Grisly Beach Discovery Reveals Broken 'Sword' That Slayed an Unlucky Shark

 When a dead Alopius vulpinus washed up onshore, it had been obvious what had killed it - a swordfish had stabbed it from behind and left an oversized hunk of its "sword" embedded within the beast, a brand new study finds.

No one saw the particular attack, so it's unclear why the swordfish jabbed the shark. But the 2 ocean predators may are competing for prey, the researchers said.

"The possible scenario is that both species were hunting on a faculty of fish or on squids within the deep," said study lead researcher Patrick Jambura, a doctoral student within the Department of Paleontology at the University of Vienna. 

(The Ichthyological Society of Japan 2020)

It's also possible the 2 ocean predators were fighting over territory, or that the swordfish accidentally stabbed the thrasher and left nearly 12 inches (30.1 centimeters) of its "sword" within the victim, he said.

News of the fight's deadly aftermath spread when the shark's body washed abreast of the Mediterranean coast of Libya, near the town of Brega in April 2020. an area citizen scientist group learned about photos and video taken of the 14.5-foot-long (4.5 meters) dead shark.

After seeing the evidence, Jambura told Live Science "I was just stunned for some moments".

Swordfish (Xiphias gladius) are known to defend themselves against blue sharks (Prionace glauca) and mako sharks (Isurus oxyrinchus), as these sharks take advantage of swordfish. 

Swordfish have also been reported attacking whales, sea turtles, inanimate objects, including boats and submarines, and even humans, Jambura and his colleagues wrote within the study.

In 2015, "a diver was killed in Hawaii when he speared a tiny low swordfish that had wandered into a marina," said Yannis Papastamatiou, a marine biologist at Florida International University, who wasn't involved in the study. "It speared him through the chest."

But thresher sharks (Alopias superciliosus) eat small fish "and wouldn't be a threat" to swordfish, Jambura said.

Whatever the reason for the stabbing, "we know that the swordfish attacked from above - the shark was presumably not even alert to the danger [it] was in until it absolutely was too late," Jambura said.

(The Ichthyological Society of Japan 2020)

It appears that the roughly 10-foot-long (3.1 m) swordfish stabbed the shark just behind the top, leaving a cut 2 inches (5 centimeters) deep and three inches (8 cm) wide where it pierced the shark's gill system.

Because nobody performed a necropsy (an animal autopsy), there aren't any thanks to knowing whether that caused deep internal damage, "but from the angle and therefore the depth of penetration, it's safe to mention that the gill region was heavily damaged, possibly also some important arteries," Jambura said.

While this is often the primary reported case of a swordfish killing an Alopius vulpinus, scientists do not know how often this happens within the water's depths.

"We rarely see evidence of those outcomes: Sharks are negatively buoyant and can sink after they die," Papastamatiou told Live Science in an email. "Unless they destroy on the beach like here (which is rare, most will sink into the deep sea), then we can't find evidence of the interaction."

The swordfish left the altercation physically damaged, but that does not mean the fish died; there are known cases of billfish (a close relative of the swordfish) that have damaged, malformed, or maybe missing rostra (or its pointy "sword") that "were apparently still in good physical shape," the researchers wrote within the study. Perhaps the assailant survived.

Artificial Intelligence Is Now Smart Enough to Know When It Can't Be Trusted

 How might The Terminator have played out if Skynet had decided it probably wasn't responsible enough to carry the keys to the complete US nuclear arsenal? because it seems, scientists could have saved us from such a future AI-led apocalypse, by creating neural networks that know when they're untrustworthy.

These deep learning neural networks are designed to mimic the human brain by weighing up a large number of things in balance with one another, spotting patterns in masses of knowledge that humans haven't got the capacity to analyze.

While Skynet might still be how off, AI is already making decisions in fields that affect human lives like autonomous driving and diagnosing, which means it is important that they are as accurate as possible. to assist towards this goal, this newly created neural network system can generate its confidence level moreover as its predictions.

"We need the flexibility to not only have high-performance models but also to know after we cannot trust those models," says scientist Alexander Amini from the MIT technology and computing Laboratory (CSAIL).

This self-awareness of trustworthiness has been given the name Deep Evidential Regression, and it bases its scoring on the standard of the available data it's to figure with – the more accurate and comprehensive the training data, the more likely it's that future predictions are visiting figure out.

