Neural Networks for Modeling and Control of Particle Accelerators

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.Comment: 21 p

Visually-guided protein crystal manipulation using micromachined silicon tools

We present a system for protein crystal micro-manipulation with focus on automated crystal mounting for the purposes of X-ray data collection. The system features a set of newly designed micropositioner end-effectors we call microshovels which address some limitations of the traditional cryogenic loops. We have used micro-electrical mechanical system (MEMS) techniques to design and manufacture various shapes and quantities of microshovels. Visual feedback from a camera mounted on the microscope is used to control the micropositioner as it lowers a microshovel into the liquid containing the crystals and approaches a selected crystal for pickup. We present experimental results that illustrate the applicability of our approach

Visually-guided protein crystal manipulation using micromachined silicon tools

We present a system for protein crystal micro-manipulation with focus on automated crystal mounting for the purposes of X-ray data collection. The system features a set of newly designed micropositioner end-effectors we call microshovels which address some limitations of the traditional cryogenic loops. We have used micro-electrical mechanical system (MEMS) techniques to design and manufacture various shapes and quantities of microshovels. Visual feedback from a camera mounted on the microscope is used to control the micropositioner as it lowers a microshovel into the liquid containing the crystals and approaches a selected crystal for pickup. We present experimental results that illustrate the applicability of our approach

A Microrobotic System For Protein Streak Seeding

We present a microrobotic system for protein crystal micromanipulation tasks. The focus in this report is on a task called streak seeding, which is used by crystallographers to entice certain protein crystals to grow. Our system features a set of custom designed micropositioner end-effectors we call microshovels to replace traditional tools used by crystallographers for this task. We have used micro-electrical mechanical system (MEMS) techniques to design and manufacture various shapes and quantities of microshovels. Visual feedback from a camera mounted on the microscope is used to control the micropositioner as it lowers a microshovel into the liquid containing the crystals for poking and streaking. We present experimental results that illustrate the applicability of our approach

Microsprinklers wet larger soil volume; boost almond yield, tree growth

In the Arbuckle area of the Sacramento Valley, a 22-acre orchard was planted in 1990 with four almond varieties (‘Nonpareil’, ‘Butte’, ‘Carmel’ and ‘Monterey’). The orchard was irrigated with three types of microirrigation — surface drip, subsurface drip and microsprinklers. The orchard soils are 3 to 4 feet of gravelly, loamy sand overlaying a restricting clay layer. The coarse-textured soil with its low water-holding capacity allows little lateral movement of water from the microirrigation emission device. Under these soil conditions, microsprinkler-irrigated trees produced larger almond yields and showed greater tree growth. In addition, irrigation system evaluations show that all three microirrigation systems provide excellent irrigation uniformity levels after 8 years of operation with only routine maintenance