Here’s an interesting idea. Moore’s Law states that the number of transistors on an integrated circuit doubles every two years or so. That has produced an exponential increase in the number of transistors on microchips and continues to do so.

But if an observer today was to measure this rate of increase, it would be straightforward to extrapolate backwards and work out when the number of transistors on a chip was zero. In other words, the date when microchips were first developed in the 1960s.

A similar process works with scientific publications. Between 1990 and 1960, they doubled in number every 15 years or so. Extrapolating this backwards gives the origin of scientific publication as 1710, about the time of Isaac Newton.

Today, Alexei Sharov at the National Institute on Ageing in Baltimore and his mate Richard Gordon at the Gulf Specimen Marine Laboratory in Florida, have taken a similar to complexity and life.

These guys argue that it’s possible to measure the complexity of life and the rate at which it has increased from prokaryotes to eukaryotes to more complex creatures such as worms, fish and finally mammals. That produces a clear exponential increase identical to that behind Moore’s Law although in this case the doubling time is 376 million years rather than two years.

That raises an interesting question. What happens if you extrapolate backwards to the point of no complexity–the origin of life?

Sharov and Gordon say that the evidence by this measure is clear. “Linear regression of genetic complexity (on a log scale) extrapolated back to just one base pair suggests the time of the origin of life = 9.7 ± 2.5 billion years ago,” they say.

And since the Earth is only 4.5 billion years old, that raises a whole series of other questions. Not least of these is how and where did life begin.

So let us celebrate James Lovelock and Lynn Margulis. Not just as scientists — their very real contributions speak for themselves — but as people with true courage and integrity. They withstood the pressure of fellow scientists turning on them. It would have been easy to drop the whole thing and say that it was a flawed hypothesis — giving themselves credit for being good Popperian scientists. But they knew there was something there that needed explaining and they had the guts to stick with it —Lovelock particularly, but Margulis too. Were they ‘holy fools’? The very friendly, entirely British Lovelock is as far from being a character in a Dostoyevsky novel as I can imagine. But in a sense they were just that, and ultimately science benefits from their thinking. Scientifically respectable or not, the Gaia hypothesis has made our culture richer for its boldness. Fools rush in where angels fear to tread, and sometimes it is better to be a little foolish than to stick to the safe, angelic, path.

 For the better part of a century, Carl Jung and (later) his estate kept the manuscript of his unfinished Red Book—orLiber Novus, as he originally entitled it—hidden safely away from public scrutiny. Jung’s most ardent admirers, making their hopeful pilgrimages to Zurich, were denied so much as a glimpse into its pages, no matter how plangent their entreaties. For a time, the book was even locked away in a Swiss bank vault. The result, inevitably, was that it became something of a legend among Jungians: a secret visionary tome, written in the master’s own hand, containing the mystic key to all his thought. Jung himself, after all, had once spoken of the book as the “numinous origin” from which all the work of his later years had flowed.

Anyone whose resolve to exercise in 2013 is a bit shaky might want to consider an emerging scientific view of human evolution. It suggests that we are clever today in part because a million years ago, we could outrun and outwalk most other mammals over long distances. Our brains were shaped and sharpened by movement, the idea goes, and we continue to require regular physical activity in order for our brains to function optimally.

(...)

To explain those outsized brain, evolutionary scientists have pointed to such occurrences as meat eating and, perhaps most determinatively, our early ancestors’ need for social interaction. Early humans had to plan and execute hunts as a group, which required complicated thinking patterns and, it’s been thought, rewarded the social and brainy with evolutionary success. According to that hypothesis, the evolution of the brain was driven by the need to think.

But now some scientists are suggesting that physical activity also played a critical role in making our brains larger.

To reach that conclusion, anthropologists began by looking at existing data about brain size and endurance capacity in a variety of mammals, including dogs, guinea pigs, foxes, mice, wolves, rats, civet cats, antelope, mongeese, goats, sheep and elands. They found a notable pattern. Species like dogs and rats that had a high innate endurance capacity, which presumably had evolved over millenniums, also had large brain volumes relative to their body size.

The researchers also looked at recent experiments in which mice and rats were systematically bred to be marathon runners. Lab animals that willingly put in the most miles on running wheels were interbred, resulting in the creation of a line of lab animals that excelled at running.

