Saturday, December 6, 2008

Quantum Trick Makes Metals Become Insulators

Researchers from Juelich, Mainz and Cologne use ultracold atoms in an optical lattice as a construction kit for electronic materials. The theoretical calculations were made on Juelich supercomputers, e.g. JUGENE. (Credit: Forschungszentrum Juelich)
ScienceDaily (Dec. 5, 2008) — The investigation of complex materials such as high-temperature superconductors is problematic because of the presence of disorder and many competing interactions in real crystalline materials. "This makes it difficult to identify the role of specific interactions and, in particular, to decide whether repulsive interactions between electrons alone can explain high-temperature superconductivity," says Dr. Theodoulos Costi from the Institute of Solid State Research, Forschungszentrum Jülich, which is a member of the Helmholtz Association.

Atoms in an optical lattice can serve as quantum simulators for many interesting phenomena such as that described above. They offer a very flexible model system in a clean and well-controlled environment and they can, for example, simulate electrons in solid, so-called condensed matter. In their technique, physicists introduce ultracold atoms into a crystal structure using an optical lattice and selectively switch this system between metallic and insulating states.
The physicists succeeded in simulating one of the most dramatic electronic phenomena with the aid of this quantum simulator: when the interactions between the electrons become too strong, a metal can suddenly become insulating. The resulting so-called Mott insulator is probably the most important example of a state of strong electronic interactions in condensed matter physics, as it is a starting point for the investigation of quantum magnetism. In addition, high-temperature superconductivity is found to arise in close proximity to this insulator.
The experimental setup in Mainz allows the density of the atoms and the strength of the repulsive interaction between the atoms to be tuned independently of each other. By investigating the behaviour of the atoms under compression and increasing interactions the experimentalists led by Prof. Immanuel Bloch of the Johannes Gutenberg University Mainz have been able to detect the Mott insulator in the quantum gas of the atoms.
A comparison with theoretical calculations by groups in Jülich and Cologne, requiring extensive simulations on a Jülich supercomputer, resulted in excellent agreement between theory and experiment. In addition, the researchers demonstrated through these calculations that one of the key methods of condensed matter theory, known by the abbreviation DMFT (dynamical mean field theory), is also applicable to real systems. The researchers expect that their theoretical and experimental techniques for investigating quantum many body states in optical lattices will soon be taken up by other groups.
Journal reference:
U. Schneider, L. Hackermueller, S. Will, Th. Best, I. Bloch, T. A. Costi, R. W. Helmes, D. Rasch and A. Rosch. Metallic and Insulating Phases of Repulsively Interacting Fermions in a 3D Optical Lattice. Science, Dec 5, 2008

Thursday, December 4, 2008

A Winning Web Formula

Advertisers could benefit from analyzing the early popularity of online content.
As online advertising money starts shrinking in the economic downturn, some researchers are looking for ways to make the most of every single dollar. Recent research from HP Labs in Palo Alto, CA, shows that it's possible to predict, with reasonable accuracy, how popular an online video clip or news story will become simply by looking at how well it does within the first few hours of being posted. If content providers can predict how many views a video or article will get over a set period, then they can match the most popular items with specific high-dollar ads. Additionally, content providers can place potentially popular content in eye-catching spots on their site, further increasing the number of people who see it and the accompanying ads.
"There's an obvious byproduct of what we're doing here for advertising," says Bernardo Huberman, a senior fellow at HP who led the work. "This will allow people who advertise to at least start getting a sense of what they want [...] if very early on you can tell if people will like a video or news story."
Huberman and his colleagues looked at historical data gathered from the video site YouTube, and from Digg, a news aggregator that lets readers' votes determine which stories become most prominent. The researchers applied mathematical models to these data sets, determining a "popularity curve" for different items. These curves allowed the researchers to extrapolate the future popularity of an item using only information about its popularity over the first few hours or days.
HP isn't the only organization trying to predict the popularity of content. Researchers at Google, Yahoo, Microsoft, and IBM, to name a few, have all invested resources and money in researching the problem. A few years ago, Duncan Watts, now a researcher at Yahoo, showed that the quality of a song is a very poor indicator of its eventual popularity, and that long-term song popularity--as measured on music-sharing networks--can be determined fairly early on, when a sort of popularity trajectory is determined.
In the case of Digg, Huberman says that within the first few hours it is clear whether a story will become popular or not (depending on how many "diggs"--or votes--it receives from the site's community of readers). Factoring in the time of day that a story is submitted (a noontime story will get, on average, twice as many early diggs as a story submitted at midnight), the researchers found that if a story receives a low number of diggs, it has relatively little hope of being one of the top viewed stories of the day. Conversely, if a story receives hundreds of diggs in the first hours, it's likely to be much more popular.



The popularity of YouTube videos follows a similar pattern, albeit on a longer timescale. By looking at the number of views a video gets on its first day, the researchers could determine the likelihood of reaching a certain level of popularity after a longer period. For instance, if only 15 people view the video during the first day, it's unlikely to become a big hit. However, if more than 100 people see it on the first day, then there's a high likelihood that it will be seen tens of thousands of times more.
In the case of both YouTube and Digg, Huberman notes that predictions become more accurate as data are considered over longer periods. For instance, within seven hours, it is possible to predict a story's future popularity on Digg nearly perfectly. Likewise for videos posted to YouTube for 20 days.
"Huberman says that other sites, such as online stores, would need their own ways of determining the popularity of their content because each site has unique characteristics. But advertisers, he says, armed with popularity predictions, could quickly determine which products might 'go viral' and then tag special ads to those.
"I think popularity prediction is an interesting topic in general," says Claudia Perlich, researcher at IBM's Watson Research Center in Yorktown Heights, NY. "And I certainly see the value [of] predicting popularity for advertising." However, she notes that it's only one part of the advertising puzzle. Increasingly, she says, advertisers are interested in the type of people who are viewing the content, and they find it useful to know the path that a Web surfer has taken before arriving at a site, so that he or she can be better targeted with a specific ad.
Perlich also raises questions about the two systems under study. "I have the slight worry that the results are driven by underlying technology," she says. It could be possible that the researchers are simply measuring the proprietary process in which stories become popular on Digg and some of the video-promotion features of YouTube. This is the problem, she says, with doing an experiment in which the systems are proprietary and it's impossible to know exactly how they work.
Huberman is confident that his methodology can predict popularity independently of specific algorithms used by the sites. He is in the process of analyzing the popularity of people on Twitter, a microblogging service that lets people post short messages to one another and subscribe to updates. Better understanding of these social networks, he says, could lead to entirely new business models. "The only thing that's of value today is people's attention," he says. "An immense amount of money is spent on trying to draw our attention to things."

