Lifeboat Foundation: Safeguarding Humanity
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Category: biotech/medical – Page 1,165

The number of vulnerability disclosures impacting extended internet of things (XIoT) devices increased by 57% in the first half of 2022 compared to the previous six months, according to a new report by Team82, the research team of cyber-physical systems (CPS) security firm Claroty.

The research also found that vendor self-disclosures increased by 69%. This would be a first for the industry, which usually relies more for disclosures on independent research teams. According to Team82, the trend indicates that more operational technology (OT), IoT, and internet of medical things (IoMT) vendors are establishing vulnerability disclosure programs and dedicating more resources to them.

Additionally, fully or partially remediated firmware vulnerabilities increased by 79% over the same time period, a significant improvement considering the relative challenges in patching firmware versus software vulnerabilities.

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Talking about some of the ideas and philosophy surrounding life extension technologies. Our own psychology and coping mechanisms that view death as a good thing. The same way we used to see some diseases as a part of a gods plan. As soon as we cured these diseases, somehow they were not a part of gods plan anymore. The same will happen with aging and death, and that is just a matter of time. Picking apart some of the ways of thinking that suggest a longer life would be a boring or bad thing. We live for all of the pleasant and amazing experiences that we can have in the world, what else could possibly matter more. The end and absence of meaning (death) does not give life meaning. It is life that gives life meaning.

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“I believe we can train the algorithm not only to picture accurately a face you’re looking at, but also any face you imagine vividly, such as your mother’s,” explains Dado.

“By developing this technology, it would be fascinating to decode and recreate subjective experiences, perhaps even your dreams,” Dado says. “Such technological knowledge could also be incorporated into clinical applications such as communicating with patients who are locked within deep comas.”

Dado’s work is focused on using the technology to help restore vision in people who, through disease or accident, have become blind, reports the Mail Online.

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The success of COVID-19 vaccines is a great example of gene medicine’s tremendous potential to prevent viral infections. One reason for the vaccines’ success is their use of lipid nanoparticles, or LNPs, to carry delicate messenger RNA to cells to generate and boost immunity. LNPs—tiny fat particles—have become increasingly popular as a carrier to deliver various gene-based medicines to cells, but their use is complicated because each LNP must be tailored specifically for the therapeutic payload it carries.

A team led by Hai-Quan Mao, a Johns Hopkins materials scientist, has created a platform that shows promise to speed up the LNP design process and make it more affordable. The new approach also can be adapted to other gene therapies.

“In a nutshell, what we have done is creating a method that screens lipid nanoparticle components and their proportions to quickly help identify and create the optimal design for use with various therapeutic ,” said Mao, director of the Institute for NanoBioTechnology at Johns Hopkins Whiting School of Engineering and professor in the departments of Materials Science and Engineering and Biomedical Engineering.

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The lead in some bullets used for hunting deer, moose, and elk is toxic to the humans who eat the harvested meat and to scavenger animals that feast on remains left in the field.

A team of researchers from the Canadian Light Source at the University of Saskatchewan (USask) and the College of Medicine at USask has for the first time used synchrotron imaging to study both the size and spread of bullet fragments in big game shot by hunters. Their findings were published today in PLOS ONE.

Like a scene right out of the hit television series CSI, the research team fired bullets into blocks of ballistic gelatin—the same material used by for ballistic testing—and examined the resulting fragments using synchrotron imaging.

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Someone taps your shoulder. The organized touch receptors in your skin send a message to your brain, which processes the information and directs you to look left, in the direction of the tap. Now, Penn State and U.S. Air Force researchers have harnessed this processing of mechanical information and integrated it into engineered materials that “think”.

The work, published today in Nature, hinges on a novel, reconfigurable alternative to integrated . Integrated circuits are typically composed of multiple electronic components housed on a single semiconductor material, usually silicon, and they run all types of modern electronics, including phones, cars and robots. Integrated circuits are scientists’ realization of information processing similar to the brain’s role in the . According to principal investigator Ryan Harne, James F. Will Career Development Associate Professor of Mechanical Engineering at Penn State, integrated circuits are the core constituent needed for scalable computing of signals and information but have never before been realized by scientists in any composition other than silicon semiconductors.

His team’s discovery revealed the opportunity for nearly any material around us to act like its own integrated circuit: being able to “think” about what’s happening around it.

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When the MIT Lincoln Laboratory Supercomputing Center (LLSC) unveiled its TX-GAIA supercomputer in 2019, it provided the MIT community a powerful new resource for applying artificial intelligence to their research. Anyone at MIT can submit a job to the system, which churns through trillions of operations per second to train models for diverse applications, such as spotting tumors in medical images, discovering new drugs, or modeling climate effects. But with this great power comes the great responsibility of managing and operating it in a sustainable manner—and the team is looking for ways to improve.

“We have these powerful computational tools that let researchers build intricate models to solve problems, but they can essentially be used as black boxes. What gets lost in there is whether we are actually using the hardware as effectively as we can,” says Siddharth Samsi, a research scientist in the LLSC.

To gain insight into this challenge, the LLSC has been collecting detailed data on TX-GAIA usage over the past year. More than a million user jobs later, the team has released the dataset open source to the computing community.

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