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One of the promising technologies being developed for next-generation augmented/virtual reality (AR/VR) systems is holographic image displays that use coherent light illumination to emulate the 3D optical waves representing, for example, the objects within a scene. These holographic image displays can potentially simplify the optical setup of a wearable display, leading to compact and lightweight form factors.

On the other hand, an ideal AR/VR experience requires relatively to be formed within a large field-of-view to match the resolution and the viewing angles of the human eye. However, the capabilities of holographic image projection systems are restricted mainly due to the limited number of independently controllable pixels in existing image projectors and spatial light modulators.

A recent study published in Science Advances reported a deep learning-designed transmissive material that can project super-resolved images using low-resolution image displays. In their paper titled “Super-resolution image display using diffractive decoders,” UCLA researchers, led by Professor Aydogan Ozcan, used deep learning to spatially-engineer transmissive diffractive layers at the wavelength scale, and created a material-based physical image decoder that achieves super-resolution image projection as the light is transmitted through its layers.

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When trying to make a purchase with a shopping app, we may quickly browse the recommendation list while admitting that the machine does know about us—at least, it is learning to do so. As an effective emerging technology, machine learning (ML) has become pretty much pervasive with an application spectrum ranging from miscellaneous apps to supercomputing.

Dedicated ML computers are thus being developed at various scales, but their productivity is somewhat limited: the workload and development cost are largely concentrated in their software stacks, which need to be developed or reworked on an ad hoc basis to support every scaled model.

To solve the problem, researchers from the Chinese Academy of Sciences (CAS) proposed a parallel computing model and published their research in Intelligent Computing on Sept. 5.

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It is common to hear news reports about large data breaches, but what happens once your personal data is stolen? Our research shows that, like most legal commodities, stolen data products flow through a supply chain consisting of producers, wholesalers and consumers. But this supply chain involves the interconnection of multiple criminal organizations operating in illicit underground marketplaces.

The stolen data begins with producers—hackers who exploit vulnerable systems and steal such as , bank account information and Social Security numbers. Next, the stolen data is advertised by wholesalers and distributors who sell the data. Finally, the data is purchased by consumers who use it to commit various forms of fraud, including fraudulent credit card transactions, identity theft and phishing attacks.

This trafficking of stolen data between producers, wholesalers and consumers is enabled by darknet markets, which are websites that resemble ordinary e-commerce websites but are accessible only using special browsers or authorization codes.

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In biological imaging, researchers aim to achieve 3D, high-speed, and high-resolution, with low photobleaching and phototoxicity. The light-sheet fluorescence microscope (LSFM) helps meet that aim. Based on a unique excitation and detection scheme, the LSFM can image live specimens with high spatiotemporal resolution and low photobleaching. It has shown great potential for 3D imaging of biological samples.

The principle of LSFM technology is to illuminate the sample with a thin and then collect the emitted fluorescence along the axis perpendicular to the transmission of the light-sheet. Therefore, only fluorophores close to the are excited and detected. Using a thinner light-sheet improves the axial , while a longer light-sheet improves the (FoV) and imaging speed. Tradeoffs are required, as it is difficult to generate a thin, uniform light-sheet.

Multiple light-sheets can be tiled to generate a virtual light-sheet with a higher aspect ratio. However, multiple beams also introduce sidelobes, decreasing the axial resolution and optical sectioning. Axially swept light-sheet microscopy (ASLM) uses a slit to reject the sidelobes. It uses the rolling shutter of the sCMOS, which naturally serves as a slit, to synchronize beam scanning. ASLM can image an arbitrarily large FoV with optimal axial resolution. However, the fluorescence signal outside the rolling shutter will be rejected, so a larger FoV comes at the price of lower photon efficiency.

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Scientists from EPFL and the University of Lausanne have used a chip that was originally designed for environmental science to study the properties of biocement formation. This material has the potential to replace traditional cement binders in certain civil engineering applications.

The chip is the size of a credit card and its surface is engraved with a flow channel measuring one meter from end to end that is as thick as a human hair. Researchers can inject a solution into one end of the channel and, with the help of time-lapse microscopy, observe the solution’s behavior over several hours. Medical scientists have used similar chips for health care applications, such as to examine how arteries get clogged or how a drug spreads into the bloodstream, while environmental engineers have applied them to the study of biofilms and contaminants in drinking water.

Now, a team of civil engineers at EPFL’s Laboratory of Soil Mechanics (LMS), together with scientists from the Faculty of Geosciences and Environment at the University of Lausanne (UNIL), have repurposed the chip to understand complex transport-reaction phenomena involved in the formation of new kinds of biocement.

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Researchers from Tokyo Metropolitan University have carried out a detailed simulation showing how a common type of bridge fails during large-scale earthquakes. They modeled I-shaped girder bridges, looking at the step-by-step mechanism by which they yield and deform under lateral forces, starting at the ends. Reinforcing ribs were shown to be effective against lateral forces and improve load-bearing capacity. Their work points bridge engineers to rational design strategies to make more resilient infrastructures.

Major earthquakes can have a devastating impact on infrastructure. The effects of a severely damaged bridge, for example, are not limited to the tragedy that befalls people on it but extends to how the loss of access affects emergency services, evacuation efforts, and the transport of crucial supplies. Understanding how seismic activity impacts common bridge structures is therefore crucial, not only to build bridges that can withstand strong quakes, but how to prevent the failure of existing ones through effective reinforcement.

Though numerous models exist that are used to assess the resilience of bridge superstructures, for the most part, there are very few examples that examine how each part of the whole bridge structure behaves during large-scale earthquakes.

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SpaceX revealed a new business segment called Starshield aimed at U.S. national security government agencies. “While Starlink is designed for consumer and commercial use, Starshield is designed for government use, with an initial focus on three areas: Earth observation, communications and hosted payloads,” the company said on its website.

This is a big deal as SpaceX is currently burning through $2 billion/year as it works to develop Starlink and Starship. So SpaceX wouldn’t mind some extra cash!

WASHINGTON — SpaceX on Dec. 2 revealed a new business segment called Starshield aimed at U.S. national security government agencies.

This sector of SpaceX intends to leverage the Starlink internet constellation in low Earth orbit to develop products and services — including secure communications, remote sensing and space surveillance payloads — that are in growing demand by U.S. defense and intelligence organizations.

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