Wednesday, December 3, 2008

Language Origins:Did Language Evolve Like the Vertebrate Eye, or Was It More Like Bird Feathers?

Review Article
Introduction
Linguistics and evolutionary theory share an extremely tenuous historical relationship, as linguistics was more concerned with philology, rather than scientific observation, when Darwin first published the Origin of Species.1 The most important argument within contemporary linguistics and evolutionary theory was sparked by Pinker and Bloom's (1990) seminal analysis outlining comments made by Noam Chomsky and Stephen Jay Gould that contradicted the basis of modern evolutionary theory; this article led to an enduring debate that has persisted over the last decade.2 Since Chomsky and Gould have made a number of assertions that language (the communication system unique to human beings), could not have evolved through natural selection, and natural selection has long been the prevailing theory in evolutionary biology, the challenge presented by Pinker and Bloom was to develop a theory of language origin that was compatible with the mainstream theory of evolution, the theory of natural selection.3 Since then, however, research has provided evidence that some aspects of language may have been naturally selected for, in line with Pinker and Bloom's arguments, while other aspects of language did not result because of natural selection, thus also supporting Chomsky and Gould. The following explores and integrates the history, evidence, and theories surrounding both selectionist and nonselectionist explanations of the origin of language.
A Brief History of Evolutionary Theory
Evolutionary theory has been wrought with controversy since its initial appearance in public debate in the late 19th century, at which time numerous biologists and theologians generated a wide variety of theories of the origins of humankind. Only one of those has withstood repeated tests of scientific merit and has been observed numerous times in ecological systems; this has come to be known as the theory of natural selection, first posited in Charles Darwin's Origin of Species.4 This theory shows how certain physical traits among members of a given population of organisms will be favored by any number of unpredictable environmental conditions, to the extent that these individuals experience a reproductive advantage and are thereby able to concentrate the expression of those traits in future generations. Of course, the environmental conditions that nurture the proliferation of a trait in one generation may be absent in the following generation, thus conferring no reproductive advantage to the offspring that receive the trait; this may lead to the eventual disappearance of the trait. Darwin discovered all of this before the existence of genes and DNA was confirmed, so he did not actually understand how physical traits were transferred from one generation to the next, but he knew that advantageous traits must be transmitted. Darwin took inspiration for his theory from his observations of Galapagos finches with beaks that seemed to be in exact proportions to the size of the seeds that were most frequent on their particular island, yet otherwise were anatomically identical.5 Darwinian natural selection is now used to explain a large proportion of evolutionary changes in species, ranging from the development of the vertebrate eye, to the origin of grammar, and even all of language.6
Natural Selection and Other Evolutionary Forces
When DNA was finally recognized by James Watson and Francis Crick to be the molecule responsible for transmitting genetic information in 1953, evolutionary biology had finally found the substance that made natural selection possible. This buttressed Darwin's theory of evolution and lead to the discovery of other mechanisms that are compatible with, but lie outside the scope of, Darwin's original theory. The discovery of these processes expanded the theory of evolution and the ability of biologists to understand evolutionary change. The other processes that drive the differentiation of populations, and ultimately, speciation (in addition to natural selection) are mutation, genetic drift, gene flow, the process of co-optation, and something that Darwin called "preadaptation."7
Mutation involves random changes in the DNA of individual organisms, often caused by mutagens in the environment such as ultraviolet radiation, chemicals, gamma rays, microwaves, or radioactive elements. Since mutations that profoundly change the structure or appearance of an organism can be deleterious to the organism and may prevent it from reaching reproductive age, massive changes to the phenotype of an individual can be evolutionarily difficult to pass on to future generations. Genetic drift includes the stochastic, unequal transmission of genes to subsequent generations and the effects this process has over time. It is also used to explain the effects of random events removing certain genes from the environment and preventing their expression. Gene flow involves the removal of a certain element of the gene pool, usually due to migration, and the way the source and contact populations are evolutionarily affected by the removal and addition of different genes. The process of co-optation is a nonselectionist evolutionary force that accounts for the existence of nondeleterious, yet nonadaptive (neutral) traits, explaining such phenomena as the brooding chamber in snails.8 "Preadaptation," although first identified by Darwin, was poorly explained in the Origin of Species, and is now called "exaptation."9 Consequently, exaptation is not considered part of natural selection and is therefore non-Darwinian, although it is an integral part of modern evolutionary theory.
Besides natural selection, exaptation is the most important evolutionary process discussed in this analysis. One kind of exaptation happens when a population of a given organism uses a bodily structure or other adaptation for something other than its original evolutionary purpose. A classic example of exaptation from evolutionary biology, as supported by the fossil record, is the theory that birds first evolved feathers for the purpose of insulation, and that this function of the feathers was later adapted for gliding in order to catch insects more efficiently.10 Talking parrots, such as African Greys (Psittacus erithacus) also demonstrate how exaptation works when they use neural oromotor structures that were selected for within-species communication in order to produce words from human languages, even though this behavior would provide them absolutely no added benefits in their natural environment. 11
Exaptation also has another way of working, which has been coined "spandrels" by Gould and is a word taken from the architectural term for the tapering, triangular shape that occurs as a result of structural necessity when two arches are joined at a right angle in order to build something on top of them (such as a dome).12 In the context of modern evolutionary theory, a spandrel is any structure or phenomenon that exists due to a physiological by-product of something else. In the animal kingdom, it can be difficult to determine if something is a spandrel or occurs because of regular exaptation, but an example used by Pinker and Bloom is found in the case of an aquatic bird that uses its wings to shade the glare off the surface of the water in order to better see its prey.13 In this situation, the bird's wings are like spandrels because they manage to block light by sheer virtue of being solid structures that are also good for flying. Similarly, in the case of a human being using his or her mouth as a hand, the mouth becomes spandrel-like, because in order to work well for chewing and eating it must also be able to grasp bite-sized objects.14
Recent research in the origins of language suggests that certain neurological processes underlying aspects of language may be derived from cerebral structures that are not only present in hominids, such as Homo sapiens, but are also present in non-human primates whose ancestors have been on Earth for a much longer time.15 What follows from this is that parts of language were exapted from cognitive structures that our pre-human ancestors used for food gathering, rule learning, tool making, and hunting, among a vast number of other purposes.16 As a consequence of these recent discoveries, selectionist and exaptationist views represent a polarity among evolutionary biologists, between those who view language as purely the result of natural selection, like the vertebrate eye, and those who view language as the result of cognitive capacities that were originally used for something else, as bird feathers may have evolved.17
Problems with Studying Evolution
