Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria

A Review of Multi- Compartment Infectious Disease Models

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156488/2/insr12402.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156488/1/insr12402_am.pd

Mindfulness meditators show altered distributions of early and late neural activity markers of attention in a response inhibition task

Attention is vital for optimal behavioural performance in every-day life. Mindfulness meditation has been shown to enhance attention. However, the components of attention altered by meditation and the related neural activities are underexplored. In particular, the contributions of inhibitory processes and sustained attention are not well understood. To address these points, 34 meditators were compared to 28 age and gender matched controls during electroencephalography (EEG) recordings of neural activity during a Go/Nogo response inhibition task. This task generates a P3 event related potential, which is related to response inhibition processes in Nogo trials, and attention processes across both trial types. Compared with controls, meditators were more accurate at responding to Go and Nogo trials. Meditators showed a more frontally distributed P3 to both Go and Nogo trials, suggesting more frontal involvement in sustained attention rather than activity specific to response inhibition. Unexpectedly, meditators also showed increased positivity over the right parietal cortex prior to visual information reaching the occipital cortex (during the pre-C1 window). Both results were positively related to increased accuracy across both groups. The results suggest that meditators show altered engagement of neural regions related to attention, including both higher order processes generated by frontal regions, and sensory anticipation processes generated by poster regions. This activity may reflect an increased capacity to modulate a range of neural processes in order to meet task requirements. This increased capacity may underlie the improved attentional function observed in mindfulness meditators.Neil W. Bailey, Gabrielle Freedman, Kavya Raj, Caley M. Sullivan, Nigel C. Rogasch, Sung W. Chung, Kate E. Hoy, Richard Chambers, Craig Hassed, Nicholas T. Van Dam, Thomas Koenig, Paul B. Fitzgeral

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm

We present the first results of the Fermilab Muon g-2 Experiment for the positive muon magnetic anomaly $a_\mu \equiv (g_\mu-2)/2$. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency $\omega_a$ between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ${\tilde{\omega}'^{}_p}$ in a spherical water sample at 34.7$^{\circ}$C. The ratio $\omega_a / {\tilde{\omega}'^{}_p}$, together with known fundamental constants, determines $a_\mu({\rm FNAL}) = 116\,592\,040(54)\times 10^{-11}$ (0.46\,ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both $\mu^+$ and $\mu^-$, the new experimental average of $a_\mu({\rm Exp}) = 116\,592\,061(41)\times 10^{-11}$ (0.35\,ppm) increases the tension between experiment and theory to 4.2 standard deviationsComment: 10 pages; 4 figure