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Textile engineers have developed a fabric woven out of ultra-fine nano-threads made in part of phase-change materials and other advanced substances that combine to produce a fabric that can respond to changing temperatures to heat up and cool down its wearer depending on need.

Materials scientists have designed an advanced textile with nano-scale threads containing in their core a phase-change material that can store and release large amounts of heat when the material changes phase from liquid to solid. Combining the threads with electrothermal and photothermal coatings that enhance the effect, they have in essence developed a fabric that can both quickly cool the wearer down and warm them up as conditions change.

A paper describing the manufacturing technique appeared in ACS Nano on August 10.

Inspired by the way termites build their nests, scientists at the California Institute of Technology (Caltech) developed a framework to design new materials that mimic the fundamental rules hidden in nature’s growth patterns. The researchers demonstrated that by using these rules, it is possible to create materials designed with specific programmable properties.

The research was published in the journal Science on August 26. It was led by Chiara Daraio, G. Bradford Jones Professor of Mechanical Engineering and Applied Physics and Heritage Medical Research Institute Investigator.

“Termites are only a few millimeters in length, but their nests can stand as high as 4 meters—the equivalent of a human constructing a house the height of California’s Mount Whitney,” says Daraio. If you peer inside a termite nest you will see a network of asymmetrical, interconnected structures, similar to the interior of a sponge or a loaf of bread. Made of sand grains, dirt, dust, saliva, and dung, this disordered, irregular structure appears arbitrary. However, a termite nest is specifically optimized for stability and ventilation.

The classification performance of all-optical Convolutional Neural Networks (CNNs) is greatly influenced by components’ misalignment and translation of input images in the practical applications. In this paper, we propose a free-space all-optical CNN (named Trans-ONN) which accurately classifies translated images in the horizontal, vertical, or diagonal directions. Trans-ONN takes advantages of an optical motion pooling layer which provides the translation invariance property by implementing different optical masks in the Fourier plane for classifying translated test images. Moreover, to enhance the translation invariance property, global average pooling (GAP) is utilized in the Trans-ONN structure, rather than fully connected layers.

Information variations in a chain-like system are associated to energy transactions with the environment, which can take place reversibly or irreversibly, with a lower theoretical energy limit^22,23. Fluctuations as a consequence of pure computations are on the order of the thermal level (i.e., similar to kT, being k the Boltzmann constant and T the absolute temperature), according to Landauer’s principle. Such energies are negligible at routine human scales but become significant when the size of the system is nanoscopic or smaller, because the work and heat it generates also compare with the thermal level. Small systems are based on nanostructures, including individual molecules and arrangements of atoms, such as biological and quantum systems.

Fluctuation theorems have appeared in recent years explaining quantitatively energy imbalances between forward and reverse pathways or between equilibrium and non-equilibrium processes^24,25. They have been tested experimentally^26,27,28, mostly in biomolecular systems analyzed on a one-by-one basis²⁹. Most of these theorems establish relations among thermodynamic potentials for general systems, often with no specific insight into information theory. This theory, in turn, deals with spatially-indexed, 1-dimensional arrangements of symbols, which may not be necessarily associated to a time order. Recent generalizations separate the role of information and feedback control^30,31, but still the interpretation of non-Markovianity, irreversibility and reversibility in terms of purely informational operations such as reading, writing and error correction^32,33 remains obscured.

Here, we analyze energy exchanges associated to the symbolic management of a sequence of characters, without reference to the physical construction of the chain. Just by considering reversibility at the single sequence level and conservation laws, we next present two pairs of fluctuations equalities in the creation of information sequences, which use depends on energy exchange constraints. Our analysis integrates key information concepts, namely, reading, writing, proof reading and editing in the thermodynamic description of a string of symbols with information.

Join cosmologist Laura Mersini-Houghton as she discusses her ground-breaking theory, and how her path from communist Albania helped her become one of the most courageous thinkers on the world stage of theoretical physics. Watch the Q&A for this video here: https://youtu.be/6xpVP_ITEYE

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Given the complexity of the human body, it’s no surprise that we’re still making new discoveries about the different parts we’re made up of – and scientists have just made a new discovery about the cerebellum at the back of the brain.

Already known as being important for properly controlling our movements, it now appears that this brain region also has a key role to play when it comes to remembering positive and negative emotional experiences.

These types of emotional experiences are particularly well remembered by the brain, not least because it helps the survival of our species to be able to remember times when we were in danger and times when we prospered.

If you often find yourself off by one when counting your socks after doing the laundry, you might want to sit down for this.

Scientists in Japan have now counted the number of extra—or missing— charges down to a precision of just one electron in single platinum nanoparticles having diameters only one-tenth those of common viruses.

This new process for precisely studying differences in net charge on metal nanoparticles will aid in the further understanding and development of catalysts for breaking down greenhouse and other harmful gases into fuels and benign gases or for efficiently producing ammonia needed for fertilizers used in agriculture.

MIT PhD student Alex Greene studies superconducting quantum computing systems, working to reduce errors that limit the length and complexity of the “programs” the computers can run.

Black Holes Could Hold a Surprising Secret About Our UniverseTake gravity and mix it with quantum mechanics.