Evolution is extremely difficult to study for a number of reasons. Darwin theorized that human beings would probably never actually be able to witness evolution in action, because the changes would be so gradual that they would be imperceptible even to the trained observer. Fortunately, since Darwin's death, we have been able to observe evolution happen, from pepper moths in England, to antibiotic-resistant bacteria, to the African cichlids of the Rift Valley lakes. Human evolution is even more arduous to study due to our longer generation times which make major evolutionary changes difficult to observe; by the time our biologists would be ready to witness the changes, if any, in the next generation of offspring they would also be ready to retire, leaving less experienced observers to continue the project. We can, however, study isolated populations such as the Amish, and evaluate and compare their genetic changes (genetic drift) with larger, less insular groups of people.
The other major problem with studying human evolution is that the fossil record of our species is incomplete, often at the precise points in time that we most need data about. It is highly likely that none of our fossil collections of hominid ancestors include a statistically representative sample of their respective populations, as none of our fossils have been randomly collected and we do not yet have reasonable estimates of the total populations of these species. This means that the structural differences we have observed between various hominid ancestors could be caused by chance rather than speciation. Moreover, when it comes to the study of hominid ancestry, the only data we have as a basis for comparison are the structural differences observed from the skeletal remains of the fossil record, as organs and other "soft" tissues are extremely poorly preserved. Ideally, if we were trying to study the neurological changes that took place in human pre-history and later gave rise to language, we would want a large number of petrified whole brains representing the numerous different species of human ancestors from a wide range of time periods, and such fossils do not exist. Numerous inferences have been made in the study of human evolution that as cranial capacity, or brain size, increased in the hominid line, so did our cognitive abilities, but if brain size were always directly correlated with cognitive ability, we would have to acknowledge that cetaceans (e.g., whales and dolphins), have the greatest cognitive capacities of all animals since they have brains that are proportionately far larger than those of human beings.
Such a paucity of data can lead one to argue that any theories about language evolution are highly conjectural; indeed, a number of inappropriate uses of adaptive theorizing have appeared throughout the literature. Pinker and Bloom warn against these kinds of arguments and characterize them as "ad hoc" and "arbitrary." The example they provide is an anecdote about Voltaire ridiculing a colleague who is wondering why spandrels exist at the San Marco Basilica in Venice; Voltaire declares that the spandrels are there because they have to be, just as noses were made for our glasses to perch on and legs were designed for pants.18 This clearly illustrates the dangers of positing ad hoc or arbitrary evolutionary hypotheses, as cause and effect can become completely obscured.
Ad hoc and arbitrary evolutionary theories can also become self-fulfilling in the sense that if a researcher is actively looking for adaptations that perform some evolutionarily advantageous function, he or she can be lead by their biases into almost always finding examples. This is because practically every structure that is not vestigial or blatantly deleterious can ultimately be argued to perform some kind of function that is perceived to be advantageous to the organism that possesses it.19 By this kind of reasoning (also known as naive adaptationism), the extremely slow reproduction rate of the Giant Panda could be argued to be an advantageous adaptation because it might allow the mother Panda to extend her reproductive lifespan by conserving more energy, even though their slow reproductive rate (coupled with habitat destruction) is now contributing to the decline of the species. But ultimately in science, hypotheses are just hypotheses until definitive data have been observed, published, and debated in peer-reviewed journals. In short, the lack of data available to evolutionary biologists has certainly been the largest blight to research on the origins of language.20
Language and Human Pre-History
The study of the evolution of language, however, is not relegated completely to making hypothetical statements that may ultimately be impossible to validate. We have found a large number of fossils of human ancestors and pre-historic Homo sapiens, and many of the artifacts found with these fossils have given us volumes of information about the subsistence patterns and lifestyles of human ancestors and early humans. One prevalent theme in the hominid archaeological record is that large amounts of tools first started appearing in human history around 2.3 million years ago in the context of the first member of the genus Homo, who was actually named after these tool associations. Homo habilis literally means 'habile man', or handyman, as tools have never been found in such high concentrations with the earlier members of the hominid line, the Australopithecines.21
The evidence that Homo habilis was probably the first of the hominids to make sturdy, lithic tools strongly suggests that Homo habilis may have had greater cognitive capabilities than his precursors. Because of this, researchers have looked for any signs that the structure of the brain of Homo habilis is different, or more complex than the brain structure of Australopithecus. ince the soft organs have long since biodegraded away, the best current method to evaluate structural neural changes in hominid fossils is by taking cranial endocasts, or plaster casts of the inside of the brain case of fossilized hominid skulls. Botha and Giv�n both discuss research that suggests that certain cerebral structures started appearing for the first time in Homo habilis that are now known to be necessary for producing language.22 Apparently, according to the cranial endocasts, the parietal, occipital, and temporal lobes of the brain merge for the first time in Homo habilis, creating an area of the brain called the POT, or Wernicke's Area.23 Broca's Area, one of the other highly important areas involved in language production and processing, can supposedly also be observed for the first time in the hominid line from endocasts of Homo habilis skulls. The argument that follows from this evidence is that the Broca's and Wernicke's areas were selected for in Homo habilis in order to make tools (and probably also for gathering food and hunting), but were subsequently exapted by later humans for the purposes of language production and processing.24
Unfortunately, cranial endocasts cannot usually provide any conclusive evidence about structural evolutionary changes in the human brain due to the lack of representative populations of fossils (mentioned earlier), and because cranial endocasts can only be made well from craniums that can be pieced back together or are more or less complete, which are not as frequent in the archaeological record as disarticulated skull fragments. Moreover, cranial endocasts only show the structure of the surface of the brain, and only insofar as it is reflected by the contours of the inside of the skull. They tell us nothing of structural changes that may or may not have taken place deep inside the cerebrum itself, and they cannot show whether the individual possessing the skull had any lesions, necrosis, or other areas of damage caused by something that would not be shown on the skull (i.e., a stroke, as opposed to blunt head trauma).
The Brains of Other Animals: Exaptation and Language
There are better ways to get a sense of the kinds of cognitive abilities that early humans might have had that are more observable in both the fossil record and in modern, living animals. Hauser et al. have shown that one of our more genetically distant primate relatives, the cotton-top tamarin (Saguius oedipus), can learn to generalize algebraic rules, which is also a skill that human infants use in acquiring language.25 If this skill is important for cotton-top tamarins (which have a brain capacity about the size of a squirrel or a rat) for some aspect of living in their environment, it can be posited that some of the cognitive processes underlying language probably existed in the most distant human/primate ancestors. Since the common ancestor that humans share with tamarins has been extinct for millions of years, subjecting it to a battery of cognitive tests is impossible. Also, since this ancestor occurred so early in the history of primates, one of two outcomes becomes possible: either the human/tamarin coancestor needed the ability to generalize rules, or humans and tamarins (and all the other primates, for that matter) developed this adaptation independently because it has been favored in all the different environments in which primates live.26
