Advanced Keyless entry system for automobiles with personalization. which is using the biometric device as fingerprint. using Arduino programming all the …

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Broad Institute of MIT and Harvard is teaming up with Google Genomics to explore how to break down major technical barriers that increasingly hinder biomedical research by addressing the need for computing infrastructure to store and process enormous datasets, and by creating tools to analyze such data and unravel long-standing mysteries about human health.

As a first step, Broad Institute’s Genome Analysis Toolkit, or GATK, will be offered as a service on the Google Cloud Platform, as part of Google Genomics. The goal is to enable any genomic researcher to upload, store, and analyze data in a cloud-based environment that combines the Broad Institute’s best-in-class genomic analysis tools with the scale and computing power of Google.

GATK is a software package developed at the Broad Institute to analyze high-throughput genomic sequencing data. GATK offers a wide variety of analysis tools, with a primary focus on genetic variant discovery and genotyping as well as a strong emphasis on data quality assurance. Its robust architecture, powerful processing engine, and high-performance computing features make it capable of taking on projects of any size.

GATK is already available for download at no cost to academic and non-profit users. In addition, business users can license GATK from the Broad. To date, more than 20,000 users have processed genomic data using GATK.

The Google Genomics service will provide researchers with a powerful, additional way to use GATK. Researchers will be able to upload genetic data and run GATK-powered analyses on Google Cloud Platform, and may use GATK to analyze genetic data already available for research via Google Genomics. GATK as a service will make best-practice genomic analysis readily available to researchers who don’t have access to the dedicated compute infrastructure and engineering teams required for analyzing genomic data at scale. An initial alpha release of the GATK service will be made available to a limited set of users.

“Large-scale genomic information is accelerating scientific progress in cancer, diabetes, psychiatric disorders, and many other diseases,” said Eric Lander, President and Director of Broad Institute. “Storing, analyzing, and managing these data is becoming a critical challenge for biomedical researchers. We are excited to work with Google’s talented and experienced engineers to develop ways to empower researchers around the world by making it easier to access and use genomic information.”

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The list of paranoia-inducing threats to your computer’s security grows daily: Keyloggers, trojans, infected USB sticks, ransomware…and now the rogue falafel sandwich.

Researchers at Tel Aviv University and Israel’s Technion research institute have developed a new palm-sized device that can wirelessly steal data from a nearby laptop based on the radio waves leaked by its processor’s power use. Their spy bug, built for less than $300, is designed to allow anyone to “listen” to the accidental radio emanations of a computer’s electronics from 19 inches away and derive the user’s secret decryption keys, enabling the attacker to read their encrypted communications. And that device, described in a paper they’re presenting at the Workshop on Cryptographic Hardware and Embedded Systems in September, is both cheaper and more compact than similar attacks from the past—so small, in fact, that the Israeli researchers demonstrated it can fit inside a piece of pita bread.

“The result is that a computer that holds secrets can be readily tapped with such cheap and compact items without the user even knowing he or she is being monitored,” says Eran Tomer, a senior lecturer in computer science at Tel Aviv University. “We showed it’s not just possible, it’s easy to do with components you can find on eBay or even in your kitchen.”

Their key-stealing device, which they call the Portable Instrument for Trace Acquisition (yes, that spells PITA) consists of a loop of wire to act as an antenna, a Rikomagic controller chip, a Funcube software defined radio, and batteries. It can be configured to either collect its cache of stolen data on an SD storage card or to transmit it via Wifi to a remote eavesdropper. The idea to actually cloak the device in a pita—and name it as such—was a last minute addition, Tomer says. The researchers found a piece of the bread in their lab on the night before their deadline and discovered that all their electronics could fit inside it.

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More than 50 percent of academic papers published are owned by five major publishers.

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With a drop of blood, a new technology called VirScan can identify all of the viruses that a person has been exposed to over the course of their life.

Viral infections come and go countless times over our lives. Some, like mononucleosis, might knock you flat for weeks, while others never produce any symptoms at all. And some may impact your immune system in subtle ways for years after the infection.

Soon, it could be possible to get a full history of every viral infection you’ve ever had, using just a drop of blood. Researchers have developed a blood test that detects the remnants of more than 1,000 strains of 206 virus species. The test could someday help doctors diagnose current ailments and reveal more about how viruses impact our long-term health.

Currently, if doctors think you might have a viral infection, they test your blood for antibodies to that virus. Today’s blood tests can only test for a single virus at a time, and doctors have to know which virus they’re looking for, so they can look for a specific set of antibodies.

Now, researchers at the Howard Hughes Medical Institute say that their new technique, which they’ve dubbed VirScan, will allow doctors to scan a patient’s blood for antibodies to every known human virus at the same time. “This means that you can look at viral exposures in an unbiased way without having to suspect a particular infection ahead of time,” researcher Tomasz Kula told Discover. “Our approach could be useful for patients with undiagnosed diseases where it is unclear which viruses to test for.”

To build VirScan, lead author George J. Xu and his team essentially created a library of mock viruses. They used a common bacteria-eating virus called a bacteriophage as their starting material. Then they added DNA for external proteins called peptides to make the viruses look, to the immune system, like one of over 1,000 different human viruses.

When the researchers put the mock viruses into a drop of blood, the antibodies in that person’s blood would bind to the peptide of whichever virus he or she had previously been exposed to, either through infection or vaccination.