The research team compares it to a self-driving car having different levels of certainty about whether to proceed through a junction or whether to attend, just just in case, if the neural network is a smaller amount confident in its predictions. the boldness rating even includes tips for getting the rating higher (by tweaking the network or the computer file, for instance).

While similar safeguards are built into neural networks before, what sets this one apart is that the speed at which it works, without excessive computing demands – it are often completed in one run through the network, instead of several, with a confidence level outputted at the identical time as a call.

"This idea is vital and applicable broadly," says the man of science Daniela Rus. "It will be wont to assess products that depend upon learned models. By estimating the uncertainty of a learned model, we also learn the way much error to expect from the model, and what missing data could improve the model."

The researchers tested their new system by getting it to gauge depths in several parts of a picture, very like a self-driving car might judge distance. The network compared well to existing setups, while also estimating its own uncertainty – the days it had been least certain were indeed the days it got the depths wrong.

As an additional bonus, the network was able to flag up times when it encountered images outside of its usual remit (so very different to the info it had been trained on) – which is a very medical situation could mean getting a doctor to require a review.

Even if a neural network is true 99 percent of the time, that missing 1 percent can have serious consequences, looking at the scenario. The researchers say they're confident that their new, streamlined trust test can help improve safety in real-time, although the work has not yet been peer-reviewed.

"We're beginning to see plenty more of those [neural network] models trickle out of the science lab and into the important world, into situations that are touching humans with potentially life-threatening consequences," says Amini.

"Any user of the tactic, whether it is a doctor or an individual within the passenger seat of a vehicle, must bear in mind of any risk or uncertainty related to that call."

Teaching Rats To Drive Tiny Cars Helps Them Relax, Scientists Discover

 A bunch of rats has learned the way to drive tiny vehicles around to choose up food. How did this unlikely scenario come around, you're little question asking? Well, for a surprisingly interesting reason, actually. 

Researchers from the University of Richmond in Virginia used the vehicle-driving rodents to indicate that an enriched environment can improve cognitive function and help sharpen the power to find out complex tasks. They also demonstrated that the mastery of an advanced skill can reduce levels of stress and help the rodents sit back. 

“The findings that the animals housed in an exceedingly complex environment had more efficient learning within the driving task confirms that the brain could be a plastic organ that's molded by our experiences to some extent,” Dr. Kelly Lambert, study author and professor of Behavioral Neuroscience at the University of Richmond, told IFLScience.

“I tell my students that they're in control of what they are doing with their brains a day of their lives – tougher and enriching lifestyles cause more complex neural networks.”  

As reported within the journal Behavioural Brain Research, the rats were presented with a rodent operated vehicle (ROV) consisting of a plastic jar on electric-powered wheels that they may move forward or steer sideways by touching a copper bar. Understandably, this can be a fairly complex task for a rodent to find out, requiring all manner of cognitive, motor, and visuospatial skills they wouldn’t usually employ together. Nevertheless, after some practice, they were able to successfully navigate around a narrow arena towards a tasty reward, a brilliant sugary Froot Loop cereal. 

Volume 21%

Out of the 11 rats tested, six were housed in standard laboratory cages, while the remaining five got the luxurious of an “enriched environment,” including different toys, and closely resembled their natural habitat.

As hypothesized, the animals living within the enriched environment performed better at the driving test, indicating that they did a more robust job at learning a brand new complex skill. The enriched rats also maintained a powerful interest within the car, even after the reward of food was removed. 

On the opposite hand, the researchers were surprised at the dearth of interest shown by the non-enriched rats and their level of underachievement shown within the driving task. 

The rats' poop was also tested for levels of two hormones, corticosterone, which may be a marker of stress, and dehydroepiandrosterone, which helps control stress. All of the rats' feces showed increasing dehydroepiandrosterone and decreasing corticosterone as their driving training continued. This suggested that each one of the animals within the study, no matter the housing group, lessen stressed after they'd mastered the complex skill. 

Obviously, this study was disbursed on rodents, so we should always watch out to not jump to any conclusions. However, the study could hold some interesting implications when it involves animals' environment and their psychological state.

“It reminds us that we will use challenging tasks with preclinical animal work to find out more about human challenging behavior and cognitive systems,” Lambert added. “We also see that the rats had healthier stress hormone profiles with driving training. we predict this learning task and operating the ROV could also be an animal model for agency or self-efficacy – two elements that are critical for psychological state.”

