The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to the level of consciousness. IIT proposes that, to quantify information integration in a system as a whole, integrated information should be measured across the partition of the system at which information loss caused by partitioning is minimized, called the Minimum Information Partition (MIP). The computational cost for exhaustively searching for the MIP grows exponentially with system size, making it difficult to apply IIT to real neural data. It has been previously shown that, if a measure of Φ satisfies a mathematical property, submodularity, the MIP can be found in a polynomial order by an optimization algorithm. However, although the first version of Φ is submodular, the later versions are not. In this study, we empirically explore to what extent the algorithm can be applied to the non-submodular measures of Φ by evaluating the accuracy of the algorithm in simulated data and real neural data. We find that the algorithm identifies the MIP in a nearly perfect manner even for the non-submodular measures. Our results show that the algorithm allows us to measure Φ in large systems within a practical amount of time.
QUANTUM gravitational effects are usually ignored in calculations of the formation and evolution of black holes. The justification for this is that the radius of curvature of space-time outside the event horizon is very large compared to the Planck length (Għ/c3)1/2 ≈ 10−33 cm, the length scale on which quantum fluctuations of the metric are expected to be of order unity. This means that the energy density of particles created by the gravitational field is small compared to the space-time curvature. Even though quantum effects may be small locally, they may still, however, add up to produce a significant effect over the lifetime of the Universe ≈ 1017 s which is very long compared to the Planck time ≈ 10−43 s. The purpose of this letter is to show that this indeed may be the case: it seems that any black hole will create and emit particles such as neutrinos or photons at just the rate that one would expect if the black hole was a body with a temperature of (κ/2π) (ħ/2k) ≈ 10−6 (M⊙/M)K where κ is the surface gravity of the black hole1. As a black hole emits this thermal radiation one would expect it to lose mass. This in turn would increase the surface gravity and so increase the rate of emission. The black hole would therefore have a finite life of the order of 1071 (M⊙/M)−3 s. For a black hole of solar mass this is much longer than the age of the Universe. There might, however, be much smaller black holes which were formed by fluctuations in the early Universe2. Any such black hole of mass less than 1015 g would have evaporated by now. Near the end of its life the rate of emission would be very high and about 1030 erg would be released in the last 0.1 s. This is a fairly small explosion by astronomical standards but it is equivalent to about 1 million 1 Mton hydrogen bombs.
In honor of pi day and the passing of Stephen Hawking, here’s one of his seminal papers published just before I was born.Syndicated copies to:
There's a new upper class that's completely disconnected from the average American and American culture at large, says Charles Murray. Take this 25-question quiz to find out just how thick your bubble is.
I’m not one for quizzes, but I’ve scored a 66 on this–on the far side of being stuck in a bubble apparently. I’m glad I can manage to see many sides of our culture.Syndicated copies to:
Social media can be a double-edged sword for modern communications, either a convenient channel exchanging ideas or an unexpected conduit circulating fake news through a large population. Existing studies of fake news focus on efforts on theoretical modelling of propagation or identification methods based on black-box machine learning, neglecting the possibility of identifying fake news using only structural features of propagation of fake news compared to those of real news and in particular the ability to identify fake news at early stages of propagation. Here we track large databases of fake news and real news in both, Twitter in Japan and its counterpart Weibo in China, and accumulate their complete traces of re-posting. It is consistently revealed in both media that fake news spreads distinctively, even at early stages of spreading, in a structure that resembles multiple broadcasters, while real news circulates with a dominant source. A novel predictability feature emerges from this difference in their propagation networks, offering new paths of early detection of fake news in social media. Instead of commonly used features like texts or users for fake news identification, our finding demonstrates collective structural signals that could be useful for filtering out fake news at early stages of their propagation evolution.
How President Trump threw aside caution and agreed to meet with North Korea’s Kim Jong-un in a daring and risky diplomatic gambit to end a nuclear standoff.
It kills me that a year and change in, they still can’t get their act together to coordinate major moves like this. Our country is not a race car that stops on a dime or turns very quickly. Trump may want it to, but it’s not going to do it easily. He’s also likely to destroy a lot of value in our economies by playing bull in the china shop.
