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Titlebook: LISS2019; Proceedings of the 9 Juliang Zhang,Martin Dresner,Xiaopu Shang Conference proceedings 2020 The Editor(s) (if applicable) and The

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樓主: Capricious
51#
發(fā)表于 2025-3-30 08:32:12 | 只看該作者
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發(fā)表于 2025-3-30 15:33:32 | 只看該作者
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發(fā)表于 2025-3-30 18:47:38 | 只看該作者
Jingyu Huang,Chang Lin,Yuehui Wuibility in human-influenced habitats most commonly documented as dietary adjustments, and as differences in activity, ranging, grouping patterns and social organization. Historically, most publications have focused on conflictual or negative interactions between humans and wild primates and only rec
54#
發(fā)表于 2025-3-31 00:00:53 | 只看該作者
Eduardo A. Hinojosa-Palafox,Oscar M. Rodríguez-Elías,José A. Hoyo-Monta?o,Jesús H. Pacheco-Ramírez shows the relationship between a person’s attitudes toward animals and their gender, age, household income, education, pet ownership, as well as geographic region. However, research into the correlation between public attitudes toward animals and ethical ideologies is still in its infancy and needs
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發(fā)表于 2025-3-31 04:33:20 | 只看該作者
Bu Erma,Jinjing Lianimal ethics (and beyond). I will argue that both options have advantages and limits, and the choice depends on what one wants to do with the idea of moral status. In assessing the merits of each approach, I will critically discuss Singer’s equal consideration of interests principle, Regan’s egalit
56#
發(fā)表于 2025-3-31 05:35:16 | 只看該作者
Weiping Cui,Rongjia Song,Suxiu Li,Lei Huangibility in human-influenced habitats most commonly documented as dietary adjustments, and as differences in activity, ranging, grouping patterns and social organization. Historically, most publications have focused on conflictual or negative interactions between humans and wild primates and only rec
57#
發(fā)表于 2025-3-31 12:47:06 | 只看該作者
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發(fā)表于 2025-3-31 16:03:38 | 只看該作者
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發(fā)表于 2025-3-31 20:21:02 | 只看該作者
60#
發(fā)表于 2025-3-31 22:02:24 | 只看該作者
Optimizing Retraining of Multiple Recommendation Models, models consumes significant time. To selectively retrain only models where new and historical consumers differ, we estimate the distance between historical and new consumers including both categorical and numerical consumer attributes to determine when to retrain each of the recommendation models.
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