Sub-seasonal soil moisture anomaly forecasting using combinations of deep learning, based on the reanalysis soil moisture records

Sub-seasonal drought forecasting is crucial for early warning in estimating agricultural production and optimizing irrigation management, as forecasting skills are relatively weak during this period. Soil moisture exhibits stronger persistence compared to other climate system quantities, which makes it especially influential in shaping land...

Precision Engineering of the Co-immobilization of Enzymes for Cascade Biocatalysis

The design and orderly layered co-immobilization of multiple enzymes on resin particles remain challenging. In this study, the SpyTag/SpyCatcher binding pair was fused to the N-terminus of an alcohol dehydrogenase (ADH) and an aldo-keto reductase (AKR), respectively. A non-canonical amino acid (ncAA), p-azido-L-phenylalanine (p-AzF), as the...

Prediction of estimated time of arrival for multi-airport systems via “Bubble” mechanism

Predicting Estimated Time of Arrival (ETA) for a Multi-Airport System (MAS) is much more challenging than for a single airport system because of complex air route structure, dense air traffic volume and vagaries of traffic conditions in an MAS. In this work, we propose a novel “Bubble” mechanism to accurately predict medium-term ETA for a...

Inference algorithms for the useful life of safety instrumented systems under small failure sample data

Safety instrumented systems(SIS) have been widely used in petroleum and chemical plants to detect and respond to dangerous events and prevent them from developing into accidents. The in-service time of SIS does not exceed its useful life is one of the crucial assumptions of IEC functional safety standards. The testing method recommended in the...

Conductive Co-based metal organic framework nanostructures for excellent potassium- and lithium-ion storage: Kinetics and mechanism studies

Thanks to the low cost and earth's abundant potassium resources, potassium ion batteries (PIBs) have attracted much interest as alternative energy storage devices. However, there is still a great challenge to develop suitable anode materials for PIBs with high specific capacity, fast charge/discharge and stable ion storage. Nowadays,...

Network-Aware Locality Scheduling for Distributed Data Operators in Data Centers

Large data centers are currently the mainstream infrastructures for big data processing. As one of the most fundamental tasks in these environments, the efficient execution of distributed data operators (e.g., join and aggregation) are still challenging current data systems, and one of the key performance issues is network communication time....