Investigation of the large Magnetocaloric effect through DFT and Monte Carlo simulations in Cu- substituted MnCoGe

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optimisation. Two ways to use them:

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When reviewing tracking data, look for patterns rather than obsessing over individual fluctuations. Is your visibility generally improving, declining, or stable? Which topics show stronger AI citation rates? Where are competitors consistently appearing instead of you? What queries used to show your content but no longer do? These patterns inform where to focus future optimization efforts and what's working well versus what needs adjustment.

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有一个我觉得很实用的小设计:转发内容之后紧接着发 // 你的评论,评论会自动合并到同一条笔记里,不用再去 Memo 里面单独编辑。飞书上直接回复消息(有 parent_id)也会自动视为评论,连 // 都不用打。系统有一个 10 秒的聚合器超时,在这个窗口内发的评论都会合并到一起。