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Manharts Homework Help

After graduating from The University of Michigan in Ann Arbor, Sam Manhart moved to the Bangor area to earn a Master’s Degree in English at The University of Maine and has lived here ever since.He has taught at Husson University, The University of Maine, and in the Maine Community College System, and has been a member of the Hampden Academy English Department since 2004.He earned a second Master’s Degree, in Education, from the University of Maine in 2009.A lifelong competitive swimmer, Mr. Manhart swims in Masters swim meets for the Maine Masters Blue Lobsters Team, competes in open water ocean races, and is the assistant coach for the Hampden Academy Swim Team.Mr. Manhart volunteers as a member of the Lura Hoit Pool Board of Directors and serves as a part-time coach for the U.S. Swimming Hurricane Swim Club.He is also an ardent sea kayaker, canoeist, skier, hiker, rock climber, and surfer who deeply enjoys introducing his two children to these activities.Mr. Manhart annually organizes the Hampden Academy Shakespeare Film Festival, conducts the Hampden Academy school-wide Poetry Out Loud Competition, and is the advisor for the Hampden Academy Chess Club.In his down time Mr. Manhart bakes artisan bread and attempts to cook fine cuisine.

Mr. Manhart teaches the following courses at Hampden Academy:
English 9 {Poetry & Drama}
Exposition
Interpersonal Communication
Career Communications
Technical English
Literature of the Sea
Creative Writing
American Writers
Advanced Short Story and Novel

Many types of large cells have multiple nuclei. In long muscle cells, nuclei are distributed almost uniformly along their length, which is crucial for cell function. However, the underlying positioning mechanisms remain unclear. We examine computationally the hypothesis that a force balance generated by microtubules positions the nuclei. Rather than assuming what the forces are, we allow for various types of forces between pairs of nuclei and between the nuclei and the cell boundary. Mathematically, this means that we start with a great number of potential models. We then use a reverse engineering approach by screening the models and requiring their predictions to fit imaging data on nuclei positions from hundreds of muscle cells of Drosophila larva. Computational screens result in a small number of feasible models, the most adequate of which suggests that the nuclei repel each other and the cell boundary with forces that decrease with distance.

This suggests that microtubules growing from nuclear envelopes push on neighboring nuclei and the cell boundary. We support this hypothesis with stochastic microscopic simulations. Using statistical and analytical tools such as correlation and bifurcation analysis, we make several nontrivial predictions: An increased nuclear density near the cell poles, zigzag patterns in wider cells, and correlations between the cell width and elongated nuclear shapes, all of which we confirm by image analysis of the experimental data.

This is joint work with Mary Baylies, Alex Mogilner and Stefanie Windner.

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