Xu and his colleagues tested VirScan on a group of 569 volunteers from Peru, South Africa, Thailand, and the U.S. Most people had antibodies in their blood for about ten different viruses, but some people had dozens. Two members of the study had antibodies to 84 different viruses, the researchers report today in Science.

In addition to diagnostics, VirScan could also help researchers understand the connection between viral infection and diseases, such as type 1 diabetes, asthma, and irritable bowel syndrome. The causes of these ailments aren’t completely understood but researchers believe they are linked to past infections. “We can look comprehensively for viral exposures that correlate with these kinds of diseases in a way that would be infeasible if you had to test for each virus separately,” said Kula. “We hope that VirScan can be used to generate new hypotheses about what role specific viral infections may play in complex diseases.”

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The mobile health industry has been revolutionizing the way both doctors and patients approach medicine today. When it comes to addressing health issues, mobile health consumers are moving toward preventing disease and increasing fitness and wellness. Through fitness trackers and wearable devices, more patients are now focused on exercise and diet.

The company Research Now conducted a survey that looked at how mobile health applications and the mobile health industry is affecting patient care and physician workflow. Research Now polled a total of 1,000 mHealth app users and 500 medical professionals. The results show that 86 percent of healthcare professionals believe mobile health apps increase their knowledge on a patient’s medical condition.

Additionally, nearly half of surveyed providers – 46 percent – felt that mHealth apps actually strengthen their relationship with their patients. Three out of four polled medical care professionals – 76 percent – have suggested that mobile health tools assist patients with managing chronic medical conditions.

Additionally, three out of five surveyed physicians and medical staff help patients who are at high risk of developing serious health problems. As previously stated, fitness trackers can help patients exercise more regularly and lose weight, which would reduce their risk of heart disease.

Additionally, more than half of those surveyed believe that mHealth applications can help consumers who are healthy remain at an optimal level of health. Also, nearly half – 48 percent – of survey takers think that the technologies within the mobile health industry may be able to help patients who were recently discharged from a hospital make a better transition to home-based care.

Most importantly, nearly all survey takers – 96 percent – believe that mobile health apps “improve their quality of life.” In addition, the survey illustrates that users of mHealth tools already improve their wellness and lifestyle through these technologies. For example, 60 percent use the tools to monitor their workouts while nearly half – 49 percent – use apps to record their calorie intake.

more at : http://mhealthintelligence.com/news/96-of-consumers-say-mobile-health-industry-improves-life

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Sentient claims to have assembled machine-learning muscle to rival Google by rounding up idle computers.

Recent improvements in speech and image recognition have come as companies such as Google build bigger, more powerful systems of computers to run machine-learning software. Now a relative minnow, a private company called Sentient with only about 70 employees, says it can cheaply assemble even larger computing systems to power artificial-intelligence software. The company’s approach may not be suited to all types of machine learning, a technology that has uses as varied as facial recognition and financial trading. Sentient has not published details, but says it has shown that it can put together enough computing power to produce significant results in some cases.

Sentient’s power comes from linking up hundreds of thousands of computers over the Internet to work together as if they were a single machine. The company won’t say exactly where all the machines it taps into are. But many are idle inside data centers, the warehouse-like facilities that power Internet services such as websites and mobile apps, says Babak Hodjat, cofounder and chief scientist at Sentient. The company pays a data-center operator to make use of its spare machines.

Data centers often have significant numbers of idle machines because they are built to handle surges in demand, such as a rush of sales on Black Friday. Sentient has created software that connects machines in different places over the Internet and puts them to work running machine-learning software as if they were one very powerful computer. That software is designed to keep data encrypted as much as possible so that what Sentient is working on–perhaps for a client–is kept confidential.

Sentient can get up to one million processor cores working together on the same problem for months at a time, says Adam Beberg, principal architect for distributed computing at the company. Google’s biggest machine-learning systems don’t reach that scale, he says. A Google spokesman declined to share details of the company’s infrastructure and noted that results obtained using machine learning are more important than the scale of the computer system behind it. Google uses machine learning widely, in areas such as search, speech recognition and ad targeting.

Beberg helped pioneer the idea of linking up computers in different places to work together on a problem (see “Innovators Under 35: 1999”). He was a founder of Distributed.net, a project that was one of the first to demonstrate that idea at large scale. Its technology led to efforts such as Seti@Home andFolding@Home, in which millions of people installed software so their PCs could help search for alien life or contribute to molecular biology research.

Sentient was founded in 2007 and has received over $140 million in investment funding, with just over $100 million of that received late last year. The company has so far focused on using its technology to power a machine-learning technique known as evolutionary algorithms. That involves “breeding” a solution to a problem from an initial population of many slightly different algorithms. The best performers of the first generation are used to form the basis of the next, and over successive generations the solutions get better and better.

Sentient currently earns some revenue from operating financial-trading algorithms created by running its evolutionary process for months at a time on hundreds of thousands of processors. But the company now plans to use its infrastructure to offer services targeted at industries such as health care or online commerce, says Hodjat.

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Source: www.ncbi.nlm.nih.gov

The genetically modified virus could stop the progression of melanoma.

Source: health.usnews.com

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A newly created “can opener” molecule is capable of opening HIV and allowing the body’s own immune system to kill the infection.

Source: www.medicaldaily.com

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