Fintech has not changed the nature and risk attributes of financial business. Its openness, interoperability, and other characteristics trigger the concealment, infectivity, universality and sudden characteristics of financial risk more obviously, and the potential systemic risk more complexly. This paper adopts fuzzy set analysis to conduct a comprehensive review of Fintech risk. It is found that the technology risk, moral hazard and legal risk, with a weight of up to 80%, are the dominant factors affecting the Fintech risk, while other prominent credit risk, market risk and operational risk in the traditional financial field account for a small proportion, but they still cannot be ignored. The research of this paper enriches the relevant research on the quantification of Fintech risk, and helps to strengthen risk prevention from the aspect of enhancing the safety of Fintech infrastructure, improving the legal system, sound the regulatory framework and strengthening industry self-discipline.

China’s high economic growth has been accompanied by deteriorating air quality in recent decades. This paper aims to explore the relation between technology innovation (defined as the invention patent counts of each region) of new energy vehicles (NEVs) in China and air quality. A panel fixed effect model is used to analyze this relation and the mediating effect methods are used to examine the role of the output of NEVs (defined as the annual production quantity of NEVs in each region (unit: thousand)). The results of our study show: (1) the impact of the technology innovation of NEVs on air quality is positive and statistically significant; (2) the mediating role of the output of NEVs is confirmed in the relation between NEVs innovation and air quality improvement; (3) the technology innovation of NEVs has a more notable impact on the air quality in the regions with higher vehicle and vessel tax (VVT). The present study implicates for the first time that the technology innovation of NEVs can enhance air quality with the mediating role of the output of NEVs and the moderating role of VVT.

Accurate determination of crop phenology information is essential for effective field management and decision-making processes. Remote sensing time series analyses are widely employed to extract the phenological stages. Each crop’s phenological stage has its unique characteristic on the crop plant, while the satellite-derived crop phenology refers to some key transition dates in time series satellite observations. Current techniques primarily estimate specific phenological stages by detecting points with distinctive features on the remote sensing time series curve. But these stages may be different from the Biologische Bundesanstalt, Bundessortenamt and CHemical Industry (BBCH) scale, which is commonly used to identify the phenological development stages of crops. Moreover, when aiming to extract various phenological stages concurrently, it becomes necessary to adjust the extraction strategy for each unique feature. This need for distinct strategies at each stage heightens the complexity of simultaneous extraction. In this study, we utilize the Sentinel-2 Normalized Difference Vegetation Index (NDVI) time series data and propose a phenology extraction framework based on the Derivative Dynamic Time Warping (DDTW) algorithm. This method is capable of simultaneously extracting complete phenological stages, and the results demonstrate that the Root Mean Square Errors (RMSEs, days) of detected phenology on the BBCH scale for corn were less than 6 days overall.

Metro TOD plays an important role in the development of commercial economy and promotes the local industry and economy. Reasonable combination of Metro TOD and tourism economy will help to form a more diversified development model. This paper puts forward a new development mode of Nanjing Shijiu Lake Metro TOD.

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