Double pendulum balanced by counter-rotary counter-masses as useful element for synthesis of dynamically balanced mechanisms

Complete dynamic balancing principles still cannot avoid a substantial increase of mass and inertia. In addition, the conditions for dynamic balance and the inertia equations can be complicated to derive. This article shows how a double pendulum can be fully dynamically balanced by using counter-rotary counter-masses (CRCMs) for reduced additional mass and inertia. New CRCM-configurations were derived that have a low inertia, a single CRCM or have all CRCMs near the base. This article also shows how a CRCM-balanced double pendulum can be used as building element in the synthesis of balanced mechanisms for which the balancing conditions and inertia equations can be written down quickly. For constrained mechanisms the procedure is to first write down the known balancing conditions and inertia equations for the balanced double pendula and subsequently substitute the kinematic relations

Characterizing Phantom Arteries with Multi-Channel Laser Ultrasonics and Photo-Acoustics

Multi-channel photo-acoustic and laser ultrasonic waves are used to sense the characteristics of proxies for healthy and diseased vessels. The acquisition system is non-contacting and non-invasive with a pulsed laser source and a laser vibrometer detector. As the wave signatures of our targets are typically low in amplitude, we exploit multi-channel acquisition and processing techniques. These are commonly used in seismology to improve the signal-to-noise ratio of data. We identify vessel proxies with a diameter on the order of 1 mm, at a depth of 18 mm. Variations in scattered and photo-acoustic signatures are related to differences in vessel wall properties and content. The methods described have the potential to improve imaging and better inform interventions for atherosclerotic vessels, such as the carotid artery

Artificial neural networks for 3D cell shape recognition from confocal images

We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.Comment: 17 pages, 8 figure