Schrödinger's kittens have never been very cute, and the latest litter is no exception. Images of nebulous clouds of ultracold atoms or microscopic strips of silicon are unlikely to go viral on the internet. All the same, these exotic objects are worth heeding, because they show with unprecedented clarity that quantum mechanics is not just the physics of the extremely small.

"Schrödinger's kittens," loosely speaking, are objects pitched midway in size between the atomic scale, which quantum mechanics was originally developed to describe, and the cat that Erwin Schrödinger famously invoked to highlight the apparent absurdity of what that theory appeared to imply. These systems are "mesoscopic" - perhaps around the size of viruses or bacteria, composed of many thousands or even billions of atoms, and thus much larger than the typical scales at which counterintuitive quantum-mechanical properties usually appear. They are designed to probe the question: How big can you get while still preserving those quantum properties?

To judge by the latest results, the answer is: pretty darn big. Two distinct types of experiments - both of them carried out by several groups independently - have shown that vast numbers of atoms can be placed in collective quantum states, where we can't definitely say that the system has one set of properties or another. In one set of experiments, this meant "entangling" two regions of a cloud of cold atoms to make their properties interdependent and correlated in a way that seems heedless of their spatial separation. In the other, microscopic vibrating objects were maneuvered into so-called superpositions of vibrational states. Both results are loosely analogous to the way Schrödinger's infamous cat, while hidden away in its box, was said to be in a superposition of live and dead states.

A new app lets school administrators send an emergency lockdown notification to their entire staff and communicate with teachers to see if they're safe.

The details

TABS-which stands for "Tracking Appropriate Behaviors"-rolled out on Tuesday. It's a web-based app meant for use on laptops and smartphones that combines tools for keeping an eye on students with ways for schools to automatically enact lockdown procedures. It's designed as a way to keep staff members in touch with each other during emergencies such as school shootings.

It's not alone

As if the need for one app weren't horrifying enough, TABS is just the latest to include this kind of lockdown capability. App makers apparently expect that schools will want to have them handy at a time when on-campus shootings regularly dominate headlines.

Research uncovers the first insect known to use the same navigation method as night-flying migratory birds.

Monarch butterflies and bogong moths are the only insects known to undertake migratory journeys to specific sites year after year.

An Australian species, bogong moths (Agrotis infusa) flee the harsh conditions of the arid plains by migrating long distances to spend summer in cool caves of the continent's alpine region. The butterflies (Danaus plexippus) use an internal sun compass for their journey, but the bogongs moths can't do that because they fly at night.

How millions of the adult moths find their way across 1000 kilometres or more of country in darkness, then back again at the end of summer, was unknown - until now. New research published in the journal Current Biology reveals that, like migratory birds, they use the Earth's magnetic field and visual landmarks to navigate this journey.

Since the 2016 U.S. presidential election, much attention has been focused on the role of bots in promoting political news on Twitter. But bots can play a role in spreading many other types of news and information as well.

Indeed, a new Pew Research Center analysis finds that suspected bots are far more active in sharing links to news sites focusing on nonpolitical content than to sites with a political focus. And when they do share political news on Twitter, suspected bots are more likely to link to sites with ideologically centrist audiences than to ones with staunchly liberal or conservative followings.

To conduct the analysis, researchers examined 108,552 tweeted links to 50 popular news websites sent during a six-week period in the summer of 2017. The sites all produce original content and include those associated with legacy news organizations (outlets that originated in print or broadcast) as well as digital-native sites (outlets that were "born on the web"). Researchers identified potential bot accounts by using a multistep process that is explained here.

Here are some key findings from the analysis:

1 Suspected bots share a smaller proportion of links to popular news sites compared with other kinds of websites. Suspected bots shared 59% of tweeted links to the 50 news sites in the analysis. While that figure may sound high, it is lower than the average from a previous Pew Research Center analysis, which found that suspected bots shared 66% of tweeted links to a broader set of more than 2,000 popular websites, including sites focused on commercial products, sports and other subjects.

The 50 sites in the news analysis include the digital versions of print newspapers such as The New York Times and The Washington Post, as well as sites for television and radio broadcasting organizations such as CNN, Fox News and NPR.

Californians have been buzzing about "The Big One," a huge earthquake that many experts feel is long overdue along one of the state's major fault lines. If you think this doesn't concern you because you don't live in the Golden State, you could end up paying a big price for that denial as experts outline just how far of a reach such a natural disaster would have.

