The economy of bitcoins: New ways to study social action on markets

ETH's researchers decipher the dynamics behind the cryptocurrency Bitcoin.
Credit: © ulchik74 / Fotolia

Anyone who strolls around the Kreuzberg district of Berlin, can't help but notice them -- the small signs on the doors of shops and cafes "Bitcoins accepted." Customers pay for their shirt or their cappuccino with their Smartphone instead of with bank notes or credit cards. The digital currency Bitcoin makes all this possible.

"The image of Bitcoin has changed fundamentally," explains David Garcia, a post-doctoral researcher with the Chair of Systems Design held by Professor Frank Schweitzer. "Bitcoins used to be the reserve of hackers and computer nerds. Today, hipsters pay for drinks with them and they are accepted in the online shops of large companies." Garcia, together with his colleagues Claudio Tessone, Pavlin Mavrodiev and Nicolas Perony, has just published a study on the social dynamics of the Bitcoin economy in the Journal of the Royal Society: Interface.

Internet activity determines exchange rates

For research the success of the digital currency (see box) is a stroke of luck as all data on every transaction carried out in Bitcoin are available in anonymised form on the Internet. Consequently, Garcia and his colleagues are able to study the Bitcoin economy using corresponding algorithms. This idea saw the light of day when they noticed that the 50,000-fold market value increase in the digital currency in just three and a half years went hand in hand with a 10,000 percent increase in Google searches for Bitcoin. The researchers hypothesise that the increase in the value of Bitcoins is markedly accelerated by activities on the Internet, in particular the search for information and interaction in the social media.

To test their hypothesis the researchers examined four different socio-economic parameters: the development of the Bitcoin user base, the price developments of the currency over time, the search for information about Bitcoin on Google and in Wikipedia (more than six million inquiries) and the exchange of information about Bitcoin on Twitter (almost seven million Tweets). In fact, over the past three the researchers established years major correlations between price developments, the number of new Bitcoin users, searches on the Internet and Tweets.

At the same time, they discovered two positive feedback loops which basically reproduced the laws of the "analogous" economy. The growing popularity of Bitcoins on the Internet leads to growing demand which, in turn, encourages activity in the social media. This all results in a higher price for Bitcoins. The second feedback concerns the user base: the more users become part of the Bitcoin transaction network, the higher the price because Bitcoins are not issued in line with demand but in an automated fashion at regular intervals. This means it is possible to calculate the available amount at any time. One negative feedback is, however, surprising. Prior to a major slump in the price of the currency, there was a dramatic increase in Bitcoin activity on the Internet. "Big changes in Internet and social media activities lead to substantial price fluctuations," comments Nicolas Perony, co-author of the article.

Understanding markets and social dynamics

Perony is convinced that the quantitative analysis of social phenomena on the Internet has major potential. "With digital currencies we can observe aspects of the economy that we didn't have access to with cash. This gives us greater understanding of how markets actually function." According to the authors, the methodology described in the article could be applied to other areas in society, too. The Bitcoin mining network, which issues the currency, already harnesses computing power today which is three hundred times bigger than that of the 500 most powerful supercomputers together. "The big question is how such a high-performance system could be used for collaborative activities which go beyond the production of money," comments Perony. One possibility would be, for instance, collaborative research in a global network or the decentralised ownership of specific goods managed by a global network. Bitcoms do not belong to anyone. Buyers merely acquire the right to use a specific amount of them. This study already outlines today the tools for accurately quantifying and analysing the social dynamics of collaborative systems of this kind in the future.

The meteoric rise of Bitcoin

The Bitcoin success story began in 2008 with an article about an alternative, digital currency published under the pseudonym Satoshi Nakamoto. In July 2010 Bitcoins were traded for the first time on the Internet exchange Mt. Gox at a rate of US$ 0.06 for 1 Bitcoin. The total value of all Bitcoins was US$ 277,000. By the end of 2013 the market value of all issued Bitcoins had climbed to more than US$ 14 billion whereby during spikes more than US$ 1,000 were paid for one Bitcoin. Today, over four million people use the digital currency. 