Interestingly, after multiple generations, these animals began to develop innately high levels of substances that promote tissue growth and health, including a protein called brain-derived neurotrophic factor, or BDNF. These substances are important for endurance performance. They also are known to drive brain growth.

To put this all into a metaphor:

The human brain is a trans-sonic plane, and the doctors studying it are engineers from 1900. They understand the the visible effects: push (a lot of random) button(s and weird glow-y panels that fill with changing words and may or may not be the result of the devil), receive thrust, and on some planes that are broken they've managed to tear off an engine and fiddle around inside it, but the avionics equipment, what with using semi-conductors and microprocessors, is basically black-box witchcraft to them, and the engines themselves are pretty much nonsense.

They recognize the basic idea of how the engines work; combustion of a hydrocarbon compound that isn't totally alien to them and is orders of magnitude more pure than anything they have outside of labs, much less in the quantities they need to run it for an extended period. The actual principles of the jet engine (compression from forced intake, fuel-air ratios, carefully tuned gear ratios and intelligent onboard systems in the engine itself to detect failures, damage and atmospheric conditions) are totally beyond them, and every engine they dismount to try to figure out stops working after two, maybe three, ignition runs since they're fueling it with total crap and have nothing hooked up to the diagnostic outputs and control inputs. Even the fucking landing gear is lightyears ahead of them; tires of vulcanized rubber, shocks based on pneumatic and hydraulic systems created through complex computer models to handle, y'know, a whole goddamn fucking plane bouncing off them. Even the goddamn metal itself that the plane is made of is alien to them, partly because aluminum was worth more than gold until some time in the late 1800's, and partly because the metallurgical techniques we use to create aircraft alloys, especially for trans-sonic planes, are utterly impossible given their level of technology.

So, to tie it all together: While the plane is in a running state, the engineers can't (from their perspective, with their tools and methods of figuring out how things work) touch a single damn thing that matters without everything breaking and flashing red. When the plane is disassembled and/or broken, they can't get anything working again and as far as they're concerned every single fundamental principle behind what we know to be how the plane operates istotally fucking impossible (remember that they hadn't even discovered heavier-than-air flight at this point. The wright brothers are still a ways off). Given a few decades or so, they'll eventually come to understand the principles behind some of the macro mechanical systems, and maybe even manage to mix up some fuel that will actually get the engine to do more than fail/explode, and at best even get an early start on powered flight in general. But actually replicating the plane itself is easily a generation or more out of their reach.

On June 5, 1995, Kees Moeliker, the curator of the Natural History Museum of Rotterdam, heard a loud bang just outside of his office. He went over to the window and discovered that a drake mallard had hit one of museum’s windows at full speed and died. Moeliker observed another male mallard came over and start picking at the dead duck’s head. The live mallard then proceeded to mount the corpse and forcefully rape it. This activity went on for a full seventy-five minutes, during which time the perpetrator took only two short breaks. Moeliker documented the entire event by taking notes and photos from safely behind the museum's windows. When the necrophiliac mallard was finished, Moeliker secured the violated corpse and stashed it in a freezer for later examination.

I found this observational study fascinating on multiple levels. Of course, the fact that someone would watch a dead duck being raped for over an hour, not to mention take copious notes while doing so, is interesting in and of itself. But what was even more fascinating to me about this article was finding out that neither necrophilia nor homosexuality is all that rare in mallard ducks. In fact, scientists have previously observed male mallards attempting to mate with deceased females, and researchers estimate that up to 1 in 5 mallard duck pairs consist of homosexual males.² It turns out that the only unique thing about this case was the combination of mallard necrophilia with homosexuality.

 Marriage counseling is so 20th century.  The 21st century may belong to relationship neuroinformaticians because they can create a mathematical model for efficient communication in your love life.

(...)

Steven Strogatz first described romance with a dynamical system in 1988. He constructed a 2-D model describing two hypothetical partners that interact emotionally. The well known example he used was Romeo and Juliet during their short, tumultuous affair. As everyone knows, a bunch of murders and suicides in a few days time are not indicative of a harmonious teenage relationship. It was not an elegant sinusoid.
But, note Natalia Bielczyk and colleagues from Radboud University Nijmegen, a Strogatz model doesn't include delays in the partner responses to each other, so they added reactivity parameters: Personal history of the couple, their ‘past’, and reactivity to their partner and his/her history. With those parameters, more complex relationships can be modeled. Some are predictably doomed to fail while others are always stable. Stability occurs when both partners reach a stable level of satisfaction and the sine wave narrows or even disappears.
They even say that delays in reactivity can bring stability to couples that are originally unstable.  Relationship counseling using the function sine. That's practical math.

