Simulation shows nuclear pasta 10 billion times harder to break than steel

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According to (This article and its images were originally posted on Phys.org September 18, 2018 at 09:03AM.)

A trio of researchers affiliated with several institutions in the U.S. and Canada has found evidence that suggests nuclear material beneath the surface of neutron stars may be the strongest material in the universe. In their paper published in the journal Physical Review Letters, M. E. Caplan, A. S. Schneider, and C. J. Horowitz describe their neutron star simulation and what it showed.

Prior research has shown that when reach a certain age, they explode and collapse into a mass of neutrons; hence the name star. And because they lose their neutrinos, become extremely densely packed. Prior research has also found evidence that suggests the surface of such stars is so dense that the material would be incredibly strong. In this new effort, the researchers report evidence suggesting that the material just below the surface is even stronger.

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This article and its images were originally posted on [Phys.org] September 18, 2018 at 09:03AM. Credit to the original author and Phys.org | ESIST.T>G>S Recommended Articles Of The Day.

 

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Climate Change Killed the Aliens, and It Will Probably Kill Us Too, New Simulation Suggests

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According to Live Science (This article and its images were originally posted on Live Science June 6, 2018 at 07:34AM.)


Did climate change already kill all the aliens we’ve been searching for?
According to astrophysicist Adam Frank, it’s certainly a possibility — and whether or not humans are doomed to the same fate may already be out of our hands.

 
Frank, a professor of physics and astronomy at the University of Rochester in New York, is the lead author of a new paper published May 1 in the journal Astrobiology, which aims to take what Frank calls a “10,000 light-year” view of anthropogenic climate change. Using mathematical models based on the disappearance of a real-life lost civilization here on Earth (the one-time inhabitants of Easter Island), Frank and his colleagues simulated how various alien civilizations might rise and fall as they increasingly converted their planet’s limited natural resources into energy. [12 Possible Reasons We Haven’t Found Aliens]

 
“The laws of physics demand that any young population, building an energy-intensive civilization like ours, is going to have feedback on its planet,” Frank said in a statement. “Seeing climate change in this cosmic context may give us better insight into what’s happening to us now and how to deal with it.”

 
The results, as you might expect, were generally pretty grim. Out of four common “trajectories” for energy-intense civilizations, three ended in apocalypse. The fourth scenario — a path that involved converting the whole alien society to sustainable sources of energy — only worked when civilizations recognized the damage they were doing to the planet, and acted in the right away.

 
“The last scenario is the most frightening,” Frank said. “Even if you did the right thing, if you waited too long, you could still have your population collapse.”

For Frank, the path to modeling an apocalypse starts with Easter Island.
“Easter Island presents a particularly useful example for our own purposes since it is often taken as a lesson for global sustainability,” Frank and his colleagues wrote in the paper. “Many studies indicate that Easter Island’s inhabitants depleted their resources, leading to starvation and termination of the island’s civilization,” the researchers wrote.

 
Working from previous equations that modeled the fall of Easter Island’s population alongside the depletion of its resources, the team found four possible endpoints for a hypothetical alien civilization similarly constrained by limited natural resources.
“The first trajectory we found is what we call the die-off,” Frank said.
In this scenario, the civilization’s population skyrockets over a short period of time, and as the aliens guzzle energy and belch out greenhouse gases, the planet’s temperature spikes too (in this study, temperature was used to represent man-made impacts on the planet’s habitability via greenhouse gas pollution). The population peaks, then suddenly plummets as rising temperatures make survival harder and harder. The population eventually levels off, but with a fraction of the people who were around before. [Doomsday: 9 Real Ways the World Could End]

 
“Imagine if seven out of 10 people you knew died quickly,” Frank said. “It’s not clear a complex technological civilization could survive that kind of change.”

 
The second scenario is sustainability. Here, the planet’s population and its global temperature both climb rapidly, but then level off when the civilization recognizes how its resource management is affecting nature. To reach an equilibrium, Frank said, the population would need to switch from resources that take a high toll on the planetl (like oil) to more sustainable resources (like solar energy). Civilization is saved!

