“A New York City medical school will offer students free tuition following a $1bn donation from the 93-year-old widow of a major Wall Street investor.”
The record-breaking donation came from a 93-year-old former professor, who is the widow of a wealthy investor.
Scientists can now 3D print more-realistic prosthetic eyes in a fraction of the time and effort required by traditional approaches.
The property is currently an observatory surrounded by open land. System officials say they’ll use it for agricultural research and other opportunities.
The International Astronomical Union has confirmed the existence of three currently unnamed moons — one around Uranus and two orbiting Neptune.
Joe Louca: “Think of it like a realistic video game set on the Moon – we want to make sure the virtual version of moon dust behaves just like the actual thing, so that if we are using it to control a robot on the Moon, then it will behave as we expect.”
After Neil Armstrong took his first steps on the Moon, he said, “It’s almost like a powder”, as he described the lunar regolith, and astronauts on future Apollo missions found working on the lunar surface rather cumbersome and tedious due to the much finer lunar dust compared to Earth’s dirt. Therefore, what steps can be taken to better prepare future rovers and astronauts for NASA’s Artemis program to work on the lunar surface?
This is what a recent study published in Frontiers in Space Technologies hopes to address as a team of researchers led by the University of Bristol developed virtual models of lunar regolith simulants that could provide cost-effective methods to prepare astronauts and robots to work on the lunar surface, someday.
This study builds on an August 2023 study conducted by these same team members that explored the trust between teleoperated robots operating at long distances from Earth with their human controllers. The team found that the human controllers desired to train on increasing difficulty for operating their robots before working the real thing.
A common belief among astronomers is that galaxy groups and clusters differ mainly in the number of galaxies they contain—there are fewer galaxies in groups and more in clusters. Led by Maret Einasto, astronomers at Tartu Observatory of the University of Tartu decided to look into that and discovered even more differences between groups and clusters.
The structure of the universe can be described as a giant network, a cosmic web, with chains (filaments) of single galaxies and small groups of galaxies connecting rich galaxy groups and clusters that can contain thousands of galaxies. Between galaxy systems, there are giant voids with almost no visible matter (galaxies and gas). Galaxy groups and clusters can, in turn, form even larger systems called superclusters.
In their study, Tartu astronomers used data on galaxy groups, their brightest galaxies (so-called main galaxies), and their surroundings. The aim was to combine these data to see whether it could provide new information about the possible classification of groups of different sizes.
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.”