Since the latter scenario is statistically far less likely and genetic testing has confirmed taxonomists' suspicions in pointing out a common ancestor of humans and tamarins, it is highly possible that the primate lineage had rule learning sorted out tens of millions of years ago. Most importantly, as tamarins and humans appeal to similar cognitive structures for this rule learning ability, and humans have language while tamarins do not, language definitely relies on cognitive processes that are useful for other things. This increases the likelihood that language, or at least the rule learning parts of it, were exapted the way bird feathers probably were.27
Another similar argument for the exaptation of certain aspects of language has been discussed only recently and comes from the optic tectum, a structure located in the midbrain of many reptiles and birds, such as barn owls (Tyto alba).28 The barn owl needs to be able to create a mental map localizing the source of prey sounds from purely auditory information, in order to effectively hunt in almost total darkness. An auditory-visual modality crossover similar to the barn owl's optic tectum is found in humans and not only enables us to visualize where a sound might be located in a space, but is also necessary for the modality shift required to code our lexicon.29 While bird and human brains are organized very differently, we have evolved similar cognitive processes for situating and relating sounds in space, which further suggests that the neural structures or pathways that make our language possible would surely be useful for other purposes.30
In fact, numerous cognitive processes that humans use for language are also found in non-human primates.31 Studies of evoked responses in human and macaque brains have shown that we use two basic neural pathways for language and cognition, and both pathways are generated from a point very close to the same basic region in the occipital lobe, known as Wernicke's Area in humans and the F5 region in other primates. The ventral pathway (or ventral stream) shared by humans and primates emanates from the occipital and proceeds through the temporal lobe, terminating in a region of the brain that includes the paleo-cortex and the amygdala. Both humans and primates use this pathway for object recognition and actions, although humans use it expressly for semantic memory, verbs, and the lexicon. The other pathway, which projects from the occipital region and progresses to the posterior part of the parietal lobe is called the dorsal stream, and it terminates in the subcortical limbic region of the hippocampus. This neural pathway is used by both humans and primates for processing motion and spatial relationships, but humans also use it for processing episodic memory and prepositions.32
If the neural hardware for so many aspects of language exists in non-human primates, then one should ask why humans are the only animals that have language. A casual observer might note that since we are more than 98% genetically identical to chimpanzees, then chimpanzees should be able to develop language also. Pinker points out that the hyrax (Procavia capensis), a very small rodent-like mammal that is 98% genetically identical to the African elephant, not only lacks a trunk, but scarcely resembles an elephant at all.33 Chimpanzees do have a rich system of communication, do use tools, and do have something that resembles human culture in the sense that different communities of chimpanzees teach their offspring how to subsist in different ways, depending on how their parents were taught, but they do not have language, a system that enables an infinite possibility of utterances.
Natural Selection and Language
Although Pinker asserts that the process of natural selection is more than sufficient to explain the evolution of the entirety of language, the recent research from Giv�n mentioned above shows that a large portion of our language abilities are derived from neural structures that an ancestor of ours probably already had, meaning they were probably exapted.34 However, exaptation cannot account for all of language, and the best evolutionary theory to explain the evolution of the facet of language known as grammar is regular old Darwinian natural selection.35
Studies of Pidgin languages and pre-grammatical child speech have shown us that vocabulary is always acquired before grammar;36 moreover, in cases of agrammatic aphasia (also known as Broca's aphasia, because the Broca's area is affected), the lexicon is preserved, allowing the patient to comprehend and actually produce connected discourse without grammar, a capability unique to the agrammatic form of aphasia. This may help explain our abilities to successfully communicate more ideas to chimpanzees and gorillas with a limited sign vocabulary than we can communicate to dogs (for instance). This mutual primate ability stems from our shared pathways for object recognition and episodic memory; but since natural selection has never made the ability to acquire grammar a favorable adaptation in chimpanzees, they will never be able to generate grammatically correct sentences.37 Accordingly, evoked responses are not activated in the primate brain in a similar way to the human brain when it processes grammatical information.
Of course, there are a number of arbitrary interpretations one can conjure up in order to explain how grammar was selected for, and many of these arguments take the form of explaining why humans have language and animals do not. Although many of these observations are purely speculative at this stage in our evaluations of language origins, hypotheses need to be forwarded so that they can ultimately be tested and challenged, and there are some very clear selective advantages that language provides. While it is clear that language enables its users to communicate salient events, it is not clear that communicating narrative events is the most important function of language, nor that the evolution of language made civilization itself possible, as an agrammatic complex society could theoretically exist.38 However, language has a vast number of attributes that seem to confirm its obvious adaptive benefits. Having language streamlines the teaching process and makes it possible without props, which is what chimpanzees have to use to teach their offspring.39 Language does not always need to rely on facial expressions to transmit meaning, so verbal language can take place easily in the dark (this also explains why verbal languages may have appeared chronologically later and lasted longer than gesture-based language systems).40 Language can be used to send or leave information without requiring the physical presence of a group member, especially if it is written down. Because of its ability to generate an infinite number of utterances, language can potentially describe or explain anything that happens.
Most importantly, human grammar greatly increased linguistic complexity, making it infinitely descriptive, converting our communicative system based on static labels and verbs into language. Among the enormous number of conceivable advantages that language brought our species undoubtedly lie some reasons that are not ad hoc and arbitrary and that would help explain why natural selection favored the probable evolution of grammar in language sometime around the appearance of the first archaic Homo sapiens, ca. 400,000 years ago or less.41
The most current evidence illustrates that language has characteristics that appear to have been exapted from primate neural pathways, and other characteristics that appear to have been naturally selected for by the prehistoric human environment.42 Our abilities for object recognition and semantic memory, in addition to spatial relations and episodic memory evolved much the same way as bird feathers did, meaning we first used these cognitive skills for finding food and mates and escaping predators, the central concerns of most vertebrates. Human grammar, which makes human language possible, conversely appears to have originated because it provided those who possessed it with a decisive reproductive advantage over those who did not, just as the vertebrate eye bestowed a definite advantage over the first vertebrates who could see.43 The broad thrust of theorists responding to Pinker and Bloom, then, casts language as a remarkable product of exaptation, leading to the development of a complex lexicon, and natural selection, leading to the development of grammar. If future empirical evidence can provide concrete validation for these theories, not only will evolutionary biology be provided with a marvelous example of how varying evolutionary processes can interact in order to produce complex traits, but we will gain valuable insight into exactly where and how human cognitive capacities have diverged from those of our closest primate relatives. Language Origins:Did Language Evolve Like the Vertebrate Eye, or Was It More Like Bird Feathers?

