‘Magic’ solvent creates stronger thin films

This micrograph image shows an initiated chemical vapor deposition coating made by doctoral student Pengyu Chen in the lab of Rong Yang, assistant professor in the Smith School of Chemical and Biomolecular Engineering in Cornell Engineering.
Image Credit: Courtesy of the researchers 

A new all-dry polymerization technique uses reactive vapors to create thin films with enhanced properties, such as mechanical strength, kinetics and morphology. The synthesis process is gentler on the environment than traditional high-temperature or solution-based manufacturing and could lead to improved polymer coatings for microelectronics, advanced batteries and therapeutics.

“This scalable technique of initiated chemical vapor deposition polymerization allows us to make new materials, without redesigning or revamping the whole chemistry. We just simply add an ‘active’ solvent,” said Rong Yang, assistant professor in the Smith School of Chemical and Biomolecular Engineering in Cornell Engineering. “It’s a little bit like a Lego. You team up with a new connecting piece. There’s a ton you can build now that you couldn’t do before.”

Yang collaborated on the project with Jingjie Yeo, assistant professor in the Sibley School of Mechanical and Aerospace Engineering, and Shefford Baker, associate professor of materials science and engineering.

VISTA X-62 Advancing Autonomy and Changing the Face of Air Power

The X-62A VISTA Aircraft flying above Edwards Air Force Base, California.
Photo Credit: Kyle Brasier, U.S. Air Force

The Lockheed Martin VISTA X-62A, a one-of-a-kind training aircraft, was flown by an artificial intelligence agent for more than 17 hours recently, representing the first time AI engaged on a tactical aircraft.

VISTA, short for Variable In-flight Simulation Test Aircraft, is changing the face of air power at the U.S. Air Force Test Pilot School (USAF TPS) at Edwards Air Force Base in California.

VISTA is a one-of-a-kind training airplane developed by Lockheed Martin Skunk Works® in collaboration with Calspan Corporation for the USAF TPS. Built on open systems architecture, VISTA is fitted with software that allows it to mimic the performance characteristics of other aircraft.

"VISTA will allow us to parallelize the development and test of cutting-edge artificial intelligence techniques with new uncrewed vehicle designs," said Dr. M. Christopher Cotting, U.S. Air Force Test Pilot School director of research. "This approach, combined with focused testing on new vehicle systems as they are produced, will rapidly mature autonomy for uncrewed platforms and allow us to deliver tactically relevant capability to our warfighter."

Ingestible sensor could help doctors pinpoint GI difficulties

MIT engineers have shown that they can use magnetic fields to track the location of this ingestible sensor within the GI tract.
Photo Credit: Courtesy of the researchers / Massachusetts Institute of Technology

Engineers at MIT and Caltech have demonstrated an ingestible sensor whose location can be monitored as it moves through the digestive tract, an advance that could help doctors more easily diagnose gastrointestinal motility disorders such as constipation, gastroesophageal reflux disease, and gastroparesis.

The tiny sensor works by detecting a magnetic field produced by an electromagnetic coil located outside the body. The strength of the field varies with distance from the coil, so the sensor’s position can be calculated based on its measurement of the magnetic field.

In the new study, the researchers showed that they could use this technology to track the sensor as it moved through the digestive tract of large animals. Such a device could offer an alternative to more invasive procedures, such as endoscopy, that are currently used to diagnose motility disorders.

“Many people around the world suffer from GI dysmotility or poor motility, and having the ability to monitor GI motility without having to go into a hospital is important to really understand what is happening to a patient,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT and a gastroenterologist at Brigham and Women’s Hospital.

Efficient technique improves machine-learning models’ reliability

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a new technique that can enable a machine-learning model to quantify how confident it is in its predictions, but does not require vast troves of new data and is much less computationally intensive than other techniques.
Image Credit: MIT News, iStock
Creative Commons Attribution Non-Commercial No Derivatives license

Powerful machine-learning models are being used to help people tackle tough problems such as identifying disease in medical images or detecting road obstacles for autonomous vehicles. But machine-learning models can make mistakes, so in high-stakes settings it’s critical that humans know when to trust a model’s predictions.

Uncertainty quantification is one tool that improves a model’s reliability; the model produces a score along with the prediction that expresses a confidence level that the prediction is correct. While uncertainty quantification can be useful, existing methods typically require retraining the entire model to give it that ability. Training involves showing a model millions of examples so it can learn a task. Retraining then requires millions of new data inputs, which can be expensive and difficult to obtain, and also uses huge amounts of computing resources.

Researchers at MIT and the MIT-IBM Watson AI Lab have now developed a technique that enables a model to perform more effective uncertainty quantification, while using far fewer computing resources than other methods, and no additional data. Their technique, which does not require a user to retrain or modify a model, is flexible enough for many applications.

'Natural killer' immune cells can modify tissue inflammation

Professor Mariapia Degli-Esposti and Dr Iona Schuster
Photo Credit: Courtesy of Monash University

Melbourne researchers have improved our understanding of how the immune system is regulated to prevent disease, identifying a previously unknown role of ‘natural killer’ (NK) immune cells.

The Monash University-led study identified a new group of immune cells, known as tissue-resident memory natural killer (NKRM) cells. NKRM cells limited immune responses in tissues and prevented autoimmunity, which is when the immune system makes a mistake and attacks the body's own tissues or organs.

While additional research is required, the discovery may ultimately be used to treat autoimmune diseases like Sjogren’s Syndrome and possibly chronic inflammatory conditions.

