Researchers explore glioblastoma's genetic complexity using innovative spatial profiling, aiming to enhance treatment ...

As someone who has spent the better part of two decades optimizing distributed systems—from early MapReduce clusters to ...

Whole-mount 3D imaging at the cellular scale is a powerful tool for exploring complex processes during morphogenesis. In organoids, it allows examining tissue architecture, cell types, and morphology ...

Comparing Modeling Approaches for Distributed Contested Logistics. American Journal of Operations Research, 15, 125-145. doi: ...

CENIEH co-leads a pioneering study that, for the first time, applies hyperspectral imaging to effectively discriminate rock blocks, sediment ...

I’ve been conducting a large-scale bibliometric study on publicly available Chinese academic literature related to hacking and crashing Western power grids. In this article, I’m sharing the main ...

Deep-learning reconstruction algorithms clarify low-dose CT or limited-echo MRI data so sharply that technologists can ...

Aim This study evaluates if characteristics (eg, location, size, volume) of clusters of defects on an initial visual field ...

Abstract: Computing the optimal solution to a spatial filtering problems in a Wireless Sensor Network can incur large bandwidth and computational requirements if an approach relying on data ...

Researchers from Carnegie Mellon University, Stanford University, and Princeton University introduced Adaptive Data Optimization (ADO), a novel method that dynamically adjusts data distributions ...