Lifeboat Foundation

Over the past decade, teams of engineers, chemists and biologists have analyzed the physical and chemical properties of cicada wings, hoping to unlock the secret of their ability to kill microbes on contact. If this function of nature can be replicated by science, it may lead to development of new products with inherently antibacterial surfaces that are more effective than current chemical treatments.

When researchers at Stony Brook University’s Department of Materials Science and Chemical Engineering developed a simple technique to duplicate the cicada wing’s nanostructure, they were still missing a key piece of information: How do the nanopillars on its surface actually eliminate bacteria? Thankfully, they knew exactly who could help them find the answer: Jan-Michael Carrillo, a researcher with the Center for Nanophase Materials Sciences at the Department of Energy’s Oak Ridge National Laboratory.

For nanoscience researchers who seek computational comparisons and insights for their experiments, Carrillo provides a singular service: large-scale, high-resolution molecular dynamics (MD) simulations on the Summit supercomputer at the Oak Ridge Leadership Computing Facility at ORNL.

In it, he explores how we can make better, scientifically informed predictions about the world around us, using maths. “Mathematics can provide us with the objective tools to bypass the foibles of our own biology – the limitations imposed by our own thought processes, the compulsions that ultimately make us human, but let us down when it comes to making inferences about the world around us,” he writes. “They are humanity’s shortcuts: the preconceptions and cognitive biases, refined over millennia of evolution, that all too often lead us astray when we try to apply our brain’s old rules to our society’s new environments.”

No matter how tempting it is to think, “Ooh, that’s a bit spooky” when faced with a completely random coincidence or chance occurrence, we should all be expecting unusual things to happen all the time, he says.

Yates describes a person who, when browsing in a secondhand bookshop far from where they grew up, opens a copy of their favourite children’s book, only to find their own name inscribed inside. Yet, he says, “the law of truly large numbers” dictates that, just as someone wins the lottery almost every week, with enough opportunities, such extraordinary coincidences are far more likely to happen than you might think. “There are so many different types of coincidences that make us say: ‘Well, that’s extraordinary.’ But it’s not unlikely that some of them happen to us every so often.”

An international group of experts argue that tackling the long-standing challenge of decoding the communication systems of whales, crows, bats, and other animals is coming within reach, following breath-taking advances in artificial intelligence (AI) research.

In an article published in Science, led by Professor Christian Rutz from the School of Biology at the University of St Andrews, the authors explain how cutting-edge machine-learning tools could provide transformative insights into the hidden lives of animals, with important implications for their conservation.

The prospect of understanding what animals say to each other, or of even initiating a conversation with another species, has fired humans’ imagination for millennia. But since there is no Rosetta Stone for translating animals’ communication signals, their meaning must be deciphered through careful observation and experimentation. Despite good research progress over the past few decades, collecting and analyzing data is a challenging task. For example, annotating recordings of bird calls, whale songs or primate gestures is time-consuming, and even experienced biologists often struggle to differentiate seemingly similar signal types.

A new technique produces perovskite nanocrystals right where they’re needed, so the exceedingly delicate materials can be integrated into nanoscale.

The nanoscale refers to a length scale that is extremely small, typically on the order of nanometers (nm), which is one billionth of a meter. At this scale, materials and systems exhibit unique properties and behaviors that are different from those observed at larger length scales. The prefix “nano-” is derived from the Greek word “nanos,” which means “dwarf” or “very small.” Nanoscale phenomena are relevant to many fields, including materials science, chemistry, biology, and physics.

All biological systems are wildly disordered. Yet somehow, that disorder enables plant photosynthesis to be nearly 100% efficient.

Some transcription factors are known as master regulators, and they can have an impact on many different biochemical pathways and processes in cells. | Cell And Molecular Biology.

In an interview with GQ, 54-year-old David Sinclair says his lifestyle changes got him back to his “20-year-old brain.”

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Our universe has been developing for about 14 billion years, but human-level intelligence, at least on Earth, has emerged in a remarkably short period of time, measured in tens or hundreds of thousands of years. What then is the future of intelligence? With the exponential growth of computing, will non-biological intelligence dominate?

Continue reading “Dimitar Sasselov — What is the Far Future of Intelligence in the Universe?” »

Quantum physics governs the world of the very small and that of the very cold. Your dog cannot quantum-tunnel her way through the fence, nor will you see your cat exhibit wave-like properties. But physics is funny, and it is continually surprising us. Quantum physics is starting to show up in unexpected places. Indeed, it is at work in animals, plants, and our own bodies.

We once thought that biological systems are too warm, too wet, and too chaotic for quantum physics to play any part in how they work. But it now seems that life is employing feats of quantum physics every day in messy, real-world systems, including quantum tunneling, wave-particle duality, and even entanglement. To see how it all works, we can start by looking right inside our own noses.

The human nose can distinguish over one trillion smells. But how exactly the sense of smell works is still a mystery. When a molecule referred to as an odorant enters our nose, it binds to receptors. Initially, the prevailing theory held that these receptors used the shape of the odorants to differentiate smells. The so-called lock and key model suggests that when an odorant finds the right receptor, it fits into it and triggers a specific smell. But the lock and key model ran into trouble when tested. Subjects were able to tell two scents apart, even when the odorant molecules were identical in shape. Some other process must be at work.