Lifeboat Foundation

It is an old-standing theory in evolutionary ecology: animal species on islands have the tendency to become either giants or dwarfs in comparison to mainland relatives. Since its formulation in the 1960s, however, the ‘island rule’ has been severely debated by scientists. In a new publication in Nature Ecology and Evolution on April 15, 2021, researchers solved this debate by analyzing thousands of vertebrate species. They show that the island rule effects are widespread in mammals, birds, and reptiles, but less evident in amphibians.

Dwarf hippos and elephants in the Mediterranean islands are examples of large species that exhibited dwarfism. On the other hand, small mainland species may have evolved into giants after colonizing islands, giving rise to such oddities as the St Kilda field mouse (twice the size of its mainland ancestor), the infamous dodo of Mauritius (a giant pigeon), and the Komodo dragon.

In 1973, Leigh van Valen was the first that formulated the theory, based on the study by mammologist J. Bristol Foster in 1964, that animal species follow an evolutionary pattern when it comes to their body sizes. Species on islands have the tendency to become either giants or dwarfs in comparison to mainland relatives. “Species are limited to the environment on an island. The level of threat from predatory animals is much lower or non-existent,” says Ana Benítez-Lopez, who carried out the research at Radboud University, now researcher at Doñana Biological Station (EBD-CSIC, Spain). “But also limited resources are available.” However, until now, many studies showed conflicting results which led to severe debate about this theory: is it really a pattern, or just an evolutionary coincidence?

The new technique, which can easily be added to current membrane-based electrodialysis desalination processes, removes nearly 100% of these toxic metals, producing a pure brine along with pure water and isolating the valuable metals for later use or disposal.

University of California, Berkeley, chemists have discovered a way to simplify the removal of toxic metals. like mercury and boron. during desalination to produce clean water, while at the same time potentially capturing valuable metals, such as gold.

A $75000 robot dog seen leaving a Manhattan housing project has outraged city residents who heard less than a month ago that the pricey Boston Dynamics bots would be banned from being used as weapons.

The dog was seen exiting the housing project on Monday with a group of human police officers, who acted almost subservient to the shiny blue metal creature while escorting it out of the Kips Bay building. While the New York Police Department insisted the faux-canine had not played an “active role” in the operation, which allegedly involved removing an armed man from an apartment belonging to a woman and her baby, its appearance seemed to cast a spell over the assembled residents.

One resident, tenant organization head Melanie Aucello, rushed back home after receiving a handful of calls about “police in the building” and was wildly disturbed by what she saw there – not just the dog, but its effects on people.

AWS researchers have published a new approach to error correction that could pave the way for a fault-tolerant quantum system.

Amazon Web Services (AWS) is partnering with the Hebrew University of Jerusalem for a new quantum computing initiative as part of the company’s efforts, launched in 2019, to explore this area of research. These include a cloud-based quantum computing service Amazon Braket to accelerate research and discovery, the Amazon Quantum Solutions Lab to help businesses explore quantum applications, and the AWS Center for Quantum Computing research and development organization.

AWS’ latest collaboration with Hebrew University will fund a team of researchers from the academic institution’s Quantum Information Science Center (QISC), founded in 2013, and the Racah Institute of Physics to advance the understanding of quantum gates – fundamental building blocks of quantum computers, the parties said in a statement on Monday. The collaboration is the first between AWS and any Israeli academic institution in the field.

The university’s Professor Alex Retzker, a researcher of quantum technologies, will lead the research group as part of his role as a Principal Research Scientist at AWS.

Yesterday Nvidia officially dipped a toe into quantum computing with the launch of cuQuantum SDK, a development platform for simulating quantum circuits on GPU-accelerated systems. As Nvidia CEO Jensen Huang emphasized in his keynote, Nvidia doesn’t plan to build quantum computers, but thinks GPU-accelerated platforms are the best systems for quantum circuit and algorithm development and testing.

As a proof point, Nvidia reported it collaborated with Caltech to develop “a state-of-the-art quantum circuit simulator with cuQuantum running on NVIDIA A100 Tensor Core GPUs. It generated a sample from a full-circuit simulation of the Google Sycamore circuit in 9.3 minutes on Selene, a task that 18 months ago experts thought would take days using millions of CPU cores.”

Majorana modes are, however, notoriously elusive. In part, this is because it is hard to create the conditions required to generate them in an experimental setting. Many theoretical proposals have predicted MZMs should be present in quasi-2D materials, which consist of a small number of 2D layers stacked on top of each other. However, all previous proposals required heterostructures – that is, structures where the stacked layers have differing material composition and structure. Practically, these heterostructures are difficult if not downright impossible to grow.

To make matters worse, Majorana modes can only be observed indirectly. Like detectives trying to catch a culprit with only circumstantial evidence, physicists have a hard time ruling out alternative explanations for the phenomena they observe. This has led to high-profile premature claims of Majorana discovery, including Microsoft Quantum Lab’s recent retraction of a Nature paper in which they purported to observe MZMs in nanowires.

In their new work, Zhang and his coauthor show that Majorana modes should be present in a much simpler setting: thin films of an iron-based superconducting material. Like previous proposals, the system they study is quasi-2D, but crucially all layers are of the same kind. The iron-based thin films naturally accommodate Majorana fermions that are helical – left or right-handed – and move along the edges of the system in their preferred direction. This is due to a special “time-reversal” symmetry, wherein interchanging the left-moving and right-moving quasiparticles makes it look like time is propagating backwards in the system.

Physics World

Interactions between matter and light in microcavities made of mirrors are fundamentally important for many modern technologies, including lasers. Researchers at the University of Michigan, Ann Arbor, US, have now gained tighter control of these interactions by exploiting a nonlinear effect that occurs in a new kind of hybrid semiconductor made from bilayers of two-dimensional materials. These semiconducting sheets form an egg-carton-like array in which the “pockets” are quantum dots that can be controlled using light, and they could be used to make ultralow-energy switches.

Led by Hui Deng, the researchers made their hybrid semiconductor from flakes of tungsten disulphide (WS₂) and molybdenum diselenide (MoSe₂) just a few atoms thick. In their bulk form, these transition-metal dichalcogenides (TMDCs) act as indirect band-gap semiconductors. When scaled down to a monolayer thickness, however, they behave as direct band-gap semiconductors, capable of efficiently absorbing and emitting light.

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Words categorize the semantic fields they refer to in ways that maximize communication accuracy while minimizing complexity. Recent studies have shown that human languages are optimally balanced between accuracy and complexity. For example, many languages have a word that denotes the color red, but no language has individual words to distinguish ten different shades of the color. These additional words would complicate the vocabulary and rarely would they be useful to achieve precise communication.

A study published on 23 March in the journal Proceedings of the National Academy of Sciences analyzed how artificial neural networks develop spontaneous systems to name colors. A study by Marco Baroni, ICREA research professor at the UPF Department of Translation and Language Sciences (DTCL), conducted with members of Facebook AI Research (France).

For this study, the researchers formed two artificial neural networks trained with two generic deep learning methods. As Baroni explains: “we made the networks play a color-naming game in which they had to communicate about color chips from a continuous color space. We did not limit the “language” they could use, however, when they learned to play the game successfully, we observed the color-naming terms these artificial neural networks had developed spontaneously.”