Huawei, Meng face new US charges of trade secrets theft

MEANWHILE CANADA IS WHERE THE HUAWEI TRIAL IS TAKING PLACE
TO SEND THE CFO, CURRENTLY UNDER HOUSE ARREST, TO THE USA FOR 
TRIAL THERE AS THE US ADDS MORE PHONY CHARGES. CANADA IS ACTING LIKE THE FRONT ENTRANCE MAT FOR TRUMP'S PHONY WAR ON CHINA/HUAWEI

by Rob Lever

US criminal charges allege the Chinese tech giant Huawei engaged in a "decades-long" effort to steal trade secrets from American companies

Chinese tech giant Huawei has been hit with fresh US criminal charges alleging a "decades-long" effort to steal trade secrets from American companies.

A US indictment unsealed in New York alleges Huawei and its proxies conspired "to misappropriate intellectual property" from six US firms as part of a strategy to grow and become the world's largest telecom equipment maker.

The new charges, including a federal racketeering allegation, add to an indictment unsealed in January 2019 that alleged Huawei stole trade secrets from US carrier T-Mobile.

The indictment names Huawei and several subsidiaries, as well as the company's chief financial officer Meng Wanzhou, who has been arrested in Canada over a related probe into Huawei's violations of US sanctions.

Huawei called the latest charges "unfounded and unfair" and predicted the case would be dismissed.

"This new indictment is part of the Justice Department's attempt to irrevocably damage Huawei's reputation and its business for reasons related to competition rather than law enforcement," the company said.

"The 'racketeering enterprise' that the government charged today is nothing more than a contrived repackaging of a handful of civil allegations that are almost 20 years old."

Huawei, one of the world's largest tech firms, has been blacklisted by Washington amid concerns over its ties to the Chinese government and intelligence services.

The sanctions are aimed at blocking Huawei from getting any US telecom equipment contracts and prevent the transfer of American technology to the Chinese firm.

But on Thursday the US Commerce Department delayed the implementation of some sanctions for an additional 45 days, saying it would help avoid disruption for certain telecom firms as they seek alternatives to Huawei.

'Long-running deception'

The new 16-count indictment says Huawei employed a "long-running practice of using fraud and deception to misappropriate sophisticated technology from US counterparts," a Justice Department statement said, without naming the American companies.

"Huawei's efforts to steal trade secrets and other sophisticated US technology were successful," according to the statement, which said the company "obtained nonpublic intellectual property relating to internet router source code, cellular antenna technology and robotics" to gain an "unfair competitive advantage" over rivals.

Huawei chief financial officer Meng Wanzhou, under house arrest in Canada pending an extradition request from the United States, has been indicted on new US criminal charges

According to the indictment, Huawei entered into confidentiality agreements with US tech firms and then violated those deals.

Huawei is accused of recruiting employees of other companies and "directing them to misappropriate their former employers' intellectual property."

The indictment also claims Huawei used "proxies" such as professors working at research institutions to steal trade secrets and "launched a policy instituting a bonus program to reward employees who obtained confidential information from competitors."

The fresh charges come amid heightened US-China trade tensions and efforts by Washington to keep Huawei from obtaining contracts for 5G, or fifth-generation wireless networks.

China on Friday repeated previous allegations that the US treatment of Huawei amounted to "economic bullying."

"We urge the US to immediately cease its unreasonable oppression of Chinese enterprises," a foreign ministry spokesman said.

According to the 56-page indictment, Huawei is also accused of using its subsidiaries around the world to conceal its dealings with Iran and North Korea, which are subject to US sanctions.

Meng, arrested in late 2018, is under house arrest in Canada pending a ruling on whether she will be extradited to face charges in the United States.

Meng is accused of lying to HSBC bank about Huawei's relationship with its Iran-based affiliate Skycom, putting the bank at risk of violating US sanctions against Tehran.

The US administration has had mixed results in persuading allies to steer clear of Huawei for 5G networks.

France announced Thursday it would not bow to American pressure to exclude Huawei from supplying equipment for its 5G networks, though the Chinese firm could be subject to restrictions.

Last month the EU and UK both released guidelines saying that governments should avoid dependence on "high risk" suppliers of 5G equipment when building their next-generation mobile networks, but stopped short of banning any one vendor outright.

