Nosimpler

Author: Beverly A. Purnell

Apparently.  Heather Sarsons has a paper on this phenomenon (pdf), the abstract is this:

Within academia, men are tenured at higher rates than women are in most quantitative fields, including economics. Researchers have attempted to identify the source of this disparity but find that nearly 30% of the gap remains unexplained even after controlling for family commitments and differences in productivity. Using data from academic economists’ CVs, I test whether coauthored and solo-authored publications matter differently for tenure for men and women. While solo-authored papers send a clear signal about one’s ability, coauthored papers are noisy in that they do not provide specific information about each contributor’s skills. I find that men are tenured at roughly the same rate regardless of whether they coauthor or solo-author. Women, however, suffer a significant penalty when they coauthor. The results hold after controlling for the total number of papers published, quality of papers, field of study, tenure institution, tenure year, and the number of years it took an individual to go up for tenure. The result is most pronounced for women coauthoring with only men and is less pronounced the more women there are on a paper, suggesting that some gender bias is at play. I present a model in which bias enters when workers collaborate and test its predictions in the data.

See also this very interesting paper on “Confidence Men,” in economic science, women seem to have more epistemic modesty than men.

Hat tip goes to Dina Pomeranz.

Same-sex sexual behavior is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here I suggest the possibility that same-sex sexual behavior arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a species, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. A simple analytical "toy model" is proposed for describing this tradeoff. The model exhibits a number of interesting features, and suggests a simple mathematical form for describing the sexual orientation continuum.

Microexpressions reveal your deepest emotions, even when you are trying to hide them. Now a machine vision algorithm has learned to spot them, with wide-ranging applications from law enforcement to psychological analysis.

Most people are good at recognizing the ordinary emotions on other people’s faces. But there are another set of facial expression that most people are almost entirely unaware of. In the late 1960s, psychologists discovered that when humans try to hide their emotions, they often display their real feelings in “microexpressions” that appear and disappear in the blink of an eye.

I spent 14 years on the faculty at the University of Chicago. I know László Babai well, we collaborated on some of my best known work. I also know Ryerson 251, a room where I've seen hundreds of talks and given more than a few myself. So I could imagine the excitement in that room on Tuesday as Babai gave the most anticipated talk in the history of theoretical computer science, the first of several talks Babai is giving on his new algorithm for graph isomorphism [Video]. Gabriel Gaster extensively live tweeted the event. Jeremy Kun has some details. Update (12/14): Paper now posted.

For this post instead of doing a bad job trying to overview Babai's proof, I'll explain the graph isomorphism problem and why it is important in the complexity world.

Suppose we have two high schools, say HS North and HS South, each with 1000 students. Consider a diagram (or graph) containing a point for each student at HS North with lines between students who are facebook friends, and a similar diagram for HS South. Is there a 1-1 map from the students at HS North to the students at HS South so that these diagrams look identical? That's the graph isomorphism problem.

To determine whether these two graphs were isomorphic you could look at all the possible mappings between students, but that's 1000! or more than 4x10²⁵⁶⁷ possible maps. There has long been known how to search a smaller number of possibilities, especially if we put some restrictions on the diagrams, but always exponential in n (the number of students) in the worst case. Ideally we'd like a polynomial-time algorithm and Babai gets very close, an algorithm that runs in time n^logkn time for some fixed k.

Graph Isomorphism is one of those few problems, like factoring, known to be in NP but not known to be in P or NP-complete. Graph non-isomorphism is the poster child for the class AM, the problems solved by a randomized verifier asking a single question to a powerful prover. Graph non-isomorphism in AM implies that Graph Isomorphism is not likely NP-complete and that under reasonable derandomization assumptions that Graph non-isomorphism is in NP. Kobler, Schöning and Toran wrote a whole book on the computational complexity issues of graph isomorphism.

Even small progress in graph isomorphism creates waves. At a theory conference in the late 80's a speaker caused a major stir when he casually mentioned he had a proof (he didn't) that Graph non-isomorphism was in NP. Babai's announced caused a huge tsunami and those of us who know him realize he wouldn't make such an announcement without being sure he has a proof. The talk put together a large number of ideas from combinatorics and graph theory. My impression is that those who saw the talk didn't leave convinced of the proof, but did feel Babai had found the pieces to make it work.

With Babai's breakthrough algorithm, the smart money says now that graph isomorphism sits in P. It took decades to get from quasipolynomial time to polynomial time for primality testing and the same time frame may be needed to get polynomial time for graph isomorphism. But it will likely happen and the complexity of graph isomorphism then gets a whole lot simpler.

A couple of thoughts: All the breakthrough results that I can remember were released as papers, ready to devour. This is the first result of this caliber I remember being announced as a talk.

Also we think of theory as a young person's game, most of the big breakthroughs coming from researchers early in their careers. Babai is 65, having just won the Knuth Prize for his lifetime work on interactive proofs, group algorithms and communication complexity. Babai uses his extensive knowledge of combinatorics and group theory to get his algorithm. No young researcher could have had the knowledge base or maturity to be able to put the pieces together the way that Babai did.

