Clusters of living worlds would hint life came from outer space
Using future telescopes to map exoplanets where life may exist could help test the panspermia theory - that life can cross space and take root on new worlds
Layer of melting ice helps spheres fall faster through water
Skaters know melting ice cuts friction, it turns out the trick works under water too. Balls coated in ice fell faster in a tank of water as the coating melted
Bitter foods are healthy: How to cook them like a pro
Learn how to cook with bitter foods and you can reap their health benefits and enjoy the delicious taste too, says chef and author Jennifer McLagan
The apps that let you earn money while you holiday
New gig economy apps that let you take on small tasks while travelling are a clever way of making a bit of extra spending money for your trip
Neptune’s sudden jolt could explain weird ring in Kuiper belt
A band of strangely tight-knit icy objects in the Kuiper belt has defied explanation. Now a simulation rewinding the solar system to its babyhood has an answer
Enjoy Your Romaine Lettuce—While It Lasts
While the Central Valley's farm economy reels under the strain of drought, farms in the Salinas Valley are operating on all cylinders.
The post Enjoy Your Romaine Lettuce—While It Lasts appeared first on WIRED.
A simulated robot with bacterial brain
Computational Simulation of microbiome-host interactions. (A) A basic gene circuit forms the core of all simulated gene network behavior. (B) Green fluorescent protein (GFP, shown as a green dot) from this circuit is conceptualized to be detected by an onboard miniature, epifluorescent microscope (EFM). (C) A computational simulation of microbiome GFP production based upon an analytical model for the circuit in (A). In a built system, this protein fluorescence signal would be the light detected by the EFM. (D) The conceptualized robot uses onboard electronics to convert the measured light signals into electrical (voltage) signals. (E) Voltage signals meeting specific criteria activate pre-programmed robot motion subroutines. (F) The resulting emergent behavior potentially leads a robot to a carbon fuel depot. Here, robot behavior resulting from a simulation of the circuit in (A) is shown. The robot was programmed with motion subroutines that activate to seek arabinose (synthesized from glucose, orange square) depots following receipt of lactose (cyan triangles). (credit: Keith C. Heyde & Warren C. Ruder/Scientific Reports)
Virginia Tech scientist Warren Ruder, an assistant professor of biological systems engineering, has created an in silico (computer-simulated) model of a biomimetic robot controlled by a bacterial brain.
The study was inspired by real-world experiments where the mating behavior of fruit flies was manipulated using bacteria, and in which mice exhibited signs of lower stress when implanted with probiotics (“healthy” bacteria).
A math model of microbiome-controlled behavior
The deeper motivation for the study was to understand how the microbiome (the bacteria in the human body, thought to number ten times more than human cells) might influence human behavior. For example, some studies show that the gut microbiome influences human eating behavior and dietary choices to favor the survival of the bacteria. (See Do gut bacteria control your mind? for example.)
As explained in an open-access paper published recently in Scientific Reports, Ruder’s study revealed unique decision-making behavior by a bacteria-robot system by coupling and computationally simulating equations that describe three distinct elements: engineered gene circuits in E. coli, microfluid bioreactors, and robot movement.
In the mathematical model, the theoretical robot was equipped with sensors and a miniature microscope to measure the color. The hypothetical robot was designed to read E. coli bacterial gene expression levels (how much protein is created by specific genes), using light sensors in miniature microscopes. The bacteria turned green or red, depending on what they ate.
Bacteria that act like tigers?
Interestingly, the bacteria in the model began to approach a fuel source with “stalk-pause-strike” behavior, characteristic of predators.
Ruder’s modeling study also demonstrates that these sorts of biosynthetic experiments could be done in the future with a minimal amount of funds, opening up the field to a much larger pool of researchers.
Understanding the biochemical sensing between organisms could have far reaching implications in ecology, biology, and robotics, Ruder suggests.
In agriculture, bacteria-robot model systems could enable robust studies that explore the interactions between soil bacteria and livestock. In healthcare, further understanding of bacteria’s role in controlling gut physiology could lead to bacteria-based prescriptions (probiotics) to treat mental and physical illnesses. Ruder also envisions droids that could execute tasks such as deploying bacteria to remediate oil spills.
