Spider silk is a proteinfiber spun by spiders. Spiders use their silk to make webs or other structures, which function as sticky nets to catch other animals, or as nests or cocoons to protect their offspring, or to wrap up prey. They can also use their silk to suspend themselves, to float through the air, or to glide away from predators. Most spiders vary the thickness and stickiness of their silk for different uses.
In some cases, spiders may even use silk as a source of food. While methods have been developed to collect silk from a spider by force, it is difficult to gather silk from many spiders in a small space, in contrast to silkworm 'farms'.
Replicating the complex conditions required to produce fibers that are comparable to spider silk has proven difficult to accomplish in a laboratory environment. What follows is a miscellaneous list of attempts on this problem. However, in the absence of hard data accepted by the relevant scientific community, it is difficult to judge whether these attempts have been successful or constructive.
One approach that does not involve farming spiders is to extract the spider silk gene and use other organisms to produce the spider silk. In 2000, Canadian biotechnology company Nexia successfully produced spider silk protein in transgenicgoats that carried the gene for it; the milk produced by the goats contained significant quantities of the protein, 1–2 grams of silk proteins per liter of milk. Attempts to spin the protein into a fiber similar to natural spider silk resulted in fibers with tenacities of 2–3 grams per denier (see BioSteel). Nexia used wet spinning and squeezed the silk protein solution through small extrusion holes in order to simulate the behavior of the spinneret, but this procedure has so far not been sufficient to replicate the properties of native spider silk.
Extrusion of protein fibers in an aqueous environment is known as "wet-spinning". This process has so far produced silk fibers of diameters ranging from 10 to 60 μm, compared to diameters of 2.5–4 μm for natural spider silk.
In March 2010, researchers from the Korea Advanced Institute of Science & Technology (KAIST) succeeded in making spider silk directly using the bacteria E.coli, modified with certain genes of the spider Nephila clavipes. This approach eliminates the need to milk spiders and allows the manufacture the spider silk in a more cost-effective manner.
The company Kraig Biocraft Laboratories has used research from the Universities of Wyoming and Notre Dame in a collaborative effort to create a silkworm that has been genetically altered to produce spider silk. In September 2010 it was announced at a press conference at the University of Notre Dame that the effort had been successful.
The company AMSilk has succeeded in making spidroin using bacteria, and making it into spider silk. They are now focusing on increasing production rate of the spider silk.
The theory called Holographic Space-time is an attempt to generalize String Theory so that one can discuss local regions of space-time. It's key feature is a mapping between quantum concepts and the geometry of space-time. Causality conditions are imposed, as in quantum field theory, by insisting that things which cannot have mutual quantum interference are things that are causally separated. Geometrical sizes are encoded via the Holographic Principle: the number of quantum states in a region is determined by the area of a certain surface surrounding that region.
In 1995, Jacobson showed that one could derive Einstein's equations by imposing this principle in every space-time region. Einstein's equations are the hydrodynamic equations of a system whose statistics obeys the Holographic connection between space-time and the number of quantum states. Dr. Banks will outline the application of these ideas to a new model of the early inflationary universe, as well as to a rough prediction of the masses of supersymmetric particles.
A bird that once darkened the skies of the 19th-century U.S. no longer exists, except as well-preserved museum specimens bearing bits of DNA. An ambitious new effort aims to use the latest techniques of genetic manipulation to bring the passenger pigeon back, as North Dakotan Ben Novak, a would-be de-extinction scientist working on the Revive & Restore project at the Long Now Foundation, told the crowd at the TEDxDeExtinction event here on March 15.
"This pigeon flock was a biological storm that was rejuvenating resources and allowing other animals to thrive," Novak said of the storms of Ectopistes migratorius feces that used to fall like rain on the landscape of eastern North America. Plus, with the regrowth of forest on the east coast "there is more passenger pigeon habitat every year."
But if a bird looks like an extinct passenger pigeon, has some of the genetic code of the passenger pigeon, but does not act like a passenger pigeon because it is raised by other breeds and few in number: is it a true passenger pigeon? That is just one of the questions posed by the idea of de-extinction—deliberately resurrecting species killed off by human activity or inactivity. And that question may just challenge one of the fundamental concepts of biology: what determines a distinct species.
Welcome to the new era of the hybrid. Species have always been promiscuous and enjoyed porous boundaries, but synthetic biologists and other scientists seem set to blur those boundaries out of existence.
On July 14, 2015, the New Horizons spacecraft flew 7,800 mi above the surface of Pluto and sent back fascinating images of the dwarf planet and its large (and intriguing) moon Charon. Many of the images show unexpected beauty and complexity on Pluto’s surface. While the data are still coming in from the encounter, Dr. Moore shows the latest photos and fills us in on the current thinking among the New Horizons team members about Pluto, its moons, and the unexplored frontier that lies beyond.
