Inspired by biological systems, materials scientists have long sought to harness self-assembly to build nanomaterials. The challenge: the process seemed random and notoriously difficult to predict.

Learn how acceptance sampling improves quality control by evaluating random samples. Discover its methods, benefits, and historical significance in manufacturing.

A breakthrough may be on the horizon for Intel’s Foundry division, as Apple is anticipated to embrace Intel’s 18A-P process for its entry-level MacBook and iPad chips. This move signals a potential ...

Grassland and savanna ecosystems are the original vegetation types of more than 30% of the Brazilian territory, but conservation and training of future professionals has largely focused on forests. In ...

Abstract: Interrupted-sampling repeater jamming (ISRJ) utilizes the characteristics of signal undersampling and matched filtering to produce multiple controllable numbers of false target points in the ...

Abstract: Unsupervised person re-identification (re-ID) remains a challenging task. While extensive research has focused on the framework design and loss function, this paper shows that sampling ...

Overnight samples aren’t just for designers anymore. Last month, Material Bank quietly debuted its long-rumored consumer-facing platform, DesignShop. The site—with its browsable library of materials ...

Objective To describe a new co-design framework termed Evidence-informed, Experience-based Co-design (E2CD). Background Involving consumers and clinicians in planning, designing and implementing ...