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In recent years, several factors, such as frequent extreme weather, disrepair of dams, and improper management, have caused frequent dam failures, posing a significant threat to people's lives downstream. At present, the life loss is evaluated using the empirical formula method, in which the recommended approximate and threshold results are obtained through linear regression or statistical analysis. However, this method is sometimes insufficient because of the lack of a historical dataset and low availability, and it tends to simplify or ignore the influence of some factors in regression. During the research, most objects are considered as individual cases, and thus, the universality and scientificity of the application of evaluation models or parameters need further discussion. The variable fuzzy set theory features rigorous mathematical clarity and fuzziness of things and is widely used in the optimal decision evaluation model. Although, the traditional variable fuzzy evaluation method is widely used to deal with the linear variation in the index, some indexes, such as dam storage capacity and downstream population at risk, can cause non-linear problems, directly affecting the accuracy of membership evaluation results. Therefore, an improved model was proposed, where the relative difference formula was improved through logarithmic transformation and boundary constraint. The improved method was applied to the sequencing of life loss risk consequences for four reservoirs. The evaluation result was consistent with the actual situation of the disaster and the actual mortality rate. The scientificity and practicability of the improved model were verified, providing a new perspective for reservoir risk ranking and enriching the risk management theory.

Blockchain has the potential to reconfigure the contemporary economic, legal, political and cultural landscape, causing a flood of research on this topic. However, limited efforts have been made to conduct retrospective research to appraise the blockchain studies in the recent period, easily leading to a neglect of new technological trends. Consequently, the present research designs a quantitative- and qualitative-analysis procedure to review the latest research status. Adopting a four-step workflow, six research hotspots (i.e., the specific application areas of blockchain technology, the integration of blockchain and other technologies, the driving factors of blockchain, the values of blockchain technology, the types of blockchain and the core technologies of blockchain) and five research frontiers (i.e., entrepreneurship, contract, industrial internet, data management and distributed ledger technology) were detected using quantitative analysis. Furthermore, three other topics (i.e., the Internet of things, access control and trust) and two research gaps (i.e., the true effect of blockchain technology on firms’ operational efficiency and the regulation of the “dark sides” of blockchain technology) were also identified, using qualitative analysis. Finally, the evolutionary paths were qualitatively analyzed, and then three phases of blockchain research were summarized. The conclusions are able to provide a more comprehensive enlightenment regarding blockchain’s research hotspots, research frontiers, evolutionary paths and research gaps in the recent period, from 2015 to 2021, and to provide a reference for future research.

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