More on Babai and graph isomorphism from Scott, Luca, Bill, Tim, Dick and Ken, Reddit, Science News, New Scientist and Science.

You’ve probably heard of Lawvere’s Hegelian taco. Now here is a paper that introduces the burrito to category theorists:

• Ed Morehouse, Burritos for the hungry mathematician.

The source of its versatility and popularity is revealed:

To wit, a burrito is just a strong monad in the symmetric monoidal category of food.

Frankly, having seen plenty of attempts to explain monads to computer scientists, I thought this should have been marketed as ‘monads for chefs’. But Mike Stay, who pointed me to this article, explained its subtext:

Haskell uses monads all over the place, and programmers who are not used to functional programming often find them confusing. This is a quote from a widely-shared article on the proliferation of “monad tutorials”:

After struggling to understand them for a week, looking at examples, writing code, reading things other people have written, he finally has an “aha!” moment: everything is suddenly clear, and Joe Understands Monads! What has really happened, of course, is that Joe’s brain has fit all the details together into a higher-level abstraction, a metaphor which Joe can use to get an intuitive grasp of monads; let us suppose that Joe’s metaphor is that Monads are Like Burritos. Here is where Joe badly misinterprets his own thought process: “Of course!” Joe thinks. “It’s all so simple now. The key to understanding monads is that they are Like Burritos. If only I had thought of this before!” The problem, of course, is that if Joe HAD thought of this before, it wouldn’t have helped: the week of struggling through details was a necessary and integral part of forming Joe’s Burrito intuition, not a sad consequence of his failure to hit upon the idea sooner.

The article is this:

• Brent Yorgey, Abstraction, intuition, and the “monad tutorial fallacy”, January 12, 2009.

If only I'd been smart enough to start a Ted Cruz Super PAC.

The super PACs backing Sen. Ted Cruz’s presidential run have yet to reserve any TV time in the early primary states — or anywhere else — despite a combined $38 million war chest that ranks second among presidential contenders only to Jeb Bush’s $103 million operation.

The total absence of ads has created confusion and growing consternation inside the Cruz campaign, which cannot legally communicate with its allied super PACs and has had to watch as its rivals lock in tens of millions of dollars in ads before prices spike, as they typically do as elections near.

So funny.

A man dubbed the Drone Slayer for shooting a miniature aircraft out of the sky has had a criminal case against him thrown out.

William Meredith drew his shotgun and took out a Phantom 3 drone after spotting it above his home in Hillview, Kentucky, this summer – landing him in jail and prompting legal proceedings.

Mr Meredith was charged with criminal mischief and wanton endangerment for destroying the $900 drone in July – but this week had both of them thrown out by a judge.

Izabella Laba, a noted mathematician at the University of British Columbia, recently posted some tweets that used me as a bad, cautionary example for how “STEM faculty should be less contemptuous of social sciences.”  Here was the offending comment of mine, from the epic Walter Lewin thread last fall:

[W]hy not dispense with the empirically-empty notion of “privilege,” and just talk directly about the actual well-being of actual people, or groups of people?  If men are doing horrific things to women—for example, lashing them for driving cars, like in Saudi Arabia—then surely we can just say so in plain language.  Stipulating that the torturers are “exercising their male privilege” with every lash adds nothing to anyone’s understanding of the evil.  It’s bad writing.  More broadly, it seems to me that the entire apparatus of “privilege,” “delegitimation,” etc. etc. can simply be tossed overboard, to rust on the ocean floor alongside dialectical materialism and other theoretical superstructures that were once pompously insisted upon as preconditions of enlightened social discourse.  This isn’t quantum field theory.  Ordinary words will do.

Prof. Laba derisively commented:

Might as well ask you to explain calculus without using fancy words like “derivative” or “continuous.”  Simple number arithmetic will do.

Prof. Laba’s tweets were favorited by Jordan Ellenberg, a mathematician who wrote the excellent popular book How Not to Be Wrong.  (Ellenberg had also criticized me last year for my strange, naïve idea that human relations can be thought about using logic.)

Given my respect for the critics, I guess I’m honor-bound to respond.

For the record, I tend not to think about the social sciences—or for that matter, the natural sciences—as monolithic entities at all.  I admire any honest attempt to discover the truth about anything.  And not being a postmodern relativist, I believe there are deep truths worth discovering in history, psychology, economics, linguistics, possibly even sociology.  Reading the books of Steven Pinker underscored for me how much is actually understood nowadays about human nature—much of it only figured out within the last half-century.  Likewise, reading the voluminous profundities of Scott Alexander taught me that even in psychiatry, there are truths (and even a few definite cures) to be had for those who seek.

I also believe that the social sciences are harder—way harder—than math or physics or CS.  They’re harder because of the tenuousness of the correlations, because of the complexity of each individual human brain (let alone 7 billion of them on the same planet), but most of all, because politics and ideology and the scientist’s own biases place such powerful thumbs on the scale.  This makes it all the more impressive when a social scientist, like (say) Stanley Milgram or Judith Rich Harris or Napoleon Chagnon, teaches the world something important and new.

