This past October, dozens of mathematicians gathered in Pasadena to create the third version of “Kirby’s list” — a compendium of the most important unsolved problems in the field.
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We all travel through space time at speed of light. But, what does it really mean? How does it explain the consequences of special relativity — time dilation, length contraction, relativity of simultaneity, and more.
Continue reading “‘We all move at speed of light through spacetime’… What does it really mean?” »
Musk said that the first human patient implanted with a Neuralink chip last month “is able to… move the mouse around the screen just by thinking.”
Nucleases present a formidable barrier to the application of nucleic acids in biology, significantly reducing the lifetime of nucleic acid-based drugs. Here, we develop a novel methodology to protect DNA and RNA from nucleases by reconfiguring their supramolecular structure through the addition of a nucleobase mimic, cyanuric acid. In the presence of cyanuric acid, polyadenine strands assemble into triple helical fibers known as the polyA/CA motif. We report that this motif is exceptionally resistant to nucleases, with the constituent strands surviving for up to 1 month in the presence of serum. The conferred stability extends to adjacent non-polyA sequences, albeit with diminishing returns relative to their polyA sections due to hypothesized steric clashes. We introduce a strategy to regenerate stability through the introduction of free polyA strands or positively charged amino side chains, enhancing the stability of sequences of varied lengths. The proposed protection mechanism involves enzyme failure to recognize the unnatural polyA/CA motif, coupled with the motif’s propensity to form long, bundling supramolecular fibers. The methodology provides a fundamentally new mechanism to protect nucleic acids from degradation using a supramolecular approach and increases lifetime in serum to days, weeks, or months.
We developed Significant Latent Factor Interaction Discovery and Exploration (SLIDE), an interpretable machine learning approach that can infer hidden states (latent factors) underlying biological outcomes. These states capture the complex interplay between factors derived from multiscale, multiomic datasets across biological contexts and scales of resolution.
Positronium has the potential to revolutionise physics but the elusive substance had been too hot to handle.
Summary: Researchers unveiled a pioneering technology capable of real-time human emotion recognition, promising transformative applications in wearable devices and digital services.
The system, known as the personalized skin-integrated facial interface (PSiFI), combines verbal and non-verbal cues through a self-powered, stretchable sensor, efficiently processing data for wireless communication.
This breakthrough, supported by machine learning, accurately identifies emotions even under mask-wearing conditions and has been applied in a VR “digital concierge” scenario, showcasing its potential to personalize user experiences in smart environments. The development is a significant stride towards enhancing human-machine interactions by integrating complex emotional data.
Since 1931, science fiction has speculated on how microbots might work and how they will change our lives.
People often believe what they want to believe rather than what the evidence implies. Here Melnikoff and Strohminger find that this seemingly irrational tendency may emerge from fully rational Bayesian calculations.
