Lifeboat Foundation

Another good use for AI. Fighting disinformation.

About 60% of adults in the US who get their news through social media have, largely unknowingly, shared false information, according to a poll by the Pew Research Center. The ease at which disinformation is spread and the severity of consequences it brings — from election hacking to character assassination — make it an issue of grave concern for us all.

Continue reading “Fake everything: how machine learning is being used to fight back against disinformation campaigns” »

A susceptibility to gain weight may be written into molecular processes of human cells, a Washington State University study indicates.

The proof-of-concept study with a set of 22 twins found an epigenetic signature in buccal or cheek cells appearing only for the twins who were obese compared to their thinner siblings. With more research, the findings could lead to a simple cheek swab test for an obesity biomarker and enable earlier prevention methods for a condition that effects 50% of U.S. adults, the researchers said.

“Obesity appears to be more complex than simple consumption of food. Our work indicates there’s a susceptibility for this disease and molecular markers that are changing for it,” said Michael Skinner, a WSU professor of biology and corresponding author of the study published in the journal Epigenetics.

Japanese scientists have developed a new type of plastic that’s strong at room temperature, but can be easily broken down on demand into its base components. In seawater, it starts to break down into food for marine life, and just to top it off, it can self-heal and remember past shapes.

Plastic is everywhere in our modern world, for better or worse. Its toughness makes it an extremely useful material for everything from household items to vehicle parts, but that same toughness makes it hard to break down for recycling or disposal.

In the new study, scientists at the University of Tokyo developed a new plastic material that can be broken down more easily, either in recycling plants or in nature. It’s based on a class of plastic called an epoxy resin vitrimer, which are strong at room temperature but can be reshaped and molded with a bit of added heat. Normally, vitrimers are brittle, but the team improved the recipe by adding a molecule called polyrotaxane.

Surface-enhanced Raman scattering (SERS) is a powerful fingerprint analysis and detection technique that plays an important role in the fields of food safety, environmental protection, bio-imaging and hazardous substance identification. Electromagnetic enhancement (EM) and chemical enhancement (CM) are the two recognized mechanisms of action for amplifying Raman signals.

EM originates from the localized surface plasmonic resonance effect of noble metal nanostructures such as gold, silver, and copper, while CM originates from the charge transfer between the substrate and the probe molecules. In principle, the charge transfer efficiency depends on the coupling of the incident laser energy to the energy levels of the substrate-molecule system.

Compared to EM-based SERS substrates, CM-based SERS substrates are usually made of two-dimensional materials including semiconductor oxides, metal carbides, and graphene and its evolutions, which have weaker signal enhancement capabilities. However, the advantages of CM-based SERS substrate, such as high specificity, homogeneity and biocompatibility, have attracted the attention of researchers.

Plants are not just able to survive in low gravity such as on the Moon, two new papers suggest – they may prefer it, at least based on the only species to sprout.

When Chang’e 4 landed on the Moon in January 2019 it carried with it a payload that could dictate the future of space exploration: seeds of four plant species it sought to grow on the lunar surface. The germination of a single cotton seed attracted plenty of attention at the time, but there’s more to growth than just sprouting. If crops grown on the Moon are less productive or more fragile than those on Earth, it’s going to be a big problem.

It’s taken more than four years, but important results from the experiment have now been released and they suggest that for all the obstacles to establishing colonies on the Moon and Mars, growing food might not be one. Then again, it’s still very early days.

Indian start-up Green Robot Machinery (GRoboMac) has developed a cotton picker with autonomous robotic arms, mounted on a semi-autonomous electric farm vehicle.

The robotic arms of the battery-operated machine are each capable of picking about 50 kgs cotton per day. That means that four arms, mounted on the vehicle, can pick about 200 kgs per day. High yielding farms can use additional arms, the company says.

https://youtube.com/watch?v=ZzsM2wd9h8k

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Read about NIH-funded research that shows reducing calories may improve health benefits.

In America, roughly 40 million Americans have diabetes and about 95% of them have type 2 diabetes. Type 2 diabetes occurs when the body cannot correctly process sugar and fuel cells. More specifically, the body does not produce enough insulin to break down sugar into glucose for the cells to use. In this case, treatment includes insulin shots or a pump in addition to a strict diet excluding sweets or high fat meals. Treatment limitations disrupt patient quality of life. Some researchers have been working on better detection for diabetic retinopathy with artificial intelligence (AI), but research is limited on how to better detect diabetes itself. Thus, many researchers are working to detect diabetes early on and discover better treatments.

Klick labs, located in multiple cities across the world, is trying to detect type 2 diabetes by having a patient speak into a microphone for 10 seconds. Klick labs believes this technology can better detect diabetes and help patients get treatment earlier. The study was published in Mayo Clinic Proceedings: Digital Health, which details how patients spoke for 10 seconds and combined with health data, including age, sex, height, and weight, created an AI model that discerns whether a person has type 2 diabetes or not. After further tests, scientists determined it has 89% and 86% accuracy for women and men, respectively.

In the study, Klick Labs collected voice recordings of 267 people, either non-diabetic or diabetic. The participants were asked to record a phrase into their smartphones six times a day for a total of 2-weeks. Over 18,000 recordings were taken and analyzed to distinguish 14 acoustic features that helped distinguish non-diabetic to type 2 diabetic individuals. The research highlights specific vocal variations in pitch and intensity that could lead to how the medical community screens for early-onset diabetes. A major barrier to early detection includes time, travel, and cost, which many people do not have. Voice diagnosis can help eliminate those barriers and improve detection and treatment in diabetic patients.