Lifeboat Foundation

Health — operanewsapp.

A new paper published in the Journal of Medical Internet Research describes how generative models such as DALL-E 2, a novel deep learning model for text-to-image generation, could represent a promising future tool for image generation, augmentation, and manipulation in health care. Do generative models have sufficient medical domain knowledge to provide accurate and useful results? Dr. Lisa C Adams and colleagues explore this topic in their latest viewpoint titled “What Does DALL-E 2 Know About Radiology?”

First introduced by OpenAI in April 2022, DALL-E 2 is an artificial intelligence (AI) tool that has gained popularity for generating novel photorealistic images or artwork based on textual input. DALL-E 2’s generative capabilities are powerful, as it has been trained on billions of existing text-image pairs off the internet.

To understand whether these capabilities can be transferred to the medical domain to create or augment data, researchers from Germany and the United States examined DALL-E 2’s radiological knowledge in creating and manipulating X-ray, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound images.

Researchers in China have successfully restored the vision of mice with retinitis pigmentosa, one of the major causes of blindness in humans. The study, to be published March 17 in the Journal of Experimental Medicine, uses a new, highly versatile form of CRISPR-based genome editing with the potential to correct a wide variety of disease-causing genetic mutations.

Researchers have previously used genome editing to restore the vision of mice with genetic diseases, such as Leber congenital amaurosis, that affect the retinal pigment epithelium, a layer of non-neuronal cells in the eye that supports the light-sensing rod and cone photoreceptor cells. However, most inherited forms of blindness, including retinitis pigmentosa, are caused by genetic defects in the neural photoreceptors themselves.

“The ability to edit the genome of neural retinal cells, particularly unhealthy or dying photoreceptors, would provide much more convincing evidence for the potential applications of these genome-editing tools in treating diseases such as retinitis pigmentosa,” says Kai Yao, a professor at the Wuhan University of Science and Technology.

I guess bee farmers won’t jut be collecting honey.

Honey bees are more than just pollen collectors! With a sense of smell on par with dogs, honey bees can be trained to detect any smell, like explosives. But how these bees are trained to detect explosives, what their advantage is over sniffer dogs, and how other animals have been trained to perform unbelievable tasks for the armed forces, is #NotWhatYouThink #NWYT #long.

Continue reading “How Honey Bees Are Trained To Detect Explosives” »

Two pairs of gigantic black holes, each in a different dwarf galaxy, are speeding towards each other, and they’re set for two separate, never-before-seen collisions.

Astronomers used NASA’s Chandra X-ray Observatory to spot the four dwarf galaxy black holes racing towards each other, dragging an enormous train of gas and stars in their wake. Some of this material is already being sucked into the black holes, causing them to grow ever larger before their eventual crashes.

https://youtube.com/watch?v=iW0mnvw3yBI

Polarons are localized quasiparticles that result from the interaction between fermionic particles and bosonic fields. Specifically, polarons are formed when individual electrons in crystals distort their surrounding atomic lattice, producing composite objects that behave more like a massive particles than electron waves.

Feliciano Giustino and Weng Hong Sio, two researchers at the University of Texas at Austin, recently carried out a study investigating the processes underpinning the formation of polarons in 2D materials. Their paper, published in Nature Physics, outlines some fundamental mechanisms associated with these particles’ formation that had not been identified in previous works.

“Back in 2019, we developed a new theoretical and computational framework to study polarons,” Feliciano Giustino, one of the researchers who carried out the study, told Phys.org. “One thing that caught our attention is that many experimental papers discuss polarons in 3D bulk materials, but we could find only a couple of papers reporting observations of these particles in 2D. So, we were wondering whether this is just a coincidence, or else polarons in 2D are more rare or more elusive than in 3D, and our recent paper addresses this question.”

Indian astronomers have analyzed observational data of a gamma-ray blazar known as PKS 0402–362, collected in the timespan of nearly 13 years. The study, published March 7 in the Monthly Notices of the Royal Astronomical Society, provides crucial information regarding the long-term behavior of this blazar.

Blazars are very compact quasars associated with supermassive black holes (SMBHs) at the centers of active, giant elliptical galaxies. They belong to a larger group of active galaxies that host active galactic nuclei (AGN), and are the most numerous extragalactic gamma-ray sources. Their characteristic features are relativistic jets pointed almost exactly toward the Earth.

Based on their optical emission properties, astronomers divide blazars into two classes: flat-spectrum radio quasars (FSRQs) that feature prominent and broad optical emission lines, and BL Lacertae objects (BL Lacs), which do not.

Germany, India, Mexico, and Spain. As multiparty democracies, these countries present a more complex picture of what brings people together—or divides them. Using social media data, a group of researchers proposes a novel approach to measuring polarization in nations with multiple political parties.

Complexity Science Hub scientist Samuel Martín-Gutiérrez and his colleagues developed a model that infers opinions from social networks, and measures the left-right political division, as well as other more nuanced sources of tension. They analyzed Twitter data from the Spanish elections of 2015 and 2019.

“It’s important to understand polarization in our society, and our findings shed new light on how political beliefs are shaped,” says Martín-Gutiérrez. “Our approach can lead to useful insights when applied to real-world debates happening on social media.”