Dragging effect of space-time detected in white pulsar-dwarf system

If a very massive object, such as a planet or star, rotates, it literally drags the surrounding space-time with it. It is a phenomenon predicted by Einstein’s general relativity also known as the “dragging effect” or the Lense-Thirring effect (from the two Austrian physicists Josef Lense and Hans Thirring who in 1918 first derived the effect within general relativity).

This effect also exists on Earth in relation to its proximity to the Sun but in our case, it is extremely small so that it has been very difficult to measure for years. The effect, however, is more pronounced with heavier and more massive objects, such as white dwarfs or neutron stars. And it is by studying a binary system composed of a white dwarf and a pulsar that researchers have found direct evidence of this effect.

The researchers, led by Vivek Venkatraman Krishnan of the Max-Planck-Institut für Radioastronomie, have in fact observed a pulsar characterized by a narrow and fast orbit around a white dwarf that has a mass similar to that of the Sun. The pulsar makes a full circle around this white dwarf in less than five hours, whizzing at a speed of over one million km/h. The two bodies are very close together and less than the diameter of the Sun.

Measuring the timing of the arrival of the very short pulses of the pulsar towards Earth, data found over a period of almost twenty years, the researchers concluded that it is the Lense-Thirring effect that causes a sort of drift, slow and long term, of the way in which the pulsar and the white dwarf orbit around each other.

It is the dragging of the same space-time that causes the orientation of the pulsar to slowly change while it revolves around the white dwarf. Among other things, this new study confirms a hypothesis, contained in other previous studies, according to which white dwarf of this binary system, called PSR J1141-6545, was formed before the pulsar. Such binary systems are considered quite rare.

This study, among other things, could also be useful to understand what is inside a white dwarf: despite decades of research, it is not yet known how matter is arranged inside this very strange cosmic object given the conditions inside it, conditions of very strong gravity to which the same matter is subjected and which are not reproducible in the laboratory.

New device uses waste electricity from plants and communicates via satellite

A device that collects electricity from cultivated fields and sends information about the same crops via low-power satellite signals was created by the Dutch company Plant-e and Lacuna Space. It is a project carried out as part of Advanced Research in Telecommunications Systems (ARTES), a project of the European Space Agency.

The device can provide information on soil and air humidity and temperature, important information for farmers to keep crops under control. The electricity needed to operate these devices comes from the fact that plants produce organic matter through photosynthesis.

This process, however, does not use all this organic matter to grow plants: part of it is stored in the soil through the roots. Right under the soil, bacteria break it down and release electrons as a sort of “waste.”

The device is capable of collecting these electrons to assimilate that small level of electrical current in order to function and transmit signals.

There is talk of a “new era in sustainable satellite communications,” as Rob Spurrett, the CEO of the company that created the device, defines it. He suggests that the device itself could be used in those regions of the world that are difficult to reach, where there is not a good supply of electricity and an Internet connection and where it is not possible to use solar energy.

Hubble analyzes huge galaxy that contains more than a trillion stars

A huge new galaxy has been observed by the Hubble Space Telescope. This time the telescope focused its attention on UGC 2885, also known as the “Rubin Galaxy,” in honour of the well-known astronomer Vera Rubin, and about 232 million light-years away from us. It is a gigantic galaxy not only because it is 2.5 times the size of our Milky Way but also because it is estimated to contain more than a trillion stars.

And these characteristics are even more remarkable considering that, as astronomers themselves report, this spiral galaxy seems to have never collided or merged with other galaxies. It simply spent its time creating many stars thanks to the considerable amount of hydrogen it has used for all these millions of years.

Because of this “quiet” nature, the galaxy has also been described by astronomers as a “gentle giant”. Even the supermassive black hole that is believed to be in the centre is half “asleep,” as it only attracts a few filaments of gas because the galaxy does not seem to feed, as all large galaxies do, on much smaller satellite galaxies and this does not bring much new material to the central black hole.

Now researchers want to understand the reasons for the underlying anomaly in this galaxy, basically how it has become so large, growing slowly, without attracting to itself almost nothing but the hydrogen of the filamentous structure of intergalactic space. Perhaps UGC 2885, in the distant past, attracted numerous small galaxies and this could be witnessed by the presence of star clusters, just what researchers are looking for inside this huge galaxy and that would explain its size.

