Lifeboat Foundation

Domino’s and Nuro teamed up for autonomous pizza delivery in Houston. Don’t get your hopes up, though, for a driverless drop-off: Many restrictions apply, and only a handful of hungry people can opt in right now.

Beginning this week, select customers who place a prepaid website order from the lone participating pizza shop in Woodland Heights can opt to have their food delivered by Nuro’s R2 robot. Those lucky patrons receive text alerts highlighting R2’s location, and can track the vehicle via GPS on the order confirmation page. Domino’s also provides a unique personal identification number required to open the bot’s door and reveal that piping hot pizza.

“We’re excited to continue innovating the delivery experience for Domino’s customers by testing autonomous delivery with Nuro in Houston,” Dennis Maloney, Domino’s senior vice president and chief innovation officer, said in a statement. “There is still so much for our brand to learn about the autonomous delivery space.”

It may be possible in the future to use information technology where electron spin is used to store, process and transfer information in quantum computers. It has long been the goal of scientists to be able to use spin-based quantum information technology at room temperature. A team of researchers from Sweden, Finland and Japan have now constructed a semiconductor component in which information can be efficiently exchanged between electron spin and light at room temperature and above. The new method is described in an article published in Nature Photonics.

It is well known that electrons have a negative charge; they also have another property called spin. This may prove instrumental in the advance of information technology. To put it simply, we can imagine the electron rotating around its own axis, similar to the way in which the Earth rotates around its own axis. Spintronics—a promising candidate for future information technology—uses this quantum property of electrons to store, process and transfer information. This brings important benefits, such as higher speed and lower energy consumption than traditional electronics.

Developments in spintronics in recent decades have been based on the use of metals, and these have been highly significant for the possibility of storing large amounts of data. There would, however, be several advantages in using spintronics based on semiconductors, in the same way that semiconductors form the backbone of today’s electronics and photonics.

A team of researchers at Technion—Israel Institute of Technology has developed a new technique for conducting real-time evanescent wave imaging using standard optical technology. In their paper published in the journal Nature Photonics, the group describes their new technology and ways they believe it can be used in photonic device characterization and other applications.

Evanescent waves are oscillating electric or magnetic fields that do not propagate—their energy remains in the vicinity of the source that created them due to a quickly decaying amplitude. They play an important role in acoustic and optical applications. Guided waves, on the other hand, have certain frequencies and energy that can travel very quickly along a designated path—they also leave a trace of their passing—an evanescent wave that decays so quickly that it is very difficult to see it with standard technology. Past attempts to image them have run into trouble, such as perturbation in the field under study, long acquisition times or the need for complex and expensive equipment. In this new effort, the researchers have developed a technique for measuring and imaging evanescent waves that overcomes all these problems.

The work involved studying evanescent waves of light by mixing them with a laser beam. Doing so resulted in the creation of a new frequency that could be both seen and studied. The method works, they note, because the laser changes the direction of the electric field. They found during experimentation that they could create different shapes using the laser. And further study showed that it was possible to both insert information into the evanescent waves and to take it out when desired. They also found that the shapes could be imaged using standard commercial cameras. The team calls the new technique nonlinear near-field optical microscopy and note that it does not require exotic equipment and can be done at very little cost.

Classical hydrodynamics laws can be very useful for describing the behavior of systems composed of many particles (i.e., many-body systems) after they reach a local state of equilibrium. These laws are expressed by so-called hydrodynamical equations, a set of mathematical equations that describe the movement of water or other fluids.

Researchers at Oak Ridge National Laboratory and University of California, Berkeley (UC Berkeley) have recently carried out a study exploring the hydrodynamics of a quantum Heisenberg spin-1/2 chain. Their paper, published in Nature Physics, shows that the spin dynamics of a 1D Heisenberg antiferromagnet (i.e., KCuF₃) could be effectively described by a dynamical exponent aligned with the so-called Kardar-Parisi-Zhang universality class.

“Joel Moore and I have known each other for many years and we both have an interest in quantum magnets as a place where we can explore and test new ideas in physics; my interests are experimental and Joel’s are theoretical,” Alan Tennant, one of the researchers who carried out the study, told Phys.org. “For a long time, we have both been interested in temperature in quantum systems, an area where a number of really new insights have come along recently, but we had not worked together on any projects.”

