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Titlebook: Integrative Biological Control; Ecostacking for Enha Yulin Gao,Heikki M. T. Hokkanen,Ingeborg Menzler-H Book 2020 Springer Nature Switzerla

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21#
發(fā)表于 2025-3-25 05:16:17 | 只看該作者
22#
發(fā)表于 2025-3-25 09:55:11 | 只看該作者
ewable energies) are analysed for assessment and quantification where data is available. The carbon footprint calculator includes the derived and influential activities that should be included in the application for the approval of urban planning instruments, within the ordinary or simplified strate
23#
發(fā)表于 2025-3-25 14:33:57 | 只看該作者
24#
發(fā)表于 2025-3-25 19:45:33 | 只看該作者
Adam Fl?hr,Johan A. Stenberg,Paul A. Eganarine-sonar-monitoring levels of vigilance, as said by Jon Kabot-Zinn (1990, p. 23), “it would be incorrect to think of meditation as a passive process; it takes a good deal of energy and effort to regulate your attention and to remain genuinely calm and nonreactive.”
25#
發(fā)表于 2025-3-25 21:52:16 | 只看該作者
26#
發(fā)表于 2025-3-26 03:03:34 | 只看該作者
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發(fā)表于 2025-3-26 08:10:26 | 只看該作者
28#
發(fā)表于 2025-3-26 10:59:32 | 只看該作者
Pingyang Zhu,Zhongxian Lu,Guihua Chen,K. L. Heongsuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers.?.What You Will Learn.Build
29#
發(fā)表于 2025-3-26 14:05:19 | 只看該作者
Chengyun Li,Jing Yang,Xiahong He,Shusheng Zhu,Youyong Zhusuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers.?.What You Will Learn.Build
30#
發(fā)表于 2025-3-26 19:32:20 | 只看該作者
Ouyang Fang,Men XingYuan,Ge Fengsuch as fairness, transparency, safety, privacy, and robustness. The book helps you think responsibly while building AI and ML models and guides you through practical steps aimed at delivering responsible ML models, datasets, and products for your end users and customers.?.What You Will Learn.Build
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