Huawei pleads not guilty to trade secrets charges in Seattle

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© 2020 AFP

Consider workplace AI's impact before it's too late, study says

by Melanie Lefkowitz, Cornell University

The consequences of workplace automation will likely impact just about every aspect of our lives, and scholars and policymakers need to start thinking about it far more broadly if they want to have a say in what the future looks like, according to a new paper co-authored by a Cornell University researcher.

"Mostly, people in our field wait until technology is implemented in a workplace to study it. And then we go in and say, 'How is work different?'" said Diane Bailey, the Geri Gay Professor of Communication in the College of Agriculture and Life Sciences. "But faced with a technology that has the potential to disrupt the landscape of work in such a universal way, immediately and simultaneously, we felt like we have to get in the barn before the horse leaves."

The paper, "Beyond Design and Use: How Scholars Should Study Intelligent Design Technologies," was published in December in Information and Organization. Bailey co-authored the study with Stephen Barley, the Christian A. Felipe Professor of Technology Management in the College of Engineering at the University of California, Santa Barbara.

According to the paper, past examples of new technology suggest it will take longer than companies predict for workplaces to become fully transformed by AI, and some jobs might not be as easily replaceable as economists believe. This means researchers have more time to gain a deeper understanding of how workplace automation will affect society, in order to have more say in how it unfolds.

Fully understanding workplace automation, the researchers said, requires an interdisciplinary approach that considers everything from the power dynamics within tech companies to the design of our societal institutions. At Cornell, Bailey and Martin Wells, the Charles A. Alexander Professor of Statistical Sciences and chair of the Department of Statistics and Data Science, are heading a core team of nine other researchers from eight departments to follow this cross-disciplinary roadmap. The group is currently seeking funding to plan the creation of an institute to study AI and work.

In the paper, Bailey and Barley identified four factors scholars should study in order to assess AI's future impact: variation; power; ideology; and institutions.

Considering variety among jobs is important, Bailey said, because not all jobs—even in the same fields—are identical. Researchers generally use U.S. Department of Labor databases to predict how automation might affect certain job categories, but most studies don't consider differences in implementation, skills, tasks and work practices across organizations or locations.

Because designers and engineers don't function independently, power is another crucial factor, the paper said. Which AI technologies are pursued and how aggressively they're implemented depends on the dynamics within companies, as well as the priorities of the government entities that might fund or regulate those companies.

The ideology of design can provide insight into how technologists create new systems, Bailey said. According to the paper, the AI community often approaches design with its own culture, potentially emphasizing technical over social aspects. This could mean that some systems that are predicted to replace humans might still require them, though possibly in different roles.

"We have to understand how all of these market mechanisms operate if we're going to be savvy enough to work in that world and say, 'No, we want technology that looks like this' [or] 'Design something that operates this way,'" Bailey said. "We need to work backwards from some desired future that we want, to get the technologies that will help us get there."

Researchers also need to consider the potential impacts of automation—and the widespread unemployment it will likely bring—on our institutions, the paper said. For example, Bailey said, being home together all day—without the demands and concrete rewards of a paid job—could strain marriages and families. Roads, highways and transit systems that were designed to move people from home to work will need to be reconsidered.

"Maybe the reasons our neighborhoods work well is that so many of us are away from them during the day," Bailey said. "We might have to rethink all of these things—and that's what the paper argues we should do."

Researchers and policymakers also need to weigh the societal benefits of work, in order to make informed decisions about which jobs are worth saving.

"We have to think about what aspects of work have meaning and value to us," Bailey said. "We might decide, 'Maybe AI can do this better than a person, but we don't care, because we get some value out of it.'"Paid leave may widen the 'mommy gap' but increase time with children

More information: Diane E. Bailey et al. Beyond design and use: How scholars should study intelligent technologies, Information and Organization (2019). DOI: 10.1016/j.infoandorg.2019.100286

Amazon wins suspension of $10 bn 'JEDI' contract to Microsoft

by Glenn Chapman

TRUMP PUT HIS FINGER ON THE SCALE AND DIRECTED THE PENTAGON NOT TO CHOOSE AMAZON ---SO MUCH FOR NOT PICKING WINNERS AND LOSERS, EH

Amazon is challenging the Pentagon's decision to award a $10 billion cloud computing contract to Microsft, claiming the process was tainted by President Donald Trump's intervention

A federal judge on Thursday temporarily blocked the US military from awarding a $10 billion cloud computing contract to Microsoft, after Amazon claimed the process was tainted by politics.

