Lifeboat Foundation

In recent years, my lab — or perhaps it’s just me — has developed an obsession with evolutionary transitions. The view that every gene originates from an ancestral state and undergoes impactful changes through its evolutionary journey, whether it’s the gain or loss of an activity or function. The challenge lies in meticulously mapping out these key evolutionary innovations that have significantly influenced function. Addressing this challenge is not merely interesting but absolutely essential in biology. Our aim as biologists transcends understanding how biological systems operate; we seek to unravel how they came to be. And the two questions are more connected than many think.

This post stems from my observation that molecular biologists sometimes appear indifferent to evolution, questioning its relevance to mechanistic research. It baffles me why the centrality of evolution in biology isn’t apparent to some. Maybe they’ve never taken a course on the subject, or perhaps they’ve never fully appreciated the profound concept that every organism and every gene is connected through an unbroken chain of descent to countless ancestors. This perspective holds profound implications for mechanistic molecular biology.

If you already appreciate the link between evolutionary biology and molecular mechanisms, you might find this post to be music to your ears. However, if you’re among those who question the value of evolutionary biology, I encourage you to stay with me; you might discover its significance in ways you hadn’t considered before.

A study analyzing the properties of polarized light from 128 non-repeating FRBs reveals mysterious cosmic explosions originate in far-away galaxies like our own Milky Way.

New research from the University of Toronto utilizing data from the Canadian Hydrogen Intensity Mapping Experiment reveals that the majority of Fast Radio Bursts (FRBs) likely originate from environments similar to our Milky Way, with modest densities and magnetic fields. This finding contrasts with earlier studies which suggested that repeating FRBs come from highly magnetized areas.

Fast Radio Burst Research Advancements

The DESI collaboration is conducting a groundbreaking experiment to understand the universe’s expansion and acceleration. Their work with the DESI instrument has enabled them to map the cosmos from its early stages to the present, challenging existing models of the universe. Initial findings suggest there may be more to discover about dark energy and cosmic acceleration. The project’s innovative approach, including a fully blinded analysis, ensures that their conclusions are based on unbiased data, paving the way for future discoveries in astrophysics. Credit: SciTechDaily.com.

The DESI collaboration is examining the universe’s accelerating expansion through comprehensive mapping from its early stages to the present. Their findings challenge traditional cosmic models and suggest new insights into dark energy, all while utilizing groundbreaking, unbiased research methods.

Continue reading “Beyond Einstein: Groundbreaking Map of the Universe Redefines Cosmic Models” »

One of the biggest challenges in quantum technology and quantum sensing is “noise”–seemingly random environmental disturbances that can disrupt the delicate quantum states of qubits, the fundamental units of quantum information.

Lowtek Games combined the multifunctionality of a screen with the beauty of a pop-up book in a unique project that will take your imagination to another level. Codenamed Lowtek Lightbook, this interactive experience allows you to not only read stories but also play various games.

For example, you can color pictures with digital paints, find hidden objects, run away from aliens, or deliver food to them – all thanks to projection mapping and Lowtek Games’ clever thinking. Moreover, the story of Bib Goes Home can be even more engaging if you manually make Bib go home and explore his surroundings using a controller and a projector.

We are all very familiar with the concept of the Earth’s magnetic field. It turns out that most objects in space have magnetic fields but it’s quite tricky to measure them. Astronomers have developed an ingenious way to measure the magnetic field of the Milky Way using polarized light from interstellar dust grains that align themselves to the magnetic field lines. A new survey has begun this mapping process and has mapped an area that covers the equivalent of 15 times the full moon.

Many people will remember experiments in school with iron filings and bar magnets to unveil their magnetic field. It’s not quite so easy to capture the magnetic field of the Milky Way though. The new method to measure the field relies upon the small dust grains which permeate space between the stars.

The grains of dust are similar in size to smoke particles but they are not spherical. Just like a boat turning itself into the current, the dust particles’ long axis tends to align with the local magnetic field. As they do, they emit a glow in the same frequency as the cosmic background radiation and it is this that astronomers have been tuning in to.

“Big machine learning models have to consume lots of power to crunch data and come out with the right parameters, whereas our model and training is so extremely simple that you could have systems learning on the fly,” said Robert Kent.

How can machine learning be improved to provide better efficiency in the future? This is what a recent study published in Nature Communications hopes to address as a team of researchers from The Ohio State University investigated the potential for controlling future machine learning products by creating digital twins (copies) that can be used to improve machine learning-based controllers that are currently being used in self-driving cars. However, these controllers require large amounts of computing power and are often challenging to use. This study holds the potential to help researchers better understand how future machine learning algorithms can exhibit better control and efficiency, thus improving their products.

“The problem with most machine learning-based controllers is that they use a lot of energy or power, and they take a long time to evaluate,” said Robert Kent, who is a graduate student in the Department of Physics at The Ohio State University and lead author of the study. “Developing traditional controllers for them has also been difficult because chaotic systems are extremely sensitive to small changes.”

Continue reading “Optimizing Machine Learning Controllers with Digital Twins” »

There’s been a recent explosion of knowledge about various circuits within our body.

New circuits discovered, old ones refined.

Reconstruction of 1 mm3 of human brain (at 1.4 petabytes of EM data) published by @stardazed0 (@GoogleAI) & Lichtman lab.

Paper: https://science.org/doi/10.1126/science.adk4858

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Continue reading “Ten years of neuroscience at Google yields maps of human brain” »