Bacteria effects on behavior
The findings also add to the ever-growing body of research about bacteria in the human body that are thought to regulate health and mood, and especially the theory that bacteria also affect behavior.
“We hope to help democratize the field of synthetic biology for students and researchers all over the world with this model,” said Ruder. “In the future, rudimentary robots and E. coli that are already commonly used separately in classrooms could be linked with this model to teach students from elementary school through the Ph.D.-level about bacterial relationships with other organisms.”
Ruder plans next to create a real-world version of the experiment, creating mobile robots with bioreactors on board that harbor living colonies of bacteria that direct the robot’s behavior.
The Air Force Office of Scientific Research funded the mathematical modeling of gene circuitry in E. coli, and the Virginia Tech Student Engineers’ Council has provided funding to move these models and resulting mobile robots into the classroom as teaching tools.
Virginia Tech | Scientist shows bacteria could control robots
Abstract of Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells
The microbiome’s underlying dynamics play an important role in regulating the behavior and health of its host. In order to explore the details of these interactions, we created anin silico model of a living microbiome, engineered with synthetic biology, that interfaces with a biomimetic, robotic host. By analytically modeling and computationally simulating engineered gene networks in these commensal communities, we reproduced complex behaviors in the host. We observed that robot movements depended upon programmed biochemical network dynamics within the microbiome. These results illustrate the model’s potential utility as a tool for exploring inter-kingdom ecological relationships. These systems could impact fields ranging from synthetic biology and ecology to biophysics and medicine.
The brain’s got rhythm
A snapshot illustration showing how the anterior (blue) and posterior (orange) regions of the frontal cortex sync up to communicate cognitive goals to one another (credit: Bradley Voytek)
Like a jazz combo, the human brain improvises while its rhythm section keeps up a steady beat. But when it comes to taking on intellectually challenging tasks, groups of neurons tune in to one another for a fraction of a second and harmonize, then go back to improvising, according to new research led by UC Berkeley.
These findings, reported Monday (July 27) in the journal Nature Neuroscience, could pave the way for more targeted treatments for people with brain disorders marked by fast, slow, or chaotic brain waves (neural oscillations) — such as Parkinson’s disease, schizophrenia and autism, which are characterized in part by offbeat brain rhythms.
Keeping the beat
“The human brain has 86 billion or so neurons all trying to talk to each other in this incredibly messy, noisy and electrochemical soup,” said study lead author Bradley Voytek. “Our results help explain the mechanism for how brain networks quickly come together and break apart as needed.”
Working with cognitively healthy epilepsy patients, Voytek and fellow researchers at UC Berkeley’s Helen Wills Neuroscience Institute used electrocorticography (ECoG) — which places electrodes directly on the exposed surface of the brain — to measure neural oscillations as the patients performed cognitively challenging tasks. This showed how the rhythms control communication between brain regions.
They found that as the mental exercises became more demanding, theta waves at 4–8 Hertz (cycles per second) synchronized within the brain’s frontal lobe, enabling it to connect with brain sub-regions, such as the motor cortex.
“In these brief moments of synchronization, quick communication occurs as the neurons between brain regions lock into these frequencies, and this measure is critical in a variety of disorders,” said Voytek, an assistant professor of cognitive science at UC San Diego who conducted the study as a postdoctoral fellow in neuroscience at UC Berkeley.
There are five types of brain wave frequencies — Gamma, Beta, Alpha, Theta and Delta — and each are thought to play a different role. For example, Theta waves help coordinate neurons as we move around our environment, and thus are key to processing spatial information.
Off-tempo
In people with autism, the connection between Alpha waves and neural activity has been found to weaken when they process emotional images, according to Voytek. And people with Parkinson’s disease show abnormally strong Beta waves in the motor cortex, locking neurons into the wrong groove and inhibiting movement. Fortunately, electrical deep brain stimulation can disrupt abnormally strong Beta waves in Parkinson’s and alleviate symptoms,
For the study, epilepsy patients viewed shapes of increasing complexity on a computer screen and were tasked with using different fingers (index or middle) to push a button depending on the shape, color or texture of the shape. The exercise started out simply with participants hitting the button with, say, an index finger each time a square flashed on the screen. But it grew progressively more difficult as the shapes became more layered with colors and textures, and their fingers had to keep up.
