Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 914

Interest in Earth-like planets orbiting within the habitable zone of their host stars has surged, driven by the quest to discover life beyond our solar system. But the habitability of such planets, known as exoplanets, is influenced by more than just their distance from the star.

A new study by Rice University’s David Alexander and Anthony Atkinson extends the definition of a habitable zone for planets to include their star’s magnetic field. This factor, well studied in our solar system, can have significant implications for life on other planets, according to the research published in The Astrophysical Journal on July 9.

The presence and strength of a planet’s magnetic field and its interaction with the host star’s magnetic field are pivotal factors in a planet’s ability to support life. An exoplanet needs a strong magnetic field to protect it from stellar activity, and it must orbit far enough from its star to avoid a direct and potentially catastrophic magnetic connection.

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Harvard researchers have shown that quantum coherence can survive chemical reactions at ultracold temperatures. Using advanced techniques, they demonstrated this with 40K87Rb bialkali molecules, suggesting potential applications in quantum information science and broader implications for understanding chemical reactions.

Zoom in on a chemical reaction to the quantum level and you’ll notice that particles behave like waves that can ripple and collide. Scientists have long sought to understand quantum coherence, the ability of particles to maintain phase relationships and exist in multiple states simultaneously; this is akin to all parts of a wave being synchronized. It has been an open question whether quantum coherence can persist through a chemical reaction where bonds dynamically break and form.

Now, for the first time, a team of Harvard scientists has demonstrated the survival of quantum coherence in a chemical reaction involving ultracold molecules. These findings highlight the potential of harnessing chemical reactions for future applications in quantum information science.

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Cognitive flexibility, the ability to rapidly switch between different thoughts and mental concepts, is a highly advantageous human capability. This salient capability supports multi-tasking, the rapid acquisition of new skills and the adaptation to new situations.

While (AI) systems have become increasingly advanced over the past few decades, they currently do not exhibit the same flexibility as humans in learning new skills and switching between tasks. A better understanding of how biological neural circuits support , particularly how they support multi-tasking, could inform future efforts aimed at developing more flexible AI.

Recently, some computer scientists and neuroscientists have been studying neural computations using artificial neural networks. Most of these networks, however, were generally trained to tackle individually as opposed to multiple tasks.

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UC biologist Joshua Gross studies blind cavefish, a species of fish that dwell in cave ponds in Mexico. In a study, supported by the National Science Foundation, Gross looked at the timeline for when the cavefish develop additional taste buds on the head and chin, finding the taste bud expansion starts at five months and continues into adulthood.

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Researchers from North Carolina State University have demonstrated miniature soft hydraulic actuators that can be used to control the deformation and motion of soft robots that are less than a millimeter thick. The researchers have also demonstrated that this technique works with shape memory materials, allowing users to repeatedly lock the soft robots into a desired shape and return to the original shape as needed.

“Soft robotics holds promise for many applications, but it is challenging to design the actuators that drive the motion of soft robots on a small scale,” says Jie Yin, corresponding author of a paper on the work (Advanced Materials, “Fully 3D-Printed Miniature Soft Hydraulic Actuators with Shape Memory Effect for Morphing and Manipulation”) and an associate professor of mechanical and aerospace engineering at NC State. “Our approach makes use of commercially available multi-material 3D printing technologies and shape memory polymers to create soft actuators on a microscale that allow us to control very small soft robots, which allows for exceptional control and delicacy.”

The new technique relies on creating soft robots that consist of two layers. The first layer is a flexible polymer that is created using 3D printing technologies and incorporates a pattern of microfluidic channels – essentially very small tubes running through the material. The second layer is a flexible shape memory polymer. Altogether, the soft robot is only 0.8 millimeters thick.

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