Research team introduced CHASER, an incentive mechanism for blockchain-based EMCS systems. It ensures budget balance, truthfulness, rationality, and high social welfare. Simulations show a 42% increase in social welfare and high task completion rates.

To make inorganic materials such as catalysts, industry mixes precursor powders and fires them in an oven. This often produces a mix of compositions and structures. In this study, researchers developed a new way to select precursors to increase yield and quickly validated their results using a robotic lab. The new recipe selection process obtained higher purity for 32 of the 35 target materials.

A recently published article in the journal Weed Science demonstrates just how devasting Palmer amaranth (Amaranthus palmeri) can be for furrow-irrigated rice production, even in small amounts. The findings show that successful, in-furrow rice production greatly hinges on Palmer amaranth-free fields – before, during and after the growing season.

UChicago researchers develop a new technology to create a spatial map of gene expression for an entire organism.

 Research team proposed DeepSwarm, a collective deep learning framework integrating swarm intelligence for bidirectional optimization of data acquisition and processing. It improves accuracy and resource efficiency in IoT scenarios, showing significant results in video analysis and federated learning.

Through the weak nuclear force, one quark flavor can transmute into another. However, current data and theory indicate that the probabilities of quark flavor transmutation do not add up to 100%, as predicted by the Standard Model of Particle Physics. To understand whether this is due to physics beyond the Standard Model or underestimated uncertainties, nuclear theorists laid out a new framework needed to extract the up-down quark flavor mixing with a precision of a few parts in ten thousand from certain nuclear beta decays.