(...)

The results are pretty intuitive though nothing you didn't already know - responses that are too delayed, or even too prompt, are a sign (get it??) of trouble. Under a certain threshold, delays mean instability and above it is stability.

(...)

Why is numerical modeling going to be better for men?  Because a range is optimal, and anything too fast causes instability, the math can tell you how lazy you can be in a relationship yet still claim you are working on maintaining a healthy response rate.  Covertly.  You are doing it for her.

"The end result is a brain that is mechanistically simple (2.5 million neurons isn’t really much to write home about), but which is surprisingly flexible. By implementing just a handful of very basic tasks, it’s interesting to see how complex behavior begins to emerge. There are some tantalizing hints as to how the brain evolved: starting with simple tasks, and then building upon and weaving them together to build complex functionality. In the video below, Spaun recognizes the pattern of a number sequence — the kind of question you would find on an actual IQ test."

A pattern emerges: humans invent mathematical concepts by way of abstracting elements from the world around them—shapes, lines, sets, groups, and so forth—either for some specific purpose or simply for fun. They then go on to discover the connections among those concepts. Because this process of inventing and discovering is man-made—unlike the kind of discovery to which the Platonists subscribe—our mathematics is ultimately based on our perceptions and the mental pictures we can conjure. For instance, we possess an innate talent, called subitizing, for instantly recognizing quantity, which undoubtedly led to the concept of number. We are very good at perceiving the edges of individual objects and at distinguishing between straight and curved lines and between different shapes, such as circles and ellipses—abilities that probably led to the development of arithmetic and geometry. So, too, the repeated human experience of cause and effect at least partially contributed to the creation of logic and, with it, the notion that certain statements imply the validity of others.

  Leibnitz raised the question almost 300 years ago with his analogy of the mill. Imagine that you can blow the mill up in size such that all components are magnified and you can walk among them. All you find are individual mechanical components, a wheel here, a spindle there. By looking at the parts of the mill you cannot deduce its function. The physical brain can also be broken into parts and their interactions examined. We now understand neurons and how they fire and a bit about neurotransmitters and so forth. But somehow the mental properties are indivisible and can’t be described in terms of neuronal firings. They need to be understood in another vocabulary.

(...)

The world is not flat. Before this truth was realized, people use to wonder what happened when you got to the end of the earth-- did you fall off? Once we knew the earth was round, the new perspective, made us see how the old questions were silly. New questions also seem silly many times until a new perspective is accepted. I think we will get over the idea of free will and and accept we are a special kind of machine, one with a moral agency which comes from living in social groups. This perspective will make us ask new kinds of questions. 

 "Sometimes researchers break into opposing camps.  They may each find well respected journals to publish their work in, but neither’s work appears capable of changing the minds of the others.  Adversarial collaboration is an approach for getting beyond this.  The idea is that intellectual opponents co-design new studies.  As much as possible, they should agree ahead of time about how the data will be analyzed, and include other neutral collaborators.  Then they write down their predictions, their uncertainties, and how different results will change their opinion.  When the study is done, hopefully they end up agreeing about how to interpret it.  But even if they didn’t, I think examining such a study, including the collaborators’ predictions beforehand, would really help other people decide what to believe."

Daqui

How does an embryo know where its face should grow? This amazing time-lapse video reveals a surprising mechanism at work: electricity.

The footage shows a frog embryo early on its development. Watch carefully and around nine seconds into the video you'll see a flash of light and dark patterns that looks like a template for where the face will subsequently develop.

These patterns are called bioelectric signals - fluxes of charged particles shooting across cells - that are already known to be involved in the formation of organs which rely heavily on electrical signals to function, such as the heart. This is the first time that they've been spotted in the formation of such a complex embryonic structure.

 "After the end of the first day, I said, "There's nothing here. Nothing's happening." The guards had this antiauthority mentality. They felt awkward in their uniforms."

(...)

