A new, extraordinarily conserved half-billion-year-old fossil deposit, was discovered in China

An article published in the journal “Science” reports the discovery of a fossil deposit dating back to about 518 million years ago in the southern China’s Hubei province. A team of researchers already led the excavation of 4,351 separate fossils representing 101 species of which 53 are new. The characteristics of the deposit are similar to those of the famous Burgess Shale in Canada and the Chengjiang deposit in China, where fossil conservation is of high quality. These organisms of what has been called Qingjiang biota date back to the period known as the Cambrian explosion and will help to better understand that diversification. Allison Daley of the University of Lausanne published in “Science” a second article concerning the work of the researchers in China.

Philippa Georgiou (Michelle Yeoh) and Michael Burnham (Sonequa Martin-Green) in The Red Angel (Image courtesy CBS / Netflix. All rights reserved)

“The Red Angel” is the 10th episode of the 2nd season of the TV show “Star Trek: Discovery” and follows “Project Daedalus”.

After the funeral of Lieutenant Commander Airiam, the USS Discovery meets again Captain Leland (Alan van Sprang) and Philippa Georgiou (Michelle Yeoh), who reveal their information on the Red Angel. When Ensign Sylvia Tilly (Mary Wiseman) discovers a file in Airiam’s memories containing a bioscan with a precise indication of Red Angel’s identity, a trap is set up to capture her.

The Slitheen Excursion by Simon Guerrier

The novel “The Slitheen Excursion” by Simon Guerrier was published for the first time in 2009.

June is visiting Greece as part of her classical studies at the university. She’s about to finish her journey and wants to see the Acropolis but during her excursion she sees what appears to be a British Police telephone booth with a man coming out and running towards the nearby caves. Curious, she follows him and sees him animatedly arguing with strange creatures that apparently want to destroy the Parthenon. She decides to intervene and helps him to capture the aliens.

June asks for explanations and discovers that the strange man is the Doctor, who doesn’t explain the events but, when he discovers the girl’s interest in ancient Greece, suggests that she travel with him back in time. The idea is to go to 480 B.C. but the discovery of an anomaly in 1500 B.C. leads to a change of plans, especially when the arrival at the new destination occurs with an explosion that leaves the Doctor stunned.

Chasing the Phoenix by Michael Swanwick (Italian edition)

The novel “Chasing the Phoenix” by Michael Swanwick was published for the first time in 2015. It’s part of the Darger and Surplus series.

Sir Blackthorpe Ravenscairn de Plus Precieux said Surplus arrived in the Chinese city of Brocade bringing with him the body of his friend Aubrey Darger in search of the Infallible Physician, the only one who can make him come back to life. Assisted by Capable Servant, whom he met in the city, he succeeds in its intent but their arrival has attracted the attention of the Hidden King, the ruler of that region.

Taken before the Hidden King, Darger and Surplus use their subterfuge to be accepted as his advisers, becoming the Perfect Strategist and the Noble Dog Warrior. Seconds only to Powerful Locomotive and White Squall, they use every trick they can think of to ingratiate themselves with the sovereign helping him to conquer the surrounding kingdoms. Their main problem seems to come from the romantic complications that develop in the royal enturage.

Neural networks to predict the mass of planets in formation

An article published in the journal “Astronomy and Astrophysics” shows an example of the use of a neural network and a deep learning algorithm to reduce the time to create simulations of star systems formation obtaining even better results. Yann Alibert of NCCR PlanetS and of the Swiss University of Bern and Julia Venturini of the International Space Science Institute (ISSI) of Bern and a PlanetS collaborator developed this new system that predicts the mass of a planet starting from the conditions in which it formed with a excellent accuracy and a much higher speed than models based on differential equations.