Lifeboat Foundation

According to a University of Portsmouth study, a new physics law could allow for the early prediction of genetic mutations.

The study discovers that the second law of information dynamics, or “infodynamics,” behaves differently from the second law of thermodynamics. This finding might have major implications for how genomic research, evolutionary biology, computing, big data, physics, and cosmology develop in the future.

Lead author Dr. Melvin Vopson is from the University’s School of Mathematics and Physics. He states “In physics, there are laws that govern everything that happens in the universe, for example how objects move, how energy flows, and so on. Everything is based on the laws of physics. One of the most powerful laws is the second law of thermodynamics, which establishes that entropy – a measure of disorder in an isolated system – can only increase or stay the same, but it will never decrease.”

A groundbreaking mathematical equation that could transform medical procedures, natural gas extraction, and plastic packaging production in the future has been discovered.

The new equation, developed by scientists at the University of Bristol, indicates that diffusive movement through permeable material can be modeled exactly for the very first time. It comes a century after world-leading physicists Albert Einstein and Marian von Smoluchowski derived the first diffusion equation, and marks important progress in representing motion for a wide range of entities from microscopic particles and natural organisms to man-made devices.

Until now, scientists looking at particle motion through porous materials, such as biological tissues, polymers, various rocks and sponges have had to rely on approximations or incomplete perspectives.

Where are all the aliens?! This is the essence to the Fermi Paradox. It’s most popular solution is the “Great Filter.” What is the obstacle that life and/or intelligent species are unlikely to survive? Let’s discuss.

00:00 Cold Open.
00:18 Introduction.
00:48 History of the Fermi Paradox.
02:48 Fermi Paradox Explained.
03:55 Drake Equation Explained.
07:04 The Great Filter.
09:56 Rare Earth Hypothesis.
10:53 Geologic Time in Galactic Years.
14:48 Evolution of Intelligent Life.
17:03 Conclusions.
19:11 Poll Results.
19:47 Outro.
20:10 Featured Comment.

Continue reading “Humans are the First Aliens. Here’s Why” »

The Dunedin Pace of Aging Algorithm (PACE) was created by researchers from Duke, and the University of Otago over the course of 50 years of longitudinal research. It offers a revolutionary way to track aging which looks at an individual’s current rate of aging, and now TruDiagnostic has announced it is offering this powerful, third-generation clock to the public at an affordable price through TruAge PACE.

Longevity. Technology: Biologically, aging is the process of human cells slowly losing function over time; this process can be tracked by examining molecular markers called methylation and using advanced algorithms to sort those markers and calculate a person’s biological age – how old they are biologically rather than they number of birthdays they have clocked up.

The ability to track aging is dependent on the ability of the algorithms themselves. Until recently, most algorithms were trained on chronological age, and this meant they had poor responsiveness to interventions that are known to impact the biological course of aging. PACE gives individuals t he ability to detect rapid aging at an early age.

The droppers are designed to drop a new version of SharkBot, dubbed V2 by Dutch security firm ThreatFabric, which features an updated command-and-control (C2) communication mechanism, a domain generation algorithm (DGA), and a fully refactored codebase.

Fox-IT said it discovered a newer version 2.25 on August 22, 2022, that introduces a function to siphon cookies when victims log in to their bank accounts, while also removing the ability to automatically reply to incoming messages with links to the malware for propagation.

For hundreds of years, there was an immutable law of physics that was never challenged: that in any reaction occurring in the Universe, mass was conserved…

Creating images from text in seconds—and doing so with a conventional graphics card and without supercomputers? As fanciful as it may sound, this is made possible by the new Stable Diffusion AI model. The underlying algorithm was developed by the Machine Vision & Learning Group led by Prof. Björn Ommer (LMU Munich).

“Even for laypeople not blessed with artistic talent and without special computing know-how and computer hardware, the new model is an effective tool that enables computers to generate images on command. As such, the model removes a barrier to ordinary people expressing their creativity,” says Ommer. But there are benefits for seasoned artists as well, who can use Stable Diffusion to quickly convert new ideas into a variety of graphic drafts. The researchers are convinced that such AI-based tools will be able to expand the possibilities of creative image generation with paintbrush and Photoshop as fundamentally as computer-based word processing revolutionized writing with pens and typewriters.

In their project, the LMU scientists had the support of the start-up Stability. Ai, on whose servers the AI model was trained. “This additional computing power and the extra training examples turned our AI model into one of the most powerful image synthesis algorithms,” says the computer scientist.

Researchers have developed a machine learning algorithm that could help reduce charging times and prolong battery life in electric vehicles by predicting how different driving patterns affect battery performance, improving safety and reliability.

The researchers, from the University of Cambridge, say their algorithm could help drivers, manufacturers and businesses get the most out of the batteries that power electric vehicles by suggesting routes and driving patterns that minimize battery degradation and charging times.

The team developed a non-invasive way to probe batteries and get a holistic view of battery health. These results were then fed into a machine learning algorithm that can predict how different driving patterns will affect the future health of the battery.

In a study published in Cell Reports, we present a novel algorithm for the digital generation of neuronal morphologies, based on the topology of their branching structure. This algorithm generates neurons that are statistically similar to the biological neurons, in terms of morphological properties, electrical responses and the connectivity of the networks they form.

This study represents a major milestone for the Blue Brain Project and for the future of computational neuroscience. The topological neuron synthesis enables the generation of millions of unique neuronal shapes from different cell types. This process will allow us to reconstruct brain regions with detailed and unique neuronal morphologies at each cell position.

The topological representation of neurons facilitates the generation of neurons that approximate morphologies that are structurally altered compared to healthy neuronal morphologies. These structural alterations of neurons are disrupting the brain systems and are contributing factors to brain diseases. The topological synthesis can be used to study the differences between healthy and diseased states of different brain regions and specifically, what structural alterations of neurons are causing important problems to the networks they form.