A preliminary injunction requested by Amazon was issued by Judge Patricia Campbell-Smith, barring the Department of Defense from starting work on the contract known as JEDI, according to a summary of the ruling.

Details of the ruling were sealed for unspecified reasons.

Amazon has alleged it was shut out of the deal because of President Donald Trump's vendetta against the company and its chief executive Jeff Bezos.

It's seeking testimony from the president and other top officials on the reasons for awarding the $10 billion, 10-year US military cloud computing contract to Microsoft.

"We are disappointed in today's ruling and believe the actions taken in this litigation have unnecessarily delayed implementing DoD's modernization strategy and deprived our warfighters of a set of capabilities they urgently need," Department of Defense spokesman Lt Col Robert Carver said.

He added that the Pentagon remained confident in its decision to award the contract to Microsoft.

The Joint Enterprise Defense Infrastructure (JEDI) program will ultimately see all military branches sharing information in a cloud-based system boosted by artificial intelligence.

An earlier court filing by Amazon detailed alleged errors that ended with Microsoft being chosen over its Amazon Web Services (AWS) cloud computing division, part of the technology group led by Bezos.

Bezos, who also owns The Washington Post, is a frequent target of the US president, who claims the newspaper is biased against him.

Amazon says the tech giant lost a major Pentagon cloud computing contract because of President Donald Trump's animosity for its CEO Jeff Bezos

Microsoft confident

Microsoft said it hoped to prevail after the merits of the case are heard in court.

"We have confidence in the Department of Defense, and we believe the facts will show they ran a detailed, thorough and fair process in determining the needs of the warfighter were best met by Microsoft," said Frank Shaw, the company's vice president of communications.

Amazon did not immediately respond to a request for comment.

Amazon was considered the lead contender to provide technology for JEDI, with AWS dominating the cloud computing arena and the company already providing classified servers for other government agencies including the CIA.

Amazon argued in court documents that the Pentagon's choice of Microsoft was mystifying if not for Trump's repeated "expressed determination to, in the words of the president himself, 'screw Amazon.'"

The protest filed in the US Court of Federal Claims urges that the rival JEDI bids be re-evaluated.

As a condition of the injunction, Amazon was directed to provide $42 million to the court that would be used to cover any costs or damages incurred if it is determined that the injunction was issued wrongly.Amazon wants Trump testimony about huge Pentagon contract

Virus could mean $5 bn in airline losses: UN agency

Credit: CC0 Public Domain

The new coronavirus outbreak could mean a $4-5 billion drop in worldwide airline revenue, the International Civil Aviation Organization said on Thursday.

The UN agency reported that 70 airlines have canceled all international flights in and out of China and 50 others have reduced their operations.

Preliminary estimates show this has meant a reduction of nearly 20 million passengers compared to expectations for the first quarter of 2020.

That figure equates to potential lost revenue of up to $5 billion, the agency said.

The virus has killed nearly 1,400 people and infected 64,000, almost all of them in China.

"Prior to the outbreak, airlines had planned to increase capacity by nine percent on international routes to/from China for the first quarter of 2020 compared to 2019," the International Civil Aviation Organization (ICAO) said in a statement.

But foreign airline traveler capacity in and out of the country has gone down 80 percent, it said.

Japan looks to be hardest-hit by a reduction in Chinese air travelers in the first quarter, ICAO said. The country could lose $1.29 billion in tourism revenue, with Thailand not far behind, facing a potential $1.15 billion loss.

ICAO said the effects of the COVID-19 virus outbreak on the airline industry are expected to be larger than the 2002-2003 SARS epidemic because flight cancellations are more widespread this time.

In addition, China's international air traffic has doubled and its domestic air traffic increased five-fold in the last 17 years.

Chinese authorities have locked down Hubei province—the virus epicenter—and have restricted movements in several cities as part of an unprecedented effort to contain the disease.

Britain, Germany, the US, Japan and others have advised against travel to China.

Airlines extend China flight suspensions

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© 2020 AFP

Researchers discover how to improve safety of nuclear power plants

by Tomsk Polytechnic University

Credit: rosatom.ru

Researchers at Tomsk Polytechnic University found a method to increase fuel lifetimes by 75%. According to the research team, it will significantly increase safety and reduce the operating cost of nuclear power plants in hard-to-reach areas. The study results were published in Nuclear Engineering and Design.

