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工业人工智能——工业应用中的人工智能系统框架(英文) 被引量:12
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作者 李杰 singh jaskaran +1 位作者 AZAMFAR Moslem 孙可意 《中国机械工程》 EI CAS CSCD 北大核心 2020年第1期37-48,共12页
人工智能正以超越人们想象的方式影响着工业生产和我们的生活。世界多国已启动的国家级人工智能计划均强调了人工智能在智能工业中的重要性和必要性。但与此同时,采用人工智能来实时解决生产的实际问题仍是当前必须面对且不能忽视的挑... 人工智能正以超越人们想象的方式影响着工业生产和我们的生活。世界多国已启动的国家级人工智能计划均强调了人工智能在智能工业中的重要性和必要性。但与此同时,采用人工智能来实时解决生产的实际问题仍是当前必须面对且不能忽视的挑战。现在的最大挑战是找到可创造价值的具体应用来满足市场和资本不断增长的期望。为了给工业系统中的人工智能的发展与实施提供一个清晰的路线图,提出了工业人工智能的系统框架和使能技术。综述了智能工业中的工业人工智能的关键使能技术的重要性,阐述了如何系统地应用这些使能技术来创造产生新价值的机会并避免出现问题。 展开更多
关键词 工业人工智能 智能制造 工业4.0 使能技术 信息物理系统
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Metagenomics-driven discovery of next-generation fermentation biocatalysts:From enzyme mining to synthetic biology applications
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作者 Atif Khurshid Wani Rashid Mumtaz Khan +5 位作者 Noureddine Elboughdiri jaskaran singh Karim Kriaa Chemseddine Maatki Bilel Hadrich Reena singh 《Food Bioscience》 2026年第3期92-113,共22页
Conventional enzyme discovery strategies relying on culturable microorganisms are fundamentally limited,as over 99%of microbes remain uncultured under laboratory conditions.This has constrained access to the vast cata... Conventional enzyme discovery strategies relying on culturable microorganisms are fundamentally limited,as over 99%of microbes remain uncultured under laboratory conditions.This has constrained access to the vast catalytic potential encoded within microbial communities inhabiting extreme,diverse,and underexplored eco-systems.Metagenomics has emerged as a transformative approach to overcome these limitations.This meth-odology rapidly unlocks access to novel enzyme families,offering orders-of-magnitude greater diversity than traditional screening.By integrating sequence-driven and function-driven strategies,metagenomics enables the discovery,characterization,and engineering of next-generation biocatalysts for fermentation-based industries.Hydrolases remain the most extensively studied,with applications in starch processing,dairy fermentation,and lignocellulosic bioconversion.Oxidoreductases,including laccases and alcohol dehydrogenases,contribute to bioethanol production,detoxification,and flavor development,while transferases,lyases,and multifunctional enzymes offer opportunities for efficient synthesis of value-added metabolites and streamlined multi-step pro-cesses.These discoveries not only improve fermentation efficiency but also reduce energy inputs,waste gener-ation,and production costs.Advances in bioinformatics pipelines,coupled with machine learning(ML)and artificial intelligence(AI),now facilitate precise gene prediction,functional annotation,and enzyme design.Despite challenges in heterologous expression due to codon usage,folding inefficiencies,and post-translational requirements,metagenomics holds immense promise.This review synthesizes current progress in enzyme mining and highlights how integrating metagenomics with synthetic biology can drive precision fermentation.This review highlights how metagenomics delivers a significant quantitative advantage,often yielding enzymes with improved stability and efficiency,which fundamentally reduce bioprocess costs and enhance industrial scalability. 展开更多
关键词 Precision fermentation Enzymes Bioinformatics Unculturable microbes Machine learning Synthetic biology Artificial intelligence
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