Lifeboat Foundation

It’s past time the world moves away from text-based passwords and verifications for mobile phones and starts embracing more secure image-based solutions, say computer scientists from the University of Surrey.

In a new study, Surrey scientists demonstrate an image-based authentication system called TIM (Transparent Image Moving) for mobile phones to help reduce the risk of shoulder surfing attacks. TIM requires users to select and move predefined images to a designated position for passing authentication checks, similar to those required for online shopping.

The proof-of-concept study found that 85% of TIM users believed it could help them to prevent password guessing and shoulder surfing attacks. The study also found that 71% of participants think TIM is a more usable image-based solution than others on the market. The research has been published in the Journal of Information Security and Applications.

Researchers from the University of Geneva (UNIGE), the Geneva University Hospitals (HUG), and the National University of Singapore (NUS) have developed a novel method for evaluating the interpretability of artificial intelligence (AI) technologies, opening the door to greater transparency and trust in AI-driven diagnostic and predictive tools. The innovative approach sheds light on the opaque workings of so-called “black box” AI algorithms, helping users understand what influences the results produced by AI and whether the results can be trusted.

This is especially important in situations that have significant impacts on the health and lives of people, such as using AI in medical applications. The research carries particular relevance in the context of the forthcoming European Union Artificial Intelligence Act which aims to regulate the development and use of AI within the EU. The findings have recently been published in the journal Nature Machine Intelligence.

Time series data—representing the evolution of information over time—is everywhere: for example in medicine, when recording heart activity with an electrocardiogram (ECG); in the study of earthquakes; tracking weather patterns; or in economics to monitor financial markets. This data can be modeled by AI technologies to build diagnostic or predictive tools.

University of Texas at Dallas researchers have developed a new approach that addresses challenges in the field of quantum computing and has the potential to revolutionize computing, communications and electronic security.

To make solid-state qubits, the basic information unit for quantum computers, a defect must be inserted into the solid material to control the spin states of electrons. Creating and positioning the defect, however, especially in the most commonly used solid material—synthetic diamonds —poses a major challenge.

UT Dallas researchers found that making qubits from thin, two-dimensional sheets of crystals called transition metal dichalcogenides (TMDs) instead of diamond can solve this problem. Led by Dr. Kyeongjae Cho, professor of materials science and engineering in the Erik Jonsson School of Engineering and Computer Science, the researchers published their findings online Dec. 6 in Nature Communications.

ChatGPT’s impact extends beyond the education sector and is causing significant changes in other areas. The AI language model is recognized for its ability to perform various tasks, including paper writing, translation, coding, and more, all through question-and-answer-based interactions.

The AI system relies on deep learning, which requires extensive training to minimize errors, resulting in frequent data transfers between memory and processors. However, traditional digital computer systems’ von Neumann architecture separates the storage and computation of information, resulting in increased power consumption and significant delays in AI computations. Researchers have developed semiconductor technologies suitable for AI applications to address this challenge.

A research team at POSTECH, led by Professor Yoonyoung Chung (Department of Electrical Engineering, Department of Semiconductor Engineering), Professor Seyoung Kim (Department of Materials Science and Engineering, Department of Semiconductor Engineering), and Ph.D. candidate Seongmin Park (Department of Electrical Engineering), has developed a high-performance AI semiconductor device using indium gallium zinc oxide (IGZO), an oxide semiconductor widely used in OLED displays.

More magnesium in our daily diet leads to better brain health as we age, according to scientists from the Neuroimaging and Brain Lab at The Australian National University (ANU).

The researchers say increased intake of magnesium-rich foods such as spinach and nuts could also help reduce the risk of dementia, which is the second leading cause of death in Australia and the seventh biggest killer globally.

The study of more than 6,000 cognitively healthy participants in the United Kingdom aged 40 to 73 found people who consume more than 550 milligrams of magnesium each day have a brain age that is approximately one year younger by the time they reach 55 compared with someone with a normal magnesium intake of about 350 milligrams a day.

Having both diabetes and tooth loss contributes to worse cognitive function and faster cognitive decline in older adults, according to a new study published in a special issue of the Journal of Dental Research focused on aging and oral health.

“Our findings underscore the importance of dental care and diabetes management for older adults in reducing the devastating personal and societal costs of Alzheimer’s disease and other related dementias,” said Bei Wu, vice dean for research at NYU Rory Meyers College of Nursing and co-director of the NYU Aging Incubator, as well as the study’s lead author.

Diabetes is a known risk factor for cognitive decline and dementia. Several of the hallmarks of diabetes —high blood sugar, insulin resistance, inflammation, and related heart disease—are thought to contribute to changes in the brain.

When people suffer spinal cord injuries and lose mobility in their limbs, it’s a neural signal processing problem. The brain can still send clear electrical impulses and the limbs can still receive them, but the signal gets lost in the damaged spinal cord.

The Center for Sensorimotor Neural Engineering (CSNE)—a collaboration of San Diego State University with the University of Washington (UW) and the Massachusetts Institute of Technology (MIT)—is working on an implantable brain chip that can record neural electrical signals and transmit them to receivers in the limb, bypassing the damage and restoring movement. Recently, these researchers described in a study published in the journal Nature Scientific Reports a critical improvement to the technology that could make it more durable, last longer in the body and transmit clearer, stronger signals.

The technology, known as a brain-computer interface, records and transmits signals through electrodes, which are tiny pieces of material that read signals from brain chemicals known as neurotransmitters. By recording brain signals at the moment a person intends to make some movement, the interface learns the relevant electrical signal pattern and can transmit that pattern to the limb’s nerves, or even to a prosthetic limb, restoring mobility and motor function.

A team from Korea created more flexible neural electrodes that minimize tissue damage and still transmit clear brain signals.

Electrodes placed in the brain record neural activity, and can help treat neural diseases like Parkinson’s and epilepsy. Interest is also growing in developing better brain-machine interfaces, in which electrodes can help control prosthetic limbs. Progress in these fields is hindered by limitations in electrodes, which are relatively stiff and can damage soft brain tissue.

Designing smaller, gentler electrodes that still pick up brain signals is a challenge because brain signals are so weak. Typically, the smaller the electrode, the harder it is to detect a signal. However, a team from the Daegu Gyeongbuk Institute of Science & Technology in Korea developed new probes that are small, flexible and read brain signals clearly.

Induced pluripotent stem cells offer great therapeutic potential and are a valuable tool for understanding how different diseases develop. New research shows that such stem cell lines should be regularly screened for genetic mutations to ensure the accuracy of the disease models.

In the past 10 years, scientists have learned to create induced pluripotent stem cells (iPSC) from ordinary cells by genetic reprogramming. These cells are widely used to study diseases, as they can be differentiated to almost any cell type of the body, and they can be generated from any individual. However, a key remaining methodological challenge is that the differentiation process is subject to major technical variation for mostly unknown reasons.

HiLIFE Tenure Track Professor Helena Kilpinen and her group at the University of Helsinki use stem cells for studying the biological mechanisms of neurodevelopmental and other brain-related diseases.