A self-driving car has a split second to decide whether to turn into oncoming traffic or hit a child who has lost control of her bicycle. An autonomous drone needs to decide whether to risk the lives of busload of civilians or lose a long-sought terrorist. How does a machine make an ethical decision? Can it “learn” to choose in situations that would strain human decision making? Can morality be programmed? These questions and more will be discussed as the leading AI experts, roboticists, neuroscientists, and legal experts debate the ethics and morality of thinking machines.
In 1960 two seminal papers in SETI were published, providing two visions for SETI. Giuseppe Cocconi and Philip Morrison’s proposed detecting deliberate radio signals ("communication SETI"), while Freeman Dyson ("artifact SETI"), proposed detecting the inevitable effects of massive energy supplies and artifacts on their surroundings. While communication SETI has now had several career-long practitioners, artifact SETI has, until recently, not been a vibrant field of study.
The launch of the Kepler and WISE satellites have greatly renewed interest in the field, however, and the recent Breakthrough Listen Initiative has provided new motivation for finding good targets for communication SETI. Dr. Wright will discuss the progress of the Ĝ Search for Extraterrestrial Civilizations with Large Energy Supplies, including its justification and motivation, waste heat search strategy and first results, and the framework for a search for megastructures via transit light curves. The last of these led to the identification of KIC 8462852 (a.k.a. "Tabby's Star") as a candidate ETI host. This star, discovered by Boyajian and the Zooniverse Planet Hunters, exhibits several apparently unique and so-far unexplained photometric properties, and continues to confound natural explanation.
How should we balance the benefits of limiting or possibly eliminating a disease that kills 1000 people a day against the possible disruption of an ecosystem? Valentino Gantz, and Ethan Bier recently published a Science paper describing a new mechanism of "gene drive."
This is not just a matter of editing the genes of a single individual, but an opportunity to make a change that will drive that change into all descendants of the original individual. Their publication resulted in international interest because of the broad potential applications of this new technology, which could rapidly produce beneficial genetic changes.
Others have argued that because of the risks and implications of such research the work should not even have been published. Series: "Exploring Ethics" [1/2016] [Science] [Show ID: 30009] (Visit: http://www.uctv.tv/)
Machine learning is typically classified into three broad categories, depending on the nature of the learning "signal" or "feedback" available to a learning system. These are:
Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs.
Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).
Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle), without a teacher explicitly telling it whether it has come close to its goal. Another example is learning to play a game by playing against an opponent.:3
Between supervised and unsupervised learning is semi-supervised learning, where the teacher gives an incomplete training signal: a training set with some (often many) of the target outputs missing. Transduction is a special case of this principle where the entire set of problem instances is known at learning time, except that part of the targets are missing.
Among other categories of machine learning problems, learning to learn learns its own inductive bias based on previous experience. Developmental learning, elaborated for robot learning, generates its own sequences (also called curriculum) of learning situations to cumulatively acquire repertoires of novel skills through autonomous self-exploration and social interaction with human teachers and using guidance mechanisms such as active learning, maturation, motor synergies, and imitation.
Another categorization of machine learning tasks arises when one considers the desired output of a machine-learned system::3
In classification, inputs are divided into two or more classes, and the learner must produce a model that assigns unseen inputs to one or more (multi-label classification) of these classes. This is typically tackled in a supervised way. Spam filtering is an example of classification, where the inputs are email (or other) messages and the classes are "spam" and "not spam".
In regression, also a supervised problem, the outputs are continuous rather than discrete.
In clustering, a set of inputs is to be divided into groups. Unlike in classification, the groups are not known beforehand, making this typically an unsupervised task.
Presented at TTI/Vanguard's Networks, Sensors, & Mobility May 3–4, 2016 San Francisco, CA Alex Kendall, Department of Engineering, University of Cambridge
We can now teach machines to recognize objects. However, in order to teach a machine to “see” we need to understand geometry as well as semantics. Given an image of a road scene, for example, an autonomous vehicle needs to determine where it is, what's around it, and what's going to happen next. This requires not only object recognition, but depth, motion and spatial perception, and instance-level identification. A deep learning architecture can achieve all these tasks at once, even when given a single monocular input image. Surprisingly, jointly learning these different tasks results in superior performance, because it causes the deep network to uncover a better deep representation by explicitly supervising more information about the scene. This method outperforms other approaches on a number of benchmark datasets, such as SUN RGB-D indoor scene understanding and CityScapes road scene understanding. Besides cars, potential applications include factory robotics and systems to help the blind.
