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Astronomers have discovered a massive dormant black hole from the early universe, just 800 million years after the Big Bang, using the James Webb Space Telescope.

This black hole, with a mass 400 million times that of our Sun, challenges existing models of black hole growth due to its size and low accretion rate.

Unprecedented black hole size and behavior.

A new model reveals how molecular interactions drive order in active systems.

Scientists from the Department of Living Matter Physics at the Max Planck Institute for Dynamics and Self-Organization (MPI-DS) have found that non-reciprocal interactions can enhance order in active systems. Using a newly developed model, they demonstrated how the degree of non-reciprocity influences the formation of patterns, providing deeper insight into the organization of complex, dynamic systems.

Living matter exhibits unique characteristics not found in simpler physical systems. One striking example is the uneven interaction between different types of particles. For instance, one molecule may be attracted to another, while the second is repelled — similar to how a predator pursues its prey, which instinctively tries to escape. This phenomenon, known as non-reciprocal interaction, can produce complex, large-scale patterns, as has been shown previously. These patterns often resemble essential structures found in living systems, such as the organization within a cell.

Scientists have found evidence of a strange state of matter called a quantum spin liquid in a material known as pyrochlore cerium stannate.

In this mysterious state, magnetic particles don’t settle into a fixed pattern but stay in constant motion, even at extremely low temperatures. Researchers used advanced tools like neutron scattering and theoretical models to detect unusual magnetic behavior that behaves like waves of light. This breakthrough could lead to new discoveries in physics and future technologies like quantum computing.

Quantum Spin Liquids

Scientists used AI to estimate the brain age of 739 healthy seniors and found that lifestyle and health conditions impact brain aging.

Researchers at Karolinska Institutet have used an AI tool to estimate the biological age of brains from MRI scans of 70-year-olds. Their analysis revealed that factors harmful to vascular health, such as inflammation and high blood sugar levels, are linked to older-looking brains, while a healthy lifestyle was associated with younger-looking brains. These findings were published today (December 20) in Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association.

Leveraging AI to determine brain age.

Run by the team at orchestration, AI, and automation platform Tines, the Tines library contains pre-built workflows shared by real security practitioners from across the community, all of which are free to import and deploy via the Community Edition of the platform.

Their bi-annual “You Did What with Tines?!” competition highlights some of the most interesting workflows submitted by their users, many of which demonstrate practical applications of large language models (LLMs) to address complex challenges in security operations.

One recent winner is a workflow designed to automate CrowdStrike RFM reporting. Developed by Tom Power, a security analyst at The University of British Columbia, it uses orchestration, AI and automation to reduce the time spent on manual reporting.