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Multi-criteria priority ranking involves determining priorities through calculations for a multitude of tasks as per potentially conflicting criteria, to aid decision-makers in efficient allocation of resources and prioritization of tasks based on their criticality. This process is essential for optimizing resource allocation and improving overall work efficiency. Over the past two decades, the field of priority ranking has seen the development of numerous mature classic methods through continuous modifications and expansions. Furthermore, new sorting methods rooted in advancing technologies in the era of big data have also emerged. To assist decision-makers in evaluating and selecting the most suitable multi-criteria prioritization methods for priority ranking needs in specific application scenarios, this paper first elucidates differences across various multi-criteria prioritization methods regarding criteria substitutability, advantages and disadvantages, data input/output requirements, and applicable scenes. It further categorizes existing multi-criteria task prioritization methods into four main types: full aggregation methods, inferiority ranking methods, reference level methods, and data processing-based prioritization methods. Additionally, it discusses in detail the basic principles, implementation steps, latest research findings, and pros and cons of representative methods within each category. Finally, this paper summarizes current research hotspots, including the analytic hierarchy process, fuzzy theory, and AI-assisted ranking technologies, while suggesting future research pathways covering AI-assisted big data ranking optimization, ranking stability enhancement, and intelligent preference identification.

Films with nanoengineered surfaces have been extensively utilized in a variety of energy-related applications such as water desalination, thermal management and solar steam generation. To generate high-quality films, various generation methods including chemical vapor deposition (CVD), electrodeposition and microlithography have been studied. Compared to these methods, however, bubble-induced self-assembly (BISA) has been developed as an alternative strategy due to the advantages of being simple and cost-effective, and has generated considerable research efforts. In this paper, we review the recent advances in the development of films with nanoengineered surfaces via the BISA of nanomaterials. The mechanism and regulation of the BISA to generate high-performance films with the desired surface characteristics are discussed in detail. We also highlight the application of the BISA strategy for use in enhanced phase-change heat transfer. In addition, other applications of the BISA strategy are described, which range from effective thermal management of electronics and concentrated photovoltaics, to advanced energy storage and conversion. Finally, we discuss the current challenges and potential research directions in the field. It is expected that this review will provide a comprehensive understanding of the design, generation, applications and perspectives of films with nanoengineered surfaces generated by the BISA. [ABSTRACT FROM AUTHOR]

We consider the problem of seeking communities in directed networks. The common approach to this problem has been to simply ignore directions of edges and use algorithms developed for community detection in undirected networks, but this approach discards potentially indispensable information involved in the directions of edges. Here, we introduce an index for node dissimilarity in directed networks in the perspective of dynamics, which are driven by a novel parameter-free signal copying model, to incorporate information contained in the directions of edges. Our dissimilarity index gives a natural fusion between the local and global viewpoints of topological structure of directed networks. Thereby, we apply our index to uncover community structure in directed networks and conduct extensive experiments on synthetic and real-world ones. The results demonstrate that our method outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]