"There was zero time for reflection. We had to feed the prisoners three meals a day, deal with the prisoner breakdowns, deal with their parents, run a parole board. By the third day I was sleeping in my office. I had become the superintendent of the Stanford county jail. That was who I was: I'm not the researcher at all. Even my posture changes—when I walk through the prison yard, I'm walking with my hands behind my back, which I never in my life do, the way generals walk when they're inspecting troops."

(...)

"What came over me was not an accident. It was planned. I set out with a definite plan in mind, to try to force the action, force something to happen, so that the researchers would have something to work with. After all, what could they possibly learn from guys sitting around like it was a country club? So I consciously created this persona. I was in all kinds of drama productions in high school and college. It was something I was very familiar with: to take on another personality before you step out on the stage. I was kind of running my own experiment in there, by saying, "How far can I push these things and how much abuse will these people take before they say, 'knock it off?'" But the other guards didn't stop me. They seemed to join in. They were taking my lead. Not a single guard said, "I don't think we should do this."

 Depois de ler isto fiquei a pensar, qual seria o comportamento dos guardas se estes não fossem tão anti-autoritários?

Será que, mais que uma demonstração de como o poder corrompe, isto não é a encenação do Poder, visto pelos olhos de quem acha que este é ontologicamente mau?

"By plotting the distributions of words used in financial articles published online between 2006 and 2010 into a computer model, we were able to identify what we call 'verb convergence' and 'noun convergence — where the language used by financial journalists shows converging agreement. Our study shows that reporters converge on the same language — 'stocks rose again', 'scaled new heights', or 'soared' — as their commentaries became more uniformly positive in the lead up to the 2007 crash. They also appear to refer to a smaller-than-usual set of market events — presumably because of an increased fixation on a small number of rapidly rising stocks."

The question that Inca scholars have grappled with since is whether or not the khipus constitute what linguists call a glottographic or "true writing" system. In true writing, a set of signs (for example, the letters C-A-T) matches the sound of speech (the spoken word "cat.") These signs must be easily decoded not just by the person who writes them, but by anyone who possesses the ability to read in that language. No such link has yet been found between a khipu and a single syllable of Quechua, the native language of the Peruvian Andes.

But what if the khipus don't fit neatly into the precise criteria established for true writing? It's possible, says Wisconsin's Salomon, that khipus were actually examples of semasiography, a system of representative symbols—such as numerals or musical notation—that conveys information but isn't tied to the speech sounds of a single language, in this instance Quechua. (By contrast, logographic languages such as Chinese and Japanese are phonetic as well as character-based.) The Incas conquered a huge number of neighboring peoples in a short time span, between 1438 and 1532; each of these groups had its own language or dialect, and the Incas wanted to integrate those new territories into their hyperefficient organizational network quickly. "It makes sense that they'd use a system that could transcend languages," Salomon says.

Taede Smedes’ project concerns the debate on science and religion, more
specifically, modern physics and religion. Relevant questions are: what impact
modern physics could possibly have on religion? Is there something in religion
which modern physics can or could clarify? Is there some veil modern physics
could lift from the religious? Another question is whether modern physics could
serve as an explanatory model for some religious accounts, as a metaphor, or as
an ‘extension to our linguistic language’? According to Smedes, physical theories
have been used in order to achieve such aims and he analyzes some of these
approaches. He chose John Polkinghorne and Arthur Peacocke’s explanations of
how divine action can be understood.

(...)

 Since, according to his critical realism, epistemology models ontology, epistemological

uncertainties (chaos) imply ontological openness, making the world an
open system. Furthermore, since there are ontological holes at the micro level
of quantum mechanics as well as at the macro level of everyday experience, and
since chaotic systems never can be overcome but only slightly diminished, there
are genuine gaps in the texture of reality and these may allow God to act in the
world. Top-down divine action meets bottom-up natural processes.

Uma civilização Drávida posteriormente destruída por invasores Arianos? Oh my... Este senhor que começe a andar com um retrovisor pela rua.

"

AUSTIN, Texas — Computer networks that can’t forget fast enough can show symptoms of a kind of virtual schizophrenia, giving researchers further clues to the inner workings of schizophrenic brains, researchers at The University of Texas at Austin and Yale University have found.

The researchers used a virtual computer model, or “neural network,” to simulate the excessive release of dopamine in the brain. They found that the network recalled memories in a distinctly schizophrenic-like fashion.

Their results were published in April in Biological Psychiatry.