Bitcoins are traded in euros, dollars and in Chinese renminbi. Unlike conventional currencies there is no central bank for Bitcoins which has a monopoly for printing money. New Bitcoins are generated by what is known as mining via a global computer network -- currently at a rate of 25 Bitcoins every ten minutes. Transactions are likewise verified and carried out on this network. Even the bankruptcy of important Bitcoin trading exchanges and negative headlines about money laundering and drug purchases on the Internet were not able to undermine confidence in the currency. A few days ago the PC giant Dell announced that it will henceforth accept Bitcoins as payment for products in its online shop.

Source: ETH Zurich

Human faces are so variable because we evolved to look unique

The amazing variety of human faces -- far greater than that of most other animals -- is the result of evolutionary pressure to make each of us unique and easily recognizable. Credit: UC Berkeley

The amazing variety of human faces -- far greater than that of most other animals -- is the result of evolutionary pressure to make each of us unique and easily recognizable, according to a new study by University of California, Berkeley, scientists.

Our highly visual social interactions are almost certainly the driver of this evolutionary trend, said behavioral ecologist Michael J. Sheehan, a postdoctoral fellow in UC Berkeley's Museum of Vertebrate Zoology. Many animals use smell or vocalization to identify individuals, making distinctive facial features unimportant, especially for animals that roam after dark, he said. But humans are different.

"Humans are phenomenally good at recognizing faces; there is a part of the brain specialized for that," Sheehan said. "Our study now shows that humans have been selected to be unique and easily recognizable. It is clearly beneficial for me to recognize others, but also beneficial for me to be recognizable. Otherwise, we would all look more similar."

"The idea that social interaction may have facilitated or led to selection for us to be individually recognizable implies that human social structure has driven the evolution of how we look," said coauthor Michael Nachman, a population geneticist, professor of integrative biology and director of the UC Berkeley Museum of Vertebrate Zoology.

The study will appear Sept. 16 in the online journal Nature Communications.

In the study, Sheehan said, "we asked, 'Are traits such as distance between the eyes or width of the nose variable just by chance, or has there been evolutionary selection to be more variable than they would be otherwise; more distinctive and more unique?'"

As predicted, the researchers found that facial traits are much more variable than other bodily traits, such as the length of the hand, and that facial traits are independent of other facial traits, unlike most body measures. People with longer arms, for example, typically have longer legs, while people with wider noses or widely spaced eyes don't have longer noses. Both findings suggest that facial variation has been enhanced through evolution.

Finally, they compared the genomes of people from around the world and found 

more genetic variation in the genomic regions that control facial characteristics than in other areas of the genome, a sign that variation is evolutionarily advantageous.

"All three predictions were met: facial traits are more variable and less correlated than other traits, and the genes that underlie them show higher levels of variation," Nachman said. "Lots of regions of the genome contribute to facial features, so you would expect the genetic variation to be subtle, and it is. But it is consistent and statistically significant."

Using Army data

Sheehan was able to assess human facial variability thanks to a U.S. Army database of body measurements compiled from male and female personnel in 1988. The Army Anthropometric Survey (ANSUR) data are used to design and size everything from uniforms and protective clothing to vehicles and workstations.

A statistical comparison of facial traits of European Americans and African Americans -- forehead-chin distance, ear height, nose width and distance between pupils, for example -- with other body traits -- forearm length, height at waist, etc. -- showed that facial traits are, on average, more varied than the others. The most variable traits are situated within the triangle of the eyes, mouth and nose.

Sheehan and Nachman also had access to data collected by the 1000 Genome project, which has sequenced more than 1,000 human genomes since 2008 and catalogued nearly 40 million genetic variations among humans worldwide. Looking at regions of the human genome that have been identified as determining the shape of the face, they found a much higher number of variants than for traits, such as height, not involving the face.

Prehistoric origins

"Genetic variation tends to be weeded out by natural selection in the case of traits that are essential to survival," Nachman said. "Here it is the opposite; selection is maintaining variation. All of this is consistent with the idea that there has been selection for variation to facilitate recognition of individuals."

