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MIT's tiny insect drone looks like a cassette tape with wings but can bounce back from mid-air collisions

ZDNet

MIT researchers have developed a tiny drone with soft actuators that can flap nearly 500 times per second, allowing it to be more resilient to mid-flight bumps and nimble enough to fly like a bee. MIT Assistant Professor Kevin Yufeng Chen led the project to build an insect-like drone that uses soft actuators rather than hard, fragile actuators. "The soft actuators are made of thin rubber cylinders coated in carbon nanotubes," explains MIT. "When voltage is applied to the carbon nanotubes, they produce an electrostatic force that squeezes and elongates the rubber cylinder. Repeated elongation and contraction causes the drone's wings to beat fast."


How Tata Steel Uses AI: A Case Study

#artificialintelligence

Tata Steel is one of the prominent names in the steel-making industry boasting over three decades of manufacturing expertise. The company is currently the world's second-most geographically-diversified steel producer, with fully integrated operations -- from mining to the manufacturing and marketing of finished products. To sustain its leadership position in a volatile market, Tata Steel needed to fortify its supply chain. Poor visibility of in-plant operations was causing delays in loading trucks. This, in turn, triggered a series of inefficiencies like traffic congestions, parking problems, and forced route diversions for inbound/outbound vehicles.


Intelligent Material Changes Shape While Learning

#artificialintelligence

Scientists created an intelligent material that acts as a brain by physically changing when it learns. This is an important step toward a new generation of computers that could dramatically increase computing power while using less energy. Currently, it is run on machine learning software. But the "smarter" computers get, the more computing power they require. This can lead to a sizable energy footprint, which could destabilize the computer.


An intelligent soft material that curls under pressure or expands when stretched

#artificialintelligence

Ideally, soft robots could mimic intelligent and autonomous behaviors in nature, combining sensing and controlled movement. But the integration of sensors and the moving parts that respond can be clunky or require an external computer. A single-unit design is needed that responds to environmental stimuli, such as mechanical pressure or stretching. Liquid metals could be the solution, and some researchers have already investigated their use in soft robots. These materials can be used to create thin, flexible circuits in soft materials, and the circuits can rapidly produce heat when an electric current is generated, either from an electrical source or from pressure applied to the circuit.