Scientists Finally Figure Out How Bees Fly

Proponents of intelligent design, which holds that a supreme being rather than evolution is responsible for life's complexities, have long criticized science for not being able to explain some natural phenomena, such as how bees fly.
Now scientists have put this perplexing mystery to rest.
Using a combination of high-speed digital photography and a robotic model of a bee wing, the researchers figured out the flight mechanisms of honeybees.
"For many years, people tried to understand animal flight using the aerodynamics of airplanes and helicopters," said Douglas Altshuler, a researcher at California Institute of Technology. "In the last 10 years, flight biologists have gained a remarkable amount of understanding by shifting to experiments with robots that are capable of flapping wings with the same freedom as the animals."
Exotic flight
The scientists analyzed pictures from hours of filming bees and mimicked the movements using robots with sensors for measuring forces.
Still frames from the bee movie.Credit: Douglas Altshuler and Jason Vance
A movie of a bee in flight, filmed at 6,000 frames per second by Douglas Altshuler and Jason Vance, is here [the link is temporary].
See Also: Flight of the Fly
Turns out bee flight mechanisms are more exotic than thought.
"The honeybees have a rapid wing beat," Altshuler told LiveScience. "In contrast to the fruit fly that has one eightieth the body size and flaps its wings 200 times each second, the much larger honeybee flaps its wings 230 times every second."
This was a surprise because as insects get smaller, their aerodynamic performance decreases and to compensate, they tend to flap their wings faster.
"And this was just for hovering," Altshuler said of the bees. "They also have to transfer pollen and nectar and carry large loads, sometimes as much as their body mass, for the rest of the colony."
Try this!
In order to understand how bees carry such heavy cargo, the researchers forced the bees to fly in a small chamber filled with a mixture of oxygen and helium that is less dense than regular air. This required the bees to work harder to stay aloft and gave the scientists a chance to observe their compensation mechanisms for the additional toil.
The bees made up for the extra work by stretching out their wing stroke amplitude but did not adjust wingbeat frequency.
"They work like racing cars," Altshuler said. "Racing cars can reach higher revolutions per minute but enable the driver to go faster in higher gear. But like honeybees, they are inefficient."
The work, supervised by Caltech's Michael Dickinson, was reported last month in the Proceedings of the National Academy of Sciences.
The scientists said the findings could lead to a model for designing aircraft that could hover in place and carry loads for many purposes such as diaster surveillance after earthquakes and tsunamis. They are also pleased that a simple thing like bee flight can no longer be used as an example of science failing to explain a common phenomenon.
Proponents of intelligent design, or ID, have tried in recent years to promote the idea of a supreme being by discounting science because it can't explain everything in nature.
"People in the ID community have said that we don't even know how bees fly," Altshuler said. "We were finally able to put this one to rest. We do have the tools to understand bee flight and we can use science to understand the world around us."

Monday, December 1, 2008

TR10: Offline Web Applications

Adobe's Kevin Lynch believes that computing applications will become more powerful when they take advantage of the browser and the desktop.

Web-based computer programs, unlike their desktop counterparts, are always up to date and are instantly available, no matter where the user is or what operating system she's running. That's why cloud computing--so called because it involves software that resides in the "clouds" of the Internet--has caused a "tidal shift in how people are actually creating software," says Kevin Lynch, chief software architect at Adobe Systems. (For a review of ­Nicholas Carr's new book on cloud computing, see "The Digital Utility.") But cloud computing has drawbacks: users give up the ability to save data to their own hard drives, to drag and drop items between applications, and to receive notifications, such as appointment reminders, when the browser window is closed.
So while many companies have rushed to send users to the clouds, Lynch and his team have been planning the return trip. With the system they're developing, the Adobe Integrated Runtime (AIR), programmers can use Web technologies to build desktop applications that people can run online or off.
The project is rooted in Lynch's recognition of both the bene­fits and the limitations of the move from desktop to Web. He envisioned hybrid applications that would allow users to take simultaneous advantage of the Interne­t and their own machines' ­capa­bil­i­ties. Lynch's team started work on the concept in 2002 and launched AIR in beta last June.
AIR is a "runtime environment," an extra layer of software that allows the same program to run on different operating systems and hardware. (Java is another example.) With AIR, developers can use Web technologies such as HTML and Flash to write software for the desktop. Users won't have to seek out AIR to enjoy its bene­fits; they'll be prompted to download it along with the first AIR applications they want to use.
The Adobe team chose to base the system on HTML and Flash for several reasons, Lynch says. First, it makes it easy for desktop applications to swap content with websites: for example, information from a website can be pulled into an AIR application with its formatting intact. Second, it should simplify development, encouraging a broader range of applications. Programmers can easily rebuild existing Web applications to work on the desktop. And in the same way that Web-based applications can be built once and will then run on any device with a browser, an application built on AIR will run on any machine that has AIR installed. (Adobe currently offers versions for Windows and ­Macintosh and is developing versions for Linux and mobile devices.)
Adobe is already working with partners to demonstrate AIR's capabilities. One example: the popular auction site eBay has released a beta AIR-based application called eBay Desktop. Designed to improve the customer's bidding experience, the application itself retrieves and displays content about eBay auctions rather than relying on a browser. It also takes advantage of the processing power of the user's computer to provide search tools more powerful than those on the website. For example, it can scan search results for related keywords--a process that product manager Alan Lewis says works better on the desktop because the applicatio­n can store and quickly access lots of relevant information on the user's computer. The program also uses desktop alerts to notify users when someone bids on auctions they are following. AIR enabled the company to create a customized user interface, without constraints imposed by the browser's design and controls.
Lynch says that AIR was a response to the Web's evolution into a more interactive medium. The browser, he notes, was created for "the Web of pages"; while developers have stretched what can be done with it, Lynch sees the need for an interface more appropriate to the Web of software that people use today. AIR, he hopes, will be just that.

Sunday, November 30, 2008

NASA Tests the Interplanetary Internet

A system designed to make space communications more robust passes its first test.

A spacecraft 20 million miles away from Earth recently sent the first dozens images back to our planet using a completely new kind of space communications: the Interplanetary Internet.
This system is being developed by NASA's Jet Propulsion Laboratory (JPL) as a more robust way to communicate in space, modelled on the terrerstrial Internet. The project is being led by Google's vice president and chief internet evangelist, Vint Cerf, who designed many of the networking protocols that launched the Internet in the 1970s. Last month, Cerf talked about the Interplanetary Internet with Technology Review and discussed a crucial protocol called Disruption-Tolerant Networking (DTN).
NASA will be testing the new communications link for a month or so to qualify the technology for use on a variety of upcoming space missions.

