MOLECULES LEFT ON CELLPHONE CAN REVEAL YOUR LIFESTYLE
The apps we use on our cellphones can tell a lot about us, but researchers now say the molecules on the outside of our phones can also reveal a lot about our lifestyles.
A study from the University of California, San Diego (UCSD) has determined that microbes left behind on everyday objects can be collected and analyzed to create a lifestyle sketch of the user of the object.
“All of these chemical traces on our bodies can transfer to objects,” said senior author Pieter Dorrestein, Ph.D., UCSD. “So we realized we could probably come up with a profile of a person’s lifestyle based on chemistries we can detect on objects they frequently use.”
Researchers took swabs from cellphones and were able to determine “diet, preferred hygiene products, health status and locations visited.”
Microbes from foods, cosmetics, medications and other everyday items can help create a personalized lifestyle “readout.”
The readouts provide a general lifestyle profile, not one-to-one matches like DNA or fingerprints.
Scientists believe that the study can be useful for criminal investigations in crime scenes that don’t have DNA or fingerprint evidence, and for medical and environmental studies.
In hopes of improving its finances following the disappointing performance of the LG G5 in the market, the South Korea tech company is rumored to be securing an iris scanner and its own mobile payment feature for the upcoming G6.
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The LG G6 is the next flagship smartphone that is coming from the South Korea tech company after the successful launch of its high-end, dual-display handset, the LG V20, this fall. If recent rumors are to be believed, it appears that the upcoming LG G5 successor is going to launch with an iris scanner and LG’s own mobile payment platform.
Over the weekend, SlashGear learned that reports from LG’s home country are claiming that the G6 is coming at an opportune time to snatch the crown from Samsung by debuting with an advanced iris scanner. Apparently, though Samsung clearly made a good impression by launching the Galaxy Note 7 that featured an iris-recognizing biometrics system, the discontinuation of the hardware meant a huge disadvantage on Samsung’s part. LG is already making a technology that combines the camera sensor and iris scanner. Once done, the feature is expected to be one of the main selling points of the G6.
Aside from the iris scanner, the LG G6 is also rumored to launch with the LG Pay, the company’s answer to Samsung Pay. According to The Korea Herald, LG’s mobile payment platform will make use of Magnetic Secure Transmission or MST solution so that mobile payment is done easily with just a touch of the smartphone to magnetic card readers in retail stores.
Previously, LG was rumored to be working on a programmable White Card for LG Pay, but with this new revelation, it seems that the company is going for a different direction. Perhaps LG has now realized how MST is more convenient than what it had in mind since the former would ensure that LG Pay would work with both NFC-based terminals and traditional swipe-based kiosks.
Another feature that is likely to come with the G6 is a removable battery. As per PhoneArena, to avoid possible “safety and yield” issues, LG could be using a removable battery pack for its upcoming flagship device.
It is important to note at this point that these features came from speculations of South Korean media. LG has declined to comment on these speculations, so everything should be treated with a grain of salt until the company confirms any or all of them.
Work on dog intelligence by Stanley Coren, a UBC professor emeritus of psychology, was featured in a Global story about the complexity of a dog’s memory.
According to Coren, the top three smartest dog breeds are border collies, poodles, and German shepherds.
New neural-network algorithm learns directly from human instructions instead of examples
November 27, 2016
Conventional neural-network image-recognition algorithm trained to recognize human hair (left), compared to the more precise heuristically trained algorithm (right) (credit: Wenzhangzhi Guo and Parham Aarabi/IEEE Trans NN & LS)
A new machine learning algorithm designed by University of Toronto researchers Parham Aarabi and Wenzhi Guo learns directly from human instructions, rather than an existing set of examples, as in traditional neural networks. In tests, it outperformed existing neural networks by 160 per cent.
Their “heuristically trained neural networks” (HNN) algorithm also outperformed its own training by nine per cent — it learned to recognize hair in pictures with greater reliability than that enabled by the training.
