Day: August 29, 2018

Why synthetic marijuana is so risky

File 20180828 86153 12l36j6’When you open a packet of a synthetic cannabinoid like K2 or Spice and pour the dried vegetation into your hand, it looks like marijuana. These dried leaves and stems can be inert or come from psychoactive plants like Wild Dagga. Some of these plants are contaminated with heavy metals, pesticides, mold or salmonella.

However, synthetic cannabinoids are anything but natural. They are mass-produced overseas and then shipped in bulk to the U.S., where they are dissolved and then mixed with dried vegetation, which absorbs the liquid. This process is very imprecise, so the dose in one packet can differ greatly within or between batches.

There are several hundred synthetic cannabinoids in existence, and they all stimulate cannabinoid type 1 receptors (CB1), just like the active component in natural marijuana, THC, that provides the high. But they do so with different intensities and for differing periods of time. Some incorporate the central ring structure of the THC molecule before laboratory modification, but many others do not. More problems arise because some of the synthetic cannabinoids stimulate non-cannabinoid receptors and can cause unanticipated effects as well. There is no way to know which synthetic cannabinoids are actually in the product you purchased.

The molecular structure of THC, the active component of marijuana. Many chemists producing synthetic cannabinoids in the lab use the three hexagonal rings as the scaffold to generate new molecules that produce a similar high. Lifestyle discover/Shutterstock.com Natural marijuana does not comprise only THC. The other constituents in natural marijuana such as cannabidiol actually help to temper the negative impact of THC but are absent in synthetic cannabinoids. In addition to these myriad risks, there is also a risk that synthetic cannabinoids can be adulterated with other chemicals, ranging from opioids to rat poison.…’

Via The Conversation

Detecting ‘deepfake’ videos in the blink of an eye

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’A new form of misinformation is poised to spread through online communities as the 2018 midterm election campaigns heat up. Called “deepfakes” after the pseudonymous online account that popularized the technique – which may have chosen its name because the process uses a technical method called “deep learning” – these fake videos look very realistic.

So far, people have used deepfake videos in pornography and satire to make it appear that famous people are doing things they wouldn’t normally. But it’s almost certain deepfakes will appear during the campaign season, purporting to depict candidates saying things or going places the real candidate wouldn’t.

Because these techniques are so new, people are
having trouble telling the difference between real videos and the deepfake videos. My work, with my colleague Ming-Ching Chang and our Ph.D. student Yuezun Li, has found a way to reliably tell real videos from deepfake videos. It’s not a permanent solution, because technology will improve. But it’s a start, and offers hope that computers will be able to help people tell truth from fiction.…

When a deepfake algorithm is trained on face images of a person, it’s dependent on the photos that are available on the internet that can be used as training data. Even for people who are photographed often, few images are available online showing their eyes closed. Not only are photos like that rare – because people’s eyes are open most of the time – but photographers don’t usually publish images where the main subjects’ eyes are shut.

Without training images of people blinking, deepfake algorithms are less likely to create faces that blink normally. When we calculate the overall rate of blinking, and compares that with the natural range, we found that characters in deepfake videos blink a lot less frequent in comparison with real people. Our research uses machine learning to examine eye opening and closing in videos…’

Via The Conversation