Saturday, November 29, 2008

Untangling Web Information

The Semantic Web organizer Twine offers bookmarking with built-in AI.
Tied together: Twine lets users create or join "twines" devoted to a particular topic in order to collect, share, and discuss information. But Twine’s semantic AI engine also helps users discover related information and people with similar interests. 
Credit: Twine
MULTIMEDIA
video Watch TR’s reporter use Twine and discuss its features.

The next big stage in the evolution of the Internet, according to many experts and luminaries, will be the advent of the Semantic Web--that is, technologies that let computers process the meaning of Web pages instead of simply downloading or serving them up blindly. Microsoft's acquisition of the semantic search enginePowerset earlier this year shows faith in this vision. But thus far, little Semantic Web technology has been available to the general public. That's why many eyes will be on Twine, a Web organizer based on semantic technology that launches publicly today.

Developed by Radar Networks, based in San Francisco, Twine is part bookmarking tool, part social network, and part recommendation engine, helping users collect, manage, and share online information related to any area of interest. For the novice, it can be tricky figuring out exactly where to start. But for experienced users, Twine can be a powerful way to research a subject collaboratively or find people with common interests, with the usual features of a bookmarking site augmented by Twine's underlying semantic technology.

After creating an account, a user adds a Twine bookmarklet to her browser's bookmarks, then adds items to her Twine page by clicking the bookmarklet as she surfs the Web. Bookmarks, too, can easily be imported from a browser or from another Web bookmarking service.

Twine uses artificial intelligence--machine learning and natural language processing--to parse the contents of Web pages and extract key concepts, such as people, places, and organizations, from the pages that a user saves. The site then uses these concepts to link information and users. For example, creating a twine--a bundle of bookmarks related to a particular topic--devoted to a specialized technique in computer game design quickly led to the discovery of twines (created by other users) devoted to other areas of game design and to twines devoted to a popular game that uses the technique. It also led to other users interested in the subject. Twine is also meant to automatically generate tags, descriptions, and summaries of bookmarked Web pages. In the preview, or beta, version, this feature didn't always work properly, but Nova Spivack, CEO of Radar Networks, says that the functionality has been improved ahead of the public launch. Twines offer a hub for collecting, sharing, and discussing information. For example, users have created twines devoted to twentieth-century music, science and technology, philosophy, and cool things found around the Web.

Highly Efficient Lithium Batteries Could Greatly Extend Battery Life Of Laptop Computers

ScienceDaily (Nov. 29, 2008) — Rechargeable lithium ion batteries provide portable devices that require a lot of energy, such as mobile telephones, digital cameras, and notebook computers, with power. However, their capacity, and thus the running time of the devices, remain somewhat limited. A notebook computer thus usually runs only about two hours.

The reason for this is the relatively small capacity of the graphite anode in these batteries to absorb lithium ions. A team led by Jaephil Cho at Hanyang University in Korea has now developed a new material for anodes, which could clear a path for a new generation of rechargeable batteries. As reported in the journal Angewandte Chemie, their new material involves three-dimensional, highly porous silicon structures.

Lithium ion accumulator batteries produce current by moving lithium ions. The battery usually contains a cathode (positive electrode) made of a mixed metal oxide, such as lithium cobalt oxide, and an anode (negative electrode) made of graphite. While the battery is being charged, lithium ions migrate into the anode, where they are stored between the graphite layers. When the battery is being discharged, these ions migrate back to the cathode.

It would be nice to have an anodic material that could store more lithium ions than graphite. Silicon presents an interesting alternative. The problem: silicon expands a great deal while absorbing lithium ions (charging) and shrinks when giving them up (discharging). After several cycles the required thin silicon layers are pulverized and can no longer be charged.

Cho’s team has now developed a new method for the production of a porous silicon anode that can withstand this strain. They annealed silicon dioxide nanoparticles with silicon particles whose outermost silicon atoms have short hydrocarbon chains attached to them at 900 °C under an argon atmosphere. The silicon dioxide particles were removed from the resulting mass by etching. What remained were carbon-coated silicon crystals in a continuous, three-dimensional, highly porous structure.

Anodes made of this highly porous silicon have a high charge capacity for lithium ions. In addition, the lithium ions are rapidly transported and stored, making rapid charging and discharging possible. A high specific capacity is also attained with high current. The changes in volume that occur upon charging and discharging cause only a small degree of swelling and shrinking of the pore walls, which have a thickness of less than 70 nm.

In addition, the first charging cycle results in an amorphous (noncrystalline) silicon mass around residual nanocrystals in the pore walls. Consequently, even after 100 cycles, the stress in the pore wall is not noticeable in the material.


Journal reference:

  1. . Three-Dimensional Porous Silicon Particles for Use in High-Performance Lithium Secondary Batteries.Angewandte Chemie International Edition, DOI:10.1002/anie.200804355

Opening the Cloud

Open-source cloud-computing tools could give companies greater flexibility.

Credit: Technology Review

Cloud-computing platforms such as Amazon's Elastic Compute Cloud (EC2), Microsoft's Azure Services Platform, and Google App Engine have given many businesses flexible access to computing resources, ushering in an era in which, among other things, startups can operate with much lower infrastructure costs. Instead of having to buy or rent hardware, users can pay for only the processing power that they actually use and are free to use more or less as their needs change.

However, relying on cloud computing comes with drawbacks, including privacy, security, and reliability concerns. So there is now growing interest in open-source cloud-computing tools, for which the source code is freely available. These tools could let companies build and customize their own computing clouds to work alongside more powerful commercial solutions.

One open-source software-infrastructure project, called Eucalyptus, imitates the experience of using EC2 but lets users run programs on their own resources and provides a detailed view of what would otherwise be the black box of cloud-computing services.

Another open-source cloud-computing project is the University of Chicago's Globus Nimbus, which is widely recognized as having pioneered the field. And a European cloud-computing initiative coordinated by IBM, called RESERVOIR, features several open-source components, including OpenNebula, a tool for managing the virtual machines within a cloud. Even some companies, such as Enomaly and 10gen, are developing open-source cloud-computing tools.

Rich Wolski, a professor in the computer-science department at the University of California, Santa Barbara, who directs the Eucalyptus project, says that his focus is on developing a platform that is easy to use, maintain, and modify. "We actually started from first principles to build something that looks like a cloud," he says. "As a result, we believe that our thing is more malleable. We can modify it, we can see inside it, we can install it and maintain it in a cloud environment in a more natural way."

