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We have started a reading Roger Penrose: The Road to Reality which so far is a subperp book. Normally we Skype-meet Tuesday morning AM 6.30 for 60-90 minutes. We normally cover 20-40 pages per session. In coming week we will have done 5 chapters:
1 The roots of science
2 An ancient theorem and a modern question
3 Kinds of number in the physical world
4 Magical complex numbers
5 Geometry of logarithms, powers, and roots
In Jotun’s view the book is great balance for formulas, intuitive explanations and historical backgrounds.
Today we turned the last page on John Maynard Keynes: General Theory. It has been an extremely impenetrable book: There is hardly any data and the formulas that are there are very simple and not central to the main arguments. I hope to arrange that we can meet with an economist (Sophocles Mavroides) a couple weeks from now. We will each suggest 2 books for what to go through next. Since reading Keynes didn’t make me understand of the overall economy has not increased a lot, so I am keen to study a more modern work with both theory and data analysis. I myself went through 2 very large papers by Mavroides that he then explained to me, which was very rewarding for me. One was on identifiability of a set of dynamics models for macroeconomics and the second was on fitting the New Keynes Philips Curve [NKPC] to economic data for the last 60 years. The Philips Curve was originally an empirical observation of reciprocicity of the levels of inflation and employment. These papers contained much of what I missed in Keynes: Data and Theory.
However, my co-readers felt they had had Economics enough for now. I intend to suggest these two for next readings:
Jotun1: Noam Chomsky (1965) Aspects of the Theory of Syntax
Chomsky is a towering intellect and I read 1 longer 1955 grammar paper and it could be the best paper I have ever read. A larger summary of this theory would be very rewarding to read and it is about 200 pages.
Jotun2: I would not suggest a book but rather to go through 10 Nobel Lectures by key economists doing 2 lectures at each meeting. I recently read 3 2013 Nobel lectures in Chemistry by the Karplus, Levitt and Washell and they were an absolute ideal introduction to the history and problems of Molecular Dynamics. So now I suggest the same for economics and it could be these laurates: Friederich Hayek, Leonid Kantorovich, Paul Samuelson, Milton Friedman, John Nash, Daniel Kahneman, Paul Krugman, Scholes, Stieglitz and Amartya Sen. This could be done in 5 meetings lastting 3+ months.
In general this Book Should:
- Read things I would/could not have read otherwise.
and the actual books fall into 2 topics:
I. Current Affairs: Global Warming, Immigration Studies, What is Democracy, The Cause of Conflicts, Theories of Religion, Understanding the Economy, Conceptual Foundation of Political Ideologies, … I rather want to read 3-500 pages of good overview, than a lot of daily news
II. Real Classics: Spinoza, Kant, Hegel, Hume, Global Sacred texts,…
2. I think too long books takes too much time. Ideally 2-300 pages, max 500.
3. I think it is a good idea to put possible books in Dropbox so we can pre-view them before buying them.
Next meeting of the Classic papers discussion group will take place next Wednesday (1 Feb. 2017) at 9:30 in the Department of Statistics room LG.05. We will be discussing a modern classic: Why Most Published Research Findings Are False by John P. A. Ioannidis. All participants are welcome (just talk to the receptionist when you arrive if you don’t have building access, she should let you in)
Link to the paper: http://dx.doi.org/10.1371/journal.pmed.0020124
Since its publication, the paper has lead to widespread debate within science about the extent of the problem of irreproducibility: how widespread it is, and what to do about it. Given the central importance of this paper within those debates, as well as the various reproducibility-studies it has spawned, we deem this paper well worth reading, and hope that many people will show up to discuss it with us.
The aim of this club is to read the papers that everyone keeps citing but which few people have read. We plan to read a paper every third week for the next 20 years.
We tend to meet Wednesday mornings, and tend to announce the papers we will read ahead of time. Everyone is welcome: if a paper sounds interesting to you, please come by.
This reading group used to be organised on facebook. The old page can be found here.
- Mathematical Chemistry and Chemoinformatics, by A. Kerber et al. (summary part I and part II)
- Phylogeny: Discrete and random processes in evolution, by M. Steel (review published on SIAM News Blog: part I, part II, part III)
- Bayesian Methods in Structural Bioinformatics, edited by
T. Hamelryck, K. Mardia and J. Ferkinghoff-Borg
Phylogenetics, by C. Semple and M. A. Steel
- Protein Physics – A course of lectures, by A. V. Finkelstein and O. Ptitsyn (summary slides)
This book club is an endeavour to broaden our horizons and critically engage with good writing from across the humanities. We intend to go through a book per term, and tend to meet roughly once every 3rd week to discuss new sections of whatever book we are currently going through. Past books that we have read include:
- The General Theory of Employment, Interest and Money, by John Maynard Keynes
- The Qurʼān – A New Annoteted Translation, by Arthur J. Droge
- On Politics, by Alan Ryan
- Capital in the Twenty-First Century, by Thomas Piketty
Summary of the paper “The Graph Grammar Library – a generic framework for chemical graph rewrite systems” by Flamm et al.
The paper explains how a C++ package works, which implements graph grammar rewriting rules for chemical reaction networks. There are some other chem(o)informatics stuff in the package as well.
The main story of the paper is that Yadav et al. requested a package like GGL, which is now available.
Most of it seems quite logical/intuitive based on the what it tries to do.
The software translates to/from SMILES at the beginning and end, but everything is done using graphs.
For more information and guides on how to use the software, see: http://www.tbi.univie.ac.at/software/GGL/