Previously, a team of researchers from the Russian Federal Nuclear Center—All-Russian Research Institute of Technical Physics, Tomsk Polytechnic University, and the Budker Institute of Nuclear Physics proposed the concept of a thorium hybrid reactor, where high-temperature plasma confined in a long magnetic trap is used to obtain additional neutrons. Unlike operating reactors, the proposed thorium hybrid reactor has moderate power, a relatively small size, high operational safety, and a low level of radioactive waste.

One of the biggest challenges for the development of remote areas, such as the Far North, is a stable energy supply. According to Tomsk researchers, often the only solution is to use low-power nuclear plants.

However, reactor refueling, one of the most hazardous and time-consuming procedures in nuclear energy, is a significant problem. "Reduction of refuel frequency will drastically improve operational safety. Furthermore, it reduces transportation costs of fresh fuel or a nuclear power plant to a transshipment site," Vladimir Nesterov, associate professor of the TPU Division for Nuclear-Fuel Cycle, says.

The scientists carried out theoretical calculations proving the possibility of creating a thorium-based nuclear fuel cycle. Thorium is four times as abundant as uranium. Additionally, thorium fuel has a significantly higher regeneration intensity of fissile isotopes necessary for energy production.

"The achieved results can draw the attention of the scientific community to the potential of the thorium nuclear fuel cycle. We demonstrated that the implementation of this cycle in a low-power reactor installation results in increasing the fuel lifetime by 75%," the expert says.

In the future, researchers want to continue experiments in the verified software and carry out thermophysical calculations of low-power reactors operating in the thorium-uranium fuel cycle with subsequent implementation of the developed calculation methods in the educational process.Scientists develop a concept of a hybrid thorium reactor

More information: Sergei V. Beliavskii et al, Effect of fuel nuclide composition on the fuel lifetime of reactor KLT-40S, Nuclear Engineering and Design (2020). DOI: 10.1016/j.nucengdes.2020.110524

Drone designs arise from butterfly study: Undulating flight saves monarchs' energy

DARPA MAKING MONARCH ROBOTS FOR WHEN THE REAL ONES GO EXTINCT

by University of Alabama in Huntsville

Credit: CC0 Public Domain

In a finding that could benefit drone design, award-winning research by a doctoral student at The University of Alabama in Huntsville (UAH) shows that the undulating flight paths of monarch butterflies are actually more energy efficient than a straight-line path.

Madhu Sridhar's paper won the 2019 AIAA Atmospheric Flight Mechanics Graduate Student Paper Competition and he was awarded at the 2020 AIAA SciTech Forum held recently in Orlando, Fla. The AIAA Scitech Forum is the largest annual aerospace conference and focuses on research and technology findings in the aerospace community. The 2020 AIAA SciTech Forum included more than 2,500 technical presentations with over 5,000 participants.

Sridhar modeled and analyzed the power consumption of monarch butterflies while working in UAH's Autonomous Tracking Optical Measurement (ATOM) Laboratory under Dr. Chang-kwon Kang, an associate professor in the Department of Mechanical and Aerospace Engineering, and Dr. Brian Landrum, an associate professor and the associate chair of the Department of Mechanical and Aerospace Engineering. The research was supported by funding from the National Science Foundation.

The finding that an undulating flight trajectory consumed less energy can be valuable in the bio-inspired design of long-range robotic miniature drones.

"One of the underlying goals of our study is to develop a drone that can fly as long as a migrating monarch," Sridhar says. "The annual migration of monarch butterflies is the longest among insects. It can be 3,000 kilometers long! Even the state-of-the-art drones cannot show these long ranges."

Researchers used a simplified analytical butterfly model in the study, focusing on the dynamic interplay between the wing aerodynamics and body dynamics, says Sridhar, who is from Bangalore, India.

"This paper shows that this model agrees reasonably well with experimental data," he says. "We used motion-tracking cameras to record a series of flight trajectories and wing and body motions of freely flying monarch butterflies in our ATOM Lab."

If there are advantages to the undulating trajectory that butterflies use, why don't bees or flies use it?

"This study shows that the coordinated wing and body motions following a bumpy trajectory require lower power for a flapping wing at the monarch scale," he says. "For smaller insects this power benefit reduces, which is probably why they fly on a straight trajectory."

Whether butterflies utilize a biologically predetermined pattern of flight or simply random undulations is one of many questions for future research. Sridhar is also looking into how the butterflies select flight altitudes.

"monarchs are known to fly at different heights from ground level along their migration route, which we find very interesting," he says. "We do not know why they choose to fly higher instead of at ground level heights."

