Laser-based range measurement systems are important in many application areas, including autonomous vehicles, robotics, manufacturing, formation flying of satellites, and basic science. Coherent laser ranging systems using dual-frequency combs provide an unprecedented combination of long range, high...
Noninvasive deep brain stimulation is an important goal in neuroscience and neuroengineering. Optogenetics normally requires the use of a blue laser inserted into the brain. Chen et al. used specialized nanoparticles that can up-convert near-infrared light from outside the brain into the local emission of blue light (see the Perspective by Feliu et al.). They injected these nanoparticles into the ventral tegmental area of the mouse brain and activated channelrhodopsin expressed in dopaminergic neurons with near-infrared light generated outside the skull at a distance of several millimeters. This technique allowed distant near-infrared light to evoke fast increases in dopamine release. The method was also used successfully to evoke fear memories in the dentate gyrus during fear conditioning. Science, this issue p. 679; see also p. 633
How does agility evolve? This question is challenging because natural movement has many degrees of freedom and can be influenced by multiple traits. We used computer vision to record thousands of translations, rotations, and turns from more than 200 hummingbirds from 25 species, revealing that distinct performance metrics are correlated and that species diverge in their maneuvering style. Our analysis demonstrates that the enhanced maneuverability of larger species is explained by their proportionately greater muscle capacity and lower wing loading. Fast acceleration maneuvers evolve by recruiting changes in muscle capacity, whereas fast rotations and sharp turns evolve by recruiting changes in wing morphology. Both species and individuals use turns that play to their strengths. These results demonstrate how both skill and biomechanical traits shape maneuvering behavior.
In Reinventing Capitalism in the Age of Big Data, Viktor Mayer-Schönberger and Thomas Ramge argue that big data will transform our economies on a fundamental level. Money will become obsolete, they argue, replaced by metadata. Instead of a single market price for each commodity, sophisticated matching algorithms will use a bundle of specifications and personal preferences to select just the right product for you. Artificial intelligence powered by machine-learning techniques will relentlessly negotiate the best possible transaction on your behalf. Capital will still be important, they concede, but increasingly just for its signaling content. "Venture informers" might even replace venture capitalists.
No-limit Texas hold'em is the most popular form of poker. Despite artificial intelligence (AI) successes in perfect-information games, the private information and massive game tree have made no-limit poker difficult to tackle. We present Libratus, an AI that, in a 120,000-hand competition, defeated four top human specialist professionals in heads-up no-limit Texas hold'em, the leading benchmark and long-standing challenge problem in imperfect-information game solving. Our game-theoretic approach features application-independent techniques: an algorithm for computing a blueprint for the overall strategy, an algorithm that fleshes out the details of the strategy for subgames that are reached during play, and a self-improver algorithm that fixes potential weaknesses that opponents have identified in the blueprint strategy.
FRET was first identified in the 1920s by Cario, Franck, and Perrin. In the late 1940s, Förster and Oppenheimer independently formulated a quantitative theory of the energy transfer between a pair of point dipoles. Stryer and Haugland verified this theory in the late 1960s and coined the term "spectroscopic ruler" for FRET. Simultaneously, Hirschfeld, and later Moerner and Orrit, pioneered optical single-molecule detection methods leading to the first demonstration of smFRET in 1996. This breakthrough made it possible to study heterogeneous systems, dynamic processes, and transient conformational changes on the nanometer scale.
The use of dynamic, self-assembled DNA nanostructures in the context of nanorobotics requires fast and reliable actuation mechanisms. We therefore created a 55-nanometer–by–55-nanometer DNA-based molecular platform with an integrated robotic arm of length 25 nanometers, which can be extended to more than 400 nanometers and actuated with externally applied electrical fields. Precise, computer-controlled switching of the arm between arbitrary positions on the platform can be achieved within milliseconds, as demonstrated with single-pair Förster resonance energy transfer experiments and fluorescence microscopy. The arm can be used for electrically driven transport of molecules or nanoparticles over tens of nanometers, which is useful for the control of photonic and plasmonic processes. Application of piconewton forces by the robot arm is demonstrated in force-induced DNA duplex melting experiments.