Fight for your life 生命的奇迹

抗癌之路:自我照料的力量
一位女性癌症患者通过积极的生活方式调整,包括合理膳食、适量运动及充足睡眠等自我照料措施,成功战胜了疾病。本文探讨了这些行为如何帮助她提高了治疗效果。
I often point out the importance of taking care of oneself. I recently visited with a woman for whom it was a matter of survival. She had a cancer arising from the throat and participated in an aggressive program involving daily radiation for six weeks in conjunction with weekly chemotherapy. The side effects of this treatment can be devastating in terms of weakness, fatigue and a decrease in quality of life. The patient lived close enough to our facility that she could have driven in each day. However, she had the insight to shift the odds in her favor and do everything possible for a cure.

She resigned her academic positions. She told her husband and young family, "I love you, but you're on your own because I'm in the greatest fight of my life." She rented a room in a hotel near the treatment facility, ordered nutritious meals, worked out as she was able, and focused on getting at least eight to 10 hours of sleep a night.

As of the last checkup, the patient appears to be cancer free. Which of these actions saved her life? I don't know, but I do know that she maximized the healing potential of treatment by taking care of herself.

Likewise, when you are injured or tired, when you anticipate a stressful time in your life, a light bulb should go on reminding you to: slow down, focus and eliminate distractions.

What did I miss? What advice do you have to share?




参考译文:
我常提到健康的重要性。近日我与一个妇人谈及健康。对她来说这是关乎生死的话题。她是一名癌症患者,曾连续六周接受放射性治疗和化疗。这种疗法的的副作用是毁灭性的,表现为体质虚弱,疲乏无力,和生命衰减。那时我们住得很近,可以随时来往。她洞悉一切般的改变了自己的生活,并为治疗做着一切准备。

首先她辞去了在学院的职位,告诉她的丈夫和家人说,“我爱你们,但是你们要靠自己了,因为我正在为我的人生全力以赴。”然后她在治疗中心附近的旅馆租了一所房子。接下来的日子她订了营养丰富的饮食,如同健康人一样参加工作,每天睡8到10个小时。

最后一次检查发现,这个病人竟然痊愈了。我不清楚到底是哪个环节救了她, 但我知道,她通过好好照顾自己,把治愈的可能性最大化了。

同样的道理,在你疲惫或受伤,当你充满压力的时候,你应该灵光一现:减速,集中精神,并且消除焦虑。

我还有什么遗漏了吗?你还有建议一起分享吗?

基于数据驱动的 Koopman 算子的递归神经网络模型线性化,用于纳米定位系统的预测控制研究(Matlab代码实现)内容概要:本文围绕“基于数据驱动的Koopman算子的递归神经网络模型线性化”展开,旨在研究纳米定位系统的预测控制问题,并提供完整的Matlab代码实现。文章结合数据驱动方法与Koopman算子理论,利用递归神经网络(RNN)对非线性系统进行建模与线性化处理,从而提升纳米级定位系统的精度与动态响应性能。该方法通过提取系统隐含动态特征,构建近似线性模型,便于后续模型预测控制(MPC)的设计与优化,适用于高精度自动化控制场景。文中还展示了相关实验验证与仿真结果,证明了该方法的有效性和先进性。; 适合人群:具备一定控制理论基础和Matlab编程能力,从事精密控制、智能制造、自动化或相关领域研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①应用于纳米级精密定位系统(如原子力显微镜、半导体制造设备)中的高性能控制设计;②为非线性系统建模与线性化提供一种结合深度学习与现代控制理论的新思路;③帮助读者掌握Koopman算子、RNN建模与模型预测控制的综合应用。; 阅读建议:建议读者结合提供的Matlab代码逐段理解算法实现流程,重点关注数据预处理、RNN结构设计、Koopman观测矩阵构建及MPC控制器集成等关键环节,并可通过更换实际系统数据进行迁移验证,深化对方法泛化能力的理解。
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