At higher altitudes the reduced air density may benefit monarch flight, the scientists theorize.

"So, to test this, we have performed experiments with monarch butterflies inside the large vacuum chamber at UAH Propulsion Research Center, where we recorded the flights at lower density air up to 4,000 meters above sea level," Sridhar says. "This helps us in observing how their wing and body motions change as the air density is lowered."

Additionally, researchers are using computer simulations to investigate how low-density air affects the flexibility of monarch wings.California's monarch butterflies critically low for 2nd year

More information: Madhu Sridhar et al. Beneficial Effect of the Coupled Wing-Body Dynamics on Power Consumption in Butterflies, AIAA Scitech 2019 Forum (2019). DOI: 10.2514/6.2019-0566

THE SIX MILLION DOLLAR*** JELLYFISH

Microelectronics embedded in live jellyfish enhance propulsion

by Thamarasee Jeewandara , Tech Xplore

A. aurita swim controller design. (A) Square wave signal generated by the swim controller with an amplitude (A) of 3.7 V and a pulse width (T) of 10 ms, set at frequencies (f) of 0.25, 0.38, 0.50, 0.62, 0.75, 0.88, and 1.00 Hz. (B) Swim controller components. Housing includes (i) a polypropylene cap with a wooden pin that embeds into the bell center, and (ii) a plastic film to waterproof the housing, both offset with stainless steel and cork weights to keep the device approximately neutrally buoyant. Microelectronics include (iii) a TinyLily mini-processor, (iv) lithium polymer battery, and (v) two platinum-tip electrodes with LEDs to visually indicate stimulation. (C) Fully assembled device, with the processor and battery encased in the housing. (D) Simplified schematics of A. aurita anatomy, highlighting the subumbrellar (top) and exumbrellar (bottom) surfaces, rhopalia, muscle ring, and circumferential muscle fiber orientation, oral arms, and gonads/gastric pouches. (E) Swim controller (inactive) embedded into a free-swimming jellyfish, bell oriented subumbrellar side up, with the wooden pin inserted into the manubrium and two electrodes embedded into the muscle and mesogleal tissue near the bell margin. Photo credits for (B), (C), and (E): Nicole W. Xu, Stanford University. Credit: Science Advances, doi: 10.1126/sciadv.aaz3194

Researchers in robotic materials aim to artificially control animal locomotion to address the existing challenges to actuation, control and power requirements in soft robotics. In a new report in Science Advances, Nicole W. Xu and John O. Dabiri at the departments of bioengineering, civil and environmental engineering and mechanical engineering at the Stanford University presented a biohybrid robot that used onboard microelectronics to induce swimming in live jellyfish. They measured the ability to substantially enhance propulsion by driving body contractions at an optimal frequency range faster than natural behavior. The manoeuvre increased swimming speed by nearly threefold, although with only a twofold increase in metabolic expenditure of the animal and 10 mW of external power input to the microelectronics. The biohybrid robot used 10 to 1000 times less external power per mass than with previously reported aquatic robots. The capability can improve the performance scope of biohybrid robots relative to native performance, with potential applications as biohybrid ocean monitoring robots.

Jellyfish are a compelling model organism to form energy-efficient underwater vehicles due to their low cost of transport (COT). Existing biomimetic robots of swimming animals that are entirely built of engineered materials can achieve velocities comparable to natural animals, but with orders of magnitude less efficient than jellyfish. Biohybrid jellyfish robots can therefore integrate live animals to address existing challenges of soft robotics. Researchers can use the jellyfish structure for actuation and solve power requirements by exploring natural feeding behaviors where they extract chemical energy from prey in situ. The approach can also allow recovery from damage via natural wound healing processes inherent to the animal, control animal locomotion and allow additional studies of live organism biomechanics in user-controlled experiments. In this study, Xu and Dabiri used a system of microelectronics to externally control a live jellyfish and form a biohybrid robot to advance science and engineering of aquatic locomotion.

In order to activate jellyfish as a natural scaffold, the team used the animal's own basal metabolism to reduce additional power requirements and leveraged its muscles for actuation while relying on self-healing and tissue regenerative properties for increased damage tolerance. The team hypothesized that increasing bell contraction frequencies of jellyfish could increase swimming speeds up to a limit. They therefore externally controlled the frequency of pulses in free-swimming animals by measuring the swim speed and oxygen intake to calculate the cost of transport (COT) and test their working hypothesis. Previously such examinations were only possible through computational or theoretical models.

