Lifeboat Foundation

Silicon Valley wants to study your brain activity.

Bismuth has been around for thousands of years, yet it’s only been used in a handful of applications — and mostly to treat stomach ailments. But as the world looks for cleaner and safer energy, bismuth might soon become the star of the heavy metals family.

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Biological systems are dynamical, constantly exchanging energy and matter with the environment in order to maintain the non-equilibrium state synonymous with living. Developments in observational techniques have allowed us to study biological dynamics on increasingly small scales. Such studies have revealed evidence of quantum mechanical effects, which cannot be accounted for by classical physics, in a range of biological processes. Quantum biology is the study of such processes, and here we provide an outline of the current state of the field, as well as insights into future directions.

Quantum mechanics is the fundamental theory that describes the properties of subatomic particles, atoms, molecules, molecular assemblies and possibly beyond. Quantum mechanics operates on the nanometre and sub-nanometre scales and is at the basis of fundamental life processes such as photosynthesis, respiration and vision. In quantum mechanics, all objects have wave-like properties, and when they interact, quantum coherence describes the correlations between the physical quantities describing such objects due to this wave-like nature.

In photosynthesis, respiration and vision, the models that have been developed in the past are fundamentally quantum mechanical. They describe energy transfer and electron transfer in a framework based on surface hopping. The dynamics described by these models are often ‘exponential’ and follow from the application of Fermi’s Golden Rule [1, 2]. As a consequence of averaging the rate of transfer over a large and quasi-continuous distribution of final states the calculated dynamics no longer display coherences and interference phenomena. In photosynthetic reaction centres and light-harvesting complexes, oscillatory phenomena were observed in numerous studies performed in the 1990s and were typically ascribed to the formation of vibrational or mixed electronic–vibrational wavepackets.

ABSTRACT. Galaxy models have long predicted that galactic bars slow down by losing angular momentum to their postulated dark haloes. When the bar slows down, resonance sweeps radially outwards through the galactic disc while growing in volume, thereby sequentially capturing new stars at its surface/separatrix. Since trapped stars conserve their action of libration, which measures the relative distance to the resonance centre, the order of capturing is preserved: the surface of the resonance is dominated by stars captured recently at large radius, while the core of the resonance is occupied by stars trapped early at small radius. The slow down of the bar thus results in a rising mean metallicity of trapped stars from the surface towards the centre of the resonance as the Galaxy’s metallicity declines towards large radii. This argument, when applied to Solar neighbourhood stars, allows a novel precision measurement of the bar’s current pattern speed |$\Omega _{\rm p}= 35.5 \pm 0.8 \, {\rm km}\, {\rm s}^{-1}\, {\rm kpc}^{-1}$|⁠, placing the corotation radius at |$R_{\rm CR}= 6.6 \pm 0.2 \, {\rm kpc}$|⁠. With this pattern speed, the corotation resonance precisely fits the Hercules stream in agreement with kinematics. Beyond corroborating the slow bar theory, this measurement manifests the deceleration of the bar of more than |$24{{\ \rm per\ cent}}$| since its formation and thus the angular momentum transfer to the dark halo by dynamical friction. The measurement therefore supports the existence of a standard dark-matter halo rather than alternative models of gravity.

Physics World

Experiment shows that classical clocks exhibit the same relationship between entropy and accuracy as their quantum counterparts.

All plant cells obtain their energy mainly from two organelles they contain—chloroplasts (responsible for photosynthesis) and mitochondria (responsible for the biochemical cycle of respiration that converts sugars into energy). However, a large number of a plant cell’s genes in its mitochondria and chloroplasts can develop defects, jeopardizing their function. Nevertheless, plant cells evolved an amazing tool called the RNA editosome (a large protein complex) to repair these kinds of errors. It can modify defective messenger RNA that result from defective DNA by transforming (deamination) of certain mRNA nucleotides.

Automatic error correction in plant cells

Automatic error correction in plants was discovered about 30 years ago by a team headed by plant physiologist Axel Brennicke and two other groups simultaneously. This mechanism converts certain cytidine nucleotides in the messenger RNA into uridine in order to correct errors in the chloroplast DNA or mitochondrial DNA. RNA editing is therefore essential to processes such as photosynthesis and cellular respiration in plants. Years later, further studies showed that a group of proteins referred to as PPR proteins with DYW domains play a central role in plant RNA editing. These PPR proteins with DYW domains are transcribed in the cell nucleus and migrate through the cells to chloroplasts and mitochondria. However, they are inactive on their way to these organelles. Only once they are within the organelles do they become active and execute their function at a specific mRNA site. How this activation works, however, has been a mystery until now.

Last week, I wrote an analysis of Reward Is Enough, a paper by scientists at DeepMind. As the title suggests, the researchers hypothesize that the right reward is all you need to create the abilities associated with intelligence, such as perception, motor functions, and language.

This is in contrast with AI systems that try to replicate specific functions of natural intelligence such as classifying images, navigating physical environments, or completing sentences.

The researchers go as far as suggesting that with well-defined reward, a complex environment, and the right reinforcement learning algorithm, we will be able to reach artificial general intelligence, the kind of problem-solving and cognitive abilities found in humans and, to a lesser degree, in animals.

Close-up views of glasswing butterflies reveal the secrets behind the insect’s see-through wings: sparse, spindly scales and a waxy coating.

Welcome to the new space race, as the world’s richest men compete over who has the biggest rocket—and the ability to win lucrative contracts.