They also compared the human genomes with recently sequenced genomes of Neanderthals and Denisovans and found similar genetic variation, which indicates that the facial variation in modern humans must have originated prior to the split between these different lineages.

"Clearly, we recognize people by many traits -- for example their height or their gait -- but our findings argue that the face is the predominant way we recognize people," Sheehan said.

Source: University of California - Berkeley

Cats and humans have shared the same households for at least 9,000 years, but we still know very little about how our feline friends became domesticated.

The scientists fitted GPS collars and motion sensors on 38 free-ranging lynx for the study. Credit: Image courtesy of Albert-Ludwigs-Universität Freiburg

An international research team recorded and analyzed the activity patterns of 38 wild cats over the course of months Whether a lynx hunts by day or by night and how active it is overall depend primarily on the behavior of the wild cat's most important prey and its individual traits -- lighting conditions, on the other hand, do not play a major role in its basic behavioral patterns. This is the key finding of a study published in the journal PLOS ONE by an international research team led by forest scientist Dr. Marco Heurich.

The scientists fitted GPS collars and motion sensors on 38 free-ranging lynx for the study. Since the study sites were located across a wide latitudinal range from Central Europe to northern Scandinavia, the length of days and nights varied greatly between them. The team recorded and analyzed the activity patterns of the wild cats on a total of more than 11,000 days. The results reveal that lynx in more southerly regions are most active at dawn and dusk and that they move more by night than by day. They take their longest break in the middle of the day, and this break is extended as daylight duration increases. However, the cats exhibit this basic behavioral pattern independently of lighting conditions: "Lynx keep to a 24-hour rhythm with an active and a resting phase even on the polar day and the polar night," reports Heurich.

What the study found to be more important for explaining the wild cats' activity patterns are their individual traits: Young lynx are more active than adult lynx, and male adults are more active than female adults. In addition, they move more in spring and summer than in fall and winter, and the farther north they live, the larger the territory they cover -- and this of course results in higher activity. Lynx adapt their hunting schedule to the behavior of their prey. In polar regions, the height of their activity at dusk is less pronounced. 

This corresponds to the behavioral pattern of reindeer, which exhibit a steady movement profile outside of their sleeping phases.. In Central Europe, by contrast, the team found a maximum amount of activity at dusk -- in lynx as well as in deer. "The findings of this study make an important contribution to our understanding of the habits of predatory animals in our landscape," says Heurich. "They also show that human activities in the areas included in the study do not have a general influence on the activity pattern of the animals."

Genetically identical ants help unlock the secrets of larval fate

Cerapachys biroi ants, native to Asia and introduced globally on tropical and subtropical islands, have no queens and have minimal genetic variation, making them ideal for research on social behavior. Credit: Image courtesy of Rockefeller University

A young animal's genes are not the only genes that determine its fate. The genetic identity of its caretakers matters too. Researchers suspect the interaction between the two can sway the fate of the young animal, but this complex dynamic is difficult to pin down in lab experiments.

However, social insect researchers have found a solution. Rockefeller University's Daniel Kronauer, head of the Laboratory of Insect Social Evolution, and his colleagues are developing a species of small raider ants as a model organism in order to ask questions about the relationships between genes, social behavior and evolution.

In a pair of recent papers, the researchers first explain the unique, and potentially useful, biology of this 2.5-millimeter-long ant. Then, in work with collaborators at the University of Paris 13, they put it to work exploring the interaction between the larvae and their nursemaids, and the influence on the young ants' reproductive success as adults.

Clonal raider ants, the species Cerapachys biroi, reproduce by cloning, and they live in colonies of as many as a few hundred nearly genetically identical workers. This makes these ants ideal for studies testing how a particular genetic makeup responds to different conditions, the researchers write in Current Biology. With the help of collaborators at BGI China, researchers in Kronauer's lab have sequenced the clonal raider ant's genome. This is an important step toward using the ant in the sorts of experiments conducted for years in traditional model organisms, such as mice and fruit flies.

"We have shown that colony mates are extremely closely related to one another, with all of the individuals in a colony being essentially genetically identical. This gives us precise control in experiments because we don't need to account for individual genetic variation," says Peter Oxley, a postdoc in the laboratory who led work establishing the clonal raider ant as a promising new model organism.

