Soft robots aren't easy to make, since they require a completely different set of components from their rigid counterparts. It's even tougher to scale down the parts they typically use for locomotion. A team of researchers from the Faculty of Physics at the University of Warsaw, however, successfully created a 15-millimeter soft micromachine that only needs light to be able to move. The microrobot is made of Liquid Crystalline Elastomers (LCEs), smart materials that change shape when exposed to visible light. Under a light source, the machine's body contracts like a caterpillar and forms waves to propel it forward.

The use of data within an organisation to improve elements of the business such as the supply chain, improve decision making, and to make cost savings, is becoming more widely accepted as being vital. It is vital in respect to the business remaining competitive, vital to remaining relevant, and vital to the future of the business. One of the industries that has been looking significantly at the use of its data is the manufacturing industry, and stepping back one level to the steel industry. Magnitogorsk Iron and Steel Works (MMK), is the third largest steel company in Russia with a revenue of 9.3bn. Established in 1870, the company has taken to using machine learning technology from Yandex Data Factory to creative a competitive advantage that will see it being competitive for years to come.

A Florida-based company has won U.S. government permission to send a robotic lander to the moon next year. The move is the first time the United States has cleared a private space mission to fly beyond Earth's orbit. The Federal Aviation Administration's unprecedented go-ahead for the Moon Express mission also sets a legal and regulatory framework for a host of other commercial expeditions to the moon, asteroids and Mars. The Florida-based company Moon Express, which is partnering with Nasa, hopes to send scientific payloads to the Moon, in the hopes to eventually provide commercial services. Artist's impression of Moon Express lander on surface of the moon pictured The moon is a'treasure chest' of lucrative materials.

The self-assembling shape shifting killer robots from the Terminator films could be a step closer, thanks to the development of self-propelling liquid metals. A team of Australian researchers is laying the groundwork for T-1000s by creating the basis of soft electric circuits. Unlike modern circuitry found in electronic devices, which remain based on circuits with solid state components, future connections could be much more flexible and able to move and reconfigure as necessary. A team at RMIT University in Melbourne used non-toxic alloys of the metal gallium, which is liquid at close to room temperature. By adding droplets of the alloy galinstan to water and changing the pH, they were able to make the drops move about freely.

The dynamic nature of air quality chemistry and transport makes it difficult to identify the mixture of air pollutants for a region. In this study of air quality in the Houston metropolitan area we apply dynamic principal component analysis (DPCA) to a normalized multivariate time series of daily concentration measurements of five pollutants (O3, CO, NO2, SO2, PM2.5) from January 1, 2009 through December 31, 2011 for each of the 24 hours in a day. The resulting dynamic components are examined by hour across days for the 3 year period. Diurnal and seasonal patterns are revealed underlining times when DPCA performs best and two principal components (PCs) explain most variability in the multivariate series. DPCA is shown to be superior to static principal component analysis (PCA) in discovery of linear relations among transformed pollutant measurements. DPCA captures the time-dependent correlation structure of the underlying pollutants recorded at up to 34 monitoring sites in the region. In winter mornings the first principal component (PC1) (mainly CO and NO2) explains up to 70% of variability. Augmenting with the second principal component (PC2) (mainly driven by SO2) the explained variability rises to 90%. In the afternoon, O3 gains prominence in the second principal component. The seasonal profile of PCs' contribution to variance loses its distinction in the afternoon, yet cumulatively PC1 and PC2 still explain up to 65% of variability in ambient air data. DPCA provides a strategy for identifying the changing air quality profile for the region studied.

The multidisciplinary project fits into the growing field of soft robotics that coalesced with the 2013 founding of the peer-reviewed Soft Robotics Journal, based at Tufts. The Boston region is a hub for research into the moving machines made of flexible materials that can change shape and size, making them useful for surgery and other complex environments.

For the past year, Tara Hutchinson has been trying to figure out what will happen to a tall building made from thin steel beams when "the big one" hits. To do that, she has erected a six-story tower that rises like a lime-green finger from atop a shrub-covered hill on the outskirts of San Diego, California. Hundreds of strain gauges and accelerometers fill the building, so sensitive they can detect wind gusts pressing against the walls. Now, Hutchinson just needs an earthquake. In most of the world, this would be a problem.

Mitsubishi Heavy Industries Ltd. on Tuesday unveiled a robot that can operate in the presence of flammable gases, such as after a gas leak following a disaster. A joint project with Chiba Institute of Technology, the Sakura No. 2 is the country's first mobile inspection unit that can operate in the presence of high concentrations of explosive gases such as methane and hydrogen. There is an increasing need for an inspection robot that is not a fire hazard as Japan steers toward becoming a hydrogen-based society, said Ken Onishi, a senior engineer in charge of the project for Mitsubishi Heavy. "There was a debate over whether to develop robots that can operate near hydrogen gas, as doing so requires an extremely high level of technology," Onishi said. "As we may encounter accidents such as collisions involving hydrogen cars or a truck loaded with hydrogen tanks rolling over inside a road tunnel, we decided to develop a robot that can deal with such situations."

Elsewhere, I have suggested that there are three junctures at which any data mining project may go the most wrong: 1. problem definition, 2. data acquisition and 3. model validation (see the Data Mining and Predictive Analytics Web log). Data acquisition is a superset of statistical sampling, and the text by Lohr is highly recommended for this topic. Model validation is well explained in the literature: see, for instance, Weiss and Kulikowski. Problem definition involves understanding the business problem and mapping an appropriate technical solution to it. This may not be as simple as it sounds, and it is easy to be naïve about the best way to construct a technical solution which most naturally solves the given problem.

Drowsy driving is notoriously tough to detect. There's no test to prove it, the way a breathalyzer can prove someone was driving drunk. But technology to detect drowsy driving is in the works. In commercial transport, one industry is leading the way: mining. The stakes are particularly high in this field since the enormous haul trucks used in mining are several times the height of a person.