Aarabi and Guo trained their HNN algorithm to identify people’s hair in photographs, a challenging task for computers. “Our algorithm learned to correctly classify difficult, borderline cases — distinguishing the texture of hair versus the texture of the background,” says Aarabi. “What we saw was like a teacher instructing a child, and the child learning beyond what the teacher taught her initially.”
Heuristic training
Humans conventionally “teach” neural networks by providing a set of labeled data and asking the neural network to make decisions based on the samples it’s seen. For example, you could train a neural network to identify sky in a photograph by showing it hundreds of pictures with the sky labeled.
With HNN, humans provide direct instructions that are used to pre-classify training samples rather than a set of fixed examples. Trainers program the algorithm with guidelines such as “Sky is likely to be varying shades of blue,” and “Pixels near the top of the image are more likely to be sky than pixels at the bottom.”
Their work is published in the journal IEEE Transactions on Neural Networks and Learning Systems.
This heuristic-training approach addresses one of the biggest challenges for neural networks: making correct classifications of previously unknown or unlabeled data, the researchers say. This is crucial for applying machine learning to new situations, such as correctly identifying cancerous tissues for medical diagnostics, or classifying all the objects surrounding and approaching a self-driving car.
“Applying heuristic training to hair segmentation is just a start,” says Guo. “We’re keen to apply our method to other fields and a range of applications, from medicine to transportation.”
Abstract of Hair Segmentation Using Heuristically-Trained Neural Networks
We present a method for binary classification using neural networks (NNs) that performs training and classification on the same data using the help of a pretraining heuristic classifier. The heuristic classifier is initially used to segment data into three clusters of high-confidence positives, high-confidence negatives, and low-confidence sets. The high-confidence sets are used to train an NN, which is then used to classify the low-confidence set. Applying this method to the binary classification of hair versus nonhair patches, we obtain a 2.2% performance increase using the heuristically trained NN over the current state-of-the-art hair segmentation method.
Tobacco smoking as the number one avoidable cause of death in the world. Photo / Getty
A middle-aged cigarette smoker who has smoked for decades is two to three times more likely to die early than someone similar who has never smoked. Tobacco smoking is well known to be a major risk factor for various cancers, lung and cardiovascular problems, and is also linked to other health problems, such as complications in pregnancy, low sperm count in men, oral problems, and increased likelihood of cataracts.
Little wonder then that the World Health Organisation (WHO) sees tobacco smoking as the number one avoidable cause of death in the world. US statistics reveal that smoking causes more deaths each year than HIV, illegal drug use, alcohol misuse, motor vehicle injuries and homicides combined. Similar comparisons can be found in UK statistics.
However, while there can be few today who are unaware of the toll smoking takes on the body, the effects of long-term tobacco smoking on other areas such as learning and memory are less well known.
Although some studies have shown that the nicotine in cigarettes can improve concentration and attention(making smokers feel more alert), there’s more to cigarettes than just nicotine. They contain over 4,000 chemicals – over 50 of which are known to be toxic in nature: the carbon monoxide also found in car exhaust fumes, butane found in lighter fluid, and arsenic, ammonia, and methanol found in rocket fuel, for example.
It’s thought that a long-term build-up of these toxic chemicals can damage the brain, leading to deficits in learning and memory. Long-term smoking has been linked with reductions in working memory, prospective memory – that used for everyday tasks such as keeping an appointment or taking medication on time – and executive function, which helps us plan tasks, pay attention to current activities, and ignore distractions. These three underpin our everyday ability to remember and learn, without which independent living would be much more difficult.
In the first study of its kind, our team of researchers from Northumbria University reported in the journal Frontiers in Psychiatry our findings that those who smoke and drink heavily show greater deficits in their everyday prospective memory. More so, in fact, than those who smoke but do not drink heavily and those who drink heavily but do not smoke combined. This suggests there’s a “double whammy” effect to combining smoking and drinking.
Recent studies of smoking-related health problems and memory deficits has included the effects of “second-hand” or “passive” smoking, where non-smokers inhale tobacco smoke from smokers. Research here has found the same range of health-related problems linked to passive smoking as found in smokers, including lung and cardiovascular disease and cognitive and memory problems. These could affect a passive smoker in a number of spheres of life, not just health but educational and occupational, given the universal requirement and use for everyday remembering.