 
The third and fourth scenarios are both called “collapse.” Here, as in the “die-off” scenario, both the planet’s population and the planet’s temperature rise dramatically over a short period of time. But this time, when people start dying from a lack of basic resources, there are no survivors. Whether a civilization merely dies off or totally collapses depends on how sensitive the environment is, and how quickly it responds to rising populations.

 
Even if the civilization realizes it’s damaging the environment and makes attempts to switch to sustainable resources — a scenario called “collapse with resource change” — it’s too late. The civilization might see a temporary slowing in the population decline, but eventually it drops to zero anyway. The damage is done; civilization is doomed.

 
Act now while civilization lasts

 
The difference between a sustainable future and a deadly collapse was largely dependent on a population’s foresight — how soon they realized they were destroying their planet, and how quickly they took action. According to Frank, this difference should motivate humans to take climate change seriously.

 
“Across cosmic space and time, you’re going to have winners — who managed to see what was going on and figure out a path through it — and losers, who just couldn’t get their act together and their civilization fell by the wayside,” Frank said.

 
“The question is, which category do we want to be in?”

Cover Image: by 

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This article and its images were originally posted on [Live Science] June 6, 2018 at 07:34AM. All credit to both the author: Brandon Specktor and Live Science | ESIST.T>G>S Recommended Articles Of The Day.

 

 

 

Session – Skateboarding simulation game by crea-ture Studios

Embrace skateboarding like never before with our unique dual stick controls and video creation tools. Skate, film, share and repeat!

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According to kickstarter.com

About

 While you take a minute or two to look over the campaign, click on the link below to download our prototype demo!

 

 

 

 

 

 

Inspired by the golden era of skateboarding, the early 90s and early 2000, Session’s primary goal is to make you experience what skateboarding really is; an incredible sport where there are no other goals other than expressing your creativity and achieving success through hard work, perseverance and bits of madness for no one else other than yourself.

The main purpose of the game is to live the sport in its entirety. Feel what it is to be a talented street skater.  Explore and tame the concrete, film yourself, your friends and share your footage on the internet with the worldwide skateboarding community.

Session focuses on the authenticity of skating, both in the way the game feels and is presented to the player.  Based on this philosophy, each feature makes the game even more innovative, fun and respectful to the skateboarding culture.

 

In Session each stick represents your feet.  From there, every skateboard is your instruction manual.  Just think about how you would move your feet or transfer your weight while on a skateboard and apply that to the sticks.

 

In Session it’s not only a matter of getting on your grinds but it’s also important to work on finding the sweet spot in order to keep your balance, slide longer and have it steezy!

Putting too much weight on the wheels while sliding will slow you down, reduce your ”pop out” or eventually end up with a wheel bite. On the other hand, if you don’t put enough weight, you’ll end up falling or losing your trick.

Eventually, you’ll be able to apply some wax to reach greater distances but remember, it won’t fix all your problems!

 

Focus on what skateboarding really is! If a handrail inspires you to do a backside lipslide, then so be it! We won’t dictate which tricks are worth more. But if you really feel like getting recognition for your hard work, share it and maybe you’ll become a virtual pro skater.

 

 

Filming has always been a big part of the skateboarding culture. Session will feature an extended video editor that will allow the player to perform their tricks; edit, create a montage in-game and share it through all the most popular social media platforms (available social media platforms will vary depending on chosen game platform).

 

Time to setup your spot lights! Whether you want to nail that rail gap as dawn light shines over the city, or are looking to tear up a pool at midnight, you can pick your prime skating time.

Have your filmer friend ready and rip some sick night footage!  Those late night sessions are the best!

 

Session is not just another skateboarding game. It is something that will live on and grow with the community and with those who wish to get involved. 

Join us and turn Session into the most authentic game that represents what the skateboarding culture really is.

Everyone’s unique, we know it but skaters need to show their colors. This is part of the skate culture and it’s no different in Session. From the type of the cap you wear, to the colors of your bolts, you’ll have access to in-depth character and skateboard customization to show off your style!

 

 

Session’s progression system rewards those who repeat, persevere and keep trying. The more you do your tricks, the more consistent you become, the higher the pop, the easier the catch will be and more!