A comparison of bell geometries for unstimulated swimming with an inactive swim controller embedded (left) and externally controlled swimming at 0.50 Hz (middle) and 0.88 Hz (right). Credit: Science Advances, doi: 10.1126/sciadv.aaz3194

Xu et al. selected Aurelia aurita as a model organism; an oblate species of jellyfish containing a flexible mesogleal bell and monolayer of coronal and radial muscles lining the subumbrellar surface. In order to swim, the organisms contracted muscles to decrease the subumbrellar cavity volume and eject water to provide a motive force alongside additional contributions from passive energy recapture and suction-based propulsion. To initiate these muscle contractions, the jellyfish activated any of its light pacemakers located in the sensor organs known as rhopalia along the bell margin. These nerve clusters activated the entire motor nerve net to cause bidirectional muscle wave propagations that originated from the activated pacemakers during natural propagation.

Robotic design integration in live jellyfish and device validation

The scientists first engineered a portable, self-contained microelectronic swim controller to generate a square pulse wave and stimulate muscle contractions from 0.25 Hz to 1.00 Hz. They composed the controller with a TinyLily mini-processor and a 10-mAh lithium polymer cell. To visually confirm the electrical signal, Xu et al. connected the wires in series to TinyLily light-emitting diodes (LEDs). They then inserted electrodes bilaterally into the subumbrellar tissue and kept the system naturally buoyant with stainless steel washers and cork. To validate that the swim controller could externally control jellyfish bell contractions, the scientists developed a method to track motion of the bell margin. For this, they completed three sets of experiments, (1) to observe endogenous contractions of the organism in the absence of any disturbances, (2) to observe if mechanically embedding inactive electrodes affected natural animal behavior and (3) to test stimulation protocols to confirm externally driven contractions.

Signal validation using visual tags and frequency spectra to track muscle contractions. (A) A. aurita medusae (n = 10, 8.0 to 10.0 cm in diameter) were placed subumbrellar surface up in a plate without seawater for constrained muscle stimulation experiments (electrode not shown). The image is inverted so that the bell and plate are white, and black areas are reflections of light from animal tissue and the plate. For clarity, the margin of the bell is outlined in a red dotted circle, and the oral arms are colorized in blue. Visible implant elastomer tags (shown as colored red dots within red circles) were injected around the margin, and one tag was tracked per video to calculate the tissue displacement as a surrogate for muscle contractions. Spatial tests to determine whether electrode location affected the spectra were conducted at four locations, labeled in red numbers: (1) adjacent to the gastric pouches, (2) midway between the gastric pouches and margin, (3) at the rhopalia, and (4) at the margin away from the rhopalia. All other tests were conducted at location 2. (B) Example tag displacement as a function of time for an animal without any external stimulus. The red line indicates the centroid displacement, with the error calculated from assuming a half-pixel uncertainty in finding the centroid of the tag in each image, over 25 s. Note the temporal variation of muscle contractions, including periods of regular pulses and successive rapid pulses. (C) Example tag displacement for an animal with an external stimulus of 0.25 Hz, with each stimulus visualized as a vertical black line. Although contractions regularly follow external stimuli, natural animal pulses also occur at low frequencies. Note, for example, the double pulse after one stimulus (t ≈ 12 s). (D) Example tag displacement for an animal with an external stimulus of 1.00 Hz, with each stimulus visualized as a vertical black line. The same time window (25 s) is shown for a fair comparison to the previous two plots. Contractions regularly follow external stimuli. (E) single-sided amplitude spectrum (SSASs) averaged for jellyfish without any external stimulus (n = 12 for 10 animals, i.e., 2 jellyfish had two replicate clips each). The red line indicates the mean of normalized SSAS for each replicate, with the SD in pink. The peak of the mean SSAS is at 0.16 Hz. The full width at half maximum (FWHM) is 0.24 Hz. (F) Jellyfish response to an inactive electrode embedded (n = 14 for 10 animals, i.e., 4 jellyfish had two replicate clips each). The peak of the mean SSAS is at 0.18 Hz. The FWHM is 0.16 Hz. Using a two-sample t test of the peak frequencies for both groups, the difference between the two samples was statistically insignificant (P = 0.68). (G) Sample SSAS for an electrical stimulus at 1.00 Hz (n = 10 jellyfish for an input signal of 4.2 V and 4.0 ms). The peak frequency occurs at 1.02 Hz, within the 0.02 window used to calculate the SSAS. Note that the spectrum has a sharper peak at the frequency of interest (FWHM of 0.04 Hz), as opposed to a wider FWHM in (B) and (C), the cases without any external stimulus. (H) Contour map of the frequency response of muscle contractions to external electrical stimuli. Each vertical line of data (centered on white lines at 0.25, 0.50, 0.75, 1.00, 1.20, 1.50, and 2.00 Hz) represents the PSD at one electrical input frequency, with the number of jellyfish tested shown above. The colors correspond to the amplitude of the PSD, in which higher values are shown in yellow and lower values in blue. The solid red line represents a one-to-one input-output response, and the dashed red line represents the reported physiological limit according to the minimum absolute refractory period of A. aurita muscle (32). Responsive trials are defined by whether the peak frequencies in the PSD lie within a window of 0.06 Hz of the solid red curve. (I) Contour maps of the unresponsive trials. Higher frequencies up to 90.00 Hz were also tested with similar unresponsive PSDs. Photo credit for (A): Nicole W. Xu, Stanford University. Credit: Science Advances, doi: 10.1126/sciadv.aaz3194

