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Category: mobile phones – Page 54

Nanoscientists have developed a wearable textile that can convert body movement into useable electricity and even store that energy. The fabric potentially has a wide range of applications from medical monitoring to assisting athletes and their coaches in tracking their performance, as well as smart displays on clothing.

The research team responsible for the describe how it works in a paper published in Nano Research Energy.

From smart watches to cordless headphones, people already have access to a wide range of wearable electronic devices. A range of health, sport and activity monitors are now integrated into smartphones.

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In today’s episode, we take a deeper look into what Apple’s Vision Pro could mean for the industry. It’s not the same class of product as an iPhone, people aren’t going to walk around with these on their head, but the headset is the IPhone’s 3D successor.

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Producer: Dagogo Altraide

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I’ve found a lot of reasons – from finding components that are overheating (which can indicate faulty components), identifying overheating wires and connectors (which can indicate damaged wires or connectors), diagnosing issues with HVAC, find draughts at home, and much, much more.

Also: This $10 gadget is my favorite repair tool of all time

I started out thinking that these cameras were gimmicks, but they’ve become an important tool in the toolbox.

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A study, published in PNAS Nexus, describes a fabric that can be modulated between two different states to stabilize radiative heat loss and keep the wearer comfortable across a range of temperatures.

Po-Chun Hsu, Jie Yin, and colleagues designed a made of a layered semi-solid electrochemical cell deployed on nylon cut in a kirigami pattern to allow it to stretch and move with the wearer’s body. Modern clothes are made with a variety of insulating or breathable fabrics, but each fabric offers only one thermal mode, determined by the fabric’s emissivity: the rate at which it emits .

The in the fabric can be electrically switched between two states—a transmissive dielectric state and a lossy metallic state—each with different emissivity. The fabric can thus keep the wearer comfortable by adjusting how much body heat is retained and how much is radiated away. A user would feel the same skin temperature whether the external temperature was 22.0°C (71.6°F) or 17.1°C (62.8°F). The authors call this fabric a “wearable variable-emittance device,” or WeaVE, and have configured it to be controlled with a .

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In one sense, it is undeniably new. Interactions with ChatGPT can feel unprecedented, as when a tech journalist couldn’t get a chatbot to stop declaring its love for him. In my view, however, the boundary between humans and machines, in terms of the way we interact with one another, is fuzzier than most people would care to admit, and this fuzziness accounts for a good deal of the discourse swirling around ChatGPT.

When I’m asked to check a box to confirm I’m not a robot, I don’t give it a second thought—of course I’m not a robot. On the other hand, when my email client suggests a word or phrase to complete my sentence, or when my phone guesses the next word I’m about to text, I start to doubt myself. Is that what I meant to say? Would it have occurred to me if the application hadn’t suggested it? Am I part robot? These large language models have been trained on massive amounts of “natural” human language. Does this make the robots part human?

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It has 19 cores which can each carry a signal and can be adopted without any infrastructure changes.

An international collaboration of researchers has achieved a new speed record after transferring 1.7 petabits of data over 41 miles (67 km) of standard optical fiber cable. That’s the equivalent speed of 17 million broadband internet connections.

Optical fiber cables are a critical component of the modern world of the internet, where they connect data centers, satellite ground stations, mobile phone towers as well as continents to one another.

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One nebulous aspect of the poll, and of many of the headlines about AI we see on a daily basis, is how the technology is defined. What are we referring to when we say “AI”? The term encompasses everything from recommendation algorithms that serve up content on YouTube and Netflix, to large language models like ChatGPT, to models that can design incredibly complex protein architectures, to the Siri assistant built into many iPhones.

IBM’s definition is simple: “a field which combines computer science and robust datasets to enable problem-solving.” Google, meanwhile, defines it as “a set of technologies that enable computers to perform a variety of advanced functions, including the ability to see, understand and translate spoken and written language, analyze data, make recommendations, and more.”

It could be that peoples’ fear and distrust of AI comes partly from a lack of understanding of it, and a stronger focus on unsettling examples than positive ones. The AI that can design complex proteins may help scientists discover stronger vaccines and other drugs, and could do so on a vastly accelerated timeline.

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Like something out of a spy movie, thermal cameras make it possible to “see” heat by converting infrared radiation into an image. They can detect infrared light given off by animals, vehicles, electrical equipment and even people—leading to specialized applications in a number of industries.

Despite these applications, technology remains too expensive to be used in many such as self-driving cars or smartphones.

Our team at Flinders University has been working hard to turn this technology into something we can all use, and not just something we see in spy movies. We’ve developed a low-cost thermal imaging that could be scaled up and brought into the lives of everyday people. Our findings are published in the journal Advanced Optical Materials.

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Have you ever made a great catch—like saving a phone from dropping into a toilet or catching an indoor cat from running outside? Those skills—the ability to grab a moving object—takes precise interactions within and between our visual and motor systems. Researchers at the Del Monte Institute for Neuroscience at the University of Rochester have found that the ability to visually predict movement may be an important part of the ability to make a great catch—or grab a moving object.

“We were able to develop a method that allowed us to analyze behaviors in a natural environment with high precision, which is important because, as we showed, differ in a controlled setting,” said Kuan Hong Wang, Ph.D., a Dean’s Professor of Neuroscience at the University of Rochester Medical Center.

Wang led the study out today in Current Biology in collaboration with Jude Mitchell, Ph.D., assistant professor of Brain and Cognitive Sciences at the University of Rochester, and Luke Shaw, a graduate student in the Neuroscience Graduate Program at the School of Medicine & Dentistry at the University of Rochester. “Understanding how natural behaviors work will give us better insight into what is going awry in an array of neurological disorders.”

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