As the tasks became more demanding, the oscillations kept up, coordinating more parts of the frontal lobe and synchronizing the information passing between those brain regions. “The results revealed a delicate coordination in the brain’s code,” Voytek said. “Our neural orchestra may need no conductor, just brain waves sweeping through to briefly excite neurons, like millions of fans in a stadium doing ‘The Wave.’”
Scientists at Brown University, the Department of Veterans Affairs, UCSF, Johns Hopkins University, and Stanford University were also involved in the research.
UPDATE July 29, 2015: lead author’s correction to UC Berkeley press release: “pre-frontal” in illustration caption changed to “frontal” and “connect with other brain regions” changed to “connect with brain sub-regions” (H/T to “betaelements” for those catches)
Abstract of Oscillatory dynamics coordinating human frontal networks in support of goal maintenance
Humans have a capacity for hierarchical cognitive control—the ability to simultaneously control immediate actions while holding more abstract goals in mind. Neuropsychological and neuroimaging evidence suggests that hierarchical cognitive control emerges from a frontal architecture whereby prefrontal cortex coordinates neural activity in the motor cortices when abstract rules are needed to govern motor outcomes. We utilized the improved temporal resolution of human intracranial electrocorticography to investigate the mechanisms by which frontal cortical oscillatory networks communicate in support of hierarchical cognitive control. Responding according to progressively more abstract rules resulted in greater frontal network theta phase encoding (4–8 Hz) and increased prefrontal local neuronal population activity (high gamma amplitude, 80–150 Hz), which predicts trial-by-trial response times. Theta phase encoding coupled with high gamma amplitude during inter-regional information encoding, suggesting that inter-regional phase encoding is a mechanism for the dynamic instantiation of complex cognitive functions by frontal cortical subnetworks.
How hybrid solar-cell materials may capture more solar energy
Innovative techniques for reducing solar-cell installation costs by capturing more solar energy per unit area by using hybrid materials have recently been announced by two universities.
Capturing more of the spectrum
Chemists at the University of California, Riverside have found an ingenious way to lower solar cell installation costs by reducing the size of solar collectors (credit: David Monniaux)
The University of California, Riverside strategy for making solar cells more efficient is to use the near-infrared region of the sun’s spectrum, which is not absorbed by current solar cells.
The researchers report in Nano Letters that a hybrid material that combines inorganic materials (cadmium selenide and lead selenide semiconductor nanocrystals) with organic molecules (diphenylanthracene and rubrene) could allow for an increase of solar photovoltaic efficiency by 30 percent or more, according to Christopher Bardeen, a UC Riverside professor of chemistry.
The new material also has wide-ranging applications such as in biological imaging, data storage and organic light-emitting diodes. “The ability to move light energy from one wavelength to [a] more useful region — for example, from red to blue — can impact any technology that involves photons as inputs or outputs,” he said.
The research was supported by grants from the National Science Foundation and the U.S. Army.
Plasmonic nanostructures and metal oxides
Rice researchers selectively filtered high-energy hot electrons from their less-energetic counterparts using a Schottky barrier (left) created with a gold nanowire on a titanium dioxide semiconductor. A second setup (right), which included a thin layer of titanium between the gold and the titanium dioxide, did not filter electrons based on energy level. (credit: B. Zheng/Rice University)
Meanwhile, new research from Rice’s Laboratory for Nanophotonics (LANP) has found a way to boost the efficiency and also reduce the cost of photovoltaic solar cells by using high-efficiency light-gathering plasmonic nanostructures combined with low-cost semiconductors, such as metal oxides.
“We can tune plasmonic structures to capture light across the entire solar spectrum,” claims Rice’s Naomi Halas, co-author of an open-access paper in Nature Communications. “The efficiency of [conventional] semiconductor-based solar cells can never be extended in this way because of the inherent optical properties of the semiconductors.”
