University Scholar Series: Jonathan Roth

Roman Warfare On April 13, 2011 Jonathan Roth spoke in the University Scholar Series hosted by Provost Gerry Selter at the Dr. Martin Luther King, Jr. Library. Jonathan Roth is a Professor in the History Department at SJSU. In this seminar, he examines the evolution of Roman war over its thousand-year history. He highlights the changing arms and equipment of the soldiers, unit organization and command structure, and the wars and battles of each era.https://scholarworks.sjsu.edu/uss/1008/thumbnail.jp

Preferential attachment during the evolution of a potential energy landscape

It has previously been shown that the network of connected minima on a potential energy landscape is scale-free, and that this reflects a power-law distribution for the areas of the basins of attraction surrounding the minima. Here, we set out to understand more about the physical origins of these puzzling properties by examining how the potential energy landscape of a 13-atom cluster evolves with the range of the potential. In particular, on decreasing the range of the potential the number of stationary points increases and thus the landscape becomes rougher and the network gets larger. Thus, we are able to follow the evolution of the potential energy landscape from one with just a single minimum to a complex landscape with many minima and a scale-free pattern of connections. We find that during this growth process, new edges in the network of connected minima preferentially attach to more highly-connected minima, thus leading to the scale-free character. Furthermore, minima that appear when the range of the potential is shorter and the network is larger have smaller basins of attraction. As there are many of these smaller basins because the network grows exponentially, the observed growth process thus also gives rise to a power-law distribution for the hyperareas of the basins.Comment: 10 pages, 10 figure

Feedback Control as a Framework for Understanding Tradeoffs in Biology

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with feedback regulation, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism's response to perturbations. We use examples from aquatic (electric fish station keeping and jamming avoidance), terrestrial (cockroach wall following) and aerial environments (flight control in moths) to highlight how one can use control theory to understand how feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.Comment: Submitted to Integr Comp Bio

Spectral Statistics for the Dirac Operator on Graphs

We determine conditions for the quantisation of graphs using the Dirac operator for both two and four component spinors. According to the Bohigas-Giannoni-Schmit conjecture for such systems with time-reversal symmetry the energy level statistics are expected, in the semiclassical limit, to correspond to those of random matrices from the Gaussian symplectic ensemble. This is confirmed by numerical investigation. The scattering matrix used to formulate the quantisation condition is found to be independent of the type of spinor. We derive an exact trace formula for the spectrum and use this to investigate the form factor in the diagonal approximation

Rapamycin reduces neuronal mutant huntingtin aggregation and ameliorates locomotor performance in Drosophila

Huntington’s disease (HD) is a neurodegenerative disease characterized by movement and cognitive dysfunction. HD is caused by a CAG expansion in exon 1 of the HTT gene that leads to a polyglutamine (PQ) repeat in the huntingtin protein, which aggregates in the brain and periphery. Previously, we used Drosophila models to determine that Htt-PQ aggregation in the heart causes shortened lifespan and cardiac dysfunction that is ameliorated by promoting chaperonin function or reducing oxidative stress. Here, we further study the role of neuronal mutant huntingtin and how it affects peripheral function. We overexpressed normal (Htt-PQ25) or expanded mutant (Htt-PQ72) exon 1 of huntingtin in Drosophila neurons and found that mutant huntingtin caused age-dependent Htt-PQ aggregation in the brain and could cause a loss of synapsin. To determine if this neuronal dysfunction led to peripheral dysfunction, we performed a negative geotaxis assay to measure locomotor performance and found that neuronal mutant huntingtin caused an age-dependent decrease in locomotor performance. Next, we found that rapamycin reduced Htt-PQ aggregation in the brain. These results demonstrate the role of neuronal Htt-PQ in dysfunction in models of HD, suggest that brain-periphery crosstalk could be important to the pathogenesis of HD, and show that rapamycin reduces mutant huntingtin aggregation in the brain

Treatment With Mycophenolate and Cyclophosphamide Leads to Clinically Meaningful Improvements in Patient‐Reported Outcomes in Scleroderma Lung Disease: Results of Scleroderma Lung Study II

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/156000/1/acr211125.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156000/2/acr211125_am.pd