Android Deals – Nov 26th, 2014: LG G Watch, HTC One M8, Moto X and More!

Published on November 26, 2014 by

Everyday, there are a ton of new products on sale. It’s our job to not just bring you all the news in the Android world, but to give you heads up on some killer deals. And that’s exactly what we do everyday with our Android Deals post. Below we have products sorted into five categories, Smartphones, Tablets, Accessories, Smartwatches and Other Tech. Under other tech you’ll find stuff that we don’t usually cover, but the deal was too good to pass up. So enjoy!





Other Tech

Rita Crook Benedict Cumberbatch Can Charm Humans, but Can He Fool a Computer?

The Imitation Game, a movie portraying Alan Turing’s life (who would have celebrated his 100thbirthday on Mathematica‘s 23rd birthday—read our blog post), was released this week, which we’ve been looking forward to. Turing machines were one of the focal points of the movie, and we launched a prize in 2007 to determine whether the 2,3 Turing machine was universal.

So of course, Cumberbatch’s promotional video where he impersonates other beloved actors reached us as well, which got me wondering, could Mathematica‘s machine learning capabilities recognize his voice, or could he fool a computer too?

I personally can’t stop myself from chuckling uncontrollably while watching his impressions, however, I wanted to look beyond the entertainment factor.

So I started wondering: Is he actually good at doing these impressions? Or are we all just charmed by his persona?

Is my psyche just being fooled by the meta-language, perhaps? If we take the data of pure voices, does he actually cut the mustard in matching these?

In order to determine the answer, 10 years ago we would have needed to stroll the streets and play audio snippets to 300 people from the James Bond movies, The Shining, Batman, and Cumberbatch’s impression snippets—then survey whether those people were fooled.

But no need, if you have your Mathematica handy!

With Mathematica‘s machine learning capabilities, it’s possible to classify sample voice snippets easily, which means we can determine whether Benedict’s impressions would be able to fool a computer. So I set myself the challenge of building a decent enough database of voice samples, plus I took snippets from each of Benedict’s impression attempts, and I let Mathematica do its magic.

We built a path to each person’s snippet database, which Mathematica exported for analysis:

Classify sample voice snippets

We imported all of the real voices:

Import real voices

The classifier was trained simply by providing the associated real voices to Classify; in the interest of speed, a pre-trained ClassifierFunction was loaded from cfActorWDX.wdx:

Classifier was trained simply by providing the associated real voices to Classify

My audio database needed to include snippets of Benedict’s own voice, snippets of the impersonated actors’ own voices, and the impressions from Cumberbatch. The sources for the training were the following: Alan Rickman, Christopher Walken, Jack Nicholson, John Malkovich,Michael Caine, Owen Wilson, Sean Connery, Tom Hiddleston, and Benedict Cumberbatch. I used a total of 560 snippets, but of course, the more data used, the more reliable the results. The snippets needed to be as “clean” as possible (no laughter, music, chatter, etc. in the background).

These all needed to be exactly the same length (3.00 seconds), and we made sure all snippets were the same length by using this function in the Wolfram Language:

Making sure snippets are all same length

Some weren’t single-channel audio files, so we needed to exclude this factor as an additional feature to optimize our results during the export stage:

Excluding single-channel audio files

Thanks go to Martin Hadley and Jon McLoone for the code.

Drum-roll… time for the verdict!

I have to break everyone’s heart now, and I’m not sure I want to be the one to do it… so I will “blame” Mathematica, because machine learning could indeed mostly tell the difference between the actors’ real voices and the impressions (bar two).

As the results below reveal, Mathematica provides 97–100% confidence on the impressions tested:

Mathematica provides 97-100% confidence on the impressions tested

For most impressions, there is a very small reported probability of any classification other than Benedict Cumberbatch or Alan Rickman.



It might be worth noting that Rickman, Connery, and Wilson all have a slow rhythm to their speech, with many pauses (especially noticeable in the snippets I used), which could have confused the algorithm.

Sad Benedict Cumberbatch

Now it’s time to be grown up about this, and not hold it against Benedict. He is still a beloved charmer, after all.

My admiration for him lives on, and I look forward to seeing him in The Imitation Game!

Does virtual reality space you out?

Put rats in an IMAX-like surround virtual world limited to vision only, and the neurons in their hippocampi* seem to fire completely randomly — and more than half of those neurons shut down — as if the neurons had no idea where the rat was, UCLA neurophysicists found in a recent experiment.

Put another group of rats in a real room (with sounds and odors) designed to look like the virtual room, and they were just fine.

“Since so many people are using virtual reality, it is important to understand why there are such big differences,” said Mayank Mehta, a UCLA professor of physics, neurology and neurobiology in the UCLA College and the study’s senior author.

When hippocampus neurons lose rhythm

When people walk or try to remember something, the activity in the hippocampus becomes very rhythmic and these complex, rhythmic patterns appear, Mehta said. Those rhythms facilitate the formation of memories and our ability to recall them. Mehta hypothesizes that in some people with learning and memory disorders, these rhythms are impaired.

The mechanisms by which the brain makes those cognitive maps remains a mystery, but neuroscientists have surmised that the hippocampus computes distances between the subject and surrounding landmarks, such as buildings and mountains. But in a real maze, other cues, such as smells and sounds, can also help the brain determine spaces and distances.

“Neurons involved in memory interact with other parts of the hippocampus like an orchestra,” Mehta said. “It’s not enough for every violinist and every trumpet player to play their music flawlessly. They also have to be perfectly synchronized.”