I will confess to contempt for anything that I regard as pompous obscurantism—for self-referential systems of jargon whose main purposes are to bar outsiders, to mask a lack of actual understanding, and to confer power on certain favored groups.  And I regard the need to be alert to such systems, to nip them in the bud before they grow into Lysenkoism, as in some sense the problem of intellectual life.  Which brings me to the most fundamental asymmetry between the hard and soft sciences.  Namely, the very fact that it’s so much harder to nurture new truths to maturity in the social sciences than it is in math or physics, means that in the former, the jargon-weeds have an easier time filling the void—and we know they’ve done it again and again, even in the post-Enlightenment West.

Time for a thought experiment.  Suppose you showed up at a university anytime between, let’s say, 1910 and 1970, and went from department to department asking (in so many words): what are you excited about this century?  Where are your new continents, what’s the future of your field?  Who should I read to learn about that future?

In physics, the consensus answer would’ve been something like: Planck, Einstein, Bohr, Schrödinger, Dirac.

In psychology, it would’ve been: Freud and Jung (with another faction for B. F. Skinner).

In politics and social sciences, over an enormous swath of academia (including in the West), it would’ve been: Marx, Engels, Trotsky, Lenin.

With hindsight, we now know that the physics advice would’ve been absolute perfection, the psychology and politics advice an unmitigated disaster.  Yes, physicists today know more than Einstein, can even correct him on some points, but the continents he revealed to us actually existed—indeed, have only become more important since Einstein’s time.

But Marx and Freud?  You would’ve done better to leave the campus, and ask a random person on the street what she or he thought about economics and psychology.  In high school, I remember cringing through a unit on the 1920s, when we learned about how “two European professors upset a war-weary civilization’s established certainties—with Einstein overturning received wisdom about space and time, and Freud doing just the same for the world of the mind.”  It was never thought important to add that Einstein’s theories turned out to be true while Freud’s turned out to be false.  Still, at least Freud’s ideas led “only” to decades of bad psychology and hundreds of innocent people sent to jail because of testimony procured through hypnosis, rather than to tens of millions of dead, as with the other social-scientific theory that reigned supreme among 20^th-century academics.

Marx and Freud built impressive intellectual edifices—sufficiently impressive for a large fraction of intellectuals to have accepted those men as gurus on par with Darwin and Einstein for almost a century.  Yet on nearly every topic they wrote about, we now know that Marx and Freud couldn’t have been any more catastrophically wrong.  Moreover, their wrongness was knowable at the time—and was known to many, though the ones who knew were typically the ones who the intellectual leaders sneered at, as deluded reactionaries.

Which raises a question: suppose that, in the 1920s, I’d taken the social experts’ advice to study Marx and Freud, didn’t understand much of what they said (and found nonsensical much of what I did understand), and eventually rejected them as pretentious charlatans.  Then why wouldn’t I have been just like Prof. Laba’s ignorant rube, who dismisses calculus because he doesn’t understand technical terms like “continuous” and “derivative”?

On reflection, I don’t think that the two cases are comparable at all.

The hard sciences need technical vocabularies for a simple reason: because they’re about things that normal people don’t spend their hours obsessively worrying about.  Yes, I’d have a hard time understanding organic chemists or differential geometers, but largely for the same reasons I’d have a hard time understanding football fans or pirates.  It’s not just that I don’t understand the arguments; it’s that the arguments are about a world that’s alien to me (and that, to be honest, I don’t care about as much as I do my world).

Suppose, by contrast, that you’re writing about the topics everyone spends their time obsessively worrying about: politics, society, the human mind, the relations between the races and sexes.  In other words, suppose you’re writing about precisely the topics for which the ordinary English language has been honed over centuries—for which Shakespeare and Twain and Dr. King and so many others deployed the language to such spectacular effect.  In that case, what excuse could you possibly have to write in academese, to pepper your prose with undefined in-group neologisms?

Well, let’s be charitable; maybe you have a reason.  For example, maybe you’re doing a complicated meta-analysis of psychology papers, so you need to talk about r-values and kurtosis and heteroskedasticity.  Or maybe you’re putting people in an fMRI machine while you ask them questions, so you need to talk about the temporal resolution in the anterior cingulate cortex.  Or maybe you’re analyzing sibling rivalries using game theory, so you need Nash equilibria.  Or you’re picking apart sentences using Chomskyan formal grammar.  In all these cases, armchair language doesn’t suffice because you’re not just sitting in your armchair: you’re using a new tool to examine the everyday from a different perspective.  For present purposes, you might as well be doing algebraic geometry.

The Freudians and Marxists would, of course, claim that they’re doing the exact same thing.  Yes, they’d say, you thought you had the words to discuss your own mind or the power structure of society, but really you didn’t, because you lacked the revolutionary theoretical framework that we now possess.  (Trotsky’s writings  are suffused with this brand of arrogance in nearly every sentence: for example, when he ridicules the bourgeoisie liberals who whine about “human rights violations” in the early USSR, yet who are too dense to phrase their objections within the framework of dialectical materialism.)

