Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

Mr. Jeremy Sameulson, EVP of AI and Innovation at IQT, publishes VEIL™ Privacy-Preserving Machine Learning Framework on arXiv: Introduces an architecture designed to enable use of sensitive data ...

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Effect of KROS 101, a small molecule GITR ligand agonist, on T effector cells, T reg cells and intratumoral CD8 T cell cytotoxicity. Phase 1 study of DK210 (EGFR), a tumor-targeted IL2 x IL10 dual ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

In this digitally dominated economy, where instantaneous transactions are the order of the day for all businesses, the landscape of accounting technology has li ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Personality tests are widely used in workplaces to shape recruitment, leadership training and team building. But what if ...