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Titlebook: Hip Arthrodesis and Associated Problems; René Liechti Book 1978 Springer-Verlag Berlin Heidelberg 1978 Hüftarthrodese.anatomy.anesthesia.b

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11#
發(fā)表于 2025-3-23 11:33:45 | 只看該作者
12#
發(fā)表于 2025-3-23 17:29:15 | 只看該作者
Complicationsent complications are PA and malposition. This is a consequence of the considerable biomechanical load placed on the arthrodesed hip and the technical difficulties encountered in adjusting the leg position correctly at operation.
13#
發(fā)表于 2025-3-23 21:26:16 | 只看該作者
14#
發(fā)表于 2025-3-24 01:00:01 | 只看該作者
ss to mitigate misinformation. Free and plural ideas are key to addressing misinformation and informing users. A key indicator of the healthy online ecosystem is the existence of diversity of ideas and others’ perspectives. Exposure to diverse sources of news promotes tolerance, social cohesion, and
15#
發(fā)表于 2025-3-24 03:23:31 | 只看該作者
the spread and amplification of misinformation, it is useful to understand the effects of these algorithms on misinformation sharing and the manner in which they spread it. This chapter examines the psychological, cognitive, and social factors involved in the processing of misinformation people rec
16#
發(fā)表于 2025-3-24 10:25:53 | 只看該作者
17#
發(fā)表于 2025-3-24 13:12:42 | 只看該作者
René Liechtised as humans are. Bias can originate from various venues, including but not limited to the design and unintended or unanticipated use of the algorithm or algorithmic decisions about the way data are coded, framed, filtered, or analyzed to train machine learning. Algorithmic bias has been widely see
18#
發(fā)表于 2025-3-24 18:46:31 | 只看該作者
René Liechtis to help steer users into fact-checking the information is much more effective than detecting misinformation. This chapter presents empirical work on the design of nudge interventions in the context of misinformation. Applying the nudge principle to misinformation, it suggests that different cognit
19#
發(fā)表于 2025-3-24 22:17:20 | 只看該作者
20#
發(fā)表于 2025-3-25 02:10:53 | 只看該作者
René Liechti, mainly because of i) insufficient analytical knowledge of the system to be controlled, and ii) because of incomplete knowledge of the physical parameters of the system..Neural networks can cope with these problems because of their capability to realize multivariate, nonlinear transformations and t
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