I submit that, even without the hindsight of 2015, there would’ve been excellent reasons to be skeptical of these claims.  Has it ever happened, you might ask yourself, that someone sat in their study and mused about the same human questions that occupied Plato and Shakespeare and Hume, in the same human way they did, and then came up with a new, scientific conclusion that was as rigorous and secure as relativity or evolution?

Let me know if I missed something, but I can’t think of a single example.  Sure, it seems to me, there have been geniuses of human nature, who enlarged our vision without any recourse to the quantitative methods of science.  But even those geniuses “only” contributed melodies for other geniuses to answer in counterpoint, rather than stones for everyone who came later to build upon.  Also, the geniuses usually wrote well.

Am I claiming that progress is impossible in the social realm?  Not at all.  The emancipation of slaves, the end of dueling and blasphemy laws and the divine right of kings, women’s suffrage and participation in the workforce, gay marriage—all these strike me as crystal-clear examples of moral progress, as advances that will still be considered progress a thousand years from now, if there’s anyone around then to discuss such things.  Evolutionary psychology, heuristics and biases, reciprocal altruism, and countless other developments likewise strike me as intellectual progress within the sciences of human nature.  But none of these advances needed recondite language!  Ordinary words sufficed for Thomas Paine and Frederick Douglass and John Stuart Mill, as they sufficed for Robert Axelrod and for Kahneman and Tversky.  So forgive me for thinking that whatever is true and important in the social world today, should likewise be defensible to every smart person in ordinary words, and that this represents a genuine difference between the social sciences and physics.

Which brings us to the central point that Prof. Laba disputed in that comment of mine.  I believe there are countless moral heroes in our time, as well as social scientists who struggle heroically to get the right answers.  But as far as I can tell, the people who build complex intellectual edifices around words like “privilege” and “delegitimation” and “entitlement” and “marginalized” are very much the same sort of people who, a few generations ago, built similar edifices around “bourgeoisie” and “dialectical” and “false consciousness.”  In both cases, there’s an impressive body of theory that’s held up as the equivalent in its domain of relativity, quantum mechanics, and Darwinism, with any skeptics denounced as science-deniers.  In both cases, enlightened liberals are tempted to side with the theorists, since the theorists believe in so many of the same causes that the enlightened liberals believe in, and hate so many of the same people who the enlightened liberals hate.  But in both cases, the theorists’ language seems to alternate between incomprehensible word-salad and fervid, often profanity-laced denunciations, skipping entirely over calm clarity.  And in both cases, the only thing that the impressive theoretical edifice ever seems to get used for, is to prove over and over that certain favored groups should get more power while disfavored ones should get less.

So I’m led to the view that, if you want to rouse people’s anger about injustice or their pity about preventable suffering, or end arbitrary discrimination codified into law, or give individuals more freedom to pursue their own happiness, or come up with a new insight about human nature, or simply describe the human realities that you see around you—for all these purposes, the words that sufficed for every previous generation’s great humanists will also suffice for you.

On the other hand, to restrict freedom and invent new forms of discrimination—and to do it in the name of equality and justice—that takes theory.  You’ll need a sophisticated framework, for example, to prove that even if two adults both insist they’re consenting to a relationship, really they might not be, because of power structures in the wider society that your superior insight lets you see.  You’ll need advanced discourse to assure you that, even though your gut reaction might be horror at (say) someone who misspoke once and then had their life gleefully destroyed on social media, your gut is not to be trusted, because it’s poisoned by the same imperialist, patriarchal biases as everything else—and because what looks like a cruel lynching needs to be understood in a broader social context (did the victim belong to a dominant group, or to a marginalized one?).  Finally, you’ll need oodles of theory (bring out the Marcuse) to explain why the neoliberal fanaticism about “free speech” and “tolerance” and “due process” and “the presumption of innocence” is too abstract and simplistic—for those concepts, too, fail to distinguish between a marginalized group that deserves society’s protection and a dominant group that doesn’t.

So I concede to Prof. Laba that the complicated discourse of privilege, hegemony, etc. serves a definite purpose for the people who wield it, just as much as the complicated discourse of quantum field theory serves a purpose for physicists.  It’s just that the purposes of the privilege-warriors aren’t my purposes.  For my purposes—which include fighting injustice, advancing every social and natural science as quickly as possible, and helping all well-meaning women and men see each other’s common humanity—I said last year and I say again that ordinary words will do.

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Update (Oct. 26): Izabella Laba has written a response to this post, for which I’m extremely grateful. Her reply reveals that she and I have a great deal of common ground, and also a few clear areas of disagreement (e.g., what’s wrong with Steven Pinker?). But my most important objection is simply that, the first time I loaded her blog, the text went directly over the rock image in the background, making it impossible to read without highlighting it.

A hat tip to Miss C at Neatorama for posting a most interesting story from Buzzfeed.

