2results about How to "Alleviate resource constraints" patented technology

This invention provides a horse chestnut tiglyl-CoA ligase gene. AcCCL3 This invention relates to the AcCCL3 protein and its applications, belonging to the field of gene technology. For the first time, this invention has identified and verified the key enzyme gene responsible for the biosynthesis of tigrazol-CoA in horse chestnut. AcCCL3 This invention provides a complete analysis of its biosynthetic pathway, filling a knowledge gap in this field. It can be based on... AcCCL3 This gene, through synthetic biology strategies and an engineered system, has achieved the synthesis of tiglyl-CoA, completely eliminating reliance on traditional, complex, and demanding chemical synthesis routes. This significantly reduces production costs from the source, enabling large-scale production and successfully solving the core challenge of large-scale, stable preparation and supply of tiglyl-CoA. It also breaks through the key precursor constraints that have hindered the biosynthetic research, drug development, and industrial production of a series of high-value aescin compounds, represented by aescin A.

The present application belongs to the technical field of distributed machine learning and edge intelligence, and discloses a self-adaptive quantization decentralized learning method and system for heterogeneous edge devices. The present application is directed to a plurality of edge devices with heterogeneous computing resources, heterogeneous storage capabilities and time-varying communication links. Under the condition of no central server participation, through training parameter and communication relationship initialization, training quantization scale self-adaptive determination, low-precision local training, communication quantization scale self-adaptive determination, quantization model information exchange and neighbor aggregation update, decentralized collaborative learning is completed. The present application can simultaneously alleviate the resource limitation problem of heterogeneous edge devices in the training stage and the communication stage, ensure the implementability of decentralized collaborative learning, improve resource utilization efficiency and improve model convergence stability.