Lifeboat Foundation

Today is Earth Day.

That said, Americans don’t fully trust the reliability of renewable sources and 67% of the population favors a mix of renewables and fossil fuels, with only about 31% in favor of completely phasing out fossil fuels altogether.

This week’s Current Climate, which every Saturday brings you the latest news about the business of sustainability. Sign up to get it in your inbox every week.

Continue reading “Current Climate: Americans Want The U.S. At Net Zero By 2050” »

There is so much that we do not yet know about neutrinos. Neutrinos are very light, chargeless, and elusive particles that are involved in a process called beta decay. Understanding this process may reveal the origin of matter in the universe.

Beta decay is a type of radioactive decay that involves a neutron converting into a proton emitting an electron and an antineutrino. Beta decay is very common—it occurs about a dozen of times per second in, for example, a banana. There might also be an ultra-rare kind of beta decay that emits two electrons but no neutrinos.

Nuclear physicists around the world are searching for this neutrinoless-double beta decay (NLDBD) in different nuclei. The interest in these decays arises from their potential to reveal unsolved mysteries related to the universe’s creation of matter. They can also provide hints toward our understanding of the currently unknown mass of neutrinos.

Scientists have created two-dimensional photonic time crystals that amplify light, with potential applications in improving wireless communications and laser technology.

Researchers have developed a way to create photonic time crystals and shown that these bizarre, artificial materials amplify the light that shines on them. These findings, described in a paper published in the journal Science Advances.

<em>Science Advances</em> is a peer-reviewed, open-access scientific journal that is published by the American Association for the Advancement of Science (AAAS). It was launched in 2015 and covers a wide range of topics in the natural sciences, including biology, chemistry, earth and environmental sciences, materials science, and physics.

Last 2020, scientists were able to pick up distinct brain signals that had never been observed before. Such findings hint at how the brain is a more powerful computational device than previously thought.

Distinct Brain Signals

Continue reading “Distinct Brain Signals Picked Up For the First Time; Findings Hint That Human Neurons Are More Powerful in Computing Than Previously Thought” »

In this talk, De Kai examines how AI amplifies fear into an existential threat to society and humanity, and what we need to be doing about it. De Kai’s work across AI, language, music, creativity, and ethics centers on enabling cultures to interrelate. For pioneering contributions to machine learning of AIs like Google/Yahoo/Microsoft Translate, he was honored by the Association for Computational Linguistics as one of only seventeen Founding Fellows worldwide and by Debrett’s HK 100 as one of the 100 most influential figures of Hong Kong. De Kai is a founding Professor of Computer Science and Engineering at HKUST and Distinguished Research Scholar at Berkeley’s ICSI (International Computer Science Institute). His public campaign applying AI to show the impact of universal masking against Covid received highly influential mass media coverage, and he serves on the board of AI ethics think tank The Future Society. De Kai is also creator of one of Hong Kong’s best known world music collectives, ReOrientate, and was one of eight inaugural members named by Google to its AI ethics council. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

Over the past year or so, generative AI models such as ChatGPT and DALL-E have made it possible to produce vast quantities of apparently human-like, high-quality creative content from a simple series of prompts.

Though highly capable – far outperforming humans in big-data pattern recognition tasks in particular – current AI systems are not intelligent in the same way we are. AI systems aren’t structured like our brains and don’t learn the same way.

Continue reading “Networks of Silver Nanowires Appear to Learn And Remember Like The Human Brain” »

The researchers found those who showed positive age beliefs were 30% more likely to recover from cognitive impairment than those who held negative age beliefs, irrespective of the severity of the cognitive decline. The time for recovery was also quicker in people with positive age beliefs.

They also found that the participants who stayed positive about aging were less likely to develop mild cognitive impairment over 12 years.

It is widely believed that memory loss associated with aging is irreversible. However, a new study says people who embrace aging positively may recover from cognitive decline.

Continue reading “Study Says Staying Positive About Aging May Help Reverse Cognitive Decline” »

Pneumonia is a potentially fatal lung infection that progresses rapidly. Patients with pneumonia symptoms – such as a dry, hacking cough, breathing difficulties and high fever – generally receive a stethoscope examination of the lungs, followed by a chest X-ray to confirm diagnosis. Distinguishing between bacterial and viral pneumonia, however, remains a challenge, as both have similar clinical presentation.

Mathematical modelling and artificial intelligence could help improve the accuracy of disease diagnosis from radiographic images. Deep learning has become increasingly popular for medical image classification, and several studies have explored the use of convolutional neural network (CNN) models to automatically identify pneumonia from chest X-ray images. It’s critical, however, to create efficient models that can analyse large numbers of medical images without false negatives.

Now, K M Abubeker and S Baskar at the Karpagam Academy of Higher Education in India have created a novel machine learning framework for pneumonia classification of chest X-ray images on a graphics processing unit (GPU). They describe their strategy in Machine Learning: Science and Technology.

Misfolded proteins are toxic to cells. They disrupt normal functions and cause some age-related human degenerative diseases, like Alzheimer’s, Parkinson’s, and Huntington’s diseases. Cells work constantly to eliminate misfolded proteins, but these clearance mechanisms are still poorly understood.

In a new study published April 20 in Nature Cell Biology, researchers at Stanford University discovered a previously unknown cellular pathway for clearing misfolded proteins from the nucleus, the compartment where the cell stores, transcribes, and replicates its DNA. Keeping junk away from those processes is critical to normal cellular function. The new pathway could be a target for age-related disease therapies.

To find the new pathway, researchers in the lab of Judith Frydman, the Donald Kennedy Chair in the School of Humanities and Sciences, integrated several genetic, imaging, and biochemical approaches to understand how yeast cells dealt with misfolded proteins. For the experiments, the team restricted misfolded proteins to either the nucleus or the cytoplasm—the area inside the cell but outside the nucleus. The team visually followed the fate of the misfolded proteins through live-cell imaging and super-resolution microscopy.