@brunowinck @codexeditor @alanlaidlaw When thinking about this, recall that in the second paragraph of The Mathematical Theory of Communication (University of Illinois Press, 1949), Claude Shannon explicitly separates the semantic meaning from the engineering problem of communication.
Backlinks in digital gardens, commonplace books, or wikis are just an abstract extension of the accounting concept of double-entry bookkeeping.
Pages 71-96 | Published online: 15 Apr 2008
Proto-organisms probably were randomly aggregated nets of chemical reactions. The hypothesis that contemporary organisms are also randomly constructed molecular automata is examined by modeling the gene as a binary (on-off) device and studying the behavior of large, randomly constructed nets of these binary “genes.” The results suggest that, if each “gene” is directly affected by two or three other “genes,” then such random nets: behave with great order and stability; undergo behavior cycles whose length predicts cell replication time as a function of the number of genes per cell; possess different modes of behavior whose number per net predicts roughly the number of cell types in an organism as a function of its number of genes; and under the stimulus of noise are capable of differentiating directly from any mode of behavior to at most a few other modes of behavior. Cellular differentiation is modeled as a Markov chain among the modes of behavior of a genetic net. The possibility of a general theory of metabolic behavior is suggested. Analytic approaches to the behavior of switching nets are discussed in Appendix 1, and some implications of the results for the origin of self replicating macromolecular systems is discussed in Appendix 6.
Hungarian biologist Tibor Gánti is an obscure figure. Now, more than a decade after his death, his ideas about how life began are finally coming to fruition.
Good to see Tibor Gánti finally getting some credit. This is a great little article with a nice overview of the Origin of Life problem (and references). The author Michael Marshall has a new book out on the topic.
The ergodic hypothesis is a key analytical device of equilibrium statistical mechanics. It underlies the assumption that the time average and the expectation value of an observable are the same. Where it is valid, dynamical descriptions can often be replaced with much simpler probabilistic ones — time is essentially eliminated from the models. The conditions for validity are restrictive, even more so for non-equilibrium systems. Economics typically deals with systems far from equilibrium — specifically with models of growth. It may therefore come as a surprise to learn that the prevailing formulations of economic theory — expected utility theory and its descendants — make an indiscriminate assumption of ergodicity. This is largely because foundational concepts to do with risk and randomness originated in seventeenth-century economics, predating by some 200 years the concept of ergodicity, which arose in nineteenth-century physics. In this Perspective, I argue that by carefully addressing the question of ergodicity, many puzzles besetting the current economic formalism are resolved in a natural and empirically testable way.
From the New York Times-bestselling author of How Not to Be Wrong, himself a world-class geometer, a far-ranging exploration of the power of geometry, which turns out to help us think better about practically everything
How should a democracy choose its representatives? How can you stop a pandemic from sweeping the world? How do computers learn to play chess, and why is learning chess so much easier for them than learning to read a sentence? Can ancient Greek proportions predict the stock market? (Sorry, no.) What should your kids learn in school if they really want to learn to think? All these are questions about geometry.
For real. If you're like most people, geometry is a sterile and dimly-remembered exercise you gladly left behind in the dust of 9th grade, along with your braces and active romantic interest in pop singers. If you recall any of it, it's plodding through a series of miniscule steps, only to prove some fact about triangles that was obvious to you in the first place. That's not geometry. OK, it is geometry, but only a tiny part, a border section that has as much to do with geometry in all its flush modern richness as conjugating a verb has to do with a great novel.
Shape reveals the geometry underneath some of the most important scientific, political, and philosophical problems we face. Geometry asks: where are things? Which things are near each other? How can you get from one thing to another thing? Those are important questions. The word geometry, from the Greek, has the rather grand meaning of measuring the world. If anything, that's an undersell. Geometry doesn't just measure the world - it explains it. Shape shows us how.
If you want to transfer a few hundred gigabytes of data, it’s generally faster to FedEx a hard drive than to send the files over the internet. This isn’t a new idea—it’s often dubbed SneakerNet—and it’s how Google transfers large amounts of data internally.
IT’S GETTING EASIER to secure your digital privacy. iPhones now encrypt a great deal of personal information; hard drives on Mac and Windows 8.1 computers are now automatically locked down; even Facebook, which made a fortune on open sharing, is providing end-to-end encryption in the chat tool WhatsApp. But none of this technology offers as much protection as you may think if you don’t know how to come up with a good passphrase.
To recognize strange extraterrestrial life and solve biological mysteries on this planet, scientists are searching for an objective definition for life’s basic units.
I’ve been following a bit of David’s work, but obviously there’s some newer material I need to catch up on. I like the general philosophical thrust of their direction here. I can see some useful abstractions to higher math here, maybe an analogy to a “calculus of biology” which doesn’t look at single points, but rates of change of that point(s).
Over recent years, new light has been shed on aspects of information processing in cells. The quantification of information, as described by Shannon’s information theory, is a basic and powerful tool that can be applied to various fields, such as communication, statistics, and computer science, as well as to information processing within cells. It has also been used to infer the network structure of molecular species. However, the difficulty of obtaining sufficient sample sizes and the computational burden associated with the high-dimensional data often encountered in biology can result in bottlenecks in the application of information theory to systems biology. This article provides an overview of the application of information theory to systems biology, discussing the associated bottlenecks and reviewing recent work.
Different quantities that go by the name of entropy are used in variational principles to infer probability distributions from limited data. Shore and Johnson showed that maximizing the Boltzmann-Gibbs form of the entropy ensures that probability distributions inferred satisfy the multiplication rule of probability for independent events in the absence of data coupling such events. Other types of entropies that violate the Shore and Johnson axioms, including nonadditive entropies such as the Tsallis entropy, violate this basic consistency requirement. Here we use the axiomatic framework of Shore and Johnson to show how such nonadditive entropy functions generate biases in probability distributions that are not warranted by the underlying data.
Zero-width characters are invisible, ‘non-printing’ characters that are not displayed by the majority of applications. For example, I’ve inserted 10 zero-width spaces into this sentence, can you tell? (Hint: paste the sentence into Diff Checker to see the locations of the characters!). These characters can be used to ‘fingerprint’ text for certain users.
A cool little trick with text for embedded steganography, security, or other communication purposes.
This could also be used for pseudo-private communication via Webmention even. Just hide your messages inside of public messages.