Scientists have been inspired by Pacman to create a plastic-eating'cocktail', which could help eradicate plastic waste. It's made up of two enzymes – called PETase and MHETase – produced by a type of bacteria that feeds on plastic bottles, called Ideonella sakaiensis. Unlike natural degradation, which can take hundreds of years, the super-enzyme is able to convert the plastic back to its original'building blocks' in a few days. The two enzymes work together like'two Pac-men joined by a piece of string' munching down snack pellets in the popular video game. The new super-enzyme digests plastic up to six times faster than the original PETase enzyme alone, which was discovered by the team in 2018.
Illustrating children's books with too many detailed, non-essential pictures makes it'harder for kids to focus and absorb knowledge', a study has demonstrated. Colourful pictures intended to motivate young readers may achieve the exact opposite by drawing attention away from the story text, US researchers warned. Although reading is considered a'gateway for learning', around 20 per cent of children in the UK do not meet the minimum level of literacy proficiency. Children's books typically include eye-catching illustrations to help readers visualise the characters and setting of the story. However, eye-tracking studies found that too many pictures can prove distracting.
The "whiteness" of artificial intelligence (AI) removes people of colour from the way humanity thinks about its technology-enhanced future, researchers argue. University of Cambridge experts suggest current portrayals and stereotypes about AI risk creating a "racially homogenous" workforce of aspiring technologists, creating machines with bias baked into their algorithms. The scientists say cultural depictions of AI as white need to be challenged, as they do not offer a "post-racial" future but rather one from which people of colour are simply erased. In their paper, "The Whiteness of AI" published in the journal, Philosophy and Technology, Leverhulme CFI Executive Director, Stephen Cave and Dr Kanta Dihal offer insights into the ways in which portrayals of AI stem from, and perpetuate, racial inequalities. Cave and Dihal cite research showing that people perceive race in AI, not only in human-like robots, but also in abstracted and disembodied AI.
There has been a loneliness pandemic in the last 20 years, marked by growing rates of opioid use and suicides, increased health care costs, lost productivity, and rising mortality. According to the experts, the ongoing COVID-19 pandemic, with its associated lockdowns and social distancing, has only made things worse. Precisely evaluating the depth and breadth of societal loneliness is a tedious task, restricted by available tools, like self-reports. Now in a new proof-of-concept article, recently published online in the American Journal of Geriatric Psychiatry on September 24th, 2020, a team of researcher headed by scientists from the University of California San Diego School of Medicine, has utilized artificial intelligence technologies to study the natural language patterns (NLP) to determine the levels of loneliness in older adults. Most studies use either a direct question of'how often do you feel lonely,' which can lead to biased responses due to stigma associated with loneliness or the UCLA Loneliness Scale which does not explicitly use the word'lonely.
As one of the hottest technologies of recent years, artificial intelligence (AI) has started penetrating both the US public and the private sectors--though to differing degrees. While the private sector seems bullish on AI, the public sector's approach appears tempered with more caution--a Deloitte survey of select early adopters of AI shows high concern around the potential risks of AI among public sector organizations (see the sidebar "About the survey"). They give a peek into how public sector organizations are approaching AI; and how the approaches, in many cases, differ from those of their private sector counterparts. AI is not completely new to the public sector. The first AI contract was awarded in 1985 by the US Social Security Administration,1 but the technology still wasn't advanced enough to become common in the following decades.
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September 23, 2020 – An artificial intelligence algorithm can detect subtle signs of osteoarthritis in MRI scans, years before symptoms of the condition even begin. Researchers at University of Pittsburgh School of Medicine and Carnegie Mellon University College of Engineering noted that right now, the primary treatment for osteoarthritis is joint replacement. The condition is so prevalent that knee replacement is the most common surgery in the US for people over the age of 45. "The gold standard for diagnosing arthritis is x-ray. As the cartilage deteriorates, the space between the bones decreases," said study co-author Kenneth Urish, MD, PhD, associate professor of orthopaedic surgery at Pitt and associate medical director of the bone and joint center at UPMC Magee-Womens Hospital. "The problem is, when you see arthritis on x-rays, the damage has already been done. It's much easier to prevent cartilage from falling apart than trying to get it to grow again."
Corn, coffee, chocolate, even wine are a few of the foods that stand to be massively disrupted by the effects of climate change, population growth and water scarcity -- if they haven't already. A recent study found the yields of the world's top ten crops have begun to decrease, a drop that is disproportionately affecting food-insecure countries. The situation stands to worsen. Researchers project that the global population will increase by 3 billion in 2050. To feed these additional global residents, agricultural production must increase by 50 percent, says Dr. Ranga Raju Vatsavai, an associate professor in computer science at North Carolina State University and the associate director of the Center for Geospatial Analytics.
A scientist from Russia has developed a new neural network architecture and tested its learning ability on the recognition of handwritten digits. The intelligence of the network was amplified by chaos, and the classification accuracy reached 96.3%. The network can be used in microcontrollers with a small amount of RAM and embedded in such household items as shoes or refrigerators, making them'smart.' The study was published in Electronics. Today, the search for new neural networks that can operate on microcontrollers with a small amount of random access memory (RAM) is of particular importance.
A new machine learning approach added to conventional magnetic resonance imaging can identify the regions of the brain causing dissociative symptoms in people with post-traumatic stress disorder, researchers found in a study published Friday by the American Journal of Psychiatry. Although MRI has long been used to document changes in the brain that occur as a result of a number of neurological conditions, bolstering the approach with machine learning enabled researchers to uncover and measure changes in functional connections between different regions of the brain in women with PTSD. These altered connections correlated with their dissociative symptoms, including memory loss or amnesia, the researchers said. "This new work may help us to establish a new standard of care for traumatized patients with PTSD who struggle with significant symptoms of dissociation," study co-author Dr. Milissa Kaufman, director of the Dissociative Disorders and Trauma Research Program at McLean Hospital, said in a statement. PTSD is a mental health disorder that occurs following trauma -- violent personal assaults, natural or human-caused disasters, accidents and military combat, for example -- according to the National Institute of Mental Health.