A Multidisciplinary journal @WileyVCH, leading research in Applications from across all areas of Natural Sciences, Life Sciences, Engineering and more.

Joined November 2020
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The October issue of @Appl_Research @WileyVCH is online! The cover image features how Silk based Hybrid-Antioxidants provide long lasting antiradical protection! Read the article 👉onlinelibrary.wiley.com/doi/… Full access issue here⚡️onlinelibrary.wiley.com/toc/…
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Ring around the galaxy… Here’s Webb’s stunning new mid-infrared image of M104. This bright core of the galaxy is dim in this view, revealing a smooth inner disk as well as details of how the clumpy gas in the outer ring is distributed. go.nasa.gov/4i1guEj
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🛎️ It's quiz time! This dramatic image of Messier 106 🌌 was the subject of our Picture of the Month in August. The galaxy has a remarkable feature – two ‘anomalous’ extra arms that cannot be seen in visible light!
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A journey of 1.8 billion miles is about to begin. All about NASA's #EuropaClipper mission to explore Jupiter's intriguing moon Europa: nasa.gov/europaclipper Launch is slated for Monday, Oct. 14. Here's how to watch: go.nasa.gov/europaclipperliv…
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🌎 Farewell, Earth! 👋 Last week, after we successfully launched our Hera mission, its instruments were switched on for the first time and the asteroid deck was pointed back towards our planet. This allowed Hera to capture the first images of Earth and the Moon from a distance of more than one million km! 🔗 esa.int/Space_Safety/Hera/He…
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This year’s chemistry laureates Demis Hassabis and John Jumper have developed an AI model, AlphaFold2, to solve a 50-year-old problem: predicting proteins’ complex structures. Check out two examples of protein structures determined using AlphaFold2. First up, a bacterial enzyme that causes antibiotic resistance. The structure is important for discovering ways of preventing antibiotic resistance. Animation: ©Terezia Kovalova/The Royal Swedish Academy of Sciences #NobelPrize
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The 2024 #NobelPrize laureates in physics used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning. John Hopfield created a structure that can store and reconstruct information. Geoffrey Hinton invented a method that can independently discover properties in data and which has become important for the large artificial neural networks now in use. Although computers cannot think, machines can now mimic functions such as memory and learning. This year’s physics laureates have helped make this possible. Using fundamental concepts and methods from physics, they have developed technologies that use structures in networks to process information.
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The 2024 #NobelPrize in Physiology or Medicine focuses on the discovery of a vital regulatory mechanism used in cells to control gene activity. Genetic information flows from DNA to messenger RNA (mRNA), via a process called transcription, and then on to the cellular machinery for protein production. There, mRNAs are translated so that proteins are made according to the genetic instructions stored in DNA. Since the mid-20th century, several of the most fundamental scientific discoveries have explained how these processes work. In 1993, this year's Nobel Prize laureates published unexpected findings describing a new level of gene regulation, which turned out to be highly significant and conserved throughout evolution. They discovered microRNA, a new class of tiny RNA molecules that play a crucial role in gene regulation. Read more: bit.ly/4dlPE6f
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BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Physics to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
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