After all, the U.S.'s second-biggest city, Los Angeles, sits on 100 geological faults and would be severely impacted by The Big One. This would have a significant knock-on effect that would reverberate throughout the American economy.

Writing for Market Watch, seismologist Dr. Lucy Jones warns that people who are focused on the loss of homes and infrastructure damage aren't seeing the big picture. When she worked at the U.S. Geological Survey, Dr. Jones was in charge of a team that was tasked with estimating what the consequences of a big earthquake would be.

Males are disappearing from the field of North American psychology - both as research subjects and as psychotherapists.
The evidence is overwhelming that psychological research is becoming heavily focused on girls' and women's issues, and that males are rapidly vanishing from psycho-therapeutic professions.

The consequences of these dual trajectories, say specialists, is that the distinct emotional struggles of boys and men are largely being sidelined and that many psychotherapists are lacking expertise in dealing effectively with males' psychological difficulties.

SINGING VOLCANO

For several months after Ecuador's Cotopaxi volcano erupted in August 2015, scientists recorded odd patterns of reverberating sound.

Ecuador's Cotopaxi volcano has a deep and distinct voice. Between late 2015 and early 2016, Cotopaxi repeated an unusual pattern of low-frequency sounds that researchers now say is linked to the unique geometry of the interior of its crater. Identifying the distinct "voiceprint" of various volcanoes could help scientists better anticipate changes within the craters, including those that foretell an eruption.

Ecuadoran scientists installed a network of specialized microphones on the volcano's flanks that can record very low frequency sounds, or infrasound. Two weeks after the volcano's August 2015 eruption, the network recorded the unusual sound pattern - a strong, clear oscillation that tapers off through time. The sound curve resembles a screw, or "tornillo" in Spanish, scientists report online June 13 in Geophysical Research Letters.

Researchers have found that 'Oumuamua - the first confirmed object to enter the solar system from interstellar space - was a comet, releasing just enough gas to subtly change its course.
In October 2017 the robotic telescope Pan-STARRS in Hawai'i detected an unusual object entering the solar system from interstellar space. In the days after the discovery, every available telescope, including Hubble, was aimed at the interloper to collect as much information as possible before it left our system. Since then, astronomers worldwide have been reviewing the observations, trying to squeeze as much knowledge as possible about the unexpected visitor.

Named 'Oumuamua ("first scout" or "first visitor" in Hawaiian), this envoy from the stars appeared to have the form of an elongated cigar - or a flattened pancake, depending whom you ask - 800 meters (0.5 mile) long and 10 times thinner. It came tumbling into the solar system from above the plane of the planets, only to have its path changed by the by the Sun's gravitational pull before leaving out system again, never to return.

Researchers from the National Research Nuclear University MEPhI's Institute of Cyber Intelligence Systems have recently developed a new learning model for the restricted Boltzmann machine (a neural network) which helps optimize the processes of semantic encoding, visualization and data recognition.

Today, deep neural networks with different architectures, such as convolutional, recurrent and autoencoder networks, are becoming an increasingly popular area of research. A number of high-tech companies, including Microsoft and Google, are using deep neural networks to design various intelligent systems. Together with deep neural networks, the term "deep" learning has gained currency.

In deep learning systems, the processes of feature selection and configuration are automated, which means that the networks can choose between the most effective algorithms for hierarchal feature extraction on their own. Deep learning is characterized by learning with the help of large samples using a single optimization algorithm. Typical optimization algorithms configure the parameters of all operations simultaneously and effectively estimate every neural network parameter's effect on error with the help of the so-called backpropagation method.

"The neural networks' ability to learn on their own is one of their most intriguing properties," explained Vladimir Golovko, Professor at the MEPhI Institute of Cyber Intelligence Systems. "Just like biological systems, neural networks can model themselves, seeking to develop the best possible model of behavior."

Over time, we've learned how to read the body language of horses - from understanding whether the movement of its ears, head, legs and tail mean its relaxed, anxious, angry or alert.

But it turns out horses are capable of pulling faces just like humans, too - which may shed more light on what they're feeling.

In fact, horses can make 17 facial movements - which is at least three more than our relatives, the chimpanzees, and just 10 less than humans.

In order to try and identify whether horses can pull more than just a long face, researchers at the University of Sussex in the United Kingdom created the Equine Facial Action Coding System (EquiFACS) to determine any discrete expressions made by horses.

By dissecting a horse's head and identifying its facial musculature, in addition to watching 15 hours of horse behavior in 86 horses ranging in breed and age, they were able to log any possible faces that the animals can make.