They found that natural animal behavior (or endogenous contraction) was irregular with high pulse rate variability—including a mean peak frequency of 0.16 Hz. An inactive electrode did not significantly change the frequency spectra, while externally driven contractions showed a physiological limit of jellyfish muscle contractions between 1.4 Hz to 1.5 Hz. The team conducted swimming trials with the implanted system in a saltwater tank and normalized the measured swimming speeds to account for variation in animal size. They scaled the normalized swimming speed by the mean of the normalized speed in the absence of stimulation (i.e. 0 Hz) to determine the enhancement factor. The maximum enhancement factor was up to 2.8 times the natural swimming speed of the animals, i.e., the swimming speed enhanced up to 2.8 times using onboard microelectronics.

Highly efficient device power consumption

The artificially controlled jellyfish required external power from the microelectronic system and internal power from the animals' own metabolism. When driven at increasing frequencies, the microelectronic system of the biohybrid robotic jellyfish consumed greater Watts per kg. However, compared to existing robots, this biohybrid robot used up to 1000 times less external power. Xu et al. compared this prototype with the medusoid and robotic ray made from rat cardiomyocytes seeded on silicon scaffolds, and with purely mechanical robots as well as autonomous underwater vehicles (AUVs). In addition to the cost-effective benefits of low external power consumption per mass of the biohybrid robot, the microelectronic system only cost less than $20 from commercially available components. The electrolocation was also non-specific and the animals immediately recovered after the experiments.

Metabolic rate experiments. To determine the metabolic rate of jellyfish, oxygen concentrations were measured in animal tissue and the surrounding water and then converted into energy expenditure. (A) Experimental setup to measure bulk dissolved oxygen concentrations (in the water). Animals were placed subumbrellar surface upward in a sealed glass dish filled with 2 liters of artificial seawater, with two electrodes for frequency-driven cases. Oxygen levels in the water were measured using a MicroOptode oxygen probe. (B) Experimental setup to measure intragel oxygen concentrations (in the tissue). Animals were placed subumbrellar surface upward in a sealed glass dish filled with 2 liters of artificial seawater, with two electrodes for frequency-driven cases. Intragel oxygen levels were measured using a MicroOptode oxygen probe embedded into the tissue. (C) Representative plot of oxygen concentrations over time, measured from the MicroOptode. This example shows measurements of bulk oxygen levels in the water surrounding an animal with a swim controller–driven frequency of 1.00 Hz. Individual data points are shown in black, the best-fit line is shown in dark blue, and the SD is shown in the light blue shaded region. (D) Oxygen consumption rates of the surrounding water (dark blue), within animal tissue (light blue), and total (sum of the water and tissue measurements, purple) were calculated over a 6- to 8-hour period (n = 7 animals).Credit: Science Advances, doi: 10.1126/sciadv.aaz3194

The new capability of external control allowed Xu et al. to address the relationship between swimming frequency and metabolic rate. Oxygen consumption rates followed a similar pattern to enhanced swimming speeds, and the scientists calculated the equivalent cost of transport using both experimental metabolic rates and experimental swimming speeds. The COT increased at mid-range frequencies and decreased at high external stimulation frequencies. The results showed that enhanced jellyfish swimming did not cause undue cost to the metabolism or health of the animal.