Reuven Cohen, founder and chief technologist of Enomaly, explains that an open-source cloud provides useful flexibility for academics and large companies. For example, he says, a company might want to run most of its computing in a commercial cloud such as that provided by Amazon but use the same software to process sensitive data on its own machines, for added security. Alternatively, a user might want to run software on his or her own resources most of the time, but have the option to expand to a commercial service in times of high demand. In both cases, an open-source cloud-computing interface can offer that flexibility, serving as a complement to the commercial service rather than a replacement.

Memristors Make Chips Cheaper

The first hybrid memristor-transistor chip could be cheaper and more energy efficient.
Hardware upgrade: Researchers removed transistors from the bottom layer of this silicon-based chip (shown in yellow and blue) and replaced them with fewer memristors in the top layer (shown in red). Memristors can do the work of transistors but require less power and space. According to HP, they could revolutionize integrated circuits and memory technology. 
Credit: Qiangfei Xia, HP
MULTIMEDIA
video Watch an introduction to memristors.

Entire industries and research fields are devoted to ensuring that, every year, computers continue getting faster. But this trend could begin to slow down as the components used in electronic circuits are shrunk to the size of just a few atoms. Researchers at HP Labs in Palo Alto, CA, are betting that a new fundamental electronic component--the memristor--will keep computer power increasing at this rate for years to come.

Memristors were first predicted in 1971 by Berkeley professor Leon Chua. They are nanoscale devices with unique properties: a variable resistance and the ability to remember the resistance even when the power is off.

After rediscovering Chua's work, researchers at HP Labs built the first working memristor in May of this year. And last week, at the first ever Memristor and Memristor Systems Symposium, in Berkeley, CA, the same team showed how memristors can be integrated into functioning circuits. Their circuits require fewer transistors, allowing more components (and more computing power) to be packed into the same physical space while also using less power to function.

"We're trying to give Moore's Law a boost," says lead researcher Stan Williams, a senior research fellow at HP, referring to a prediction made by Intel founder Gordon Moore that the number of transistors on a computer circuit (and therefore computer performance) should double roughly every two years.

Increasing performance has usually meant shrinking components so that more can be packed onto a circuit. But instead, Williams's team removes some transistors and replaces them with a smaller number of memristors. "We're not trying to crowd more transistors onto a chip or into a particular circuit," Williams says. "Hybrid memristor-transistor chips really have the promise for delivering a lot more performance."

A memristor acts a lot like a resistor but with one big difference: it can change resistance depending on the amount and direction of the voltage applied and can remember its resistance even when the voltage is turned off. These unusual properties make them interesting from both a scientific and an engineering point of view. A single memristor can perform the same logic functions as multiple transistors, making them a promising way to increase computer power. Memristors could also prove to be a faster, smaller, more energy-efficient alternative to flash storage.

Although memristor research is still in its infancy, HP Labs is working on a handful of practical memristor projects. And now Williams's team has demonstrated a working memristor-transistor hybrid chip.

Saturday, November 8, 2008

PUTTING PSYCHOLOGY INTO BEHAVIORAL ECONOMICS


Richard Thaler, Sendhil Mullainathan, Daniel Kahneman





RICHARD THALER: Behavioral economics and good psychology, there's a lot of art. There is science and there are well-crafted experiments, but thinking about what the right experiment to run, was art and, there are 80 gazillion experiments, which ones are relevant to getting people to plant the right seed. That's a problem that Sendhil and I have been talking about for, well, since he was born. You're now seeing the results of 15 years of conversations. And there wasn't a scientific way of answering that question.
SENDHIL MULLAINAITHAN: A lot of what makes behavioral economics interesting is psychology, it is about what happens inside the mind. These phenomena are taking things that are happening inside the mind and interfacing them with things happening in the world, the environment, and getting feedback or getting interesting responses from that.
We happen to call the word economics. But it's not economics. You could be talking about crime, you could be talking about many things, in the social domain, the entire spectrum of human behavior. Anyone who is interested in the broader world should be interested in something we currently call "behavioral economics".
DANIEL KAHNEMAN: What we're saying is that there is a technology emerging from behavioral economics. It's not only an abstract thing. You can do things with it. We are just at the beginning. I thought that the input of psychology into behavioral economics was done. But hearing Sendhil was very encouraging because there was a lot of new psychology there. That conversation is continuing and it looks to me as if that conversation is going to go forward. It's pretty intuitive, based on research, good theory, and important.
Sean Parker, Anne Treisman, Paul Romer, Danny Hillis, Jeff Bezos, Salar Kamangar, George Dyson, France LeClerc



Saturday, November 1, 2008

Hubble Back In Business: Pair Of Gravitationally Interacting Galaxies In Full View

Perfect "10" due to the chance alignment of two galaxies. The left-most galaxy, or the "one" in this image, is relatively undisturbed, apart from a smooth ring of starlight. It appears nearly edge-on to our line of sight. The right-most galaxy, the "zero" of the pair, exhibits a clumpy, blue ring of intense star formation. (Credit: NASA, ESA, and M. Livio (STScI))

ScienceDaily (Nov. 1, 2008) — The Hubble Space Telescope is back in business with a snapshot of the fascinating galaxy pair Arp 147.

Just a couple of days after the orbiting observatory was brought back online, Hubble aimed its prime working camera, the Wide Field Planetary Camera 2 (WFPC2), at a particularly intriguing target, a pair of gravitationally interacting galaxies called Arp 147.

The image demonstrated that the camera is working exactly as it was before going offline, thereby scoring a "perfect 10" both for performance and beauty.

And literally "10" for appearance too, due to the chance alignment of the two galaxies. The left-most galaxy, or the "one" in this image, is relatively undisturbed, apart from a smooth ring of starlight. It appears nearly edge-on to our line of sight. The right-most galaxy, the "zero" of the pair, exhibits a clumpy, blue ring of intense star formation.

The blue ring was formed after the galaxy on the left passed through the galaxy on the right. Just as a pebble thrown into a pond creates an outwardly moving circular wave, or ripples, an outwardly propagating ring of higher density was generated at the point of impact of the two galaxies. As this excess density collided with outer material that was moving inwards due to the gravitational pull of the two galaxies, shocks and dense gas were produced, stimulating star formation.

The dusty reddish knot at the lower left of the blue ring probably marks the location of the original nucleus of the galaxy that was hit.

Arp 147 appears in the Arp Atlas of Peculiar Galaxies, compiled by Halton Arp in the 1960s and published in 1966. This picture was assembled from WFPC2 images taken with three separate filters. The colours blue, green, and red represent the blue, visible-light, and infrared filters respectively.

The galaxy pair was photographed on 27-28 October 2008. Arp 147 lies in the constellation of Cetus, more than 400 million light-years away from Earth.


Adapted from materials provided by ESA/Hubble Information Centre.

