As artificial intelligence models grow larger and consume more energy, experts have begun to worry about their impact on Earth’s climate.
Summary: A new genetic engineering strategy significantly reduces levels of tau in animal models of Alzheimer’s disease. The treatment, which involves a single injection, appears to have long-last effects.
Source: Mass General.
Researchers have used a genetic engineering strategy to dramatically reduce levels of tau–a key protein that accumulates and becomes tangled in the brain during the development of Alzheimer’s disease–in an animal model of the condition.
Layers of ice and rock obviate the need for “habitable zone” and shield life against threats.
SwRI researcher theorizes worlds with underground oceans may be more conducive to life than worlds with surface oceans like Earth.
One of the most profound discoveries in planetary science over the past 25 years is that worlds with oceans beneath layers of rock and ice are common in our solar system. Such worlds include the icy satellites of the giant planets, like Europa, Titan, and Enceladus, and distant planets like Pluto.
Urban Air Port has chosen to build its first Air-One transport hub for autonomous delivery drones and electric flying cars next to the Ricoh Arena in Coventry, UK. The futuristic facility will launch later this year. It will support delivery drone and air taxi technology and eventually transport cargo and people across cities.
A supermassive black hole is speeding across the galaxy, and astronomers are baffled as to why.
The Research Group on Synthetic Biology for Biomedical Applications at Pompeu Fabra University in Barcelona, Spain, has designed a cellular device capable of computing by printing cells on paper. For the first time, they have developed a living device that could be used outside the laboratory without a specialist, and it could be produced on an industrial scale at low cost. The study is published in Nature Communications and was carried out by Sira Mogas-Díez, Eva Gonzalez-Flo and Javier Macía.
We currently have many electronic devices available to us such as computers and tablets whose computing power is highly efficient. But, despite their power, they are very limited devices for detecting biological markers, such as those that indicate the presence of a disease. For this reason, a few years ago ‘biological computers’ began to be developed—in other words, living cellular devices that can detect multiple markers and generate complex responses. In them, the researchers leverage biological receptors that allow detecting exogenous signals and, by means of synthetic biology, modify them to emit a response in accordance with the information they detect.
So far, cellular devices have been developed that must operate in the laboratory, for a limited time, under specific conditions, and must be handled by a specialist in molecular biology. Now, a team of researchers from Pompeu Fabra University has developed new technology to ‘print’ cellular devices on paper that can be used outside the laboratory.
Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect some of the most relevant recent discoveries and papers — particularly in but not limited to artificial intelligence — and explain why they matter.
This week brings a few unusual applications of or developments in machine learning, as well as a particularly unusual rejection of the method for pandemic-related analysis.
One hardly expects to find machine learning in the domain of government regulation, if only because one assumes federal regulators are hopelessly behind the times when it comes to this sort of thing. So it may surprise you that the U.S. Environmental Protection Agency has partnered with researchers at Stanford to algorithmically root out violators of environmental rules.
Researchers at the University of Ottawa have debunked the decade-old myth of metals being useless in photonics – the science and technology of light – with their findings, recently published in Nature Communications, expected to lead to many applications in the field of nanophotonics.
“We broke the record for the resonance quality factor (Q-factor) of a periodic array of metal nanoparticles by one order of magnitude compared to previous reports,” said senior author Dr. Ksenia Dolgaleva, Canada Research Chair in Integrated Photonics (Tier 2) and Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at the University of Ottawa.
“It is a well-known fact that metals are very lossy when they interact with light, which means they cause the dissipation of electrical energy. The high losses compromise their use in optics and photonics. We demonstrated ultra-high-Q resonances in a metasurface (an artificially structured surface) comprised of an array of metal nanoparticles embedded inside a flat glass substrate. These resonances can be used for efficient light manipulating and enhanced light-matter interaction, showing metals are useful in photonics.”
Astroscale’s ELSA-d mission is set to launch into orbit to demonstrate technologies that could help clean up space debris around Earth.