The progression system in Session is based on what you do and how often.  For example, if you keep doing kickflips, you’re gonna get better at it. You’ll be able to flip faster when you need to, pop higher and have an easier time catching your trick. This way your skills will continuously open new venues and spots to shred!  However, if you think everything you gain stays forever, you’re wrong! Like any other athlete, if you don’t keep practicing, you’ll lose that edge!

 

Build a better tomorrow, with us! Session is built upon the concept of city hubs that will grow on a regular basis and evolve based on your feedback.

With the help of heat maps and in-game feedback tools, we’ll have useful information about skater habits across the cities, the most skated spots and what they like or don’t like. This will help us identify what we should be fixing or modifying first!

A spot sucks? Let us know, we’ll put construction signs for a couple weeks and we’ll fix it. This skate plaza is always empty? Development metrics will tell us why and we’ll redo it.

 

 

Every city hubs are directly inspired by real life cities with accurate and to-scale reproductions of their most legendary and best skate spots. Have a spot you want to see? Let us know! Session is the right place to be vocal.

 

Skate with friends online, have a game of skate on the couch, film a big part with your filmer friends or simply go to your favorite secret hubba and have a session!

Online Filmer Mode - Concept
Online Filmer Mode – Concept

 

The filmer mode allows a second player to follow their skater friends online and film their performance live during the session.

Controls scheme is subject to change
Controls scheme is subject to change

It also lets the player record movies easily while following their friends and find the best angles without feeling overwhelmed.  It’s designed to help the player feel like a professional cameraman, with presets such as auto-follow, auto target, optimal angles and much more.

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This article and images were originally posted on [kickstarter.com] December 14, 2017 at 08:50AM. Credit to Author and kickstarter.com | ESIST.T>G>S Recommended Articles Of The Day

 

 

 

Journey Through Gorgeous Nebulas in New Simulation

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According to Space.com


NEBULAE – a cosmic meditation from Teun van der Zalm on Vimeo.

A new video by visual artist Teun van der Zalm takes viewers on an intimate tour of computer-simulated nebulas — enormous cosmic clouds gas and dust.

The Hubble Space Telescope gave humanity its very first up-close-views of cosmic nebulas, where dying stars explode and spread their ashes across space. From that ejected material, new stars are born.

As unforgettable as those Hubble images are, the telescope could never provide the kind of views offered by the new video, called “Nebulae.” The use of a computer simulation allows for a much closer look at these colorful cosmic clouds.

In the short movie, the “camera” appears to move around and through enormous clouds, which are rich with colors, from deep purples to fiery reds. Tranquil music allows the viewer to sit back and bask in the beauty. (It’s worth noting that many of the nebulas imaged by Hubble would appear quite different to a human who traveled to see them up close. These objects are frequently too faint to be seen with the naked eye, or they emit light in wavelengths that the human eye cannot see.)

In the movie’s description on the website Vimeo, the creator quotes astronomer and science popularizer Carl Sagan from the first episode of the TV show “Cosmos: A Personal Voyage,” which Sagan hosted: “A cloud that veils one of nature’s secret places. This is a stellar nursery, a place where stars are born. They condense by gravity from gas and dust until their temperatures become so high that they begin to shine. Such clouds mark the births of stars, as others bear witness to their deaths.”

While the simulated nebulas clearly have a lot in common with the real-world nebulas photographed by Hubble, it’s not clear how scientifically accurate the simulations are. But, as the video’s subtitle indicates, the short movie works perfectly as a “cosmic meditation.”

 

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This article and images were originally posted on [Space.com] November 8, 2017 at 07:05AM

Credit to Author and Space.com | ESIST.T>G>S Recommended Articles Of The Day

 

 

 

Drone Uses AI and 11,500 Crashes to Learn How to Fly

 

“Learning to Fly by Crashing,” a paper from CMU roboticists Dhiraj Gandhi, Lerrel Pinto, and Abhinav Gupta, has such a nice abstract that I’ll just let them explain what this research is all about:

[T]he gap between simulation and real world remains large especially for perception problems. The reason most research avoids using large-scale real data is the fear of crashes! In this paper, we propose to bite the bullet and collect a dataset of crashes itself! We build a drone whose sole purpose is to crash into objects [. . .] We use all this negative flying data in conjunction with positive data sampled from the same trajectories to learn a simple yet powerful policy for UAV navigation.

