Lifeboat Foundation

The liver’s ability to regenerate itself is legendary. Even if more than 70% of the organ is removed, the remaining tissue can regrow an entire new liver.

Kristin Knouse, an MIT assistant professor of biology, wants to find out how the liver is able to achieve this kind of regeneration, in hopes of learning how to induce other organs to do the same thing. To that end, her lab has developed a new way to perform genome-wide studies of the liver in mice, using the gene-editing system CRISPR.

With this new technique, researchers can study how each of the genes in the mouse genome affects a particular disease or behavior. In a paper describing the technique, the researchers uncovered several genes important for liver cell survival and proliferation that had not been seen before in studies of cells grown in a lab dish.

Bacteria that cause leprosy are shown to safely grow and regenerate the liver, in animal experiments.

Machine learning programs mean even encrypted information can give cybercriminals insight into your daily habits.

Smart technology claims to make our lives easier. You can turn on your lights, lock your front door remotely and even adjust your thermostat with the click of a button.

But new research from the University of Georgia suggests that convenience potentially comes at a cost—your personal security.

Researchers have discovered the heaviest-known bound isotope of sodium and characterized other neutron-rich isotopes, offering important benchmarks for refining nuclear models.

The neutron dripline marks a boundary of nuclear existence—indicating isotopes of a given element with a maximum number of neutrons. Adding a neutron to a dripline isotope will cause the isotope to become unbound and release one or more of its neutrons. Mapping the dripline is a major goal of modern nuclear physics, as this boundary is a testing ground for nuclear models and has implications for our understanding of neutron stars and of the synthesis of elements in stellar explosions. Now studies by two groups extend our knowledge of the properties of nuclei close to the dripline [1, 2]. Working at the Radioactive Isotope Beam Factory (RIBF) in Japan, Deuk Soon Ahn of RIKEN and colleagues have discovered sodium-39 (³⁹ Na), which likely marks the dripline location for the heaviest element to date (Fig. 1) [1].

Quantum circuits still can’t outperform classical ones when simulating molecules.

Quantum computers promise to directly simulate systems governed by quantum principles, such as molecules or materials, since the quantum bits themselves are quantum objects. Recent experiments have demonstrated the power of these devices when performing carefully chosen tasks. But a new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are no more accurate than those of classical computers [1]. The results offer a benchmark for judging how close quantum computers are to becoming useful tools for chemists and materials scientists.

Richard Feynman proposed the idea of quantum computers in 1982, suggesting they might be used to calculate the properties of quantum matter. Today, quantum processors are available with several hundred quantum bits (qubits), and some can, in principle, represent quantum states that are impossible to encode in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a few days that would take many millennia on current classical computers [2]. But this “quantum advantage” is achieved only for selected computational tasks that play to these devices’ strengths. How well do such quantum computers fare for the sorts of everyday challenges that researchers studying molecules and materials actually wish to solve?

Researchers at Purdue University have discovered new waves with picometer-scale spatial variations of electromagnetic fields that can propagate in semiconductors like silicon. The research team, led by Dr. Zubin Jacob, Elmore Associate Professor of Electrical and Computer Engineering and Department of Physics and Astronomy, published their findings in Physical Review Applied in a paper titled “Picophotonics: Anomalous Atomistic Waves in Silicon.”

“The word microscopic has its origins in the length scale of a micron, which is a million times smaller than a meter. Our work is for light matter interaction within the picoscopic regime which is far smaller, where the discrete arrangement of atomic lattices changes light’s properties in surprising ways,” says Jacob.

These intriguing findings demonstrate that natural media host a variety of rich light-matter interaction phenomena at the atomistic level. The use of picophotonic waves in semiconducting materials may lead researchers to design new, functional optical devices, allowing for applications in quantum technologies.

Femtosecond pulsed lasers—which emit light in ultrafast bursts lasting a millionth of a billionth of a second—are powerful tools used in a range of applications from medicine and manufacturing, to sensing and precision measurements of space and time. Today, these lasers are typically expensive table-top systems, which limits their use in applications that have size and power consumption restrictions.

An on-chip femtosecond pulse source would unlock new applications in quantum and optical computing, astronomy, optical communications and beyond. However, it’s been a challenge to integrate tunable and highly efficient pulsed lasers onto chips.

Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a high-performance, on-chip femtosecond pulse source using a tool that seems straight out of science fiction: a time lens.

It’s diversifying from its initial reliance on Taiwan-made chips.

Apple is diversifying its supply chain away from Taiwan as it has plans to buy some of its chips from a factory in Arizona, company CEO Tim Cook said last month at an internal meeting in Germany, according to a report by Bloomberg News.

Manufacturing A-series and M-series processors

Continue reading “Apple plans to source chips from Arizona plant by 2024” »

Researchers solved a differential equation behind the interaction of two neurons through synapses, creating a faster AI algorithm.

Artificial intelligence uses a technique called artificial neural networks (ANN) to mimic the way a human brain works. A neural network uses input from datasets to “learn” and output its prediction based on the given information.

Continue reading “MIT reveals a new type of faster AI algorithm for solving a complex equation” »