A couple had a child with fertility assistance, but later found out that the child’s blood type did not match either parent. A paternity test, using cheek swabs, determined that the man was not the father of the baby. The couple had more tests, and was prepared to sue the fertility clinic. Then they did a genetic test through 23andMe, which tests many more markers than a standard paternity test in order to establish genetic ties in extended families. That test said the man was the baby’s uncle!

The explanation is that the man is a genetic chimera. Before he was born, he had a fraternal twin that did not develop into a viable baby. But the vanished twin’s DNA survived by being absorbed into the surviving twin...

However, since the cells of his lost twin brother are a part of him, he is still the father. The case shows how a person cannot be defined by their DNA. About one in eight single-child births start out as multiple pregnancies, so chimerism is probably more common than we know.

Last year I posted a similar article involving a young mother:

In order to qualify for financial assistance in supporting her young family, Fairchild was required to undergo DNA testing to prove that she was the mother of children for whom she was claiming... To her horror, the young mother was informed that she would be the subject of an investigation into possible welfare fraud as the DNA tests had revealed no genetic link between her and the children she claimed were hers...

More information at the links, or type "chimera" in the new search box in the right sidebar to see unusual butterflies, apples, and legendary monsters.

One wonders how many lives have been affected/disrupted by genetic testing that did not take the possibility of chimerism into account - especially paternity cases.

Author(s): Otto X. Cordero

High-resolution tracking of the population abundances in a simple, closed microbial ecosystem shows that the intrinsic dynamics of the system are strongly deterministic.

[Physics 8, 101] Published Mon Oct 26, 2015

Resonant cavities are one of the basic building blocks in various disciplines of science and technology, with numerous applications ranging from abstract theoretical modeling to everyday life devices. The eigenfrequencies of conventional cavities are a function of its geometry, and, thus, the size and shape of a resonant cavity is selected in order to operate at a specific frequency. Here, we demonstrate theoretically the existence of geometry-invariant resonant cavities, i.e., resonators whose eigenfrequency is invariant with respect to geometrical deformations. This effect is obtained by exploiting the unusual properties of zero-index metamaterials, which enable decoupling of the time and spatial field variations. This new class of resonators may inspire alternative design concepts, and it might lead to the first generation of deformable resonant devices.

Random projections have proven extremely useful in many signal processing and machine learning applications. However, they often require either to store a very large random matrix, or to use a different, structured matrix to reduce the computational and memory costs. Here, we overcome this difficulty by proposing an analog, optical device, that performs the random projections literally at the speed of light without having to store any matrix in memory. This is achieved using the physical properties of multiple coherent scattering of coherent light in random media. We use this device on a simple task of classification with a kernel machine, and we show that, on the MNIST database, the experimental results closely match the theoretical performance of the corresponding kernel. This framework can help make kernel methods practical for applications that have large training sets and/or require real-time prediction. We discuss possible extensions of the method in terms of a class of kernels, speed, memory consumption and different problems.

Human skin relies on cutaneous receptors that output digital signals for tactile sensing in which the intensity of stimulation is converted to a series of voltage pulses. We present a power-efficient skin-inspired mechanoreceptor with a flexible organic transistor circuit that transduces pressure into digital frequency signals directly. The output frequency ranges between 0 and 200 hertz, with a sublinear response to increasing force stimuli that mimics slow-adapting skin mechanoreceptors. The output of the sensors was further used to stimulate optogenetically engineered mouse somatosensory neurons of mouse cortex in vitro, achieving stimulated pulses in accordance with pressure levels. This work represents a step toward the design and use of large-area organic electronic skins with neural-integrated touch feedback for replacement limbs. Authors: Benjamin C.-K. Tee, Alex Chortos, Andre Berndt, Amanda Kim Nguyen, Ariane Tom, Allister McGuire, Ziliang Carter Lin, Kevin Tien, Won-Gyu Bae, Huiliang Wang, Ping Mei, Ho-Hsiu Chou, Bianxiao Cui, Karl Deisseroth, Tse Nga Ng, Zhenan Bao

In this paper we study the concept of using the interaction between waves and a trainable medium in order to construct a matrix-vector multiplier. In particular we study such a device in the context of the backpropagation algorithm, which is commonly used for training neural networks. Here, the weights of the connections between neurons are trained by multiplying a `forward' signal with a backwards propagating `error' signal. We show that this concept can be extended to trainable media, where the gradient for the local wave number is given by multiplying signal waves and error waves. We provide a numerical example of such a system with waves traveling freely in a trainable medium, and we discuss a potential way to build such a device in an integrated photonics chip.

"A $4,200 recording booth, $5,400 worth of movie animation software and two $750 sewing machines. No, it’s not the wish list of a particularly spoiled, artsy kid. It’s a plan for the future of the Dakota County libraries.

The county is looking to join several Twin Cities libraries that have added “maker spaces.” The areas filled with technical equipment for do-it-yourself projects have grown in popularity over the past few years, and are changing libraries’ roles in their communities.