Quitting smoking improves health and leads to improvements in cognition. This may be linked to an increase in the thickness of the brain’s cortex – the outer layer of the brain which plays a critical role in information processing and memory. The cortex naturally thins with age, but smoking can worsen this effect causing the cortex to thin at an accelerated rate.
Stopping smoking can help partially to reverse this effect on the cortex, but not to the levels found in a non-smoker. Traditional methods of quitting smoking have focused on nicotine replacement therapy (NRT), such as nicotine chewing gum, patches, inhalators and nasal sprays. This typically takes around eight to 12 weeks before producing demonstrable health improvements.
An increasingly popular form of NRT is the e-cigarette: a battery-powered electronic nicotine delivery device resembling a cigarette that does not contain tobacco. The use of e-cigarettes over smoking tobacco recently has been found to improve everyday prospective memory (memory for future activities), but we presently know little about what long-term impact e-cigarettes may have upon health, mood and cognitive functions.
GROUNDBREAKING STUDY DISCOVERS OVER 1,400 NEW VIRUSES
Humans are surrounded by numerous viruses but fortunately most of them do not transmit diseases
Sequencing the samples directly taken from invertebrates, researchers have uncovered a trove of new viruses. Researchers have found that humans are surrounded by numerous viruses, which stem from insects, worms and spiders living in and around our houses. However, most of them do not cause diseases.
“This groundbreaking study re-writes the virology text book by showing that invertebrates carry an extraordinary number of viruses – far more than we ever thought.” Professor Edward Holmes, one of the Australian researchers involved in the study said.
For the study, researchers extracted the RNA samples from over 220 land and sea invertebrates living in China. The metagenomics revealed that those invertebrates were home to 1,455 new viruses, including several new families.
The findings not only expand the number of known viruses but also indicate that these viruses have existed for billions of years. Previously, it was thought that these microorganisms have been around not more than millions of years and there source of origin was also not confirmed.
“It is remarkable that invertebrate like insects carry so many very viruses – no one had thought to look before because most of them had not been associated with human borne illnesses.” Holmes said.
Though most of the invertebrates or animals lacking backbone do not generally spread diseases but there are still many infects like mosquitoes or ticks that can transmit potentially harmful viruses in humans like dengue, zika and Lyme disease.
“We have discovered that most groups of viruses that infect vertebrates – including humans, such as those that cause well-known diseases like influenza – are in fact derived from those present in invertebrates.” Holmes said
The identification of new viruses was not straightforward but advanced sequencing techniques made it possible to expand the catalogue of viruses. The technology can also works as a powerful tool to determine what pathogens cause human diseases.
“Our study utilized new techniques in meta-genomics, which we are also using to provide insights into the causes of human-borne diseases,” said Holmes.
“The new, expensive technologies available to researchers which have allowed us to do this landmark project, provide the ultimate diagnostic tool.”
The pioneering study is a collaborative effort between University of Sydney and the Chinese Centre for Disease Control and Prevention in Beijing.
Over the last decade or so, battery technology has improved massively. While those lithium cells have enabledthin, powerful smartphones and quadcopters, [patrick] thought it would be a good idea to do something a littlesimpler. He built a USB power bank with an 18650 cell. While it would be easier to simply buy a USB power bank,that’s not really the point, is it?
This project is the follow-up to one of [patrick]’s earlier projects, a battery backup for the Raspberry Pi. This earlierproject used an 14500 cell and an MSP430 microcontroller to shut the Pi down gracefully when the battery wasnearing depletion.
While the original project worked well with the low power consumption Pi Model A and Pi Zero, it struggled withUPS duties on the higher power Pi 3. [patrick] upgraded the cell and changed the electronics to provide enoughcurrent to keep a high-power Pi on even at 100% CPU load.
The end result is a USB power bank that’s able to keep a Raspberry Pi alive for a few hours and stays relativelycool.
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