Quantitative susceptibility maps from magnetic resonance images can provide both prognostic and diagnostic information in multiple sclerosis, a neurodegenerative disease characterized by the formation of lesions in white matter brain tissue. In particular, susceptibility maps provide adequate contrast to distinguish between "rim" lesions, surrounded by deposited paramagnetic iron, and "non-rim" lesion types. These paramagnetic rim lesions (PRLs) are an emerging biomarker in multiple sclerosis. Much effort has been devoted to both detection and segmentation of such lesions to monitor longitudinal change. As paramagnetic rim lesions are rare, addressing this problem requires confronting the class imbalance between rim and non-rim lesions. W e produce synthetic quantitative susceptibility maps of paramagnetic rim lesions and show that inclusion of such synthetic data improves classifier performance and provide a multi-channel extension to generate accompanying contrasts and probabilistic segmentation maps. W e exploit the projection capability of our trained generative network to demonstrate a novel denoising approach that allows us to train on ambiguous rim cases and substantially increase the minority class. W e show that both synthetic lesion synthesis and our proposed rim lesion label denoising method best approximate the unseen rim lesion distribution and improve detection in a clinically interpretable manner . W e release our code and generated data at https://github.com/agr78/PRLx-GAN

We develop a self-learning approach for conjecturing of induction predicates on a dataset of 16197 problems derived from the OEIS. These problems are hard for today's SMT and ATP systems because they require a combination of inductive and arithmetical reasoning. Starting from scratch, our approach consists of a feedback loop that iterates between (i) training a neural translator to learn the correspondence between the problems solved so far and the induction predicates useful for them, (ii) using the trained neural system to generate many new induction predicates for the problems, (iii) fast runs of the z3 prover attempting to prove the problems using the generated predicates, (iv) using heuristics such as predicate size and solution speed on the proved problems to choose the best predicates for the next iteration of training. The algorithm discovers on its own many interesting induction predicates, ultimately solving 5565 problems, compared to 2265 problems solved by CVC5, Vampire or Z3 in 60 seconds.

Speed and precision are two major issues in robotics and in Industry of the Future (also known as Industry 4.0). Within this framework, RoMoCo research team of AS2M department at FEMTO-ST Institute has developed MiGriBot, a miniature robot able to perform 720 pick-and-place operations of sub-millimeter objects per minute. The results of this research work have been published in Science Robotics. These performances are made possible thanks to its architecture, that allows it to grip and manipulate micro-objects barely visible to the naked eye (from 40 micrometers to several hundred micrometers). In fact, where other microrobots have a rigid end-effector, MiGriBot is based on a principle with an articulated end.

WASHINGTON: The National Geospatial-Intelligence Agency (NGA) will announce plans in May to contract with commercial companies to for analyze satellite and other imagery data of military targets, says David Gauthier, head of NGA's new(ish) Commercial and Business Operations Group. While the first contracts will be small, the move is a big step toward the spy agency's goal of creating a "hybrid" pool of data that combines commercial imagery with low-resolution but high re-revisit rates with traditional high-resolution that is less timely Intelligence Community imagery provided by the National Reconnaissance Office (NRO) and others. "We do foresee in the future a hybrid architecture, where we definitely require both national systems for their capabilities, and commercial systems for their capabilities," he said. While Gauthier wouldn't provide a budget for the new effort, he told me earlier this week that the plan is to evaluate the capabilities of a number of commercial companies to meet NGA's needs. "I don't want to discuss numbers at this time, but we are still operating at small scale and plan on contracting with multiple vendors to compare and contrast their capabilities," he said.