People are visiting libraries less as e-books become more popular, Deputy Library Director Ben Trapskin said. So communities are rethinking how to use the buildings. “We really want to breathe some new life into what we’re all about,” he said. “This is a good reason for people to come back into the space.”...

While Hennepin County libraries do not have a maker spaces for adults, they have added programming, like a knitting group, to fill that niche, Turner said...

Equipment and furnishings are expected to cost $55,000 and will be covered by a grant and a donation. The county is still figuring out how to cover future expenses like repairing equipment and training staff, Trapskin said.

Staffing the area will require a balancing act, said Darcy Schatz, who is on the county’s Library Advisory Committee. Employees will need to help run the equipment without sacrificing other services, she said.

But as communities’ needs have changed, Trapskin said libraries have gotten used to shifting staff and resources — like the donation that will help fund Dakota County’s maker space. That money was originally designated for print reference books."

See also this article about libraries that lend tools (to be blogged separately later).

Neurons live for decades in a postmitotic state, their genomes susceptible to DNA damage. Here we survey the landscape of somatic single-nucleotide variants (SNVs) in the human brain. We identified thousands of somatic SNVs by single-cell sequencing of 36 neurons from the cerebral cortex of three normal individuals. Unlike germline and cancer SNVs, which are often caused by errors in DNA replication, neuronal mutations appear to reflect damage during active transcription. Somatic mutations create nested lineage trees, allowing them to be dated relative to developmental landmarks and revealing a polyclonal architecture of the human cerebral cortex. Thus, somatic mutations in the brain represent a durable and ongoing record of neuronal life history, from development through postmitotic function. Authors: Michael A. Lodato, Mollie B. Woodworth, Semin Lee, Gilad D. Evrony, Bhaven K. Mehta, Amir Karger, Soohyun Lee, Thomas W. Chittenden, Alissa M. D’Gama, Xuyu Cai, Lovelace J. Luquette, Eunjung Lee, Peter J. Park, Christopher A. Walsh

Perlman and collaborators find that students inventing new words use certain types of vocalizations with certain words. For example, made-up words for “up” have a rising pitch, words for “down” have a falling pitch. “Slow” has a long duration and a low pitch, whereas “fast” has a short duration and high pitch. And “smooth” has a high degree of harmonicity, whereas “rough” has a high degree of the opposite quality—noise. This suggests that vocal communication systems can originate from spontaneously created iconic characteristics of sound, just as gestural communication systems can originate from spontaneously created iconic gestures. The chart shows the data describing characteristics of words invented for 18 contrasting ideas: up, down, big, small, good, bad, fast, slow, far, near, few, many, long, short, rough, smooth, attractive, and ugly.

The plots show the acoustic characteristics of each of the 18 meanings. The five variables are represented on the x-axis: D, duration; H, harmonics to noise ratio; I, intensity; P, pitch; C, pitch change. All values are normalized (z-scored) for each of the five measures. The red line shows the median and the blue box spans the first and third quartiles. The up and down arrows indicate variables that differed reliably between antonymic meanings. For example, vocalizations for bad differed from those for good by having a lower harmonics to noise ratio and pitch. The variables marked with arrows were the basis for the iconic template of each meaning.

That's one description of Skunk:

Imagine being soaked, head to toe, in a frothy mix of pureed compost, gangrenous human flesh, and road kill, and you might get some idea of what it’s like to be sprayed with Skunk, according to those who’ve had the misfortune of being doused.

Police departments in the United States have reportedly begun purchasing the spray, a non-lethal riot-control weapon concocted by an Israeli firm for use against demonstrators in the occupied West Bank. The sticky fluid, which Palestinians say smells like a “mixture of excrement, noxious gas and a decomposing donkey,” is usually fired from armored vehicles equipped using high-pressure water cannons.

Mistral Security, a firm based in Bethesda, Maryland, markets Skunk to U.S. police and military as a crowd-control tool capable of “rapidly and effectively” dispersing unruly crowds. Recommended applications include “border crossings, correctional facilities, demonstrations and sit-ins.”

Mistral Security offers a number of delivery systems for Skunk, according to the company’s website, including 60 ounce canisters with a range of 40 feet; a “skid sprayer” equipped with a 50 gallon tank and a 5 hp motor that can shoot over 60 feet at up to 7 gallons per minute; and a 40mm grenade that can fired by a 12-gauge shotgun.

An automated images-to-graphs framework for high resolution connectomics.

