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Researchers have discovered a gene that increases muscle strength when activated by exercise, opening the door to the creation of therapeutic treatments that replicate some of the benefits of working out.

The University of Melbourne-led research, which was published in Cell Metabolism, demonstrated how various forms of exercise alter the molecules in our muscles and led to the identification of the new C18ORF25 gene, which is activated by all forms of exercise and is responsible for enhancing muscle strength. Animals lacking C18ORF25 have weaker muscles and worse exercise performance.

Dr. Benjamin Parker, project leader, said that by activating the C18ORF25 gene, the research team could observe muscles grow significantly stronger without necessarily becoming larger.

Some New Yorkers who completed their vaccine series should receive a single lifetime booster shot, health officials said. These individuals include people who might have contact with someone infected or thought to be infected with poliovirus or members of the infected person’s household.

Health care workers should also get a booster if they work in areas where poliovirus has been detected and they might handle specimens or treat patients who may have polio. People who might be exposed to wastewater due to their job should also consider getting a booster, health officials said.

All children should receive four doses of the polio vaccine. The first dose is administered between 6 weeks and 2 months of age, the second dose is given at 4 months, the third at 6 months to 18 months, and the fourth dose at 4 to 6 years old.

Skin-like electronics could seamlessly integrate with the body for applications in health monitoring, medication therapy, implantable medical devices, and biological studies.

With the help of the Polsky Center for Entrepreneurship and Innovation, Sihong Wang, an assistant professor of molecular engineering at the University of Chicago’s Pritzker School of Molecular Engineering, has secured patents for the building blocks of these novel devices.

Drawing on innovation in the fields of semiconductor physics, solid mechanics, and energy sciences, this work includes the creation of stretchable polymer semiconductors and transistor arrays, which provide exceptional electrical performance, high semiconducting properties, and mechanical stretchability. Additionally, Wang has developed triboelectric nanogenerators as a new technology for harvesting energy from a user’s motion—and designed the associated energy storage process.

University of Texas at Dallas physicists and their collaborators at Yale University have demonstrated an atomically thin, intelligent quantum sensor that can simultaneously detect all the fundamental properties of an incoming light wave.

The research, published April 13 in the journal Nature, demonstrates a new concept based on quantum geometry that could find use in health care, deep-space exploration and remote-sensing applications.

“We are excited about this work because typically, when you want to characterize a wave of light, you have to use different instruments to gather information, such as the intensity, wavelength and polarization state of the light. Those instruments are bulky and can occupy a significant area on an optical table,” said Dr. Fan Zhang, a corresponding author of the study and associate professor of physics in the School of Natural Sciences and Mathematics.

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As demonstrated by breakthroughs in various fields of artificial intelligence (AI), such as image processing, smart health care, self-driving vehicles and smart cities, this is undoubtedly the golden period of deep learning. In the next decade or so, AI and computing systems will eventually be equipped with the ability to learn and think the way humans do—to process continuous flow of information and interact with the real world.

However, current AI models suffer from a performance loss when they are trained consecutively on new information. This is because every time new data is generated, it is written on top of existing data, thus erasing previous information. This effect is known as “catastrophic forgetting.” A difficulty arises from the stability-plasticity issue, where the AI model needs to update its memory to continuously adjust to the new information, and at the same time, maintain the stability of its current knowledge. This problem prevents state-of-the-art AI from continually learning from real world information.

Edge computing systems allow computing to be moved from the cloud storage and data centers to near the original source, such as devices connected to the Internet of Things (IoTs). Applying continual learning efficiently on resource limited edge computing systems remains a challenge, although many continual learning models have been proposed to solve this problem. Traditional models require high computing power and large memory capacity.

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.

When one of China’s biggest celebrities, Simon Gong —also known as Gong Jun—released a new music video in June 2022, it quickly attracted 15 million views on the country’s Twitter-like microblogging site Weibo. But the event also stood out for a different reason—one that only eagle-eyed fans might have noticed. The singer in the video was not Gong himself, but a digital replica created by Baidu, a “digital human” powered by artificial intelligence (AI). Likewise, the lyrics and melody were generated by AI, marking the recording as China’s first AI-generated content music video.

Deloitte defines digital humans as AI-powered virtual beings that can produce a whole range of human body language. In recent years, businesses focused on providing round-the-clock services, as well as the media and entertainment industry, are increasingly adopting this nascent technology, aiming to capture a growing market. And as digital humans increasingly populate other sectors like retail, health care, and finance, Emergen Research forecasts that the global market for digital humans will jump to about $530 billion in 2030, from $10 billion in 2020.

If you are used to getting regular health checkups, you might be familiar with endoscopes. The endoscope is an imaging device consisting of a camera and a light guide attached to a long flexible tube. It is particularly useful for acquiring images of the inside of a human body. For example, stomach and colon endoscopy are widely used for the early detection and diagnosis of diseases such as ulcers and cancers.

In general, an endoscope is manufactured by attaching a camera sensor to the end of a probe or using an optical fiber, which allows for information to be transmitted using light. In the case of an endoscope that uses a camera sensor, the thickness of the probe increases, which makes the endoscopy rather invasive. In the case of an endoscope using an optical fiber bundle, it can be manufactured in a thinner form factor, which minimizes invasiveness and results in much less discomfort to the patients.

However, the downside is that in a conventional fiber-bundle endoscope, it is difficult to perform high-resolution imaging, because the resolution of the obtained image is limited by the size of the individual fiber cores. Much of the image information is also lost due to reflection from the probe tip. Furthermore, in fiber endoscopy, it is often necessary to label the target with fluorescence, especially in biological samples with low reflectivity, due to strong back-reflection noise generated from the tip of the thin probe.