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Hurricane-based company breaks ground on 20,000-square-foot robotics facility in Toquerville

TOQUERVILLE, Washington County — The Hurricane-based robotics company IME Automation recently announced the purchase of 6.5 acres of land at Anderson Junction in Toquerville, where the company has broken ground for its new 20,000-square-foot facility.

IME Automation develops custom robotic systems for manufacturing operations worldwide. This new facility will expand its capabilities and footprint in the region.

The land was acquired approximately eight months ago during the summer of 2024, brokered by sales agent Brandon Price with the commercial real estate agency NAI Excel. Price said he delayed putting out information about the acquisition until IME Automation was completely ready to break ground.

Scientists find cellular brain changes tied to PTSD

The human brain is made up of billions of interconnected cells that are constantly talking to each other. A new study published in Nature zooms in to the single-cell level to see how this cellular communication may be going wrong in brains affected by post-traumatic stress disorder (PTSD).

Until recently, researchers did not have the technology to study within individual cells. But now that it’s available, a team led by Matthew Girgenti, Ph.D., assistant professor of psychiatry at Yale School of Medicine, has been analyzing to uncover genetic variants that might be associated with psychiatric diseases such as (MDD) and PTSD.

Their latest study is one of the first to examine a major psychiatric disorder, PTSD, at the single-cell level. For years, doctors have been prescribing antidepressants to treat the condition because there are currently no drugs specifically designed for PTSD. Girgenti hopes that identifying novel molecular signatures associated with the psychiatric disease can help researchers learn how to develop new drugs or repurpose existing ones to treat it more effectively.

All-topographic neural networks more closely mimic the human visual system

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a result, in addition to tackling various real-world computational problems, they could help neuroscientists and psychologists to better understand the underpinnings of specific sensory or cognitive processes.

Researchers at Osnabrück University, Freie Universität Berlin and other institutes recently developed a new class of artificial neural networks (ANNs) that could mimic the human visual system better than CNNs and other existing deep learning algorithms. Their newly proposed, visual system-inspired computational techniques, dubbed all-topographic neural networks (All-TNNs), are introduced in a paper published in Nature Human Behaviour.

“Previously, the most powerful models for understanding how the brain processes visual information were derived off of AI vision models,” Dr. Tim Kietzmann, senior author of the paper, told Tech Xplore.

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