In this work, we carry out KS-MD simulations for a range of elements, temperatures, and densities, allowing for a systematic comparison of three RPP models. While multiple RPP models can be selected, 7–11 7. J. Vorberger and D. Gericke, “Effective ion–ion potentials in warm dense matter,” High Energy Density Phys. 9, 178 (2013). https://doi.org/10.1016/j.hedp.2012.12.009 8. Y. Hou, J. Dai, D. Kang, W. Ma, and J. Yuan, “Equations of state and transport properties of mixtures in the warm dense regime,” Phys. Plasmas 22, 022711 (2015). https://doi.org/10.1063/1.4913424 9. K. Wünsch, J. Vorberger, and D. Gericke, “Ion structure in warm dense matter: Benchmarking solutions of hypernetted-chain equations by first-principle simulations,” Phys. Rev. E 79, 010201 (2009). https://doi.org/10.1103/PhysRevE.79.010201 10. L. Stanton and M. Murillo, “Unified description of linear screening in dense plasmas,” Phys. Rev. E 91, 033104 (2015). https://doi.org/10.1103/PhysRevE.91.033104 11. W. Wilson, L. Haggmark, and J. Biersack, “Calculations of nuclear stopping, ranges, and straggling in the low-energy region,” Phys. Rev. B 15, 2458 (1977). https://doi.org/10.1103/PhysRevB.15.2458 we choose to compare the widely used Yukawa potential, which accounts for screening by linearly perturbing around a uniform density in the long-wavelength (Thomas–Fermi) limit, a potential constructed from a neutral pseudo-atom (NPA) approach, 12–15 12. L. Harbour, M. Dharma-wardana, D. D. Klug, and L. J. Lewis, “Pair potentials for warm dense matter and their application to x-ray Thomson scattering in aluminum and beryllium,” Phys. Rev. E 94, 053211 (2016). https://doi.org/10.1103/PhysRevE.94.053211 13. M. Dharma-wardana, “Electron-ion and ion-ion potentials for modeling warm dense matter: Applications to laser-heated or shock-compressed Al and Si,” Phys. Rev. E 86, 036407 (2012). https://doi.org/10.1103/PhysRevE.86.036407 14. F. Perrot and M. Dharma-Wardana, “Equation of state and transport properties of an interacting multispecies plasma: Application to a multiply ionized al plasma,” Phys. Rev. E 52, 5352 (1995). https://doi.org/10.1103/PhysRevE.52.5352 15. L. Harbour, G. Förster, M. Dharma-wardana, and L. J. Lewis, “Ion-ion dynamic structure factor, acoustic modes, and equation of state of two-temperature warm dense aluminum,” Phys. Rev. E 97, 043210 (2018). https://doi.org/10.1103/PhysRevE.97.043210 and the optimal force-matched RPP that is constructed directly from KS-MD simulation data.
Each of the models we chose impacts our physics understanding and has clear computational consequences. For example, success of the Yukawa model reveals the insensitivity to choices in the pseudopotential and screening function and allows for the largest-scale simulations. Large improvements are expected from the NPA model, which makes many fewer assumptions with a modest cost of pre-computing and tabulating forces. (See the Appendix for more details on the NPA model.) The force-matched RPP requires KS-MD data and is therefore the most expensive to produce, but it reveals the limitations of RPPs themselves since they are by definition the optimal RPP.
Using multiple metrics of comparison between RPP-MD and KS-MD including the relative force error, ion–ion equilibrium radial distribution function g (r), Einstein frequency, power spectrum, and the self-diffusion transport coefficient, the accuracy of each RPP model is analyzed. By simulating disparate elements, namely, an alkali metal, multiple transition metals, a halogen, a nonmetal, and a noble gas, we see that force-matched RPPs are valid for simulating dense plasmas at temperatures above fractions of an eV and beyond. We find that for all cases except for low temperature carbon, force-matched RPPs accurately describe the results obtained from KS-MD to within a few percent. By contrast, the Yukawa model appears to systematically fail at describing results from KS-MD at low temperatures for the conditions studied here validating the need for alternate models such as force-matching and NPA approaches at these conditions.