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A comet has been captured on camera streaking across the skies over Stonehenge.
Comet Neowise has been spotted by stargazers across the UK and around the world as it heads past Earth.
Continue reading “Comet Neowise streaks over Stonehenge night sky” »
Invisible radio signals from the cosmos have revealed previously unknown phenomena from prebiotic molecules in a starburst about 250 million light-years from Earth to the true rotation of Mercury. But the most famous occurred on August 6, 1967, when a squiggly stretch of high-speed recordings occupying less than a quarter-inch of astronomer Jocelyn Bell Burnell’s radio-telescope readouts revealed the first sign of something strange — an unknown cosmic mystery.
The minuscule signal appeared over and over again in the same part of the sky and she realized she was looking at a cosmic mystery — a repeating string of radio pulses spaced a bit more than a second apart that were unlike anything anyone had ever seen before. Bell-Burnell had detected the first evidence of a pulsar LGM-1 for Little Green Men. They thought the pulses could possibly be a beacon from an alien source.
Fast forward to today — mysterious circles of radio waves have left astronomers who are part of a pilot survey for a new project called the Evolutionary Map of the Universe (EMU) baffled with no idea how they formed, or even how big or far away they are. They don’t seem to match anything that has been seen before in the cosmos. The researchers dubbed them Odd Radio Circles, or ORCs.
The presence of outliers in a classification or regression dataset can result in a poor fit and lower predictive modeling performance.
Identifying and removing outliers is challenging with simple statistical methods for most machine learning datasets given the large number of input variables. Instead, automatic outlier detection methods can be used in the modeling pipeline and compared, just like other data preparation transforms that may be applied to the dataset.
In this tutorial, you will discover how to use automatic outlier detection and removal to improve machine learning predictive modeling performance.
“We need to go to space to help us here on Earth. Satellites have played an enormous role in improving the state of the world, and will do even more”.
I’m often asked: ‘Why are you building satellites for space when there are so many problems to fix here on Earth?’ It’s a perfectly rational question. The short answer is that we need to go to space to help us here on Earth. Satellites have played an enormous role in improving the state of the world, and will do even more as an explosion of technology innovation enables large new fleets of small satellites to be deployed with radical new capabilities.
One idea, which has been in gestation for some years, could be about to have its break-out moment. A new agreement, the Treaty on the Prohibition of Nuclear Weapons (TPNW), is expected to become international law next year — and scientists have a chance to play a part in helping it to succeed.
Seventy-five years after the bombing of Hiroshima and Nagasaki, a new treaty offers renewed hope for a nuclear-free world.
Must watch astronomy events this month.
Top 5 Space Apps: https://www.secretsofuniverse.in/astronomy-apps/
How to watch the planets: https://www.secretsofuniverse.in/planet-roundup-august-2020/
Continue reading “Don’t Miss These Astronomy Events In The Month Of August 2020!” »
A team of computer scientists has developed a new AI that can write code and predict software solutions for programmers navigating through numerous application programming interfaces (APIs).
For years, research scientists have been studying how programs can generate instant feedback that coders can address immediately. A wide range of applications has already been created, all of which aim to detect faulty or questionable lines of code. While this has only been minimally integrated into most developers’ software tools, a team of computer scientists from Rice University has recently figured out a way for developers and programmers to receive feedback on their code while suggesting solutions for their programs—all through artificial intelligence (AI).
In a Q&A, spacesuit designer Amy Ross explains how five samples, including a piece of helmet visor, will be tested aboard the rover, which is targeting a July 30 launch.
NASA is preparing to send the first woman and next man to the Moon, part of a larger strategy to send the first astronauts to the surface of Mars. But before they get there, they’ll be faced with a critical question: What should they wear on Mars, where the thin atmosphere allows more radiation from the Sun and cosmic rays to reach the ground?
Amy Ross is looking for answers. An advanced spacesuit designer at NASA’s Johnson Space Center in Houston, she’s developing new suits for the Moon and Mars. So Ross is eagerly awaiting this summer’s launch of the Perseverance Mars rover, which will carry the first samples of spacesuit material ever sent to the Red Planet.
Scientists have found a novel way to prevent pesky magnetic bubbles in plasma from interfering with fusion reactions—delivering a potential way to improve the performance of fusion energy devices. And it comes from managing radio frequency (RF) waves to stabilize the magnetic bubbles, which can expand and create disruptions that can limit the performance of ITER, the international facility under construction in France to demonstrate the feasibility of fusion power.
Magnetic islands
Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have developed the new model for controlling these magnetic bubbles, or islands. The novel method modifies the standard technique of steadily depositing radio (RF) rays into the plasma to stabilize the islands—a technique that proves inefficient when the width of an island is small compared with the characteristic size of the region over which the RF ray deposits its power.
