Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams

Tsui, To-Hung; Loosdrecht, Mark C.M. van; Dai, Yanjun; Tong, Yen Wah

doi:10.1016/j.biortech.2022.128445

Cited by 47 publications

(16 citation statements)

References 82 publications

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“…Independent variable filtering was performed via full subset regression and automatic model filtering (dredge function). K-means clustering, a machine-learning-based method, was used to verify whether the characteristics of the fish community, flora, and microbes in the same habitat were closer [26]. Considering that abiotic factors such as the habitat, temperature, and water quality also have an impact on biological factors, a structural equation model (SEM) path analysis was carried out on the basis of the linear model, and the abiotic factors were used as exogenous variables and the biological factors were used as endogenous variables to analyze the main influencing factors.…”

Section: Discussionmentioning

confidence: 99%

Abiotic and Biotic Effects on Microbial Diversity of Small Water Bodies in and around Towns

Peng

2023

Sustainability

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Microbial communities play very important roles in pollutant treatment and absorption and material and energy cycling in wetlands. Among different wetland types, wetlands in and around towns are the most closely related to human life, but how human activities affect microbes in small water bodies has received little attention. In this study, nine small water bodies of three different landscape types were chosen in the Lishui District of Nanjing City, China. The microbial community characteristics of four different seasons were revealed by metagenomics in 2021, and the possible effects of abiotic and biological factors such as the effects of alien organisms on microbial communities were analyzed. The results showed significant differences in microbial community structure in different seasons and habitats. Abiotic and biological factors jointly affected the microbial communities, and the influence of water quality was greater than that of the habitat type and biological factors. This study shows that in addition to the water quality, the wetland biome structure, especially the abundance of alien species, may have an impact on microbial communities. The results emphasize that human activities such as land use and the introduction of alien species have significant impacts on the ecosystem structure and function.

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Section: Discussionmentioning

confidence: 99%

Abiotic and Biotic Effects on Microbial Diversity of Small Water Bodies in and around Towns

Peng

2023

Sustainability

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“…Another critical research direction is the application of ML in biopolymer recycling and waste reduction. ,, As the world grapples with plastic pollution, biopolymers offer a sustainable alternative. ML can be leveraged to improve recycling processes, optimize waste management systems, and develop new biodegradable materials.…”

Section: Future Workmentioning

confidence: 99%

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

Bin Abu Sofian,

Sun,

Gupta

et al. 2024

Energy Fuels

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This review illuminates the pivotal synergy between machine learning (ML) and biopolymers, spotlighting their combined potential to reshape sustainable energy, fuels, and biochemicals. Biobased polymers, derived from renewable sources, have garnered attention for their roles in sustainable energy and fuel sectors. These polymers, when integrated with ML techniques, exhibit enhanced functionalities, optimizing renewable energy systems, storage, and conversion. Detailed case studies reveal the potential of biobased polymers in energy applications and the fuel industry, further showcasing how ML bolsters fuel efficiency and innovation. The intersection of biobased polymers and ML also marks advancements in biochemical production, emphasizing innovations in drug delivery and medical device development. This review underscores the imperative of harnessing the convergence of ML and biobased polymers for future global sustainability endeavors in energy, fuels, and biochemicals. The collective evidence presented asserts the immense promise this union holds for steering a sustainable and innovative trajectory.

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“…It is highly likely that robotics and artificial intelligence/machine learning tools will play a role in shaping the bioeconomy in the future. 224…”

Section: Summary and Future Possibilitiesmentioning

confidence: 99%

White & grey biotechnologies for shaping a sustainable future

Roy¹,

Gupta²

2023

RSC Sustain.

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Machine learning and circular bioeconomy: Building new resource efficiency from diverse waste streams

Cited by 47 publications

References 82 publications

Abiotic and Biotic Effects on Microbial Diversity of Small Water Bodies in and around Towns

Abiotic and Biotic Effects on Microbial Diversity of Small Water Bodies in and around Towns

Advances, Synergy, and Perspectives of Machine Learning and Biobased Polymers for Energy, Fuels, and Biochemicals for a Sustainable Future

White & grey biotechnologies for shaping a sustainable future

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