I’m still astounded that he’s managed to keep any businesses afloat when making snap decisions like this. It’s really his family’s incredible wealth that in large part has prevented him from reverting to the mean over his lifetime. I can only imagine what additional damage he might do if he actually had any executive capabilities.
If I were his Secretary of State, I’d be resigning and then doing some additional speaking out of school.Syndicated copies to:
Text, as the Hypothesis annotation client understands it, is HTML, or PDF transformed to HTML. In either case, it’s what you read in a browser, and what you select when you make an annotation. What’s the equivalent for audio and video? It’s complicated because although browsers enable us to select passages of text, the standard media players built into browsers don’t enable us to select segments of audio and video. It’s trivial to isolate a quote in a written document. Click to set your cursor to the beginning, then sweep to the end. Now annotation can happen. The browser fires a selection event; the annotation client springs into action; the user attaches stuff to the selection; the annotation server saves that stuff; the annotation client later recalls it and anchors it to the selection. But selection in audio and video isn’t like selection in text. Nor is it like selection in images, which we easily and naturally crop. Selection of audio and video happens in the temporal domain. If you’ve ever edited audio or video you’ll appreciate what that means. Setting a cursor and sweeping a selection isn’t enough. You can’t know that you got the right intro and outro by looking at the selection. You have to play the selection to make sure it captures what you intended. And since it probably isn’t exactly right, you’ll need to make adjustments that you’ll then want to check, ideally without replaying the whole clip.
Jon Udell has been playing around with media fragments to create some new functionality in Hypothes.is. The nice part is that he’s created an awesome little web service for quickly and easily editing media fragments online for audio and video (including YouTube videos) which he’s also open sourced on GitHub.
I suspect that media fragments experimenters like Aaron Parecki, Marty McGuire, Kevin Marks, and Tantek Çelik will appreciate what he’s doing and will want to play as well as possibly extend it. I’ve already added some of the outline to the IndieWeb wiki page for media fragments (and a link to fragmentions) which has some of their prior work.
I too look forward to a day where web browsers have some of this standardized and built in as core functionality.
Highlights, Quotes, & Marginalia
This selection tool has nothing intrinsically to do with annotation. It’s job is to make your job easier when you are constructing a link to an audio or video segment.
(If I were Virginia Eubanks I might want to capture the pull quote myself, and display it on my book page for visitors who aren’t seeing it through the Hypothesis lens.)
Of course, how would she know that the annotation exists? Here’s another example of where adding webmentions to Hypothesis for notifications could be useful, particularly when they’re more widely supported. I’ve outlined some of the details here in the past: http://boffosocko.com/2016/04/07/webmentions-for-improving-annotation-and-preventing-bullying-on-the-web/Syndicated copies to:
In a new study at the University of Wisconsin-Madison, we look at how often, and in what context, Twitter accounts from the Internet Research Agency—a St. Petersburg-based organization directed by individuals with close ties to Vladimir Putin, and subject to Mueller’s scrutiny—successfully made their way from social media into respected journalistic media. We searched the content of 33 major American news outlets for references to the 100 most-retweeted accounts among those Twitter identified as controlled by the IRA, from the beginning of 2015 through September 2017. We found at least one tweet from an IRA account embedded in 32 of the 33 outlets—a total of 116 articles—including in articles published by institutions with longstanding reputations, like The Washington Post, NPR, and the Detroit Free Press, as well as in more recent, digitally native outlets such as BuzzFeed, Salon, and Mic (the outlet without IRA-linked tweets was Vice).
How are outlets publishing generic tweets without verifying the users actually exist? This opens up a new type of journalistic fraud in which a writer could keep an army of bots and feed out material that they could then self-quote for their own needs without a story really existing.Syndicated copies to:
A summer school for advanced undergraduates June 11-22, 2018 @ Princeton University What would it mean to have a physicist’s understanding of life? How do DYNAMICS and the EMERGENCE of ORDER affect biological function? How do organisms process INFORMATION, LEARN, ADAPT, and EVOLVE? See how physics problems emerge from thinking about developing embryos, communicating bacteria, dynamic neural networks, animal behaviors, evolution, and more. Learn how ideas and methods from statistical physics, simulation and data analysis, optics and microscopy connect to diverse biological phenomena. Explore these questions, tools, and concepts in an intense two weeks of lectures, seminars, hands-on exercises, and projects.