Front Neuroinform. 2015;9:20

Authors: Gray Roncal WR, Kleissas DM, Vogelstein JT, Manavalan P, Lillaney K, Pekala M, Burns R, Vogelstein RJ, Priebe CE, Chevillet MA, Hager GD

Abstract
Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have produced massive 3D image volumes of nanoscale brain tissue for the first time. The resolution of EM allows for individual neurons and their synaptic connections to be directly observed. Recovering neuronal networks by manually tracing each neuronal process at this scale is unmanageable, and therefore researchers are developing automated image processing modules. Thus far, state-of-the-art algorithms focus only on the solution to a particular task (e.g., neuron segmentation or synapse identification). In this manuscript we present the first fully-automated images-to-graphs pipeline (i.e., a pipeline that begins with an imaged volume of neural tissue and produces a brain graph without any human interaction). To evaluate overall performance and select the best parameters and methods, we also develop a metric to assess the quality of the output graphs. We evaluate a set of algorithms and parameters, searching possible operating points to identify the best available brain graph for our assessment metric. Finally, we deploy a reference end-to-end version of the pipeline on a large, publicly available data set. This provides a baseline result and framework for community analysis and future algorithm development and testing. All code and data derivatives have been made publicly available in support of eventually unlocking new biofidelic computational primitives and understanding of neuropathologies.

PMID: 26321942 [PubMed]

On Sept. 2, 2005, during a nationally televised telethon benefit for victims of Hurricane Katrina, hip-hop legend Kanye West went off script to directly criticize the media and the White House’s handling of the storm. "I hate the way they portray us in the media," he said. "If you see a black family, it says they’re looting. If you see a white family, it says they’re searching for food." West went on to say, "George Bush doesn’t care about black people." Bush later wrote in his memoir that this moment was an all-time low of his presidency.

The possibility that quantum processing with nuclear spins might be operative in the brain is proposed and then explored. Phosphorus is identified as the unique biological element with a nuclear spin that can serve as a qubit for such putative quantum processing - a neural qubit - while the phosphate ion is the only possible qubit-transporter. We identify the "Posner molecule", $\text{Ca}_9 (\text{PO}_4)_6$, as the unique molecule that can protect the neural qubits on very long times and thereby serve as a (working) quantum-memory. A central requirement for quantum-processing is quantum entanglement. It is argued that the enzyme catalyzed chemical reaction which breaks a pyrophosphate ion into two phosphate ions can quantum entangle pairs of qubits. Posner molecules, formed by binding such phosphate pairs with extracellular calcium ions, will inherit the nuclear spin entanglement. A mechanism for transporting Posner molecules into presynaptic neurons during a "kiss and run" exocytosis, which releases neurotransmitters into the synaptic cleft, is proposed. Quantum measurements can occur when a pair of Posner molecules chemically bind and subsequently melt, releasing a shower of intra-cellular calcium ions that can trigger further neurotransmitter release and enhance the probability of post-synaptic neuron firing. Multiple entangled Posner molecules, triggering non-local quantum correlations of neuron firing rates, would provide the key mechanism for neural quantum processing. Implications, both in vitro and in vivo, are briefly mentioned.

A new paper proposes that dark matter may be a quantum fluid that has condensed in puddles to seed galaxies.

If Superfluid was a superhero, it would creep through the tiniest door slits and flow up the walls to then freeze the evil villain to death. Few things are cooler than superfluids, an utterly fascinating state that some materials, such as Helium, reach at temperatures close to absolute zero. Superfluid’s superpower is its small viscosity, which measures how the medium sticks to itself and can resist flowing. Honey has a larger viscosity than oil, which has a lager viscosity than water. And at the very end of this line, at almost vanishing viscosity, you find superfluids.

There are few places on Earth cold enough for superfluids to exist, and most of them are beleaguered by physicists. But outer space is cold and plenty. It is also full with dark matter whose microscopic nature has so far remained mysterious. In a recent paper (arXiv:1507.01019), two researchers from the University of Pennsylvania propose that dark matter might be puddles of a superfluid that has condensed in the first moments of the universe, and then caught the matter we readily see by its gravitational pull.

This research reflects how much our understanding of quantum mechanics has changed in the century that has passed since its inception. Contrary to what our experience tells us, quantum mechanics is not a theory of the microscopic realm. We do not witness quantum effects with our own senses, but the reason is not that human anatomy is coarse and clumsy compared to the teensy configurations of electron orbits. The reason is that our planet is a dense and noisy place, warm and thriving with thermal motion. It is a place where particles constantly collide with each other, interact with each other, and disturb each other. We do not witness quantum effects not because they are microscopic, but because they are fragile and get easily destroyed. But at low temperatures, quantum effects can enter the macroscopic range. They could, in fact, span whole galaxies.

The idea that dark matter may be a superfluid has been proposed before, but it had some shortcomings that the new model addresses; it does so by combining the successes of existing theories which cures several problems these theories have when looked at separately. The major question about the nature of dark matter is whether it is a type of matter, or whether it is instead a modification of gravity, or MOG for short. Most of the physics community presently favors the idea that dark matter is matter, probably some kind of as-yet-unknown particle, and they leave gravity untouched. But a stubborn few have insisted pursuing the idea that we can amend general relativity to explain our observations.