Published in Immunity, the preclinical research is led by senior author Professor Mariapia Degli-Esposti and first author Dr Iona Schuster from the Monash Biomedicine Discovery Institute (BDI), in close ongoing collaboration with the Lions Eye Institute.

Stress levels sky high for families of neurodiverse kids

Almost 80 per cent of caregivers experienced poor wellbeing, high levels of stress and poor mental health
Photo Credit: Jordan Whitt

New Curtin University-led research has found caregivers of neurodivergent children are more likely to experience clinically significant levels of stress, poor mental health, financial hardship, and negative relationships.

The research, published in the Journal of Autism and Developmental Disorders, explored the health and wellbeing of caregivers of children living with neurological conditions such as autism spectrum disorder, attention deficit/ hyperactive disorder (ADHD), cerebral palsy, and learning disabilities, and whether current support services were sufficient to meet their needs.

Lead researcher Dr Ben Milbourn, from the Curtin School of Allied Health, said children diagnosed with neurodevelopmental conditions often require significant levels of support from their caregivers and meeting their emotional, physical, social and learning needs can be challenging.

The 'flip-flop' qubit: realization of a new quantum bit in silicon controlled by electric signals

Dr Tim Botzem, Professor Andrea Morello and Dr Rostyslav Savytskyy in the quantum computing lab at UNSW Sydney.
Photo Credit: Richard Freeman/UNSW

UNSW Sydney research demonstrates a new type of quantum bit in silicon, called ‘flip-flop’ qubit, which can facilitate the construction of a large-scale quantum computer.

A team led by Professor Andrea Morello has just demonstrated the operation of a new type of quantum bit, called ‘flip-flop’ qubit, which combines the exquisite quantum properties of single atoms, with easy controllability using electric signals, just as those used in ordinary computer chips.

A deliberate target: electrical control of a single-atom quantum bit

“Sometimes new qubits, or new modes of operations, are discovered by lucky accident. But this one was completely by design,” says Prof. Morello. “Our group has had excellent qubits for a decade, but we wanted something that could be controlled electrically, for maximum ease of operation. So, we had to invent something completely new.”

New damselfly sharing habitat with UK natives

A male small red-eyed damselfly.
Photo Credit Pam Taylor

A damselfly species that came to the UK from Europe poses a minimal risk to native damselflies and dragonflies; new research shows.

As tens of thousands of species shift their “range” (the areas they live in) due to climate change, the small red-eyed damselfly has spread northwards from the Mediterranean. It was first observed in the UK in 1999 and has since established itself.

The new study – by the University of Exeter and the UK Centre for Ecology & Hydrology – used data from the British Dragonfly Society to see if it had caused native damselflies and dragonflies to decline.

The results showed most native dragonflies and damselflies were either found more often or were unchanged in areas colonized by the small red-eyed damselfly.

However, two damselfly species might have been negatively affected, and more research is needed to investigate this.

“With range-shifting increasing globally, we need to understand what impact newly arrived species have on ecosystems,” said Dr Regan Early, of the Centre for Ecology and Conservation on Exeter's Penryn Campus in Cornwall.

Extracts from two wild plants inhibit COVID-19 virus

 Emory University graduate student Caitlin Risener, first author of the study, gathers tall goldenrod in South Georgia.
Photo Credit: Tharanga Samarakoon

Two common wild plants contain extracts that inhibit the ability of the virus that causes COVID-19 to infect living cells, an Emory University study finds. Scientific Reports published the results — the first major screening of botanical extracts to search for potency against the SARS-CoV-2 virus.

In laboratory dish tests, extracts from the flowers of tall goldenrod (Solidago altissima) and the rhizomes of the eagle fern (Pteridium aquilinum) each blocked SARS-CoV-2 from entering human cells.

The active compounds are only present in miniscule quantities in the plants. It would be ineffective, and potentially dangerous, for people to attempt to treat themselves with them, the researchers stress. In fact, the eagle fern is known to be toxic, they warn.

“It’s very early in the process, but we’re working to identify, isolate and scale up the molecules from the extracts that showed activity against the virus,” says Cassandra Quave, senior author of the study and associate professor in Emory School of Medicine’s Department of Dermatology and the Center for the Study of Human Health. “Once we have isolated the active ingredients, we plan to further test for their safety and for their long-range potential as medicines against COVID-19.”

Single drug injection wards off COVID-19 hospitalizations

A single injection of PEG-lambda interferon proved to be effective against all variants of the coronavirus tested by researchers at Stanford Medicine.
Image Credit: Gerd Altmann

In an international, multicenter, pivotal Phase 3 trial, a single under-the-skin injection of a biological drug given to patients within seven days of the onset of COVID-19 symptoms cut the likelihood they needed to be hospitalized in half. Patients treated within three days of showing symptoms fared even better. Among unvaccinated patients who were treated soon after symptom onset, hospitalization likelihood plummeted markedly.

The drug, pegylated lambda-interferon, or PEG-lambda, proved effective against all COVID-19 viral variants tested, including omicron. Side effects were no greater than those reported by placebo recipients.

A report on the success of the randomized, double-blind, placebo-controlled trial of nearly 2,000 newly infected COVID-19 patients was published online Feb. 9 in the New England Journal of Medicine.

PEG-lambda is a synthetic version of lambda-interferon, a naturally occurring protein that infected cells secrete as a first line of defense against viral infection.