In the second study, one of the first to make use of the clonal raider ant, a team led by Serafino Teseo of the University of Paris 13 used the unique aspects of the ants' biology to test the indirect role genes play in shaping the future identity of larvae and whole colonies by looking at the interaction between larvae and adults. They did so by observing the success of two ant clones, A and B, in pure colonies or mixed together into chimeric colonies. They also swapped broods, so A adults raised B larvae and vice versa.

It turned out that A and B larvae developed differently depending on whether A or B nurses raised them. Left alone, pure A colonies produced the most young after six generations, making them more successful than B. However, in mixed colonies, B did better because its larvae more frequently turned into large adults that specialize in egg-laying rather than smaller, foraging-focused individuals.

The researchers suspect an indirect genetic effect -- specifically, a social influence. To begin to tease apart the dynamic, they had adults from one clone raise larvae from the other. Again, B did better when raised by A nurses than any of the other combinations. The results were published in Nature Communications.

The B colony's strategy of favoring reproduction over foraging when raised by A colony nurses smacks of social parasitism, in which one organism exploits another's social behavior for its own benefit. "This doesn't mean B is a parasite in the making, just that uncoupling the normal interaction between larvae and their nearly identical adult nursemaids reveals the presence of this mechanism," Kronauer says.

The study shows that, in social species, genetic makeup alone does not provide enough information to predict social behavior. Instead, interactions between social partners, such as larvae and their caregivers, are crucial determinants and can lead to surprising outcomes.

Source: Rockefeller University

'Family' matters when predicting ecosystems' reaction to global change

This is a picture of the experimental setup in the greenhouse.
Credit: Jennifer Schweitzer, co-author and associate professor at UT

Humans are rapidly changing the look and function of earth's ecosystems, from the increase of greenhouse gases to the unintentional and harmful spread of plants and animals to new environments. A major challenge for ecologists is to understand how and why communities respond to factors that underlie global change.

A University of Tennessee, Knoxville, study is finding some clues. It shows that just as our family histories dictate what we look like and how we act, plant evolutionary history shapes community responses to interacting agents of global change.

The research, published in the open-access journal PLOS ONE, may help predict what ecosystems will look like in the future and how they will work.

"The issues of global change have already begun to jeopardize the natural functioning of ecosystems and important services that we often take for granted like clean air, clean water, food and fiber production," said Rachel Wooliver, lead author and doctoral student in ecology and evolutionary biology. "Our study is the first to experimentally show that plant communities with different evolutionary backgrounds will respond differently to human-caused physical and biological changes."

In other words, regarding the future effects of global change on ecosystem services and processes humans rely upon, it's all in the family.

Wooliver and colleagues from UT, the University of Tasmania and Villanova University used eucalypt species native to Tasmania, Australia, to compare plant growth in cultures of all the same species to that of mixtures with native species with an introduced hardwood plantation species. They analyzed plant activity in an ambient environment versus one of increased levels of carbon dioxide and soil nitrogen.

"We found that only those communities composed of native species within one evolutionary lineage responded significantly to elevated carbon dioxide and nitrogen by taking carbon from the atmosphere and sequestering it into biomass," said co-author John Senior of the University of Tasmania. "Communities from another lineage, on the other hand, showed no response, which suggests that they will play a less crucial role in offsetting the rise of carbon dioxide and global warming."

This means that evolutionary history will shape which species will effectively sequester carbon and which won't.

Further, the presence of the nonnative species in these communities influenced productivity differently depending on the evolutionary background of the interacting native species. Thus, family trees can be used to predict how the spread of nonnative species by humans will shape the look and function of ecosystems as global change continues.

"Overall, this study provides new direction for global change scientists by highlighting that evolutionary history is key to understanding outcomes of plant function and diversity with rapid ecological change," said Wooliver.

The work is promising to researchers that are trying to figure out if species interactions change how ecosystems are responding to global change, as well as conservation biologists who aim to determine which species might be at higher risk for extinction in the future.

Source: University of Tennessee