NASA accidentally films the BEST UFO sightings yet (VIDEO)

 

In the movie, a mysterious object - with a peculiar disc-shaped design - seems to move from 

the Earth's atmosphere causing a huge debate on social networks. What it was? Alien vehicle?

Space debris? Optical illusion or simply Swamp Gas? Some are convinced that it is the 

latest evidence that Earth is being visited by alien beings, while others remain skeptical 

and still not convinced.



Ever since the movie was uploaded to YouTube, it has generated controversy both among those 

who support the idea that it could be an extraterrestrial object, and between those who are 

completely skeptical about the subject, and as a joke they suggest that "the UFOs that they 

are planning to enter our airspace should be registered and pay taxes. "



The truth is that on many occasions only fragments of video are released in which these 

mysterious objects are visible.

However, the fact that NASA interrupts its live feed broadcasts is what raises most 

suspicions among those who are eager to find new evidence for the existence of alien life, 

UFOs and how we are all part of a massive conspiracy.

A user wrote on YouTube:

"The question is not" is it an alien spaceship? "But really" Why didn't NASA cut or blur 

this video like they always do with other strange places? "

According to many people, in today's era, it is no longer a question of whether UFOs are 

real. Indeed, if we look back into the past, we will see numerous fascinating statements 

made by ex astronauts, military officers and scientists about Alien about the life and 

existence of UFOs.

NASA Has Released Awesome Footage That Has Revolutionized Our Understanding Of Mars

 

NASA's Jet Propulsion Laboratory shared some surprising new footage of their latest flights 

over Mars. Some recent flybys have revealed new avalanche images that are forming on Mars. 

These flybys have helped scientists develop new and more accurate theories of the sea and 

its past. Learn more about this in the video below:

China Is Planning To Visit Mars By 2020 And Beat Nasa To Set Up The First Manned Moon Base

 

China has finally announced that it plans to visit Mars by 2020, along with being one of the first nations to walk on the “far side” of the moon. In an unusual video discussion with the BBC, Wu Weiren, a high-ranking official in the China National Space Administration (CNSA) who worked as chief of China’s moon and Mars missions, publicized that China is presently working on a certain Mars probe exploration mission. Wu said “We will orbit Mars, land and deploy a rover — all in one mission. We could have started our Mars mission earlier but finally the country has given its approval.”

What’s even more interesting is that, China also aims to effectively colonize the moon by establishing a manned base. Wu explained “Our short-term goal is to orbit the moon, land on the moon and take samples back from the moon. Our long-term goal is to explore, land, and settle. We want a manned lunar landing to stay for longer periods and establish a research base. It’s quite challenging to land there, but according to research there might be water or ice because of the lack of sunlight, so we’d very much like to check that out.”

Seems like the movie “The Martian” has made quite an impression on China. Contrary to what you are thinking, Wu also said that China is very much hopeful to cooperate with space agencies from other countries such as NASA in the US – much like in film The Martian, where China’s space agency presents its Taiyang Shen space rocket booster to direct rescue supplies to NASA astronaut Mark Watney, who is trapped on Mars with decreasing resources.

In this whole situation China is not the bad guy neither is the US but US Congress has already passed a spending bill in 2011 particularly restricting NASA from working in China, due to a high risk of spying.

Wu said “We would like to co-operate with the US, especially for space and moon exploration. We have urged the US many times to get rid of restrictions so scientists from both countries can work together on future exploration.”

According to Reuters, a senior Chinese space official Xu Dazhe, the chief of the China National Space Administration, said at a press conference on 22 April that The Martian film displays that the US would not be adverse to working with China.

Xu said “When I saw the US film The Martian, which envisages China-US cooperation on a Mars rescue mission under emergency circumstances, it shows that our U.S. counterparts very much hope to co-operate with us.”

“However, it’s very regrettable that, for reasons everyone is aware of, there are currently some impediments to cooperation. I believe that on this matter, China is more and more open, and I hope our American friends can take note.”

As some people might think, this is not a race because overall, this all is going to be a huge step in human history regardless of who goes first.

Astronomers Discovered A Second ‘Alien Megastructure’ Star That’s Even Stranger Than Kic 8462852

 

The strangest star in the universe is not alone. In 2015, astronomers reported unusual 

behaviors in the star "KIC 8462852" which they could not explain. Now, another team has 

discovered a second star that behaves similarly to KIC 8462852. It is called 

"EPIC 204278916" and is even stranger than the first. Find out more about this mysterious 

star in the video below: