Scientists could be one step closer to a solution to atherosclerosis by preventing the buildup of plaques that clog the arteries and lead to strokes and heart attacks.
What is atherosclerosis?
Atherosclerosis is the accumulation of cholesterol-containing plaques in the walls of arteries; this causes them to narrow, leading to reduced blood flow, higher blood pressure, and an increased risk of a heart attack or stroke. Atherosclerosis is the number one cause of death globally, and, by far, the highest risk factor for this disease is aging, although there are lifestyle factors, such as poor diet, smoking, obesity, and being sedentary.
Scientists from Wake Forest Baptist Medical Center partnered with researchers from the University of Southern California to develop an innovative procedure to give hope to people struggling with remembering important information. A new implant uses a person’s own memory patterns in order to boost the brain’s natural ability to encode those memories and recall them quickly. There has been a reported 35 to 37 % increase in short-term memory performance.
“This is the first time scientists have been able to identify a patient’s own brain cell code or pattern for memory and, in essence, ‘write in’ that code to make existing memory work better, an important first step in potentially restoring memory loss,” said the study’s lead author Robert Hampson, Ph.D., professor of physiology/pharmacology and neurology at Wake Forest Baptist.
Epilepsy patients from Wake Forest Baptist were surgically implanted with electrodes in the various parts of their brains. The electronic prosthetic system is based on a multi-input-multi-output (or MIMO) mathematical model to influence the patterns of neurons firing within the hippocampus.
Before I started working on real-world robots, I wrote about their fictional and historical ancestors. This isn’t so far removed from what I do now. In factories, labs, and of course science fiction, imaginary robots keep fueling our imagination about artificial humans and autonomous machines.
Real-world robots remain surprisingly dysfunctional, although they are steadily infiltrating urban areas across the globe. This fourth industrial revolution driven by robots is shaping urban spaces and urban life in response to opportunities and challenges in economic, social, political, and healthcare domains. Our cities are becoming too big for humans to manage.
Good city governance enables and maintains smooth flow of things, data, and people. These include public services, traffic, and delivery services. Long queues in hospitals and banks imply poor management. Traffic congestion demonstrates that roads and traffic systems are inadequate. Goods that we increasingly order online don’t arrive fast enough. And the WiFi often fails our 24/7 digital needs. In sum, urban life, characterized by environmental pollution, speedy life, traffic congestion, connectivity and increased consumption, needs robotic solutions—or so we are led to believe.
Exclusive: 71 million people stand to benefit from reduced price treatment for virus which can lead to liver cirrhosis, cancer and death.
Thu 12 Apr 2018 01.00 EDT Last modified on Thu 12 Apr 2018 19.55 EDT.
People are remarkably good at focusing their attention on a particular person in a noisy environment, mentally “muting” all other voices and sounds. Known as the cocktail party effect, this capability comes natural to us humans. However, automatic speech separation — separating an audio signal into its individual speech sources — while a well-studied problem, remains a significant challenge for computers.
In “Looking to Listen at the Cocktail Party”, we present a deep learning audio-visual model for isolating a single speech signal from a mixture of sounds such as other voices and background noise. In this work, we are able to computationally produce videos in which speech of specific people is enhanced while all other sounds are suppressed. Our method works on ordinary videos with a single audio track, and all that is required from the user is to select the face of the person in the video they want to hear, or to have such a person be selected algorithmically based on context. We believe this capability can have a wide range of applications, from speech enhancement and recognition in videos, through video conferencing, to improved hearing aids, especially in situations where there are multiple people speaking.
People with a rare kind of dementia that initially attacks the language center of the brain end up recruiting other areas of the brain to decipher sentences, according to a new study.
The study is one of the first to show that people with a neurodegenerative disease can call upon intact areas of the brain for help. People who have had strokes or traumatic brain injuries sometimes use additional regions of the brain to accomplish tasks that were handled by the now-injured part.
“We were able to identify regions of the brain that allowed the patients to compensate for the dying of neurons in the brain,” says first author Aneta Kielar, an assistant professor of speech, language, and hearing sciences and of cognitive science at the University of Arizona.