Passion for Life

spring 2014"MU alumna and cancer survivor takes Relay For Life experience full circle."Story by Kelsey Allen ; Photos courtesy of Melanie Dickens Oberkro

Magnetic Field Structures in a Facular Region Observed by THEMIS and Hinode

The main objective of this paper is to build and compare vector magnetic maps obtained by two spectral polarimeters, i.e. THEMIS/MTR and Hinode SOT/SP, using two inversion codes (UNNOFIT and MELANIE) based on the Milne-Eddington solar atmosphere model. To this end, we used observations of a facular region within active region NOAA 10996 on 23 May 2008, and found consistent results concerning the field strength, azimuth and inclination distributions. Because SOT/SP is free from the seeing effect and has better spatial resolution, we were able to resolve small magnetic polarities with sizes of 1" to 2", and we could detect strong horizontal magnetic fields, which converge or diverge in negative or positive facular polarities. These findings support models which suggest the existence of small vertical flux tube bundles in faculae. A new method is proposed to get the relative formation heights of the multi-lines observed by MTR assuming the validity of a flux tube model for the faculae. We found that the Fe 1 6302.5 \AA line forms at a greater atmospheric height than the Fe 1 5250.2 \AA line.Comment: 20 pages, 9 figures, 3 tables, accepted for publication in Solar Physic

Forman's Ricci curvature - From networks to hypernetworks

Networks and their higher order generalizations, such as hypernetworks or multiplex networks are ever more popular models in the applied sciences. However, methods developed for the study of their structural properties go little beyond the common name and the heavy reliance of combinatorial tools. We show that, in fact, a geometric unifying approach is possible, by viewing them as polyhedral complexes endowed with a simple, yet, the powerful notion of curvature - the Forman Ricci curvature. We systematically explore some aspects related to the modeling of weighted and directed hypernetworks and present expressive and natural choices involved in their definitions. A benefit of this approach is a simple method of structure-preserving embedding of hypernetworks in Euclidean N-space. Furthermore, we introduce a simple and efficient manner of computing the well established Ollivier-Ricci curvature of a hypernetwork.Comment: to appear: Complex Networks '18 (oral presentation

Properties of tug-of-war model for cargo transport by molecular motors

Molecular motors are essential components for the biophysical functions of the cell. Our current quantitative understanding of how multiple motors move along a single track is not complete; even though models and theories for single motor chemomechanics abound. Recently, M.J.I. M$\ddot{\rm u}$ller {\em et al.} have developed a tug-of-war model to describe the bidirectional movement of the cargo (PNAS(2008) 105(12) P4609-4614). Through Monte Carlo simulations, they discovered that the tug-of-war model exhibits several qualitative different motility regimes, which depend on the precise value of single motor parameters, and they suggested the sensitivity can be used by a cell to regulate its cargo traffic. In the present paper, we carry out a thorough analysis of the tug-of-war model. All the stable, i.e., biophysically observable, steady states are obtained. Depending on several parameters, the system exhibits either uni-, bi- or tristability. Based on the separating boundary of the different stable states and the initial numbers of the different motor species that are bound to the track, the steady state of the cargo movement can be predicted, and consequently the steady state velocity can be obtained. It is found that, the velocity, even the direction, of the cargo movement change with the initial numbers of the motors which are bound to the track and several other parameters

Undergraduate Commencement Exercises Program, May 22, 1993.

Bryant University Undergraduate Commencement Exercises Program, May 22, 1993

The latitude dependence of the rotation measures of NVSS sources

In this Letter I use the variation of the spread in rotation measure (RM) with Galactic latitude to separate the Galactic from the extragalactic contributions to RM. This is possible since the latter does not depend on Galactic latitude. As input data I use RMs from the catalogue by Taylor, Stil, and Sunstrum, supplemented with published values for the spread in RM (`sigmaRM') in specific regions on the sky. I test 4 models of the free electron column density (which I will abbreviate to `DMinf') of the Milky Way, and the best model builds up DMinf on a characteristic scale of a few kpc from the Sun. sigmaRM correlates well with DMinf. The measured sigmaRM can be modelled as a Galactic contribution, consisting of a term sigmaRM,MW that is amplified at smaller Galactic latitudes as 1/sin|b|, in a similar way to DMinf, and an extragalactic contribution, sigmaRM,EG, that is independent of latitude. This model is sensitive to the relative magnitudes of sigmaRM,MW and sigmaRM,EG, and the best fit is produced by sigmaRM,MW approx. 8 rad/m^2 and sigmaRM,EG approx. 6 rad/m^2. The 4 published values for sigmaRM as a function of latitude suggest an even larger sigmaRM,MW contribution and a smaller sigmaRM,EG. This result from the NVSS RMs and published sigmaRM shows that the Galactic contribution dominates structure in RM on scales between about 1degr -- 10degr on the sky. I work out which factors contribute to the variation of sigmaRM with Galactic latitude, and show that the sigmaRM,EG I derived is an upper limit. Furthermore, to explain the modelled sigmaRM,MW requires that structure in has a 1-sigma spread <~ 0.4 microG.Comment: 6 pages, 3 figures, 1 table. Published in MNRAS Letters; the definitive version is available at wileyonlinelibrary.com, http://onlinelibrary.wiley.com/doi/10.1111/j.1745-3933.2010.00957.x/pd

Bayesian model predictive control: Efficient model exploration and regret bounds using posterior sampling

Tight performance specifications in combination with operational constraints make model predictive control (MPC) the method of choice in various industries. As the performance of an MPC controller depends on a sufficiently accurate objective and prediction model of the process, a significant effort in the MPC design procedure is dedicated to modeling and identification. Driven by the increasing amount of available system data and advances in the field of machine learning, data-driven MPC techniques have been developed to facilitate the MPC controller design. While these methods are able to leverage available data, they typically do not provide principled mechanisms to automatically trade off exploitation of available data and exploration to improve and update the objective and prediction model. To this end, we present a learning-based MPC formulation using posterior sampling techniques, which provides finite-time regret bounds on the learning performance while being simple to implement using off-the-shelf MPC software and algorithms. The performance analysis of the method is based on posterior sampling theory and its practical efficiency is illustrated using a numerical example of a highly nonlinear dynamical car-trailer system

Cabaret (1985)

Music: John Kander Lyrics: Fred Ebb Director: Robert Jenkins Musical Direction: Michael West Choreographer: Annette MacDonald Set Design: Paul Manchester Costumes: Elizabeth M. Poindexter Academic Year: 1984-1985https://scholarworks.sjsu.edu/productions_1980s/1040/thumbnail.jp