Mehta believes that by retuning and synchronizing these rhythms, doctors will be able to repair damaged memory, but said doing so remains a huge challenge.

The study was published in the journal Nature Neuroscience. The research was funded by the W.M. Keck Foundation and the National Institutes of Health.

* The hippocampus is a brain region (on both sides of the brain) involved in spatial learning and constructing and using mental maps.

Wireless electronic implants deliver antibiotic, then harmlessly dissolve

November 25, 2014

Imagine an electronic implant that delivers a drug when triggered by a remote wireless signal — then harmlessly dissolves (no post-surgical infection concerns, no fuss, no muss) within minutes or weeks.

That’s what researchers at Tufts University and the University of Illinois at Champaign-Urbana have demonstrated* in mice, using a resistor (as a source of heat for releasing drug and help dissolving the implant) and a power-receiving coil made of magnesium deposited onto a silk protein”pocket” that also protects the electronics and controls its dissolution time.


There have been other implantable medical devices, but they typically use non-degradable materials that have limited operational lifetimes and must eventually be removed or replaced — requiring more surgery.

The research was published online in the Proceedings of the National Academy of Sciences Early Edition the week of November 24–28, 2014. and was supported by the National Institutes of Health and the National Science Foundation.

* Devices were implanted in vivo in S. aureus-infected tissue and activated by a wireless transmitter for two sets of 10-minute heat treatments. Tissue collected from the mice 24 hours after treatment showed no sign of infection, and surrounding tissues were found to be normal. Devices completely dissolved after 15 days, and magnesium levels at the implant site and surrounding areas were comparable to levels typically found in the body. The researchers also conducted in vitro experiments in which similar remotely controlled devices released the antibiotic ampicillin to kill E. coli and S. aureus bacteria. The wireless activation of the devices was found to enhance antibiotic release without reducing antibiotic activity.

Disruptive sounds help aging brain ignore distractions

November 26, 2014

As we age, we have an increasingly harder time ignoring distractions. But by learning to make discriminations of a sound amidst progressively more disruptive distractions, we can diminish our distractibility, new research in Cell Press journalNeuron reveals.

A similar strategy might also help children with attention deficits or individuals with other mental challenges.

Distractibility (the inability to sustain focus on a goal due to attention to irrelevant stimuli) can have a negative effect on basic daily activities, and is a hallmark of the aging mind.

Where were we? Oh, right, the research. To address the problem, a team led by researchers at the University of California, San Francisco used sounds at various frequencies as targets along with distractors, with the goal of having trainees focus on the target frequencies while ignoring the distractor frequencies.

The training

In both aged rats and older humans, trainees learned to identify the target tone in each training session through reinforcement feedback, and then they had to continue to correctly identify that target tone amidst progressively more challenging distractor frequencies. In both rats and humans, training led to diminished distraction-related errors, and trainees’ memory and attention spans improved. Also, electrophysiological brain recordings in both rats and humans revealed that neural responses to distractors were reduced.

“We show that by learning to discriminate amidst progressively more challenging distractions, we can diminish distractibility in rat and human brains,” says lead author Dr. Jyoti Mishra.

The approach could also be modified to help individuals struggling with a variety of distractions. “This same training could be generalized to more complex stimuli and across sensory modalities — such as auditory, visual, and tactile — to broadly benefit distractor processing in diverse impaired populations needing such training,” says senior author Dr. Adam Gazzaley.

In addition to highlighting the therapeutic potential of this type of brain training to improve our ability to focus with age, it also shows that even in the aged adult, the brain is responsive to learning-based approaches that can improve cognition.

Congrats if you read this without any distractions. …

New targeted, noninvasive treatments for mental illness to combine TMS and ultrasound

November 26, 2014

A new interdisciplinary Stanford University initiative called NeuroCircuit aims to find the specific brain circuits that are responsible for mental-health conditions and then develop ways of noninvasively stimulate those circuits to potentially lead to improved treatments for depression, anxiety, and post-traumatic stress disorder.

“You see things activated in brain images but you can’t tell just by watching what is cause and what is effect,” said Amit Etkin, Neurocircuit co-leader and a Stanford assistant professor of psychiatry and behavioral sciences. “Right now, if a patient with a mental illness goes to see their doctor they would likely be given a medication that goes all over the brain and body. While medications can work well, they do so for only a portion of people and often only partially.”

Etkin has been working with transcranial magnetic stimulation (TMS) to map and remotely stimulate parts of the brain. A TMS device generates a strong magnetic field that stimulates brain circuits near the surface. TMS is currently used as a way of treating depression and anxiety, but Etkin said the brain regions being targeted are the ones available to TMS, not necessarily the ones most likely to treat a person’s condition. They are also not personalized for the individual.

The solution may involve combining TMS with ultrasound. In his lab, Baccus has been using ultrasound to stimulate nerve cells of the retina to develop a prosthetic retina. Other members of the team are modifying existing ultrasound technology to direct it deep within the brain at a safe frequency. If the team is successful, ultrasound could be a more targeted and focused tool than TMS for remotely stimulating circuits that underlie mental health conditions.

Baccus said that before merging with Etkin’s team they had been focusing on the technology without specific brain diseases in mind. “This merger really gives a target and a focus to the technology.”

The initiative is part of the Stanford Neurosciences Institute‘s Big Ideas, which bring together teams of researchers from across disciplines to solve major problems in neuroscience and society.

Stanford University/Kurt Hickman | Researchers hope to find the brain circuits that are responsible for mental
health conditions, develop ways to remotely stimulate those circuits, and potentially treat those conditions.

Chemicals in sunscreen, aftershave may affect male fertility