Dawn Aerospace.

In case you have not heard of them, Dawn Aerospace is one of the fastest-growing private space companies in the world, with clients from Europe, Asia, and the United States. They call themselves a “green” in-space propulsion supplier, and they also, to date, have around 11 operational satellites currently in orbit.

Just published from my son.

Automatic hippocampus imaging, with about 20 minutes of cloud computing per scan.

Like neocortical structures, the archicortical hippocampus differs in its folding patterns across individuals. Here, we present an automated and robust BIDS-App, HippUnfold, for defining and indexing individual-specific hippocampal folding in MRI, analogous to popular tools used in neocortical reconstruction. Such tailoring is critical for inter-individual alignment, with topology serving as the basis for homology. This topological framework enables qualitatively new analyses of morphological and laminar structure in the hippocampus or its subfields. It is critical for refining current neuroimaging analyses at a meso-as well as micro-scale. HippUnfold uses state-of-the-art deep learning combined with previously developed topological constraints to generate uniquely folded surfaces to fit a given subject’s hippocampal conformation. It is designed to work with commonly employed sub-millimetric MRI acquisitions, with possible extension to microscopic resolution. In this paper, we describe the power of HippUnfold in feature extraction, and highlight its unique value compared to several extant hippocampal subfield analysis methods.

Keywords: Brain Imaging Data Standards; computational anatomy; deep learning; hippocampal subfields; hippocampus; human; image segmentation; magnetic resonance imaging; neuroscience.

© 2022, DeKraker et al.

What is the point of all that wealth if you don’t get to be petty?

Twitter blocked links to Jack Sweeney’s Instagram and Facebook accounts tracking Elon Musk’s jet and announced an updated privacy policy.

Over the last several decades, I’ve witnessed a lot of change in the fields of machine learning (ML) and computer science. Early approaches, which often fell short, eventually gave rise to modern approaches that have been very successful. Following that long-arc pattern of progress, I think we’ll see a number of exciting advances over the next several years, advances that will ultimately benefit the lives of billions of people with greater impact than ever before. In this post, I’ll highlight five areas where ML is poised to have such impact. For each, I’ll discuss related research (mostly from 2021) and the directions and progress we’ll likely see in the next few years.

Scientists have discovered that a two graphene layers can conduct electrons showing superconductivity if the two hexagonal nets are twisted against each other at a 1.1 degree angle.

A technique developed at Western University to visually iron out the wrinkles and folds in one region of the brain may provide researchers a more accurate picture to understand brain disorders.

The hippocampus is a region of the brain often looked at by clinicians and researchers for clues to understand disease progression and response to treatment for brain disorders. Made up of two seahorse-shaped brain structures, the hippocampus is located at the centre of the brain and plays an important role in memory formation.

It is one of the first regions of the brain to show damage from Alzheimer’s and other neurodegenerative diseases and is implicated in epilepsy and major depressive disorder. The anatomy of the hippocampus differs greatly from person to person, specifically when looking at the way that it folds in on itself.