MOG, an improved version of the earlier MOdified Newtonian Dynamics (MOND), has some things going for it; it captures some universal relations that are difficult to obtain with dark matter. The velocities of stars orbiting the center of galaxies – the galactic rotation curves – cannot be explained by visible matter alone but can be accounted for by adding dark matter. And yet, many of these curves can also be explained by stunningly simple modifications of the gravitational law. On the other hand, the simple modification of MOND fails for clusters of galaxies, where dark matter still has to be added, and requires some fudging to get the solar system right. It has been claimed that MOG fits the bill on all accounts but on the expense of introducing more additional fields, which makes it look more and more like some type of dark matter.

Another example of an observationally found but unexplained connection is the Tully-Fisher relation between galaxies’ brightness and the velocity of the stars farthest away from the galactic center. This relation can be obtained with modifications of gravity, but it is hard to come by with dark matter. On the other hand, it is difficult to reproduce the separation of visible matter from dark matter, as seen for example in the Bullet Cluster, by modifying gravity. The bottom line is, sometimes it works, sometimes it doesn’t.



It adds to this that modifications of gravity employ dynamical equations that look rather peculiar and hand-made. For most particle physicists, these equations appear unfamiliar and ugly, which is probably one of the main reasons they have stayed away from it. So far.

In their new paper, Berezhiani and Khoury demonstrate that the modifications of gravity and dark matter might actually point to the same origin, which is a type of superfluid. The equations determining the laws of condensates like superfluids at lowest temperatures take forms that are very unusual in particle physics (they often contain fractional powers of the kinetic terms). And yet these are exactly the strange equations that appear in modified gravity. So Berezhiani and Khoury use a superfluid with an equation that reproduces the behavior of modified gravity, and end up with the benefits of both, particle dark matter and modified gravity.

Superfluids aren’t usually purely super, instead they generally are a mixture between a normally flowing component, and a superfluid component. The ratio between these components depends on the temperature – the higher the temperature the more dominant the normal component. In the new theory of superfluid dark matter the temperatures can be determined from the observed spread of velocities in the dark matter puddles, putting galaxies at lower temperatures than clusters of galaxies. And so, while the dark matter in galaxies like our Milky Way is dominantly in the superfluid phase, the dark matter in galactic clusters is mostly in the normal phase. This model thus naturally explains why modified gravity works only on a galactic scales, and should not be applied to clusters.

Moreover, on scales like that of our solar system, gravity is strong compared to the galactic average, which causes the superfluid to lose its quantum properties. This explains why we do not measure any deviations from general relativity in our own vicinity, another fact that is difficult to explain with the existing models of modified gravity. And since the superfluid is matter after all, it can be separated from the visible matter, and so it is not in conflict with the observables from colliding clusters of galaxies. In fact, it might fit the data better than single-particle dark matter because the strength of the fluid dark matter’s self-interaction depends on the fraction of normal matter and so depends on the size of the clusters.

Superfluids have another stunning property which is that they don’t like to rotate. If you try to make a superfluid rotate by spinning a bucket full of it, it just won’t. Instead it will start to form vortices that carry the angular momentum. The dark matter superfluid in our galaxy should contain some of these vortices, and finding them might be the way to test this new theory. But to do this, the researchers first have to calculate how the vortices would affect normal matter.

I find this a very interesting idea that has a lot of potential. Of course it leaves many open questions, for example how the matter formed in the early universe, so as the scientists always say: more work is needed. But if dark matter was a superfluid that would be amazingly cool – a few milli Kelvin to be precise.

When it comes to superpowers, I’ll chose science over fiction anytime.

Astrocytes are important regulatory elements in brain function. They respond to neurotransmitters and release gliotransmitters that modulate synaptic transmission. However, the cell- and synapse-specificity of the functional relationship between astrocytes and neurons in certain brain circuits remains unknown. In the dorsal striatum, which mainly comprises two intermingled subtypes (striatonigral and striatopallidal) of medium spiny neurons (MSNs) and synapses belonging to two neural circuits (the direct and indirect pathways of the basal ganglia), subpopulations of astrocytes selectively responded to specific MSN subtype activity. These subpopulations of astrocytes released glutamate that selectively activated N-methyl-d-aspartate receptors in homotypic, but not heterotypic, MSNs. Likewise, astrocyte subpopulations selectively regulated homotypic synapses through metabotropic glutamate receptor activation. Therefore, bidirectional astrocyte-neuron signaling selectively occurs between specific subpopulations of astrocytes, neurons, and synapses. Authors: R. Martín, R. Bajo-Grañeras, R. Moratalla, G. Perea, A. Araque

Throughout our nervous systems, neurons are faced with an enormous number of inputs, only some of which are relevant for accurate perceptions and appropriate behavior. On page 730 of this issue, Martín et al. (1) uncover a mechanism through which activation of one neuron temporarily enhances the responsiveness of neighboring neurons of the same type. This allows specific populations of neurons to effectively compare notes about their inputs, increasing the chance that if a group of neurons is activated simultaneously, a signal will propagate and change behavior. It turns out that the cellular machinery required to orchestrate this coordination extends beyond the neurons themselves to the surrounding network of glia, revealing a previously unrealized dimension of cellular specificity within the nervous system. Authors: Aryn H. Gittis, Daniel J. Brasier