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

Evidence for RNA transport in rat optic nerve

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66066/1/j.1471-4159.1969.tb08995.x.pd

Social Emotional Learning in a Guatemalan Preschool Sample: Does Socioeconomic Status Moderate the Effects of a School-Based Prevention Program?

Researchers evaluated the effectiveness of a universal social skills program and compared social emotional knowledge on individual skills interviews with 100 Guatemalan preschool children from resource rich (N = 47) and resource poor (N = 53) backgrounds. Participant ages ranged from 3- to 6-years-old. SEL was evaluated prior and subsequent to receiving a school-based social emotional educational program. Results were analysed in terms of effectiveness of SEL by error type. Data show that preschool children from both poor and wealthy families made significant gains in social-emotional knowledge as a result of SEL instruction. In order to better understand where SEL might be improved, analyses of incorrect responses provided by children from each SES group were analysed. Findings demonstrated no significant differences between the two groups in terms of incorrect or socially unacceptable responses although, overall, the groups differed in depth of social emotional knowledge. Implications for ‘closing the gap’ between children’s social emotional development in high and low SES groups are discussed

Construction and analysis of causally dynamic hybrid bond graphs

Engineering systems are frequently abstracted to models with discontinuous behaviour (such as a switch or contact), and a hybrid model is one which contains continuous and discontinuous behaviours. Bond graphs are an established physical modelling method, but there are several methods for constructing switched or ‘hybrid’ bond graphs, developed for either qualitative ‘structural’ analysis or efficient numerical simulation of engineering systems. This article proposes a general hybrid bond graph suitable for both. The controlled junction is adopted as an intuitive way of modelling a discontinuity in the model structure. This element gives rise to ‘dynamic causality’ that is facilitated by a new bond graph notation. From this model, the junction structure and state equations are derived and compared to those obtained by existing methods. The proposed model includes all possible modes of operation and can be represented by a single set of equations. The controlled junctions manifest as Boolean variables in the matrices of coefficients. The method is more compact and intuitive than existing methods and dispenses with the need to derive various modes of operation from a given reference representation. Hence, a method has been developed, which can reach common usage and form a platform for further study

Submacropulse electron-beam dynamics correlated with higher-order modes in a Tesla-type cryomodule

Experiments were performed at the Fermilab Accelerator Science and Technology (FAST) facility to elucidate the effects of long-range wakefields (LRWs) in TESLA-type superconducting rf cavities. In particular, we investigated the higher-order modes (HOMs) generated in the eight cavities of a cryomodule (CM) due to off-axis steering with correctors located ~4 m upstream of the CM. We have observed correlated submacropulse centroid slews of a few-hundred microns and centroid oscillations at ~240 kHz in the rf BPM data after the CM. The entrance energy into the CM was 25 MeV, and the exit energy was 100 MeV with 125 pC/b and 400 pC/b in 50-bunch pulse trains. These experimental results were evaluated for machine learning training aspects which will be used to inform the commissioning plan for the Linac Coherent Light Source-II injector CM