A half-century ago, astronomers began trying to "eavesdrop" for radio messages from nearby star systems. They haven't found any intelligent messages yet, but many new ideas have come up to increase our chances. Seth Shostak (SETI Institute) summarizes them in this video.
From ancient single-celled organisms evolved multicellular animals whose immense numbers of specialized cell types—skin, muscle, nerve—allow division of labor. Each cell type forms in the right place, is suited to its task, and activates certain genes. Powerful cell-to-cell communication systems organize structured tissues such as lungs, limbs and brain. Dr. Scott will discuss half-billion-year-old genes that have been gradually modified to give rise to the vast diversity of animals.
Scientists say a world that's 490 light-years away qualifies as the first confirmed Earth-sized exoplanet that could sustain life as we know it — but in an environment like nothing we've ever seen. The planet, known as Kepler-186f, is "more of an Earth cousin than an Earth twin," Elisa Quintana, an astronomer at the SETI Institute at NASA Ames Research Center, told the journal Science. Quintana is the lead author of a report on the planet published by Science this week.
"This discovery does confirm that Earth-sized planets do exist in the habitable zones of other stars," Quintana said during a Thursday news briefing at NASA Headquarters.
Kepler-186f goes around an M-type dwarf star that's smaller and cooler than our sun. But it orbits much closer to its parent star than Earth does, within what would be Mercury's orbit in our own solar system. Those two factors combine to produce an environment that could allow for liquid water on the surface, assuming that the planet had a heat-trapping atmosphere.
"The star, to our eyes, would look slightly orange-y," about a third again as big as our sun but only a third as bright, said co-author Thomas Barclay, a staff scientist for NASA's Kepler mission who is also affiliated with NASA and the Bay Area Environmental Research Institute. At midday, Kepler-186f's landscape might look similar to what we see on Earth an hour before sunset, he told NBC News. Or it might not: If the planet lacked an atmosphere to retain and redistribute its sun's warmth, it would be a cold, dry, lifeless world.
Kepler-186f probably rates as the most potentially Earthlike planet discovered so far, said Jim Kasting, a geoscientist at Penn State University who did not play a role in the Science study. But he told NBC News that it's still "less likely to be habitable than planets around more sunlike stars." Even better prospects for alien habitability might well be identified in the months and years to come.
Kepler-186f is just the latest discovery to be pulled out of terabytes' worth of data collected by the Kepler mission. Before it went on the fritz last year, the Kepler space telescope stared at more than 150,000 stars in a patch of sky, looking for the telltale dimming of starlight as planets passed over the stars' disks. Nearly 1,000 exoplanets have been confirmed using Kepler data, and almost 3,000 more candidates are still awaiting confirmation.
It takes years of observation to confirm the pattern of dimming and brightening that's associated with alien planets, particularly if the planets are small and far from their parent stars. In February, astronomers reported that at least four worlds circled the dwarf star known as Kepler-186 or KOI-571. In this week's Science paper, Quintana and her colleagues confirm the existence of Kepler-186f as the fifth and outermost world. They report that Kepler-186f is about 10 percent wider than Earth, tracing a 130-day orbit around its sun at a mean distance of 0.35 astronomical units. (An astronomical unit is the distance between Earth and our sun, which is 93 million miles or 150 million kilometers.) That would put Kepler-186f on the cooler, outer side of the star's habitable zone — the range of orbital distances where liquid water could exist on a planet's surface.
Astronomers have confirmed the existence of other planets in their stars' habitable zone, but those prospects are super-Earth-size. Smaller habitable-zone candidates also have been found, but they have yet to be confirmed as planets.
Barclay said Kepler-186f was particularly promising because it's less than 1.5 times the size of Earth. Planets in that size range are more likely to be rocky with a thinner atmosphere, like Earth, Mars and Venus. But worlds exceeding that size stand a better chance of retaining a thick atmosphere of hydrogen and helium, like the giant planet Neptune.
"While those planets also could be rocky, they don't remind us of home," Barclay said. Could we actually detect signs of life on Kepler-186f? That's a tough one. The astronomers behind the discovery acknowledge that the planet might be just too far away for follow-up studies. The SETI Institute has been searching for radio signals from the Kepler-186 system over a wide frequency range (1 to 10 GHz), but so far nothing has been detected.
Kasting, the author of "How to Find a Habitable Planet," said worlds around M-class dwarf stars faced several disadvantages in the habitability department. For one thing, such planets generally end up being tidally locked to their stars — meaning that one side of the planet is always facing its parent sun while the other is always turned away.
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