Lifeboat Foundation

Disease contagion is suppressed when different social groups have a large overlap in membership.

As object identification and three-dimensional (3D) reconstruction techniques become essential in various reverse engineering, artificial intelligence, medical diagnosis, and industrial production fields, there is an increasing focus on seeking vastly efficient, faster speed, and more integrated methods that can simplify processing.

In the current field of object identification and 3D reconstruction, extracting sample contour information is primarily accomplished by various computer algorithms. Traditional computer processors suffer from multiple constraints, such as high-power consumption, low-speed operation, and complex algorithms. In this regard, there has recently been growing attention in searching for alternative optical methods to perform those techniques.

The development of optical computing theory and image processing has provided a more complete theoretical basis for object identification and 3D reconstruction techniques. Optical methods have received more attention as an alternative paradigm than traditional mechanisms in recent years due to their enormous advantages of ultra-fast operation speed, high integration, and low latency.

The researchers found 139 genes that are common across the primate groups but highly divergent in their expression in human brains.

An international team led by researchers at the University of Toronto has uncovered over 100 genes that are common to primate brains but have undergone evolutionary divergence only in humans – and which could be a source of our unique cognitive ability.

The researchers, led by Associate Professor Jesse Gillis from the Donnelly Centre for Cellular and Biomolecular Research and the Department of Physiology at U of T’s Temerty Faculty of Medicine, found the genes are expressed differently in the brains of humans compared to four of our relatives – chimpanzees, gorillas, macaques, and marmosets.

Feng Guo, an associate professor of intelligent systems engineering at the Indiana University Luddy School of Informatics, Computing and Engineering, is addressing the technical limitations of artificial intelligence computing hardware by developing a new hybrid computing system—which has been dubbed “Brainoware”—that combines electronic hardware with human brain organoids.

Advanced AI techniques, such as machine learning and deep learning, which are powered by specialized silicon computer chips, expend enormous amounts of energy. As such, engineers have designed neuromorphic computing systems, modeled after the structure and function of a human brain, to improve the performance and efficiency of these technologies. However, these systems are still limited in their ability to fully mimic brain function, as most are built on digital electronic principles.

In response, Guo and a team of IU researchers, including graduate student Hongwei Cai, have developed a hybrid neuromorphic computing system that mounts a brain organoid onto a multielectrode assay to receive and send information. The brain organoids are brain-like 3D cell cultures derived from stem cells and characterized by different brain cell types, including neurons and glia, and brain-like structures such as ventricular zones.

Amid a rise in the innovation of wearable technology, researchers are looking for ways to harness the adaptive sensing ability of the human body.

A recent University of Melbourne panel discussion covered the future of wearable sensors. Professor Graham Kerr, Bill Dimopoulos, Galen Gan and Professor Peter Lee considered the management of information generated from such technology and its interpretation for improving health.

This is not a work of art. It’s an image of microscopic blood flow in a rat’s brain, taken with one of many new tools that are yielding higher levels of detail in brain imaging.

Here are seven more glorious images from neuroscience research →

Alexandre Dizeux

Regulatory efforts to protect data are making strides globally. Patient data is protected by law in the United States and elsewhere. In Europe the General Data Protection Regulation (GDPR) guards personal data and recently led to a US $1.3 billion fine for Meta. You can even think of Apple’s App Store policies against data sharing as a kind of data-protection regulation.

“These are good constraints. These are constraints society wants,” says Michael Gao, founder and CEO of Fabric Cryptography, one of the startups developing FHE-accelerating chips. But privacy and confidentiality come at a cost: They can make it more difficult to track disease and do medical research, they potentially let some bad guys bank, and they can prevent the use of data needed to improve AI.

“Fully homomorphic encryption is an automated solution to get around legal and regulatory issues while still protecting privacy,” says Kurt Rohloff, CEO of Duality Technologies, in Hoboken, N.J., one of the companies developing FHE accelerator chips. His company’s FHE software is already helping financial firms check for fraud and preserving patient privacy in health care research.

High-frequency terahertz waves have great potential for a number of applications including next-generation medical imaging and communication. Researchers at Linköping University, Sweden, have shown, in a study published in the journal Advanced Science, that the transmission of terahertz light through an aerogel made of cellulose and a conducting polymer can be tuned. This is an important step to unlock more applications for terahertz waves.

The terahertz range covers wavelengths that lie between microwaves and infrared light on the electromagnetic spectrum. It has a very high frequency. Thanks to this, many researchers believe that the terahertz range has great potential for use in space exploration, security technology and communication systems, among other things.

In medical imaging, it can also be an interesting substitute for X-ray examinations as the waves can pass through most non-conductive materials without damaging any tissue.

Ocean bays that pinch West Antarctica are home to two distinct populations of Turquet’s octopus (Pareledone turqueti). The shared secrets of their ancestors do not bode well for the future health of our planet.

A new DNA analysis of the two geographically separated octopus populations indicates they were once part of one big family.

This direct historical connection suggests that around 125,000 years ago, the massive 2.2 million cubic kilometer (530,000 cubic mile) West Antarctic Ice Sheet (WAIS) that separates the two bays had fully collapsed into the sea.