Lifeboat Foundation

Scientists from the University of California San Diego and CEA-Leti have created a revolutionary piezoelectric-based DC-DC converter that unifies all power switches onto a single chip to increase power density. This new power topology, which extends beyond existing topologies, blends the advantages of piezoelectric converters with capacitive-based DC-DC converters.

The power converters the team developed are much smaller than the huge, bulky inductors currently used for this role. The devices could eventually be used for any type of DC-DC conversation, in everything from smartphones, to computers, to server farms and AR/VR headsets.

Why smarter phones and cutting-edge headsets will change everything.

Professor Ronjon Nag presents about his project on AI and healthcare, aiming at creating a multi-faceted approved therapy for extending lifespan and curing aging.

Dr. Ronjon Nag is an inventor, teacher and entrepreneur. He is an Adjunct Professor in Genetics at the Stanford School of Medicine, becoming a Stanford Distinguished Careers Institute Fellow in 2016. He teaches AI, Genes, Ethics, Longevity Science and Venture Capital. He is a founder and advisor/board member of multiple start-ups and President of the R42 Group, a venture capital firm which invests in, and creates, AI and Longevity companies. As an AI pioneer of smartphones and app stores, his companies have been sold to Apple, BlackBerry, and Motorola. More recently he has worked on the intersection of AI and Biology. He has numerous interests in the intersection of AI and Healthcare including being CEO of Agemica.ai working on creating a therapy for aging.

Continue reading “Can We CURE AGING In 7 YEARS With Combination Therapy??” »

Say cheese, get gold.

Many electronic devices, such as smartphones, computers, and televisions, contain small amounts of gold in components like connectors, circuit boards, and integrated circuits, but they are usually considered electronic waste.

Uncover the innovative use of whey protein to extract gold from electronic waste. A sustainable and efficient solution for reducing e-waste.

Continue reading “Scientists extract gold from electronic waste using a cheese byproduct” »

Researchers in Imperial College London’s Department of Materials have developed a new portable maser that can fit the size of a shoebox.

Imperial College London pioneered the discovery of room-temperature solid-state masers in 2012, highlighting their ability to amplify extremely faint electrical signals and demonstrate high-frequency stability. This was a significant discovery because microwave signals can pass through the Earth’s atmosphere more easily than other wavelengths of light. Additionally, microwaves have the capability to penetrate through the human body, a feat not achievable by lasers.

Masers have extensive applications in telecommunications systems—everything from mobile phone networks to satellite navigation systems. They also have a key role in advancing quantum computing and improving medical imaging techniques, like MRI machines. They are typically large, bulky, stationary equipment found only in research laboratories.

During a demonstration, a Motorola representative showed how the phone could bend in various ways to wrap around a wrist or stand up on a table.

When the phone is wrapped around the wrist, the way information is displayed changes. For example, the apps appear at the top of the screen.

The representative said the phone is “contextually aware” so adapts depending on how it has been bent.

Transforming base materials into gold was one of the elusive goals of the alchemists of yore. Now Professor Raffaele Mezzenga from the Department of Health Sciences and Technology at ETH Zurich has accomplished something in that vein. He has not of course transformed another chemical element into gold, as the alchemists sought to do. But he has managed to recover gold from electronic waste using a byproduct of the cheesemaking process.

Electronic waste contains a variety of valuable metals, including copper, cobalt, and even significant amounts of gold. Recovering this gold from disused smartphones and computers is an attractive proposition in view of the rising demand for the precious metal.

However, the recovery methods devised to date are energy-intensive and often require the use of highly toxic chemicals. Now, a group led by ETH Professor Mezzenga has come up with a very efficient, cost-effective, and above all far more sustainable method: with a sponge made from a protein matrix, the researchers have successfully extracted gold from electronic waste.

The AI boom could push us toward more helpful devices, but it’s unclear if it can galvanize mobile sales.

Can smartphones apps be used to monitor a user’s mental health? This is what a recently submitted study scheduled to be presented at the 2024 ACM CHI Conference on Human Factors in Computing Systems hopes to address as a collaborative team of researchers from Dartmouth College have developed a smartphone app known as MoodCapture capable of evaluating signs of depression from a user with the front-facing camera. This study holds the potential to help scientists, medical professionals, and patients better understand how to identify signs of depression so proper evaluation and treatment can be made.

For the study, the researchers enlisted 177 participants for a 90-day trial designed to use their front-facing camera to capture facial images throughout their daily lives and while the participants answered a survey question with, “I have felt, down, depressed, or hopeless.” All participants consented to the images being taken at random times, not only when they used the camera to unlock their phone. During the study period, the researchers obtained more than 125,000 images and even accounted for the surrounding environment in their final analysis. In the end, the researchers found that MoodCapture exhibited 75 percent accuracy when attempting to identify early signs of depression.

“This is the first time that natural ‘in-the-wild’ images have been used to predict depression,” said Dr. Andrew Campbell, who is a professor in the Computer Science Department at Dartmouth and a co-author on the study. “There’s been a movement for digital mental-health technology to ultimately come up with a tool that can predict mood in people diagnosed with major depression in a reliable and non-intrusive way.”