Lifeboat Foundation

Emerging quantum materials can be defined by topology and strong electron correlations, although their applications in experimental systems are relatively limited. Weyl semimetals incorporating magnetism offer a unique and fertile platform to explore emerging phenomena in developing topological matter and topological spintronics. The triangular antiferromagnet Mn₃Sn exhibits many exotic physical properties as an antiferromagnetic (AFM) Weyl semimetal (WSM), including an attractively large spontaneous Hall effect.

The spontaneous Hall effect was discovered more than a century ago and understood in terms of time-reversal symmetry breaking by the internal spin structure of antiferromagnetic, ferromagnetic or skyrmionic (small swirling topological defects in the magnetization) forms.

In a new report now published on Science Advances, Durga Khadka and a team of scientists in physics, materials science, neutron research and engineering in the U.S. reported the synthesis of epitaxial Mn_3+x Sn_1−x films with compositions similar to bulk samples. When they replaced the tin (Sn) atoms with magnetic manganese (Mn) atoms in the samples, they noted the Kondo effect; a celebrated example of strong correlations to emerge, then develop coherence and induce a hybridization energy gap. The process of magnetic doping and gap opening facilitated rich extraordinary properties for the new materials.

Rabia Nusrat, an environmental engineering student, Global UGRAD alumni, in her final year at University of Engineering and Technology, UET, Lahore, Pakistan and the first ideaXme public interviewer, interviews Shayan Sohail Sarwar, Forbes 30 Under 30 Asia Innovator and Chief Technology Officer PakVitae.

PakVitae:

Continue reading “Forbes 30 under 30 Asia Innovators 2020 from Pakistan Create PakVitae for the World” »

The brain is an inherently dynamic system, and much work has focused on the ability to modify neural activity through both local perturbations and changes in the function of global network ensembles. Network controllability is a recent concept in network neuroscience that purports to predict the influence of individual cortical sites on global network states and state changes, thereby creating a unifying account of local influences on global brain dynamics. While this notion is accepted in engineering science, it is subject to ongoing debates in neuroscience as empirical evidence linking network controllability to brain activity and human behavior remains scarce. Here, we present an integrated set of multimodal brain–behavior relationships derived from fMRI, diffusion tensor imaging, and online repetitive transcranial magnetic stimulation (rTMS) applied during an individually calibrated working memory task performed by individuals of both sexes. The modes describing the structural network system dynamics showed direct relationships to brain activity associated with task difficulty, with difficult-to-reach modes contributing to functional brain states in the hard task condition. Modal controllability (a measure quantifying the contribution of difficult-to-reach modes) at the stimulated site predicted both fMRI activations associated with increasing task difficulty and rTMS benefits on task performance. Furthermore, fMRI explained 64% of the variance between modal controllability and the working memory benefit associated with 5 Hz online rTMS. These results therefore provide evidence toward the functional validity of network control theory, and outline a clear technique for integrating structural network topology and functional activity to predict the influence of stimulation on subsequent behavior.

SIGNIFICANCE STATEMENT The network controllability concept proposes that specific cortical nodes are able to steer the brain into certain physiological states. By applying external perturbation to these control nodes, it is theorized that brain stimulation is able to selectively target difficult-to-reach states, potentially aiding processing and improving performance on cognitive tasks. The current study used rTMS and fMRI during a working memory task to test this hypothesis. We demonstrate that network controllability correlates with fMRI modulation because of working memory load and with the behavioral improvements that result from a multivisit intervention using 5 Hz rTMS. This study demonstrates the validity of network controllability and offers a new targeting approach to improve efficacy.

Studies will explore controversial cooling approaches.

A new image shows what Venus would look like if it had water on its surface, similar to the Earth.

Brownian motion of particles in fluid is a common collective behavior in biological and physical systems. In a new report on Science Advances, Kai Leong Chong, and a team of researchers in physics, engineering, and aerospace engineering in China, conducted experiments and numerical simulations to show how the movement of vortices resembled inertial Brownian particles. During the experiments, the rotating turbulent convective vortical flow allowed the particles to move ballistically at first and diffusively after a critical time in a direct behavioral transition—without going through a hydrodynamic memory regime. The work implies that convective vortices have inertia-induced memory, so their short-term movement was well-defined in the framework of Brownian motion here for the first time.

Brownian motion

Albert Einstein first provided a theoretical explanation to Brownian motion in 1905 with the movement of pollen particles in a thermal bath, the phenomenon is now a common example of stochastic processes that widely occur in nature. Later in 1908, Paul Langevin noted the inertia of particles and predicted that their motion would be ballistic within a short period of time, changing to diffuse motion after a specific timeline. However, due to the rapidity of this transition, it took more than a century for researchers to be able to directly observe the phenomenon. Nevertheless, the “pure” Brownian motion predicted by Langevin was not observed in liquid systems and the transition spanned a broad range of time scales. The slow and smooth transition occurred due to the hydrodynamic memory effect, to ultimately generate long-range correlations.

Mike Snead, P.E., president of the Spacefaring Institute, was invited to present at the Envision Humanity conference held in Portugal on 18 July 2020. This presentation was delivered via video. It addresses the world green energy needed to “globally reset” human civilization using astroelectricity (GEO space-based solar power) to achieve sustainable, prosperous living worldwide. The presentation also shows why the “Green New Deal’s” call to use terrestrial nuclear and renewable energy to replace fossil carbon fuels is not a practical solution. The presentation provides an interesting way to understand the magnitude of the engineering challenge and options available to complete this important transition to sustainable energy.

Our muscles start to shrink and weaken when we reach our 50s and 60s in a process called sarcopenia, but new research in mice from the University of Michigan offers new insights into why this loss may occur, and how we might begin to prevent it.

Sarcopenia is the progressive loss of muscle mass in aging, and it’s linked to other age-related pathologies such as osteoarthritis, cardiovascular disease and cancer, as well as an overall reduction in function and independence.

The research, led by Carlos Aguilar, a U-M assistant professor of biomedical engineering, focused on muscle stem cells since they are dedicated solely to keeping muscles healthy. And to better understand stem cell function during aging, testing was conducted on two sets of mice, one “young” and one “old,” before and after muscle injury.

The world’s fastest data transmission rate has been achieved by a team of University College London engineers who achieved internet transmission speed a fifth faster than the previous record.

Working with two companies, Xtera and KDDI Research, the research team led by Dr. Lidia Galdino (UCL Electronic & Electrical Engineering), achieved a data transmission rate of 178 terabits a second (178,000,000 megabits a second) – a speed at which it would be possible to download the entire Netflix library in less than a second.

The record, which is double the capacity of any system currently deployed in the world, was achieved by transmitting data through a much wider range of colors of light, or wavelengths, than is typically used in optical fiber. (Current infrastructure uses a limited spectrum bandwidth of 4.5THz, with 9THz commercial bandwidth systems entering the market, whereas the researchers used a bandwidth of 16.8THz.)