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樓主: 民俗學(xué)
21#
發(fā)表于 2025-3-25 03:23:27 | 只看該作者
John Williamsis desk, advises his patient that he should take complete rest. ‘By the way’, he enquires, ‘what is your occupation?’ Grumpily slouched in his chair, the patient responds ‘I’m an anarchist’, to which the doctor retorts, ‘Well, don’t throw any more bombs for a month at least.’. Clearly this sketch di
22#
發(fā)表于 2025-3-25 08:40:44 | 只看該作者
Type-2 Neuro-Fuzzy Modeling for a Batch Biotechnological Processable to drive uncertainty like that arising from process measurements. The developed model is contrasted with an usual type-1 fuzzy model driven by the same uncertain data. Model development is conducted, mainly, by experimental data which is comprised by thirteen data sets obtained from different p
23#
發(fā)表于 2025-3-25 14:00:22 | 只看該作者
24#
發(fā)表于 2025-3-25 16:01:12 | 只看該作者
25#
發(fā)表于 2025-3-25 22:52:31 | 只看該作者
Einführung in die organische Chemieg, durch Umlagerung der Atome in der anorganischen Verbindung Ammoniumcyanat die typisch organische Verbindung Harnstoff herzustellen: Mit dieser .’schen Synthese war aber der Beweis erbracht, da? die sogenannte ?Lebenskraft“ nicht erforderlich ist. Dennoch behielt man den Begriff ?organische Chemie
26#
發(fā)表于 2025-3-26 02:19:40 | 只看該作者
27#
發(fā)表于 2025-3-26 07:46:18 | 只看該作者
Moreover, important traits of plants such as taste,flavour, smell, colour, or resistance against pests and diseases arealso related to secondary metabolites. .The genetic modification of plants is feasible nowadays. What does thepossibility of engineering plant secondary metabolite pathways mean?In
28#
發(fā)表于 2025-3-26 09:17:45 | 只看該作者
Zooming Assisted Stereo Matching,ed the ‘Dyings’ began. Between the passing of her father in 1874 and her own death in 1886, she was to lose every person of importance to her, save her brother, sister, and sister-in-law … The death of her father … was the first great loss of many, and in some ways it proved to be the hardest” (Lundin 224).
29#
發(fā)表于 2025-3-26 14:45:37 | 只看該作者
30#
發(fā)表于 2025-3-26 16:59:29 | 只看該作者
https://doi.org/10.1007/978-3-662-63028-0p of the continuous particle swarm optimization algorithm. The FCM was trained using a new evolutionary approach based on the area under curve (AUC) of the output concept. In order to evaluate the efficacy of the presented scheme, comparisons with benchmark machine learning algorithms were conducted
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