The researchers found in an experiment that a solar cell using a “Schottky barrier” device allowed only “hot electrons” (electrons in the metal that have a much higher energy level) to pass from a gold nanowire to the semiconductor, unlike an “Ohmic device,” which let all electrons pass.
Today’s most efficient photovoltaic cells use a combination of semiconductors that are made from rare and expensive elements like gallium and indium, so this finding promises to further reduce the cost of solar cells.
Abstract of Hybrid Molecule–Nanocrystal Photon Upconversion Across the Visible and Near-Infrared
The ability to upconvert two low energy photons into one high energy photon has potential applications in solar energy, biological imaging, and data storage. In this Letter, CdSe and PbSe semiconductor nanocrystals are combined with molecular emitters (diphenylanthracene and rubrene) to upconvert photons in both the visible and the near-infrared spectral regions. Absorption of low energy photons by the nanocrystals is followed by energy transfer to the molecular triplet states, which then undergo triplet–triplet annihilation to create high energy singlet states that emit upconverted light. By using conjugated organic ligands on the CdSe nanocrystals to form an energy cascade, the upconversion process could be enhanced by up to 3 orders of magnitude. The use of different combinations of nanocrystals and emitters shows that this platform has great flexibility in the choice of both excitation and emission wavelengths.
Abstract of Distinguishing between plasmon-induced and photoexcited carriers in a device geometry
The use of surface plasmons, charge density oscillations of conduction electrons of metallic nanostructures, to boost the efficiency of light-harvesting devices through increased light-matter interactions could drastically alter how sunlight is converted into electricity or fuels. These excitations can decay directly into energetic electron–hole pairs, useful for photocurrent generation or photocatalysis. However, the mechanisms behind plasmonic carrier generation remain poorly understood. Here we use nanowire-based hot-carrier devices on a wide-bandgap semiconductor to show that plasmonic carrier generation is proportional to internal field-intensity enhancement and occurs independently of bulk absorption. We also show that plasmon-induced hot electrons have higher energies than carriers generated by direct excitation and that reducing the barrier height allows for the collection of carriers from plasmons and direct photoexcitation. Our results provide a route to increasing the efficiency of plasmonic hot-carrier devices, which could lead to more efficient devices for converting sunlight into usable energy.
AI and robotics researchers call for global ban on autonomous weapons
More than 1,000 leading artificial intelligence (AI) and robotics researchers and others, including Stephen Hawking and Elon Musk, just signed and published an open letter from the Future of Life Institute (FLI) today calling for a ban on offensive autonomous weapons.
FLI defines “autonomous weapons” as those that select and engage targets without human intervention, such as armed quadcopters that can search for and eliminate people meeting certain pre-defined criteria, but do not include cruise missiles or remotely piloted drones for which humans make all targeting decisions.
The researchers believe that AI technology has reached a point where the deployment of such systems is feasible within years, not decades, and that the stakes are high: autonomous weapons have been described as the third revolution in warfare, after gunpowder and nuclear arms.
Only be a matter of time until they appear on the black market
“If any major military power pushes ahead with AI weapon development, a global arms race is virtually inevitable, and the endpoint of this technological trajectory is obvious: autonomous weapons will become the Kalashnikovs of tomorrow. Unlike nuclear weapons, they require no costly or hard-to-obtain raw materials, so they will become ubiquitous and cheap for all significant military powers to mass-produce.
“It will only be a matter of time until they appear on the black market and in the hands of terrorists, dictators wishing to better control their populace, warlords wishing to perpetrate ethnic cleansing, etc. Autonomous weapons are ideal for tasks such as assassinations, destabilizing nations, subduing populations and selectively killing a particular ethnic group. We therefore believe that a military AI arms race would not be beneficial for humanity.”
The proposed ban is similar to the broadly supported international agreements that have successfully prohibited chemical, biological weapons, blinding laser weapons, and space-based nuclear weapons.
“We believe that AI has great potential to benefit humanity in many ways, and that the goal of the field should be to do so. Starting a military AI arms race is a bad idea, and should be prevented by a ban on offensive autonomous weapons beyond meaningful human control,” the letter concludes.