Shifting ground

Science

Fleets of radar satellites are measuring movements on Earth like never before. East Africa has been called the cradle of humanity. But the geologically active region has also given birth to dozens of volcanoes. Few have been monitored for warnings of a potential eruption, and until recently, most were believed to be dormant. Then, Juliet Biggs decided to take a closer look—or rather, a farther look. Biggs, a geophysicist at the University of Bristol, uses a technique called interferometric synthetic aperture radar (InSAR) to detect tiny movements of Earth's surface from space. In a series of studies, she and her co-authors analyzed satellite data on the East African volcanoes. According to their latest results, which were published last month, 14 have been imperceptibly growing or shrinking in the past 5 years—a clue that magma or water is moving underground and that the volcanoes are not completely asleep. “It's really changed the way these volcanoes are viewed, from something that's kind of dormant to really very active systems,” Biggs says. After data showed that the Corbetti volcano, which abuts the fast-growing city of Hawassa, Ethiopia, is inflating steadily at a rate of 6.6 centimeters per year, Biggs's Ethiopian colleagues included it in the country's geological hazard monitoring network. No other technology could produce such a comprehensive survey. Individual GPS stations can track surface movements of less than 1 millimeter, but InSAR can measure changes almost as subtle across a swath hundreds of kilometers wide. That has made it a vital tool for earth scientists studying the heaves and sighs of our restive planet. “We tend to think of the ground as this solid platform,” Biggs says, “and actually, it's really not.” With InSAR, scientists are tracking how ice streams flow, how faults slip in earthquakes, and how the ground moves as fluids are pumped in or out. “Everywhere you look on Earth, you see something new,” says Paul Rosen, an InSAR pioneer at NASA's Jet Propulsion Laboratory (JPL). “It's a little bit like kids in a candy store.” And the flood of InSAR data is growing fast. Since 2018, the number of civil and commercial SAR satellites in orbit has more than doubled. And at least a dozen more are set to launch this year, which would bring the total to more than 60. With the help of computing advances that make data processing easier, the satellite fleets may soon be able to detect daily or even hourly surface changes at just about every patch of ground on Earth. As the technology grows more powerful and ubiquitous, InSAR is spreading beyond the geosciences. With InSAR data, railroads are monitoring the condition of their tracks and cities are monitoring shifts in buildings caused by construction. “It's popping up everywhere,” says Dáire Boyle, who follows trends in the space industry for Evenflow, a consulting firm in Brussels. Analysts value the SAR market at roughly $4 billion, and expect that figure to nearly double over the next 5 years. Many believe InSAR will eventually underpin our daily lives. From measuring the water stored in mountain snowpacks to enabling quick responses to natural disasters, InSAR data will prove invaluable to governments and industries, says Cathleen Jones, a science team leader for NISAR, an upcoming joint SAR mission from NASA and the Indian Space Research Organisation (ISRO). “I want it to become so socially relevant that they can't go back to not having this data.” SYNTHETIC APERTURE RADAR , the “SAR” on which InSAR depends, originated in the 1950s as a tool for airborne military reconnaissance. Like traditional radar, SAR instruments captured images of the planet by sending out microwave pulses and recording the echoes. And like a traditional radar, the instruments could penetrate clouds and worked equally well at night. A key difference was the “synthetic” aspect of SAR. Larger radar antennas, like larger apertures on a camera, collect more of the echoes and enable sharper pictures. But building a single antenna large enough to take a high-resolution image isn't practical. Researchers realized they could instead create an artificially large aperture by combining the signals received on a much smaller antenna as it moved through space. Today, SAR satellites with antennas just a few meters across can produce images with pixel resolutions as sharp as half a meter—better than many satellite-borne cameras. SAR images, on their own, suffice for many types of surveillance, from counterterrorism to tracking oil spills in the ocean. But InSAR goes further, by looking for differences between multiple SAR images. The technique takes advantage of phase information in the returning microwaves—in other words, where a signal is in its sinusoidal path when it hits the antenna. Any phase difference in the signal between SAR images taken from the same position at different times means the round-trip distance has changed, and can reveal surface movements down to a few millimeters. “There's nothing else that compares to it,” says Michelle Sneed, a hydrologist at the U.S. Geological Survey. “I'm still amazed by it after a couple of decades.” The 1978 launch of Seasat, NASA's first ocean-observing satellite, provided data for early InSAR efforts. Seasat operated for just 105 days before a power failure brought the mission to an untimely end. But in that time, it collected repeat images of California's Imperial Valley taken over the course of 12 days. Scientists at JPL later compared those images using InSAR to show the subtle swelling of fields as they soaked up irrigation water. “It is not hard to think of numerous applications for the type of instrument demonstrated,” the authors wrote in a 1989 paper. And they were right. ![Figure][1] CREDITS: (GRAPHIC) N. DESAI/ SCIENCE ; (DATA) ESA; WMO; GUNTER'S SPACE PAGE A classic InSAR study came in 1993, when a team of scientists in France used data from the SAR-enabled European Remote Sensing satellite to study a powerful earthquake that rocked Landers, California, the year before. By analyzing images taken before and after the quake, they calculated that the fault had slipped by up to 6 meters, which agreed with detailed field observations. The InSAR data also revealed how the ground buckled for kilometers around the fault—illustrating the full effects of the temblor at an unprecedented scale. The paper inspired scientists like Sneed, who went on to use InSAR to study how groundwater extraction causes the ground to sink. During a drought in California's San Joaquin Valley in the late 2000s, she and her colleagues discovered that the surface was subsiding as fast as 27 centimeters per year in places where farmers pumped the most groundwater. Irrigation canals were sagging as a result of uneven sinking, impeding water flow. “It's a really expensive problem,” Sneed says. (Another recent InSAR study linked specific water-intensive crops—notably corn, cotton, and soy—to increased subsidence.) Glaciologists adopted the technology, too. As a young researcher at JPL in the 1990s, Ian Joughin used InSAR—which tracks both vertical and horizontal movements—to measure the speed of polar ice streams. Some scientists thought flow rates would be relatively immune to climate change. But, sadly for the world, InSAR studies by Joughin and others proved those predictions wrong. “Especially in the early 2000s, we just saw all kinds of glaciers double their speed,” says Joughin, who now studies the fate of polar ice sheets and their contribution to sea-level rise at the University of Washington, Seattle. By the 2000s, many earth scientists were using InSAR—and grappling with its limitations. There were few SAR satellites in orbit, and they tended to switch between instruments or imaging modes to accommodate different users' needs, making the data hard to use for InSAR. The early missions collected the repeat images needed for InSAR only about once a month, and researchers often had to correct for their wobbly orbits. That meant that although scientists could study an event after it happened, they could rarely watch it unfold in real time. Leaders at the European Space Agency (ESA) were convinced there was a better way. MALCOLM DAVIDSON REMEMBERS the excitement and anxiety he felt on 3 April 2014, the day the first Sentinel-1 satellite launched. “All