Lifeboat Foundation

Turbulence makes many people uneasy or downright queasy. And it’s given researchers a headache, too. Mathematicians have been trying for a century or more to understand the turbulence that arises when a flow interacts with a boundary, but a formulation has proven elusive.

Now an international team of mathematicians, led by UC Santa Barbara professor Björn Birnir and the University of Oslo professor Luiza Angheluta, has published a complete description of boundary layer turbulence. The paper appears in Physical Review Research, and synthesizes decades of work on the topic. The theory unites empirical observations with the Navier-Stokes equation—the mathematical foundation of fluid dynamics—into a mathematical formula.

This phenomenon was first described around 1920 by Hungarian physicist Theodore von Kármán and German physicist Ludwig Prandtl, two luminaries in fluid dynamics. “They were honing in on what’s called boundary layer turbulence,” said Birnir, director of the Center for Complex and Nonlinear Science. This is turbulence caused when a flow interacts with a boundary, such as the fluid’s surface, a pipe wall, the surface of the Earth and so forth.

As robots are introduced in an increasing number of real-world settings, it is important for them to be able to effectively cooperate with human users. In addition to communicating with humans and assisting them in everyday tasks, it might thus be useful for robots to autonomously determine whether their help is needed or not.

Researchers at Franklin & Marshall College have recently been trying to develop computational tools that could enhance the performance of socially assistive robots, by allowing them to process social cues given by humans and respond accordingly. In a paper pre-published on arXiv and presented at the AI-HRI symposium 2021 last week, they introduced a new technique that allows robots to autonomously detect when it is appropriate for them to step in and help users.

Continue reading “A technique that allows robots to detect when humans need help” »

Have you ever seen the popular movie called The Matrix? In it, the main character Neo realizes that he and everyone else he had ever known had been living in a computer-simulated reality. But even after taking the red pill and waking up from his virtual world, how can he be so sure that this new reality is the real one? Could it be that this new reality of his is also a simulation? In fact, how can anyone tell the difference between simulated reality and a non-simulated one? The short answer is, we cannot. Today we are looking at the simulation hypothesis which suggests that we all might be living in a simulation designed by an advanced civilization with computing power far superior to ours.

The simulation hypothesis was popularized by Nick Bostrum, a philosopher at the University of Oxford, in 2003. He proposed that members of an advanced civilization with enormous computing power may run simulations of their ancestors. Perhaps to learn about their culture and history. If this is the case he reasoned, then they may have run many simulations making a vast majority of minds simulated rather than original. So, there is a high chance that you and everyone you know might be just a simulation. Do not buy it? There is more!

Continue reading “The Simulation Hypothesis | Is Anything ‘Real’” »

It’s one of the most fascinating aspects of the natural world: shapes repeat over and over. The branches of a tree extending into the sky look much the same as blood vessels extending through a human lung, if upside-down. The largest mammal, the whale, is a scaled-up version of the smallest, the shrew. Recent research even suggests the structure of the human brain resembles that of the entire universe. It’s everywhere you look, really. Nature reuses its most successful shapes.

Theoretical physicist Geoffrey West of the Santa Fe Institute in New Mexico is concerned with fundamental questions in physics, and there are few more fundamental than this one: why does nature continually reuse the same non-linear shapes and structures from the smallest scale to the very largest? In a new Big Think video (see above), West explains that the scaling laws at work are nothing less than “the generic universal mathematical and physical properties of the multiple networks that make an organism viable and allow it to develop and grow.”

Continue reading “Could a pill that lowers our body temperature make us live longer?” »

Learning science is about understanding complex systems and interactions among their entities. Telescopes are for observing objects that are far away, and microscopes are for exploring the tiniest objects. But what tools do we have for visualizing general patterns, processes, or relationships that can be defined in terms of compact mathematical models? Visualizing the unseeable can be a powerful teaching tool.

SETI Institute affiliate Dr. Mojgan Haganikar has written a book, Visualizing Dynamic Systems, that categorizes the visualization skills needed for various types of scientific problems. With the emergence of new technologies, we have more powerful tools to visualize invisible concepts, complex systems, and large datasets by revealing patterns and inter-relations in new ways. Join the SETI Institute’s Pamela Harman as she explores what is possible with Haganikar.

Continue reading “SETI Live: How to Better Visualize Complex Systems?” »

“…The authors modified a well-used climate model for exoplanet research and applied it to the planet in Dune. The work was carried out in their spare time and is intended as an appropriate outreach piece to demonstrate how climate scientists use mathematical models to better understand our world and exoplanets…”

Looks like the Kingdom of Jordan to me. 😉

Is Dune scientifically plausible? We ran a climate model to find out.

Continue reading “Dune: we simulated the desert planet of Arrakis to see if humans could survive there” »

Collaboration, transparency & urgency for rare disease research — mike graglia, managing director & co-founder, syngap research fund — SRF.

Mike Graglia is the Managing Director & Co-Founder of the SynGAP Research Fund (SRF — https://www.syngapresearchfund.org/), an organization that he set up in 2018 with his wife Ashley, after their son was diagnosed with a rare neurological disease caused by an insufficiency in SynGAP protein, which causes the life-changing diagnoses of Epilepsy, Autism, sleep disorder and intellectual disability.

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Oh the things we can see and accomplish when time and death can no longer hinder us.

Immortality is eternal life, being exempt from death, unending existence.
Human beings seem to be obsessed with the idea of immortality. But a study published in the journal Proceedings of the National Academy of Sciences has stated, through a mathematical equation, that it is impossible to stop ageing in multicellular organisms, which include humans, bringing the immortality debate to a possible end.
So you probably don’t want to die, most people don’t. But death takes us all no matter what we want. However, today in our scenario, humans have found a way to obtain that immortality. Watch the whole timeline video to find out how reaching immortality changes the world and the way we live.

Continue reading “Timeline: What If Humans Were Immortal” »

(2021). Nuclear Science and Engineering: Vol. 195 No. 9 pp. 977–989.

Earlier work has demonstrated the theoretical development of covert OT defenses and their application to representative control problems in a nuclear reactor. Given their ability to store information in the system nonobservable space using one-time-pad randomization techniques, the new C² modeling paradigm⁶ has emerged allowing the system to build memory or self-awareness about its past and current state. The idea is to store information using randomized mathematical operators about one system subcomponent, e.g., the reactor core inlet and exit temperature, into the nonobservable space of another subcomponent, e.g., the water level in a steam generator, creating an incorruptible record of the system state. If the attackers attempt to falsify the sensor data in an attempt to send the system along an undesirable trajectory, they will have to learn all the inserted signatures across the various system subcomponents and the C² embedding process.

We posit that this is extremely unlikely given the huge size of the nonobservable space for most complex systems, and the use of randomized techniques for signature insertion, rendering a level of security that matches the Vernam-Cipher gold standard. The Vernam Cipher, commonly known as a one-time pad, is a cipher that encrypts a message using a random key (pad) and can only be decrypted using this key. Its strength is derived from Shannon’s notion of perfect secrecy ⁸ and requires the key to be truly random and nonreusable (one time). To demonstrate this, this paper will validate the implementation of C² using sophisticated AI tools such as long short-term memory (LSTM) neural networks ⁹ and the generative adversarial learning [generative adversarial networks (GANs)] framework, ¹⁰ both using a supervised learning setting, i.e., by assuming that the AI training phase can distinguish between original data and the data containing the embedded signatures. While this is an unlikely scenario, it is assumed to demonstrate the resilience of the C² signatures to discovery by AI techniques.

Continue reading “Validation of Covert Cognizance Active Defenses” »