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Titlebook: Organic Waste to Biohydrogen; Mohammed Kuddus,Ghazala Yunus,Gustavo Molina Book 2022 The Editor(s) (if applicable) and The Author(s), unde

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11#
發(fā)表于 2025-3-23 12:25:28 | 只看該作者
Nanotechnological Approaches in Biohydrogen Production,ological approaches and significant improvements have been achieved in hydrogen production efficiency in recent years. This chapter explains the nanobiotechnological potentials of hydrogen production with the use of nanomaterials in organic wastes and highlights the latest developments in reaction m
12#
發(fā)表于 2025-3-23 14:29:36 | 只看該作者
Microalgal Biomass as a Promising Feedstock for the Production of Biohydrogen: A Comprehensive Revidrogen. In microalgae metabolism, the enzymes hydrogenase and nitrogenase are principally responsible for the biological hydrogen generation process. Despite successful laboratory-scale research into microalgae hydrogen production, low yield has been identified as a problem due to light absorption e
13#
發(fā)表于 2025-3-23 21:16:19 | 只看該作者
Biohydrogen: Future Energy Source for the Society,e municipal waste separation process. This residual stream still contains around 24% of organic matter, 28% of paper and cardboard, 25% of plastic materials, and 9% of textiles, among other elements, but the specific characteristics of such materials currently do not enable their reuse or recycling.
14#
發(fā)表于 2025-3-24 00:03:09 | 只看該作者
Book 2022read use of everlasting renewable energy source. This book is useful for professional scientists, academicians, biotechnologist and environmentalist along with research scholars in various biotechnology and bioenergy industries by addressing the latest research going on in the field of renewal bioen
15#
發(fā)表于 2025-3-24 05:02:18 | 只看該作者
ITS uses a bank of artificial neural networks to automatically profile a learner’s comprehension using webcam images, and intervenes to help improve learner motivation and avoid impasse. The considerable issue of trust in AI is discussed, and a study of public opinion on ethical use of AI in educati
16#
發(fā)表于 2025-3-24 06:48:20 | 只看該作者
Karina J. Salazar-Batres,Guillermo Quijano,Iván Moreno-AndradeITS uses a bank of artificial neural networks to automatically profile a learner’s comprehension using webcam images, and intervenes to help improve learner motivation and avoid impasse. The considerable issue of trust in AI is discussed, and a study of public opinion on ethical use of AI in educati
17#
發(fā)表于 2025-3-24 11:12:58 | 只看該作者
Iván Moreno-Andrade,Karina J. Salazar-Batres,Edith Villanueva-Galindo,Jonathan F. Cortez-Cervantes,Ums emerged as an excellent optimisation method for neuroevolution, as they provide faster convergence, with a reduced computational cost. This chapter presents an overview of quantum-inspired evolutionary algorithms and their application to the configuration of different neural network models, such
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發(fā)表于 2025-3-24 16:56:57 | 只看該作者
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發(fā)表于 2025-3-24 22:35:48 | 只看該作者
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發(fā)表于 2025-3-25 00:18:15 | 只看該作者
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