Topological insulators have notable manifestations of electronic properties. The helicity-dependent photocurrents in such devices are underpinned by spin momentum-locking of surface Dirac electrons that are weak and easily overshadowed by bulk contributions. In a new report now published on Science Advances, X. Sun and a research team in photonic technologies, physics and photonic metamaterials in Singapore and the U.K. showed how the chiral response of materials could be enhanced via nanostructuring. The tight confinement of electromagnetic fields in the resonant nanostructures enhanced the photoexcitation of spin-polarized surface states of a topological insulator to allow an 11-fold increase of the circular photogalvanic effect and a previously unobserved photocurrent dichroism at room temperature. Using this method, Sun et al. controlled the spin transport in topological materials via structural design, a hitherto unrecognized ability of metamaterials. The work bridges the gap between nanophotonics and spin electronics to provide opportunities to develop polarization-sensitive photodetectors.

Chirality

Chirality is a ubiquitous and fascinating natural phenomenon in nature, describing the difference of an object from its mirror image. The process manifests in a variety of scales and forms from galaxies to nanotubes and from organic molecules to inorganic compounds. Chirality can be detected at the atomic and molecular level in fundamental sciences, including chemistry, biology and crystallography, as well as in practice, such as in the food and pharmaceutical industry. To detect chirality, scientists can use interactions with electromagnetic fields, although the process can be hindered by a large mismatch between the wavelength of light and the size of most molecules at nanoscale dimensions. Designer metamaterials with structural features comparable to the wavelength of light can provide an independent approach to devise optical properties on demand to enhance the light-matter interaction to create and enhance the optical chirality of metamaterials. In this work, Sun et al.

In real-world attacks, “a simple scenario… would have an attacker infiltrating a manufacturing network via an RCE on an exposed IoT device then causing a production line to stop by causing a DoS on an industrial controller,” Daniel dos Santos, research manager at Forescout Research Labs, said. “Similarly, the attacker could switch off the lights of a target company by leveraging a vulnerable building automation controller.”

Many of the Name: Wreck vulnerabilities stem from DNS implementations of a protocol feature called message compression. Message compression reduces the size of DNS messages, due to DNS response packets often including the same domain name. This compression mechanism has been problematic to implement on products for 20 years, said researchers, causing issues on DNS servers, enterprise devices and, more recently, TCP/IP stacks. Forescout researchers disclosed three flaws relating to message compression during previous research into TCP/IP vulnerabilities (particularly the Ripple20 and AMNESIA:33 sets of flaws). Consequently, they hunted for other similar types of flaws in other protocol stacks.

As part of the ensuing Name: Wreck research, researchers found DNS message compression vulnerabilities in four popular TCP/IP stacks, including FreeBSD (version 12.1), IPnet (version VxWorks 6.6), NetX (version 6.0.1) and Nucleus Net (version 4.3). The most critical flaws exist in FreeBSD, popular IT software used by high-performance servers in millions of IT networks, including major websites such as Netflix and Yahoo; and in Siemens’ Nucleus NET firmware, which has been used for decades by critical OT and Internet-of-Things (IoT) devices.

Microsoft has released patches for a Windows bug that is being exploited in the wild and for four new Exchange vulnerabilities.

Up to 97 percent of organizations reported facing mobile threats that used multiple attack vectors during 2020, as cybercriminals continue to adopt new tactics to target mobile devices.

MIT Technology Review Insights, in association with AI cybersecurity company Darktrace, surveyed more than 300 C-level executives, directors, and managers worldwide to understand how they’re addressing the cyberthreats they’re up against—and how to use AI to help fight against them.

Cyberattacks continue to grow in prevalence and sophistication. With the ability to disrupt business operations, wipe out critical data, and cause reputational damage, they pose an existential threat to businesses, critical services, and infrastructure. Today’s new wave of attacks is outsmarting and outpacing humans, and even starting to incorporate artificial intelligence (AI). What’s known as “offensive AI” will enable cybercriminals to direct targeted attacks at unprecedented speed and scale while flying under the radar of traditional, rule-based detection tools.

Some of the world’s largest and most trusted organizations have already fallen victim to damaging cyberattacks, undermining their ability to safeguard critical data. With offensive AI on the horizon, organizations need to adopt new defenses to fight back: the battle of algorithms has begun.

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