面板数据进行了实证研究。研究发现:(1)对于第三产业发展迅猛的地区,互联网技术进步对第三产业生产率的贡献大于第二产业,可以促进产业结构升级;但部分地区二、三产业市场化进程缓慢、消费服务业发展滞后导致三大产业生产率不趋同,不利于结构优化。(2)对于具有工业化结构的地区,互联网技术进步不利于产业结构升级,但对于其中农业现代化水平较高的地区,"互联网+农业"的发展缩小了第一产业与二、三产业生产率的差距,有利于结构优化。(3)对于产业结构具有"服务化"特征的地区,互联网技术对其结构高度化的驱动作用要远大于具有"服务化"倾向和"工业化"特征的地区。

Adsorption of VOCs on reduced graphene oxide

A modified Hummer＇s method was adopted for the synthesis of graphene oxide（GO） and reduced graphene oxide（rGO）. It was revealed that the modified method is effective for the production of GO and rGO from graphite. Transmission electron microscopy（TEM） images of GO and rGO showed a sheet-like morphology. Because of the presence of oxygenated functional groups on the carbon surface, the interlayer spacing of the prepared GO was higher than that of rGO. The presence of ／OH and CO groups in the Fourier transform infrared spectra（FTIR） spectrum and G-mode and 2D-mode in Raman spectra confirmed the synthesis of GO and rGO. rGO（292.6 m2/g） showed higher surface area than that of GO（236.4 m2/g）. The prepared rGO was used as an adsorbent for benzene and toluene（model pollutants of volatile organic compounds（VOCs）） under dynamic adsorption/desorption conditions. rGO showed higher adsorption capacity and breakthrough times than GO. The adsorption capacity of rGO for benzene and toluene was 276.4 and 304.4 mg/g, respectively.Desorption experiments showed that the spent rGO can be successfully regenerated by heating at 150.0℃. Its excellent adsorption/desorption performance for benzene and toluene makes rGO a potential adsorbent for VOC adsorption.

Classification method of cultivated land based on UAV visible light remote sensing

The accurate acquisition of the grain crop planting area is a necessary condition for realizing precision agriculture.UAV remote sensing has the advantages of low cost use,simple operation,real-time acquisition of remote sensor images and high ground resolution.It is difficult to separate cultivated land from other terrain by using only a single feature,making it necessary to extract cultivated land by combining various features and hierarchical classification.In this study,the UAV platform was used to collect visible light remote sensing images of farmland to monitor and extract the area information,shape information and position information of farmland.Based on the vegetation index,texture information and shape information in the visible light band,the object-oriented method was used to study the best scheme for extracting cultivated land area.After repeated experiments,it has been determined that the segmentation scale 50 and the consolidation scale 90 are the most suitable segmentation parameters.Uncultivated crops and other features are separated by using the band information and texture information.The overall accuracy of this method is 86.40%and the Kappa coefficient is 0.80.The experimental results show that the UAV visible light remote sensing data can be used to classify and extract cultivated land with high precision.However,there are some cases where the finely divided plots are misleading,so further optimization and improvement are needed.

Corrigendum to ‘Adsorption of VOCs on reduced graphene oxide’ [J. Environ. Sci. 67 (2018) 171-178]

The authors regret“In the whole text,ppm and mg/L was confusing.As in aqueous phase,1 ppm=1 mg/L,but in gaseous phase,1 ppm=0.001%o.In this paper,in text and figures,the concentration units were ppm,but when calculating the adsorption ca-pacity,the concentration units ppm were mistakenly used as mg/L.As for benzene,1 ppm=3.4871 x 10^-3 mg/L,as for toluene。