Now we can all go back to 2019.
In a new peer-reviewed paper, a senior honors undergraduate says he has mathematically proven the physical feasibility of a specific kind of time travel. The paper appears in Classical and Quantum Gravity.
đ€Ż You love time travel. So do we. Letâs nerd out over it together.
Air pollution involving very fine dust, such as PM2.5 particles, poses a serious threat to human health. Scientists in Austria have developed what they call the smallest particle sensor in the world, designed specifically to detect these harmful pollutants and offer a highly localized picture of air quality by being integrated into wearables and mobile devices.
According to the World Health Organization, air pollution contributes to more than four million premature deaths each year. While PM10 particles with a diameter of 10 microns or less can also make their way into their lungs, the finer PM2.5 particles are even more dangerous, as they can penetrate the lung barrier, slip into the blood stream and, through chronic exposure, cause severe forms of cardiovascular and respiratory disease, along with other health problems.
Concentrations of PM2.5 particles can be gauged through monitoring stations positioned around cities and regions, in fact the US Environmental Protection Agency uses a nationwide network of these stations to track air quality trends. But scientists from Austriaâs Graz University of Technology (TU Graz) have been working on a more cost-effective, compact and versatile solution that can alert individual users of dangerous conditions in real time.
Rewriting the rules in GAN: Copy & paste features contextually.
GAN architecture has been the standard for generating content through AI, but can it actually invent new content outside whatâs available in the training dataset? Or itâs just imitating the training data and mixing the features in new ways?
Posted in habitats
In recent years, researchers have been developing machine learning algorithms for an increasingly wide range of purposes. This includes algorithms that can be applied in healthcare settings, for instance helping clinicians to diagnose specific diseases or neuropsychiatric disorders or monitor the health of patients over time.
Researchers at Massachusetts Institute of Technology (MIT) and Massachusetts General Hospital have recently carried out a study investigating the possibility of using deep reinforcement learning to control the levels of unconsciousness of patients who require anesthesia for a medical procedure. Their paper, set to be published in the proceedings of the 2020 International Conference on Artificial Intelligence in Medicine, was voted the best paper presented at the conference.
âOur lab has made significant progress in understanding how anesthetic medications affect neural activity and now has a multidisciplinary team studying how to accurately determine anesthetic doses from neural recordings,â Gabriel Schamberg, one of the researchers who carried out the study, told TechXplore. âIn our recent study, we trained a neural network using the cross-entropy method, by repeatedly letting it run on simulated patients and encouraging actions that led to good outcomes.â
The Always Home Cam foils a very sloppy burglar.
Ring has given a brief demo of its flying security camera drone in a new ad. The Always Home Cam will be available next year and can be controlled with your phone.
A recent international scientific study published in the journal PLOS ONE has shown that the way the brain stores temporary information is different depending on the use one might give to that information in the future.
The research analysed the brain activity of 14 participants through functional magnetic resonance imaging while they were performing simple visual memory tasks on a computer screen. Differences in their brain activity patterns were found between participants who had to answer by communicating verbally or by pressing a button.
The memory that is under study is designated âworking memoryâ and is used at all times. It is the type of memory that allows us to memorise a phone number or a license plate and use that information after (or not). This information is used and processed and, if it proves to be important, stored in the long-term memory.
ESA Astronaut Pesquet revealed Crew-2 has been actively training for âMission Alphaâ aboard Crew Dragon. He shared photographs via Twitter of him training on SpaceXâs Crew Dragon simulator which involves learning how to control the spacecraftâs functions via a trio of touchscreen displays. â âHereâs the posse together, training on @SpaceX crew dragon. @Aki_Hoshide looking like a boss, and all of us wishing we had as cool socks as our awesome pilot @Astro_Megan. #MissionAlpha,â he wrote. During training, all astronauts are wearing face masks to protect each other from the coronavirus respiratory illness, pictured below.
Hereâs the posse together, training on @SpaceX crew dragon. @Aki_Hoshide looking like a boss, and all of us wishing we had as cool socks as our awesome pilot @Astro_Megan. #MissionAlpha pic.twitter.com/UCDJvTcRgpâ Thomas Pesquet (@Thom_astro) September 23, 2020
To familiarize with the spacecraft, the astronauts train with an interactive simulator and touchscreen interface that is a replica of Dragonâs cockpit. Earlier this year, SpaceX released an online game that allows players to try to dock the Crew Dragon spacecraft to the Space Station, using similar controls the astronauts will use during their voyage in space. You can play the online game on SpaceXâs website: Crew Dragon Simulator.
According to Blue Origin, the launch is now set for Friday, Sept. 25 at 10 a.m. central time. You can watch the launch live here.
Boeing to Face Independent Ethics Probe Over Lunar Lander Bid
According to a press release, the New Shepard will fly 12 commercial payloads to space and back, including a demonstration of a lunar landing sensor that will test technologies for future missions to the Moon in support of NASAâs Artemis program.
Researchers took a silica nanoparticle designated as âGenerally Recognized As Safeâ by the US Food and Drug Administration and coated it with L-phenylalanine, and found that in lab tests with mice it killed cancer cells effectively and very specifically, by causing them to self-destruct.
Cancer cells are killed in lab experiments and tumor growth reduced in mice, using a new approach that turns a nanoparticle into a âTrojan horseâ that causes cancer cells to self-destruct, a research team at the Nanyang Technological University, Singapore (NTU Singapore) has found.
The researchers created their âTrojan horseâ nanoparticle by coating it with a specific amino acid â L-phenylalanine â that cancer cells rely on, along with other similar amino acids, to survive and grow. L-phenylalanine is known as an âessentialâ amino acid as it cannot be made by the body and must be absorbed from food, typically from meat and dairy products.
Studies by other research teams have shown that cancer tumor growth can be slowed or prevented by âstarvingâ cancer cells of amino acids. Scientists believe that depriving cancer cells of amino acids, for example through fasting or through special diets lacking in protein, may be viable ways to treat cancer.