“The hypothesis is that dopamine encodes the importance — the salience — of experience,” says Uli Grasemann, a graduate student in the Department of Computer Science at The University of Texas at Austin. “When there’s too much dopamine, it leads to exaggerated salience, and the brain ends up learning from things that it shouldn’t be learning from.”

The results bolster a hypothesis known in schizophrenia circles as the hyperlearning hypothesis, which posits that people suffering from schizophrenia have brains that lose the ability to forget or ignore as much as they normally would. Without forgetting, they lose the ability to extract what’s meaningful out of the immensity of stimuli the brain encounters. They start making connections that aren’t real, or drowning in a sea of so many connections they lose the ability to stitch together any kind of coherent story.

The neural network used by Grasemann and his adviser, Professor Risto Miikkulainen, is called DISCERN. Designed by Miikkulainen, DISCERN is able to learn natural language. In this study it was used to simulate what happens to language as the result of eight different types of neurological dysfunction. The results of the simulations were compared by Ralph Hoffman, professor of psychiatry at the Yale School of Medicine, to what he saw when studying human schizophrenics.

In order to model the process, Grasemann and Miikkulainen began by teaching a series of simple stories to DISCERN. The stories were assimilated into DISCERN’s memory in much the way the human brain stores information-not as distinct units, but as statistical relationships of words, sentences, scripts and stories.

“With neural networks, you basically train them by showing them examples, over and over and over again,” says Grasemann. “Every time you show it an example, you say, if this is the input, then this should be your output, and if this is the input, then that should be your output. You do it again and again thousands of times, and every time it adjusts a little bit more towards doing what you want. In the end, if you do it enough, the network has learned.”

In order to model hyperlearning, Grasemann and Miikkulainen ran the system through its paces again, but with one key parameter altered. They simulated an excessive release of dopamine by increasing the system’s learning rate-essentially telling it to stop forgetting so much.

“It’s an important mechanism to be able to ignore things,” says Grasemann. “What we found is that if you crank up the learning rate in DISCERN high enough, it produces language abnormalities that suggest schizophrenia.”

After being re-trained with the elevated learning rate, DISCERN began putting itself at the center of fantastical, delusional stories that incorporated elements from other stories it had been told to recall. In one answer, for instance, DISCERN claimed responsibility for a terrorist bombing.

In another instance, DISCERN began showing evidence of “derailment”-replying to requests for a specific memory with a jumble of dissociated sentences, abrupt digressions and constant leaps from the first- to the third-person and back again.

“Information processing in neural networks tends to be like information processing in the human brain in many ways,” says Grasemann. “So the hope was that it would also break down in similar ways. And it did.”

The parallel between their modified neural network and human schizophrenia isn’t absolute proof the hyperlearning hypothesis is correct, says Grasemann. It is, however, support for the hypothesis, and also evidence of how useful neural networks can be in understanding the human brain.

“We have so much more control over neural networks than we could ever have over human subjects,” he says. “The hope is that this kind of modeling will help clinical research.”

"Some Black Holes May Pre-Date The Big Bang"

Black holes are regions of space in which gravity is so strong that nothing can escape, not even light. Conventionally, black holes form during a gravitational collapse, after a large supernova for example.

But there is another class of objects called primordial black holes that cosmologists think must have formed in a different way. These are essentially leftovers from the hugely dense ball of stuff from which the universe expanded, some parts of which must have been dense enough to form black holes.

These primordial black holes would then have been widely dispersed as the universe expanded.

Primordial black holes are very different beasts to the ones that form when stars die, in particular because they ought to be much smaller.

Although nobody has yet seen a primordial black hole, our knowledge of them comes from thinking about the processes that must have occurred shortly after the Big Bang.

In recent years, however, cosmologists have begun to think seriously about processes that occurred before the Big Bang. One idea, is that the Universe may eventually collapse leading to an endless cycle of Big Bangs and Crunches.

Today, Bernard Carr at Queen Mary University of London, UK, and Alan Coley at Dalhousie University in Canada, ask what might happen in such a universe in the moments before a crunch.

By some accounts, a Big Crunch generates a singularity that ought to cause everything in the Universe to merge. But Carr and Coley say that in some circumstances, black holes of a certain mass could avoid this fate and survive the crunch as separate entities. The masses for which this is possible range from a few hundred million kilograms to about the mass of our Sun.

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