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May 29, 2020

DARPA Selects Teams to Increase Security of Semiconductor Supply Chain

Posted by in categories: computing, economics, internet, security

As Internet of Things (IoT) devices rapidly increase in popularity and deployment, economic attackers and nation-states alike are shifting their attention to the vulnerabilities of digital integrated circuit (IC) chips. Threats to IC chips are well known, and despite various measures designed to mitigate them, hardware developers have largely been slow to implement security solutions due to limited expertise, high cost and complexity, and lack of security-oriented design tools integrated with supporting semiconductor intellectual property (IP). Further, when unsecure circuits are used in critical systems, the lack of embedded countermeasures exposes them to exploitation. To address the growing threat this poses from an economic and national security perspective, DARPA developed the Automatic Implementation of Secure Silicon (AISS) program. AISS aims to automate the process of incorporating scalable defense mechanisms into chip designs, while allowing designers to explore chip economics versus security trade-offs based on the expected application and intent while maximizing designer productivity.

Today, DARPA is announcing the research teams selected to take on AISS’ technical challenges. Two teams of academic, commercial, and defense industry researchers and engineers will explore the development of a novel design tool and IP ecosystem – which includes tool vendors, chip developers, and IP licensors – allowing, eventually, defenses to be incorporated efficiently into chip designs. The expected AISS technologies could enable hardware developers to not only integrate the appropriate level of state-of-the-art security based on the target application, but also balance security with economic considerations like power consumption, die area, and performance.

“The ultimate goal of the AISS program is to accelerate the timeline from architecture to security-hardened RTL from one year, to one week – and to do so at a substantially reduced cost,” said the DARPA program manager leading AISS, Mr. Serge Leef.

May 29, 2020

A nuclear periodic table

Posted by in categories: chemistry, particle physics

There has been plenty of empirical evidence which shows that the single-particle picture holds to a good approximation in atomic nuclei. In this picture, protons and neutrons move independently inside a mean-field potential generated by an interaction among the nucleons. This leads to the concept of nuclear shells, similar to the electronic shells in atoms. In particular, the magic numbers due to closures of the nucleonic shells, corresponding to noble gases in elements, have been known to play an important role in nuclear physics. Here we propose a periodic table for atomic nuclei, in which the elements are arranged according to the known nucleonic shells. The nuclear periodic table clearly indicates that nuclei in the vicinity of the magic numbers can be understood in terms of a shell closure with one or two additional nucleons or nucleon holes, while nuclei far from the magic numbers are characterized by nuclear deformation.

May 29, 2020

Terahertz Second-Harmonic Generation from Lightwave Acceleration of Symmetry-Breaking Nonlinear Supercurrents

Posted by in categories: materials, quantum physics

We report terahertz (THz) light-induced second harmonic generation, in superconductors with inversion symmetry that forbid even-order nonlinearities. The THz second harmonic emission vanishes above the superconductor critical temperature and arises from precession of twisted Anderson pseudospins at a multicycle, THz driving frequency that is not allowed by equilibrium symmetry. We explain the microscopic physics by a dynamical symmetry breaking principle at sub-THz-cycle by using quantum kinetic modeling of the interplay between strong THz-lightwave nonlinearity and pulse propagation. The resulting nonzero integrated pulse area inside the superconductor leads to light-induced nonlinear supercurrents due to subcycle Cooper pair acceleration, in contrast to dc-biased superconductors, which can be controlled by the band structure and THz driving field below the superconducting gap.

May 29, 2020

SpaceX and NASA are launching astronauts—and a new orbital economy?

Posted by in categories: economics, space travel

Still, commercial crew has managed to move faster and stay on budget compared to other NASA projects which explicitly eschew private capital and insist that NASA is the only suitable customer for their wares. The agency estimates it saved as much as $30 billion by building its new spacecraft this way.


What if THIS is the most important thing that happens in 2020?

May 29, 2020

We can see when your brain forms a memory

Posted by in categories: biotech/medical, neuroscience

Subtle patterns can be seen in people’s reaction times as their memories are recalled, and boosting these brainwaves could help treat Alzheimer’s disease.

May 29, 2020

Researchers Identify 19 New Genetic Variants for Problematic Drinking

Posted by in category: genetics

An international team of scientists has identified 29 independent genetic risk variants — 19 of them novel — linked to problematic alcohol use and revealed genetic relationships with numerous other traits.

May 29, 2020

New study finds COVID-19 patients remain infectious for only this number of days

Posted by in category: biotech/medical

A study of 73 COVID-19 patients found that they only remain infectious for 11 days.

May 29, 2020

Here’s what to expect as SpaceX launches its first human crew to space

Posted by in category: space travel

On May 30th, SpaceX is slated to launch its first human passengers to space on the company’s new Crew Dragon spacecraft. The mission is a critical test flight for NASA as part of the agency’s Commercial Crew Program, aimed at getting private companies to create vehicles that can take astronauts to orbit. Here’s what to expect as the mission unfolds.

May 29, 2020

First map of tumour microbiomes finds bacteria live in many cancers

Posted by in category: biotech/medical

More than 500 strains of bacteria have been found living in seven types of tumour. Understanding their behaviour may lead to new kinds of treatments.

May 29, 2020

AI And The Digital Mine

Posted by in categories: bioengineering, climatology, robotics/AI

When you think of the words “data” and “mine”, no doubt the idea of data mining comes first. However, just as much as we find value in mining the rich resources of data, so too can we apply the advanced techniques for dealing with data to real-world mining — that is, extracting natural resources from the earth. The world is just as dependent on natural resources as it is data resources, so it makes sense to see how the evolving areas of artificial intelligence and machine learning have an impact on the world of mining and natural resource extraction.

Mining has always been a dangerous profession, since extracting minerals, natural gas, petroleum, and other resources requires working in conditions that can be dangerous for human life. Increasingly, we are needing to go to harsher climates such as deep under the ocean or deep inside the earth to extract the resources we still need. It should come as little surprise then that mining and resource extraction companies are looking to robotics, autonomous systems, and AI applications of all sorts to minimize risk, maximize return, and also lessen the environmental impact that mining has on our ecosystem.

On a recent AI Today podcast episode, Antoine Desmet of mining technology and equipment company Komatsu shared how they’re using advanced forms of AI, automation, and robotics to make an impact on the organization’s operations. Antoine has an interesting background, starting his career as a telecom engineer and receiving a Ph.D in neural network engineering. After getting his Ph.D, he returned to Komatsu and started working in surface analytics. He states that at the time there was a lot of data to work with, but very few analytics in place. He decided to start implementing machine learning and in the last few years his company has seen significant growth through this approach, with his data science team growing from just one person to ten people.