Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

Cryptocurrency Reaction to FOMC Announcements: Evidence of Heterogeneity Based on Blockchain Stack Position

Abstract: We examine the response of a broad set of digital assets to US Federal Fund interest rate and quantitative easing announcements, specifically examining associated volatility spillover and feedback effects. We classify each digital asset into one of three categories: Currencies; Protocols; and Decentralised Applications (dApps). Currency-based digital assets experience idiosyncratic spillovers in the period immediately after US monetary policy announcements, while application or protocol-based digital assets are largely immune to policy volatility spillover and feedback. Mineable digital assets are found to be more susceptible to monetary policy volatility spillovers and feedback than non-mineable. Responses indicate a diverse market within which, not all assets are comparable to Bitcoin.

Mapping Spatial Variability of Soil Salinity in a Coastal Paddy Field Based on Electromagnetic Sensors

Abstract: In coastal China, there is an urgent need to increase land area for agricultural production and urban development, where there is a rapid growing population. One solution is land reclamation from coastal tidelands, but soil salinization is problematic. As such, it is very important to characterize and map the within-field variability of soil salinity in space and time. Conventional methods are often time-consuming, expensive, labor-intensive, and unpractical. Fortunately, proximal sensing has become an important technology in characterizing within-field spatial variability. In this study, we employed the EM38 to study spatial variability of soil salinity in a coastal paddy field. Significant correlation relationship between ECa and EC1:5 (i.e. r >0.9) allowed us to use EM38 data to characterize the spatial variability of soil salinity. Geostatistical methods were used to determine the horizontal spatio-temporal variability of soil salinity over three consecutive years. The study found that the distribution of salinity was heterogeneous and the leaching of salts was more significant in the edges of the study field. By inverting the EM38 data using a Quasi-3D inversion algorithm, the vertical spatio-temporal variability of soil salinity was determined and the leaching of salts over time was easily identified. The methodology of this study can be used as guidance for researchers interested in understanding soil salinity development as well as land managers aiming for effective soil salinity monitoring and management practices. In order to better characterize the variations in soil salinity to a deeper soil profile, the deeper mode of EM38 (i.e., EM38v) as well as other EMI instruments (e.g. DUALEM-421) can be incorporated to conduct Quasi-3D inversions for deeper soil profiles.