Artificial intelligence passes the third grade scientific test for the first time

A software based on artificial intelligence has passed an eighth American school test (comparable to the third year of high school), according to an article in the New York Times. It is the first time that artificial intelligence has passed a test of this level.

It’s been a few years since hundreds of computer scientists entered a competition to create artificial intelligence that can pass a test of this level, but the only one to pass seems to have been the Allen Institute for Artificial Intelligence.

In fact, this Seattle Institute has created a new artificial intelligence system that seems to have passed the scientific test by correctly answering more than 90% of the questions. The software, called Aristo, is designed to mimic the logic of human decision-making.

And it is perhaps precisely for this reason that he managed to overcome not only the questions that made a “simple” information search possible (something that even Google can do now if the questions are very simple), but also questions that needed a real reasoning, essentially the classic and simple “problems” that primary or secondary school students have to solve, issues that, however, require the use of logic.

The standardized scientific tests used in schools are increasingly being used to assess the level of artificial intelligence and the manufacturers themselves see them as excellent benchmarks for understanding the progress and level their software achieves. These types of tests are considered more important than the classic tests based on games such as chess or backgammon.

The latter may, in fact, be governed by the rules to learn, but a scientific test, a series of questions that also includes the use of logic, is more difficult to overcome. Jingjing Liu, one of the Microsoft researchers who has also worked on various Allen Institute initiatives based on artificial intelligence, seems to be cautious and openly declares that it is not yet possible to compare such technology with real human students of the third degree: their ability to reason, at least for the moment, is still superior.

However, the progress that has been made with Aristo can already be used in the short term in a range of different services, ranging from the answers that an Internet search engine can provide to the various tasks that a digital assistant can perform. However, the progress made in artificial intelligence, especially in neural networks that can understand the natural language thanks to models built on the basis of huge amounts of data, does not seem to deny it.

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Scientists discover new geometric models that are more resistant to shocks and explosions

A method to make materials more resistant to vibration and shock, for example during earthquakes, was developed by a group of engineers at the University of California in San Diego.

Professor Veronica Eliasson and her colleagues have discovered during several experiments that have seen the use of a particular device that generates powerful explosions in the laboratory, a particular structural conformation that can reduce the energy of shock waves and therefore to reduce the total damage.

In particular, they discovered that certain grooves in the geometric models used reduced the impact of the so-called “reflected shock wave.” “This research can also be used in military and civil applications to design materials and buildings to better withstand high-intensity explosions,” says Christina Scafidi, one of the researchers working on the project.

Another researcher involved in the research, aerospace engineer Alexander Ivanov, says in the press release: “The coal industry has had many fatal accidents and we believe this research is a valid reason to protect workers from eruptions that can easily spread throughout an entire coal mine. If the entire coal wall could be covered with these solid geometric obstacles, this would be an economical way to protect all miners. ”

Algorithm recognizes bullies and molesters on Twitter with an accuracy of 90%

A new algorithm that recognizes bullies and online attackers has been developed by a group of researchers from the University of Binghamton. Specifically, the researchers developed an algorithm that, with an accuracy of 90% according to the press release, recognizes the bullies on Twitter.

More and more IT and Artificial Intelligence laboratories and researchers are spending their time trying to develop methods for automatically recognizing bullying and aggression on the internet, in order, quite clearly, to benefit even large companies, they keep the social networks that, at least for the time being, mostly use human moderators.

Jeremy Blackburn, an American university computer scientist, is trying to bridge this gap by analyzing the behavioral patterns of “bullies” on Twitter and comparing them to those of “normal” users. It is precisely for this reason that the researcher, together with his colleagues, has created special crawlers to collect data from Twitter faster and more efficiently.

He then relied on natural language processing algorithms and other tools already available for social network analysis and was able to develop an algorithm that automatically classifies two models of offensive behavior online: cyberbullying and cyber aggression.

The accuracy of the algorithm would be 90%. The algorithm is able to identify tricky behavior, for example users who launch threats make racist comments to other users.

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