The main robotic limit of the study was the power requirement of the microelectronic system relative to animal versus microelectronic power needs. Further improvement to microelectronics can decrease the energetic costs and extended studies can also strive to minimize endogenous animal contractions without harming the organism to improve controllability of live-animal-based biohybrid robots. The artificial control of jellyfish can expand ocean monitoring techniques with improved controllability by incorporating microelectronic sensors to leverage the existing tagging technology.Bionic jellyfish swim faster and more efficiently

More information: Nicole W. Xu et al. Low-power microelectronics embedded in live jellyfish enhance propulsion, Science Advances (2020). DOI: 10.1126/sciadv.aaz3194

XI. The Croonian lecture.—Preliminary observations on the locomotor system of medusæ, Published:01 January 1876. Philosophical Transactions. doi.org/10.1098/rstl.1876.0011

Guang-Zhong Yang et al. The grand challenges of Science Robotics, Science Robotics (2018). DOI: 10.1126/scirobotics.aar7650

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Supercharging decarbonization through intelligent technologies

by Louise Renwick, Cambridge Centre for Advanced Research and Education in Singapore

Digital technologies provide the possibility of decarbonising industry through big data, machine learning and the Internet of Things. Credit: Cambridge CARES

Integrating digital tools into the world's energy systems could reduce carbon emissions by more than 50%, a new review has found.

The review reassesses the marginal abatement cost curve (MACC) popularized by McKinsey and finds that digitalization of energy systems completely alters the curve, thanks to the creation of novel pathways for the transition to low-carbon energy. If cyber-physical systems are integrated into our energy systems, carbon abatement potential can be expected to increase by 20%, rising to 30% when artificial intelligence (AI) is included.

MACCs illustrate both the cost and potential of various carbon dioxide reduction strategies and are used by policy makers to assess which paths to pursue. The addition of cyber-physical systems –digital technologies that interact with the physical world – is a substantial update to the MACC and further establishes it as an indispensable tool for those working on decarbonization.

Decarbonising the world's energy systems is a crucial part of mitigating climate change through the reduction of greenhouse gas emissions. While decarbonization is non-negotiable if climate breakdown is to be halted, it must be balanced with ensuring economic stability and a smooth transition to sustainable energy.

Digital technologies such as big data, machine learning and the Internet of Things hold immense potential to help us meet this challenge. Their applications range from helping to reduce our power bills by employing smart meters in the home, to assisting with peer-to-peer energy trading between power stations via blockchain.

The impact of cyber-physical system technologies on the marginal abatement cost of selected decarbonisation technologies in energy transition. Credit: Cambridge CARES

An international team of researchers from Singapore, Switzerland, the U.K. and the U.S. found that while existing digital technologies have numerous and effective applications when considered individually, the potential reduction of carbon emissions is multiplied when they are combined. Such combinations are called cyber-physical systems – interacting networks of physical infrastructure and computers that allow for smarter analysis, decision-making and optimization of energy systems.

Introducing AI into these cyber-physical systems can lead to further carbon savings; up to 30% more than without AI. This combination of technologies creates what is dubbed "intelligent cyber-physical systems". Benefits include more resilient infrastructure and operational flexibility, among others.

Enhanced renewable energy forecasting is one good example of how an intelligent cyber-physical system can be applied. The wind and solar energy sectors have seen much growth and while the price of these technologies has come down, the intermittent nature of this type of power has limited its application. The integration of backup energy systems (natural gas plants, for example) or energy storage technologies is required. Intelligent cyber-physical technologies, in particular machine learning, could help with this integration through improved forecasting of solar and wind variability.

Other large energy systems such as power plants can also benefit. When applied to carbon capture and storage plants, for example, these technologies can convert operational data into actionable intelligence, thereby reducing costs and improving energy efficiency through improved processes.

Cyber-physical systems, especially those combined with AI, provide the much-needed boost required for countries to meet their decarbonization and emissions targets. It is now up to policy makers to take this forward by incentivizing the deployment of these technologies to combat climate change.

Renewables are a better investment than carbon capture for tackling climate change

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More information: The impact of intelligent cyber-physical systems on the decarbonization of energy. Oliver Inderwildi, Chuan Zhang, Xiaonan Wang and Markus Kraft, Energy Environ. Sci., (2020), DOI: 10.1039/c9ee01919g

Provided by Cambridge Centre for Advanced Research and Education in Singapore