Computing with RNA: Devices that self-assemble from biological molecules could represent the future of drug delivery.

Credit: Technology Review

Scientists in California have created molecular computers that are able to self-assemble out of strips of RNA within living cells. Eventually, such computers could be programmed to manipulate biological functions within the cell, executing different tasks under different conditions. One application could be smart drug delivery systems, says Christina Smolke, who carried out the research with Maung Nyan Win and whose results are published in the latest issue of Science.

The use of biomolecules to perform computations was first demonstrated by the University of Southern California'sLeonard Adleman in 1994, and the approach was later developed by Ehud Shapiro of the Weizmann Institute of Science, in Rehovot, Israel. But according to Shapiro, "What this new work shows for the first time is the ability to detect the presence or absence of molecules within the cell."

That opens up the possibility of computing devices that can respond to specific conditions within the cell, he says. For example, it may be possible to develop drug delivery systems that target cancer cells from within by sensing genes used to regulate cell growth and death. "You can program it to release the drug when the conditions are just right, at the right time and in the right place," Shapiro says.

Smolke and Win's biocomputers are built from three main components--sensors, actuators, and transmitters--all of which are made up of RNA. The input sensors are made from aptamers, RNA molecules that behave a bit like antibodies, binding tightly to specific targets. Similarly, the output components, or actuators, are made of ribozymes, complex RNA molecules that have catalytic properties similar to those of enzymes. These two components are joined by yet another RNA molecule that serves as a transmitter, which is activated when a sensor molecule recognizes an input chemical and, in turn, triggers an actuator molecule.

Smolke and Win designed their RNA computers to detect the drugs tetracycline and theophylline within yeast cells, producing a fluorescent protein as an output. By combining the RNA components in certain ways, the researchers showed that they can get them to behave like different types of logic gates--circuit elements common to any computer. For example, an AND gate produces an output only when its inputs detect the presence of both drugs, while a NOR gate produces an output only when neither drug is detected.

But this is just a demonstration, Smolke says. "We're using these modular molecules that have a sort of plug-and-play capability," she says--meaning that they can be combined in a number of different ways. Different kinds of aptamers could potentially detect thousands of different metabolic or protein inputs.

Smolke and Win produce their device by encoding RNA sequences into DNA and introducing it into the cell. "So the cell is making these devices," Smolke says. "RNA is actually a very programmable substrate."

Indeed, the attractive thing about this approach is that the components of the device and the substrate holding them together are all made from RNA, says Friedrich Simmel, a bioelectronics researcher at the Technical University of Munich, in Germany. "This is something that we also would like to do," he says, for not only do such devices self-assemble, but they can also be produced on a single long strand of RNA, all at once.

Smolke and Win have already found collaborators for possible animal studies, to see how biocomputers can be delivered to cells and used once they're there. Smolke also envisions a large-scale collaboration to create a huge library of sensors out of which these devices can be made.

Mimicking Body Biosensors: Artificial antibodies could be used in cheap, field-ready toxin sensors.

Lock and key: An artificial antibody targets a toxic protein called melittin (top). The polymer “antibody” is grown around melittin, shaping it into a binding shell (middle). When the melittin is rinsed away, the polymer retains its shape (bottom) and is ready to bind with the protein again. 
Credit: Kenneth Shea

Antibodies aren't just a critical part of the body's defense against disease: they're also the gold standard for biosensing. These natural proteins are widely used in diagnostic tests for cancer and other diseases because they recognize and bind so efficiently to disease markers, which include bacterial and viral proteins and protein fragments. However, protein antibodies are expensive to synthesize in the lab and only last a few months. Now biochemists have developed a method to make artificial antibodies that may be just as effective as the real thing.

Researchers have been working on synthetic antibodies for about twenty years. Artificial antibodies, made from polymers rather than proteins, promise to be cheap and long lasting, says Kenneth Shea, a professor of chemistry at the University of California, Irvine, who led development of the new method. However, no one has been able to make artificial antibodies that bind their targets as tightly and as specifically as natural antibodies do.

To make the new and improved artificial antibodies, Shea and his collaborators at the Tokyo Institute of Technology refined a technique called molecular imprinting. This involves taking a target molecule and placing it in a solution containing the building blocks of a polymer antibody. The polymer then grows around its target, conforming to its shape; once it's done, the target molecule is rinsed away. Then, when the artificial antibody next meets the target molecule, they fit together like a key in a lock. "You can make a mold around almost any molecule," explains Klaus Mosbach, founder of the Center for Molecular Imprinting at the Center for Chemistry and Chemical Engineering, in Lund, Sweden, who pioneered the technique.

Molecular imprinting is "a beautiful idea and a great technology," says Vincent Rotello, a professor of chemistry at the University of Massachusetts Amherst. Plastic antibodies have found some industrial applications, mostly for separating small molecules out of solutions. But they have not been suitable for therapeutic, diagnostic, or biosensing applications because none that have been made work as well as natural antibodies in water-based solutions such as blood. And they could not be made to effectively target large molecules such as proteins.

The researchers developed much better plastic antibodies by enhancing the imprinting process in a novel way. Shea and his collaborators started with a target protein, melittin, and screened libraries of polymer building blocks for those that would bind to it most effectively. "Some effort went into determining the composition that would minimize interaction with [nontarget] garden-variety proteins," says Shea. His artificial antibody has a high affinity for its target protein, comparable in strength to that of a natural antibody, and also works in water solutions. The synthesis is described in a paper in the Journal of the American Chemical Society. 

Shea says that better synthetic antibodies could be used therapeutically in parts of the body where normal antibodies break down quickly, such as the digestive tract. They could also be used in portable devices designed to detect traces of chemical weapons.

The new method for making the artificial antibodies is "a dramatic breakthrough," says Ken Shimizu, a chemist at the University of South Carolina. "People always say their polymers work a lot like antibodies, but in truth, they never did." He adds that Shea's work comes close to living up to this promise. "This is the first time you could imagine these [synthetics] would rival antibodies."

David Spivak, a chemistry professor at Louisiana State University, agrees that Shea's work is "the first example of an imprinted polymer acting like an antibody." Spivak expects that Shea's method will work with other target molecules, including proteins besides melittin. Indeed, Shea says that he is working on targeting about five more complex proteins.

However, some chemists are skeptical that Shea's artificial protein is targeting melittin like a real antibody. They suggest that melittin, which has positively charged regions, may simply be attracted to negative charge on the polymer. But Shea says he selected polymer building blocks based on their ability to bind regions of melittin, and that he has performed controlled experiments to demonstrate that the binding is indeed specific. Further, he says that he has unpublished work showing that his polymer binds to melittin in cell cultures and in small animals, suppressing its toxic activity.