SIAM Review, Volume 66, Issue 3, Page 605-615, May 2024.
The theme of this collection of book reviews is arguably about the “usefulness” of mathematics, or how we can try to understand aspects of our world by developing mathematical or data-driven models. Thus, it is fitting that our featured review is written by John Stillwell, on the book Why Does Math Work . . . If It's Not Real?, written by Dragan Radulović. Stillwell characterizes the book as “an offbeat and entertaining take on the mystery that Eugene Wigner famously called the `unreasonable effectiveness of mathematics.'” I haven't read the book, so I can't say if it is as “enjoyable and thought-provoking” as the reviewer says it is. But the review is lively and entertaining, that I can vouch for. Perhaps just to showcase the usefulness of mathematics, our next book, reviewed by me, is An Invitation to Mathematical Biology, written by David G. Costa and Paul J. Schulte. As I note in the review, the book's title, which says “Invitation” and not the typical “Introduction,” is a clue to what the book is about: making math biology less scary to undergraduate biology majors, while at the same time gently guiding them to dive deeper in some topics. With the advancement of computational and sequencing methods, a large amount of biological data is generated. Dealing with complex biological networks and extracting the meaningful picture requires new approaches. One such approach is systems biology. Whch brings us to the next review, by Herbert M. Sauro, on Systems Biology: Modelling, Analysis, and Simulation, by Jinzhi Lei. Systems biology is a fast-growing field, and Lei's book is one of several texts in the area published in recent years, with a focus on gene regulatory networks. Systems biology is a data-driven approach, and data is what the next book is about. High-Dimensional Data Analysis with Low-Dimensional Models, by John Wright and Yi Ma, is reviewed by one of our associate editors, Alfio Borzí. Alfio lays out rather clearly in his review what you can learn from this book, and he concludes that it would serve well for him as “a companion text while doing research and teaching in the field of data analysis with low-dimensional models.” The next two books focus on methodologies. Tim Hoheisel reviews An Optimization Primer, authored by Johannes O. Royset and Roger J.-B. Wets. With the explosive growth of machine learning and artificial intelligence applications, optimization has received increasingly more and more attention. A search for recently published books with the word “optimization” in their titles returned pages and pages of results. Hoheisel's review will give you a clue to how this book compares with its many alternatives. Circling back to the “usefulness” of mathematics. Most of the books reviewed so far focus on biology. Our last review can show you that math has applications aplenty in other fields. Abdon Atangana reviews Mathematical Modelling, by Simon Serovajsky. The book covers applications of math modeling in physics, engineering, chemistry, biology, medicine, economics, ecology, sociology, psychology, political science, and so on.

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 书评


《SIAM 评论》，第 66 卷，第 3 期，第 605-615 页，2024 年 5 月。

这本书评集的主题可以说是关于数学的“用处”，或者我们如何通过开发数学或数据驱动的模型来尝试理解我们世界的各个方面。因此，我们的专题评论是由约翰·斯蒂尔韦尔（John Stillwell）在《数学为何有效》一书中撰写的，这是很合适的。 。 。如果这不是真的？，德拉甘·拉杜洛维奇 (Dragan Radulović) 撰写。斯蒂尔韦尔将这本书描述为“对尤金·维格纳著名的‘数学的不合理有效性’之谜的另类和有趣的诠释。”我还没有读过这本书，所以我不能说它是否是“令人愉快和思考的”正如评论家所说，“令人发指”。但我可以保证，评论是生动有趣的。也许只是为了展示数学的有用性，我审阅的下一本书是《数学生物学的邀请》，作者是大卫·G·科斯塔 (David G. Costa) 和保罗·J·舒尔特 (Paul J. Schulte)。正如我在评论中指出的那样，这本书的标题是“邀请”而不是典型的“引言”，这是这本书的内容的线索：让数学生物学对生物学专业的本科生来说不那么可怕，同时温和地引导他们更深入地研究某些主题。随着计算和测序方法的进步，产生了大量的生物数据。处理复杂的生物网络并提取有意义的图像需要新的方法。其中一种方法是系统生物学。这给我们带来了 Herbert M. Sauro 的下一篇评论，作者是 Jinzhi Lei，其关于系统生物学：建模、分析和模拟。系统生物学是一个快速发展的领域，雷的书是该领域近年来出版的几本著作之一，重点关注基因调控网络。系统生物学是一种数据驱动的方法，而数据就是下一本书的主题。 John Wright 和 Yi Ma 所著的《使用低维模型进行高维数据分析》由我们的副编辑之一 Alfio Borzí 审阅。阿尔菲奥在他的评论中相当清楚地列出了你可以从这本书中学到什么，他的结论是，这本书非常适合他作为“在低维模型数据分析领域进行研究和教学时的配套文本”。接下来的两本书重点讨论方法论。 Tim Hoheisel 评论了 Johannes O. Royset 和 Roger J.-B 撰写的《优化入门》。湿。随着机器学习和人工智能应用的爆炸式增长，优化越来越受到人们的关注。搜索标题中包含“优化”一词的最近出版的书籍会返回一页又一页的结果。 Hoheisel 的评论将为您提供线索，让您了解本书与众多其他书籍的比较情况。回到数学的“用处”。到目前为止，大多数评论的书籍都集中在生物学上。我们的上一篇评论可以向您展示数学在其他领域的广泛应用。 Abdon Atangana 评论了 Simon Serovajsky 所著的《数学建模》。本书涵盖了数学建模在物理、工程、化学、生物学、医学、经济学、生态学、社会学、心理学、政治学等领域的应用。