your life goes into a few minutes,” says Davidson, mission scientist for ESA's flagship SAR program. He also remembers the relief when the satellite safely reached orbit, and the awe that came over him when he saw its first image, of ocean swells. “It was very convincing that the mission was going to do great things,” he says. With Sentinel-1, the plan was simple: “We cut out all the experiments, and we said, ‘Look, this is a mapping machine.’” He and his colleagues chose a primary imaging mode to use over land—surveying a 250-kilometer swath at a resolution of 5 meters by 20 meters—that they hoped would satisfy most researchers, and made sure the orbits would overlap precisely, so all the data would be suitable for InSAR. The first satellite, Sentinel-1a, retraced its path every 12 days. Then, in 2016, ESA launched a clone that made repeat images available about every 6 days for many places on Earth. SAR missions like Italy's COSMO-SkyMed and Germany's TerraSAR-X also support InSAR and can achieve even higher resolutions. But they do not distribute data freely like Sentinel, which many credit for driving a transition from opportunistic experiments to what Davidson sees as “a more operational view of the world.” With Sentinel-1 data, Norway created a national deformation map that has helped identify rockslide hazards and revealed that parts of Oslo's main train station were sinking. Water managers in California rely on the data to track groundwater use and subsidence. And in Belgium, it is used to monitor the structural integrity of bridges. “It can all be done remotely now, saving time, saving money,” Boyle says. The large and growing body of InSAR data has also revealed small surface movements that were previously hidden by noise. As radar signals pass through the atmosphere, they slow down by an amount that depends on the weather, producing variability that can swamp tiny but important displacements. Thanks to long-term records from missions like Sentinel, researchers can now tease information from the noise, for example, helping them track movements of just a few millimeters per year in Earth's crust—enough to strain faults and eventually cause earthquakes. Such efforts would not have been possible without huge gains in computing power. In the 1990s, stacking a single pair of SAR images could take days, Sneed says, and interpreting the results could take much longer. Now, researchers can process hundreds of images overnight, and they increasingly rely on artificial intelligence (AI) algorithms to make sense of the data. In one recent test, an AI algorithm was tasked with identifying small fault movements known as slow earthquakes. It correctly found simulated and historical events, including ones that had eluded human InSAR experts, says Bertrand Rouet-Leduc, a geophysicist at Los Alamos National Laboratory who presented preliminary results in December 2020 at the annual meeting of the American Geophysical Union. Rouet-Leduc and his team now plan to monitor faults around the world using the same approach. He says it's mostly a matter of exploiting the vast quantity of data that “sits on servers without being looked at,” because it's simply too much for scientists to tackle. The researchers hope they will be able to answer questions like when and why slow earthquakes happen, and whether they can trigger big, damaging events by increasing stress on other parts of a fault. Commercial users often lack the expertise to process InSAR data, so hundreds of companies have sprung up to help. One, Dares Technology, monitors the ground for the construction, mining, and oil and gas industries. By tracking surface changes as fluids are injected or extracted from an oil reservoir, for example, Dares can help companies estimate pumping efficiency and prevent dangerous well failures. In the beginning, convincing clients that InSAR data were useful and trustworthy was difficult, says Dares CEO Javier Duro. Now, he says, “Everybody wants to include InSAR in their operations.” Duro is particularly interested in detecting precursors to accidents, for example, by looking for signs of instability in the walls of open-pit mines or in the dams used to store mine tailings. The company usually sends out several alerts per month to clients, who can take actions to avoid disasters. “Typically, InSAR data have been used for back analysis,” Duro says. “Our mission is to focus on the present and the future, and try to predict what could happen.” THE SURGE IN SATELLITES promises to bring yet another InSAR revolution. Italy, Japan, Argentina, and China all plan to launch additional SAR satellites soon, and NISAR, the NASA-ISRO mission, will take flight in late 2022 or early 2023. NISAR will image Earth's full land surface every 6 days, on average, says Rosen, the mission's project scientist. Its two radar sensors will help researchers track many things, including crop growth and changes in woody biomass—crucial for understanding the climate system. With a better view of Antarctica than other missions, NISAR can also monitor changes in ice. Taken together, Sentinel-1, NISAR, and the other civil satellites will image most places on Earth at least every 12 hours, Rosen says. But the temporal resolution of InSAR will remain constrained by the revisit rate of the individual missions, because the technique can't be done with imagery from different missions. However, private companies with large constellations of microsatellites hope to vault the field into yet another realm, by radically increasing revisit frequencies. On 24 January, a SpaceX Falcon 9 rocket blasted off from Cape Canaveral, Florida, carrying three satellites, each about the size of a minifridge and weighing less than 100 kilograms, from Iceye. The Finnish SAR startup has raised more than $150 million toward its audacious goal of imaging every square meter of Earth every hour. The launch brought Iceye's commercial constellation to six, giving it an early lead over rival companies such as Capella Space—which had two satellites on the same rocket—and Umbra, both based in California. Iceye plans to add at least eight more satellites this year, allowing it to revisit most of the globe once a day. “That is groundbreaking,” says Pekka Laurila, who co-founded Iceye as an undergraduate at Aalto University and now serves as the company's chief strategy officer. Ultimately, Iceye hopes to assemble a constellation of as many as 100 satellites as it approaches its hourly monitoring objective. That would open up new applications, like tracking how buildings and dams expand during the heat of the day and contract at night—a clue to their structural integrity. Already, Iceye data have been used to guide ships through Arctic sea ice and to track illegal fishing vessels. “If you can work closer to real time, you can actually do something about it,” Laurila says. So far, though, Iceye has focused on flood monitoring, which can guide disaster response efforts. In fact, the company provided some of the first images of Grand Bahama after Hurricane Dorian devastated the island in 2019, Laurila says. Precise flood data are also valuable to insurers, who can use them to trigger automatic insurance payouts after an event instead of processing claims and sending out inspectors. Until now, Iceye has tracked floods using regular SAR data, but it hopes to start to apply InSAR as it increases its revisit frequencies, because the technique can measure the height and extent of inundation much more precisely. And that's just the beginning of what Laurila hopes Iceye will do. His ultimate goal is to build a “new layer of digital infrastructure” that will provide a “real-time, always-available, objective view on the world,” he says. He believes that, like modern GPS, reliable SAR and InSAR data will support myriad applications, many of which have yet to be imagined. “Nobody thought of your Uber and pizza delivery when they thought of GPS,” Laurila says. If Iceye and its peers succeed, they will expose the shifts and shudders of the planet, day in and day out. They will spy tilting buildings and slumping slopes, and they will witness the growth of crops and the flow of commodities around the world. If space-based imagery often portrays Earth as quiet and still, InSAR reveals the true restlessness of our living planet. [1]: pending:yes


