With the development of electrochemical energy storage systems with intrinsic safety, zinc–nickel batteries (ZNBs) have attracted widespread attention. However, the poor cycling life and shelf life restrict their further application. Herein, a porous-structured “Ryomen Sukuna” (RS)...

The targeted capture of heavy metals from wastewater is urgently necessary in response to strategic demands of sustainable resource utilization, but it is severely hampered by the formation of specific adsorbent-adsorbate interactions. Herein, the conjugated microporous polymer CMP-1 with...

The smart workshop is a powerful tool for manufacturing companies to reduce waste and improve production efficiency through real-time data analysis for self-organized production. Automated Guided Vehicles (AGVs) have been widely used for material handling in smart workshop due to their high...

There is considerable debate about the sustainability of the hydraulic fracturing (HF) water cycle in North America. Recently, this debate has expanded to China, where HF activities continue to grow. Here, we provide a critical review of the HF water cycle in China, including water withdrawal...

Even though blockchain as a research topic incites broad academic interest, there is arguably a balkanization that occurred along the natural delineation between public-permissionless blockchains and private-permissioned blockchains. IS researchers, for instance, have been more inclined to...

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis...

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs model interpretability and their ability to provide adequate guidance in the design of crisis...

We develop a mixed-frequency, tree-based, gradient-boosting model designed to assess the default risk of privately held firms in real time. The model uses data from publicly-traded companies to construct a probability of default (PD) function. This function integrates high-frequency,...