Cool, let’s get crashing!

One way to think of flying (or driving or walking or any other form of motion) is that success is simply a continual failure to crash. From this perspective, the most effective way of learning how to fly is by getting a lot of experience crashing so that you know exactly what to avoid, and once you can reliably avoid crashing, you by definition know how to fly. Simple, right? We tend not to learn this way, however, because crashing has consequences that are usually quite bad for both robots and people.

The CMU roboticists wanted to see if there are any benefits to using the crash approach instead of the not crash approach, so they sucked it up and let an AR Drone 2.0 loose in 20 different indoor environments, racking up 11,500 collisions over the course of 40 hours of flying time. As the researchers point out, “since the hulls of the drone are cheap and easy to replace, the cost of catastrophic failure is negligible.” Each collision is random, with the drone starting at a random location in the space and then flying slowly forward until it runs into something. After it does, it goes back to its starting point, and chooses a new direction. Assuming it survives, of course.

During this process, the drone’s forward-facing camera is recording images at 30 Hz. Once a collision happens, the images from the trajectory are split into two parts: the part where the drone was doing fine, and the part just before it crashes. These two sets of images are fed into a deep convolutional neural network (with ImageNet-pretrained weights as initialization for the network), which uses them to learn, essentially, whether a given camera image means that going straight is a good idea or not. After 11,500 collisions, the resulting algorithm is able to fly the drone autonomously, even in narrow, cluttered environments, around moving obstacles, and in the midst of featureless white walls and even glass doors. The algorithm that controls the drone is simple: It splits the image from the AR Drone’s forward camera into a left image and a right image, and if one of those two images looks less collision-y than going straight, the drone turns in that direction. Otherwise, it continues moving forward.

How well does this work? It’s usually not as good as a human pilot, except in relatively complex environments, like narrow hallways or hallways with chairs. But compared to a baseline approach using monocular depth estimation, it’s massively better, somewhere between 2x and 10x the performance (in both time in the air and distance flown), depending on the environment. The biggest benefit comes from navigating around featureless walls and glass doors, both of which are notoriously challenging for depth estimation.

The obvious question to ask is whether this method is actually more effective than the alternative, which is teaching a drone to fly through not crashing instead. I’m not sure what the answer is, but the point is that if you allow crashing, the entire learning process can be self-supervised: Just set the drone up in a room and let it do its thing. You’ll have to change the batteries (and the hull, on occasion) but otherwise all of the data collection and learning is completely autonomous. If, on the other hand, you try to teach a drone to fly through not crashing, you have to find a way to make sure that it doesn’t crash. You can do that by learning from a human pilot, or putting it in some environment with a motion capture system and some 3D maps of obstacles and whatnot, but that adds cost and complexity. Crashing is so much easier.

“Learning to Fly by Crashing,” by Dhiraj Gandhi, Lerrel Pinto, and Abhinav Gupta from the Robotics Institute at Carnegie Mellon University, can be read in its entirety at the link below.

[ Paper ]

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This article and images was originally posted on [IEEE Spectrum Robotics] May 10, 2017 at 09:18AM

By Evan Ackerman

 

 

 

 

 

 

Watch the Milky Way’s birth in this Caltech simulation

A team of Caltech astronomers created what could be the most accurate computer simulation of our galaxy’s birth. See, according to computations for older simulations, our galaxy should be surrounded by thousands of dwarf galaxies. In reality, though, there are only around 30 dwarf galaxies nearby. Astronomers thought their computations were incorrect, because we still don’t understand the true nature of dark matter that permeates every corner of the universe. However, the Caltech team found out that it’s not dark matter that’s the problem. Their computations were able to achieve the current state of our galaxy simply by incorporating the effects of supernovae.

“We had thought before that perhaps our understanding of dark matter was incorrect in these simulations, but these new results show we don’t have to tinker with dark matter,” says team leader Andrew Wetzel. “When we more precisely model supernovae, we get the right answer.”

 

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By Mariella Moon

 

 

Source: Watch the Milky Way’s birth in this Caltech simulation