A trusty robot to carry farms into the future

#artificialintelligence

Farming is a tough business. Global food demand is surging, with as many as 10 billion mouths to feed by 2050. At the same time, environmental challenges and labor limitations have made the future uncertain for agricultural managers. A new company called Future Acres proposed to enable farmers to do more with less through the power of robots. The company, helmed by CEO Suma Reddy, who previously served as COO and co-founder at Farmself and has held multiple roles and lead companies focused on the agtech space, has created an autonomous, electric agricultural robotic harvest companion named Carry to help farmers gather hand-picked crops faster and with less physical demand. Automation has been playing an increasingly large role in agriculture, and agricultural robots are widely expected to play a critical role in food production going forward.


How explainable artificial intelligence can help humans innovate

AIHub

The field of artificial intelligence (AI) has created computers that can drive cars, synthesize chemical compounds, fold proteins and detect high-energy particles at a superhuman level. However, these AI algorithms cannot explain the thought processes behind their decisions. A computer that masters protein folding and also tells researchers more about the rules of biology is much more useful than a computer that folds proteins without explanation. Therefore, AI researchers like me are now turning our efforts toward developing AI algorithms that can explain themselves in a manner that humans can understand. If we can do this, I believe that AI will be able to uncover and teach people new facts about the world that have not yet been discovered, leading to new innovations.


A trusty robot to carry farms into the future

ZDNet

Farming is a tough business. Global food demand is surging, with as many as 10 billion mouths to feed by 2050. At the same time, environmental challenges and labor limitations have made the future uncertain for agricultural managers. A new company called Future Acres proposed to enable farmers to do more with less through the power of robots. The company, helmed by CEO Suma Reddy, who previously served as COO and co-founder at Farmself and has held multiple roles and lead companies focused on the agtech space, has created an autonomous, electric agricultural robotic harvest companion named Carry to help farmers gather hand-picked crops faster and with less physical demand. Automation has been playing an increasingly large role in agriculture, and agricultural robots are widely expected to play a critical role in food production going forward.


Smart materials: From tiny robots to colour-swapping clothes

BBC News

"You see lots of little bits of it happening. So, now is the time to get the scientific community together to say: 'This is where we're going, so now let's change our mode of working'. At the moment it is very disparate, with pockets of work all over the place, not talking to each other and without a common aim."


New Products

Science

![Figure][1] Porvair Sciences announces Ultravap Mistral—an automation-ready sample evaporator that offers throughput advantages to laboratories looking to optimize and accelerate sample preparation. The Mistral directly and consistently delivers heated gas up to 80°C in each microplate well or tube, facilitating speedy, convenient evaporation of most common chromatography solvents, including dichloromethane, methanol, acetonitrile, hexane, and water. The option for straight or spiral needles allows users to choose between faster drydown (spiral) and better final drying in V-well plates (straight). Highly intuitive software and up to 15 easy-to-use, stored multistep evaporation programs enable even occasional users to gain the full benefits of this unit. For regular users, the Mistral offers the versatility of fully flexible programming, for example, providing for the ideal rate of evaporation for each solvent type. Nova Biomedical announces the addition of a Sample Retain Collector (SRC) for the BioProfile FLEX2 cell-culture analyzer. The FLEX2 automated analyzer offers comprehensive analysis of up to 16 key parameters, including pH, gases, metabolites, osmolality, cell density, and cell viability. A single FLEX2 with the SRC and the previously introduced Online Autosampler (OLS) module provides automated sampling and analysis of these fundamental cell-culture chemistries from as many as 10 bioreactors—and storage by the SRC in as fast as 1 h. This automation package saves hours of time spent on manual sampling, analysis, sample storage, and after-hours cell culture monitoring. The SRC automatically collects cell-culture samples from the FLEX2 OLS and stores them in a refrigerated environment to fulfill regulatory requirements for long-term sample retains, also enabling further offline testing. The SRC allows user-selectable retained sample volumes from 200 μL to 50 mL at a storage temperature of 4°C. BioChromato reports that pharmaceutical companies undertaking absorption, distribution, metabolism, and excretion (ADME) studies are benefiting from integrating RAPID Easy Piercing Seals (EPS) into their screening protocols. ADME scientists commonly use 96- or 384-well microplates to store large numbers of samples for screening. Sample-contamination issues can often arise in ADME studies, as common HPLC solvents such as acetonitrile, water, and dimethyl sulfoxide can extract siloxane out of the silicon-based adhesives used in the microplate seal. RAPID EPS seals use a synthetic-rubber adhesive to create a high-integrity, airtight microplate seal, preventing contamination of ADME samples analyzed by HPLC. In addition, the seals leave no particulate material when pierced by an HPLC autosampler, further safeguarding samples from contamination and eliminating damage to or clogging of your autosampler. They are proven to offer dependable microplate sealing over a working temperature range of −80°C to 80°C. The OpenStand modular platform allows for easy customization. This fully configurable, motorized optical stand, when combined with a range of readily available optics, light sources, and accessories, creates a complete, customizable optical microscope. It is ideal for optogenetics, physiology, electrophysiology, neuroscience, industrial, and general imaging applications. Its modular approach allows maximum interchangeability and flexibility, enabling users to image a wide range of samples for virtually any life science and industrial application, and offering the largest imaging space available. It features a cost-effective, custom development platform that can be set up quickly as a fast-track to a prototype instrument. OpenStand lets you select only the components you need for your specific application, resulting in significant savings while giving you the flexibility to expand and add additional components if requirements change. CS Medical is pleased to announce its distribution agreement with AirClean Systems to offer the AirClean UV Light Box. The growing demand to decontaminate N95 respirators has made shortwave UV light—used for years to decontaminate surfaces—an alternative to other chemical-based methods. Designed to protect the user from exposure to potentially harmful shortwave light energy, the AirClean UV Light Box is available in two widths and performs decontamination of N95 respirators in a total cycle time of 60 min, 30 min per side. Decontamination will make the masks reusable up to five times, helping alleviate the PPE shortage that is common in so many health care facilities and other industries across the nation right now. FUJIFILM Irvine Scientific announces cellnest, a recombinant peptide attachment substrate that provides optimal adhesion and proliferation of stem cells in chemically defined, animal component–free conditions. Attachment substrates mimic the extracellular matrix, a complex, dynamic environment in which cells reside in vivo, and allow for adhesion, expansion, and potential differentiation of stem cells. Unlike animal-derived components, which can introduce unpredictability in results, cellnest delivers consistent results and can smooth the regulatory path to commercialization. It is compatible with any adherent cell type that binds to the Arg-Gly-Asp (RGD) domain, an amino-acid sequence within the extracellular matrix protein fibronectin that mediates cell attachment. cellnest is an ideal companion product to our PRIME-XV portfolio of xeno-free, chemically defined media for stem-cell culture and is well suited for the attachment and growth of mesenchymal stem cells. [1]: pending:yes