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Volumetric representations of electron microscopy reveal nanometer structural features of the mitochondrion. These organelles are the cell's 'power plant,' generating most of the adenosine triphosphatethe main source of chemical energy for a cell. Visualized here are the mitochondria present in human heart muscle. A texture-based volume rendering engine, named Cyclops and developed by Chris Burns while at the Texas Advanced Computing Center illuminate the structure of these organelles. Data was provided by Chris Gilpin at the University of Texas Southwestern Medical Center in Dallas, Texas. Volume rendering was performed in real-time on the Longhorn Visualization and Data Analysis cluster at the Texas Advanced Computing Center.

The two most common ways to activate intelligent voice assistants (IVAs) are button presses and trigger phrases. This paper describes a new way to invoke IVAs on smartwatches: simply raise your hand and speak naturally. To achieve this experience, we designed an accurate, low-power detector that works on a wide range of environments and activity scenarios with minimal impact to battery life, memory footprint, and processor utilization. The raise to speak (RTS) detector consists of four main components: an on-device gesture convolutional neural network (CNN) that uses accelerometer data to detect specific poses; an on-device speech CNN to detect proximal human speech; a policy model to combine signals from the motion and speech detector; and an off-device false trigger mitigation (FTM) system to reduce unintentional invocations trigged by the on-device detector. Majority of the components of the detector run on-device to preserve user privacy. The RTS detector was released in watchOS 5.0 and is running on millions of devices worldwide. CCS CONCEPTS • Human-centered computing → Gestural input; • Computing methodologies → Speech recognition; Neural networks; Supervised learning by classification.