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According to researchers, dogs are more capable of understanding situations from a human’s point of view than has previously been recognized.

They found dogs were four times more likely to steal food they had been forbidden, when lights were turned off so humans in the room could not see.

This suggested the dogs were able to alter their behavior when they knew their owners’ perspective had changed.

The study, published in Animal Cognition, conducted tests on 84 dogs.

The experiments had been trying to find whether dogs could adapt their behavior in response to the changed circumstances of their human owners.

It wanted to see if dogs had a “flexible understanding” that could show they understood the viewpoint of a human.

It found that when the lights were turned off, dogs in a room with their human owners were much more likely to disobey and steal forbidden food.

The study says it is “unlikely that the dogs simply forgot that the human was in the room” when there was no light. Instead it seems as though the dogs were able to differentiate between when the human was unable or able to see them.

The experiments had been designed with enough variations to avoid false associations – such as dogs beginning to associate sudden darkness with someone giving them food, researchers said.

According to researchers, dogs are more capable of understanding situations from a human's point of view than has previously been recognized

According to researchers, dogs are more capable of understanding situations from a human’s point of view than has previously been recognized

Dr. Juliane Kaminski, from the University of Portsmouth’s psychology department, said the study was “incredible because it implies dogs understand the human can’t see them, meaning they might understand the human perspective”.

This could also be important in understanding the capacities of dogs that have to interact closely with humans, such as guide dogs for the blind and sniffer dogs.

Previous studies have suggested that although humans might think that they can recognize different expressions on their dogs’ faces, this is often inaccurate and a projection of human emotions.

“Humans constantly attribute certain qualities and emotions to other living things. We know that our own dog is clever or sensitive, but that’s us thinking, not them,” said Dr. Juliane Kaminski.

“These results suggest humans might be right, where dogs are concerned, but we still can’t be completely sure if the results mean dogs have a truly flexible understanding of the mind and others’ minds. It has always been assumed only humans had this ability.”

A new mobile phone app made by a team from the University of Portsmouth’s School of Computing, UK, will prepare users for receiving good or bad news on their phones, say researchers.

The app distinguishes good messages from bad and neutral ones, and color codes them accordingly.

Users may choose not to open negative messages if they are already having a stressful day.

But some experts think that ignoring such messages may also be stressful.

For now, the app has been tested on phones running Android OS, and the results of the study will be presented at the 16th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems in Spain in September.

The app automatically color codes incoming messages, making them green for positive, red for negative and blue for neutral.

This way, a user can see before opening a message whether it is likely to be worrying or not.

The app automatically color codes incoming messages, making them green for positive, red for negative and blue for neutral

The app automatically color codes incoming messages, making them green for positive, red for negative and blue for neutral

“The application works by learning from past messages how the user perceives the content as being positive, negative or objective,” said lead researcher Dr. Mohamed Gaber.

“The ultimate objective… is to make the user aware of the negative contents they receive so they are able to manage their stress in the best possible way.

“For example, if most of what is received from social media websites by a user on a particular day was negative, it is important that the user attempts to take an action in order to not get stressed, especially if this may affect the individual’s performance at work and/or their behavior at home.”

The scientist added that the app comes “pre-trained”, but users are able to self-label any incoming text message to personalize it – as some messages may be perceived in a different way by different users.

But Pamela Briggs, a psychologist from the British Psychological Society, thinks the main question is whether or not a user can trust that the app will indeed interpret the information correctly.

“Researchers are increasingly able to use various kinds of linguistic analysis to determine message content, and so it is reasonable to assume that some kind of color coding is viable in this context,” said Dr. Pamela Briggs.

“But the bigger question is whether or not such an app will genuinely let us manage stress more effectively.

“Imagine that you get a ‘bad’ message from a boss, husband or friend – the researchers suggest that you might want to put this to one side, to open at a more appropriate moment, but stress is often made worse by the anticipation of an unpleasant event and actually dissipated once you tackle the problem directly.

“The app seems to do the job of a traditional mail envelope – this message is a tax bill, that message is a card from a friend – but taken to an electronic extreme.

“What if we decide to delete the ‘bad’ message, rather than to read it – and then spend several days worrying about it. I’d like to see some behavioral research on the stress claims made by the authors, before we can assume that it might make our lives easier.”

The scientists say they were inspired by previous research in the area, in particular by a system called SentiCorr, developed by a team from the Eindhoven University of Technology in the Netherlands.

This is a system “for automated sentiment analysis on multilingual user generated content from various social media and e-mails”, as described in the research paper.

It also uses color coding for positive, negative or neutral content.

“Our system is aimed at helping individual users become more aware of the sentiment in their correspondence,” states the paper.