Flux tubes, visons, and vortices in spin-charge separated superconductors

The idea of spin-charge separation in cuprate superconductors has been recently energized by Senthil and Fisher who formulated a Z_2 gauge theory and, within its context, proposed a ``vison detection'' experiment as a test for topological order in a sample with multiply connected geometry. Here we show that the same experiment can be performed to test for the spin-charge separation in U(1) [but not in SU(2)] theory and argue that vortex core spectroscopy can in fact distinguish between the different symmetries of the fictitious gauge field.Comment: 3 pages, 1 ps figure. Invited talk at the 13th International Symposium on Superconductivity in Toky

Unattended Autonomous Mission and System Management of an Unmanned Seaplane

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90651/1/AIAA-2011-1614-249.pd

Autonomous Flight, Fault, and Energy Management of the Flying Fish Solar-Powered Seaplane.

The Flying Fish autonomous unmanned seaplane is designed and built for persistent ocean surveillance. Solar energy harvesting and always-on autonomous control and guidance are required to achieve unattended long-term operation. This thesis describes the Flying Fish avionics and software systems that enable the system to plan, self-initiate, and autonomously execute drift-flight cycles necessary to maintain a designated watch circle subject to environmentally influenced drift. We first present the avionics and flight software architecture developed for the unique challenges of an autonomous energy-harvesting seaplane requiring the system to be: waterproof, robust over a variety of sea states, and lightweight for flight. Seaplane kinematics and dynamics are developed based on conventional aircraft and watercraft and upon empirical flight test data. These models serve as the basis for development of flight control and guidance strategies which take the form of a cyclic multi-mode guidance protocol that smoothly transitions between nested gain-scheduled proportional-derivative feedback control laws tuned for the trim conditions of each flight mode. A fault-tolerant airspeed sensing system is developed in response to elevated failure rates arising from pitot probe water ingestion in the test environment. The fault-tolerance strategy utilizes sensor characteristics and signal energy to combine redundant sensor measurements in a weighted voting strategy, handling repeated failures, sensor recovery, non-homogenous sensors, and periods of complete sensing failure. Finally, a graph-based mission planner combines models of global solar energy, local ocean-currents, and wind with flight-verified/derived aircraft models to provide an energy-aware flight planning tool. An NP-hard asymmetric multi-visit traveling salesman planning problem is posed that integrates vehicle performance and environment models using energy as the primary cost metric. A novel A* search heuristic is presented to improve search efficiency relative to uniform cost search. A series of cases studies are conducted with surface and airborne goals for various times of day and for multi-day scenarios. Energy-optimal solutions are identified except in cases where energy harvesting produces multiple comparable-cost plans via negative-cost cycles. The always-on cyclic guidance/control system, airspeed sensor fault management algorithm, and the nested-TSP heuristic for A* are all critical innovation required to solve the posed research challenges.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91453/1/eubankrd_1.pd

Fault Detection and Fail-Safe Operation with a Multiple-Redundancy Air-Data System

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83640/1/AIAA-2010-7855-622.pd

Energy-Aware Multiflight Planning for an Unattended Seaplane: Flying Fish

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/143017/4/1.i010484.pd

Multi-scale immunoepidemiological modeling of within-host and between-host HIV dynamics: systematic review of mathematical models.

OBJECTIVE: The objective of this study is to conduct a systematic review of multi-scale HIV immunoepidemiological models to improve our understanding of the synergistic impact between the HIV viral-immune dynamics at the individual level and HIV transmission dynamics at the population level. BACKGROUND: While within-host and between-host models of HIV dynamics have been well studied at a single scale, connecting the immunological and epidemiological scales through multi-scale models is an emerging method to infer the synergistic dynamics of HIV at the individual and population levels. METHODS: We reviewed nine articles using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework that focused on the synergistic dynamics of HIV immunoepidemiological models at the individual and population levels. RESULTS: HIV immunoepidemiological models simulate viral immune dynamics at the within-host scale and the epidemiological transmission dynamics at the between-host scale. They account for longitudinal changes in the immune viral dynamics of HIV+ individuals, and their corresponding impact on the transmission dynamics in the population. They are useful to analyze the dynamics of HIV super-infection, co-infection, drug resistance, evolution, and treatment in HIV+ individuals, and their impact on the epidemic pathways in the population. We illustrate the coupling mechanisms of the within-host and between-host scales, their mathematical implementation, and the clinical and public health problems that are appropriate for analysis using HIV immunoepidemiological models. CONCLUSION: HIV immunoepidemiological models connect the within-host immune dynamics at the individual level and the epidemiological transmission dynamics at the population level. While multi-scale models add complexity over a single-scale model, they account for the time varying immune viral response of HIV+ individuals, and the corresponding impact on the time-varying risk of transmission of HIV+ individuals to other susceptibles in the population

The Flying Fish Persistent Ocean Surveillance Platform

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77030/1/AIAA-2009-1902-584.pd

M-CSF Signals through the MAPK/ERK Pathway via Sp1 to Induce VEGF Production and Induces Angiogenesis In Vivo

BACKGROUND: M-CSF recruits mononuclear phagocytes which regulate processes such as angiogenesis and metastases in tumors. VEGF is a potent activator of angiogenesis as it promotes endothelial cell proliferation and new blood vessel formation. Previously, we reported that in vitro M-CSF induces the expression of biologically-active VEGF from human monocytes. METHODOLOGY AND RESULTS: In this study, we demonstrate the molecular mechanism of M-CSF-induced VEGF production. Using a construct containing the VEGF promoter linked to a luciferase reporter, we found that a mutation reducing HIF binding to the VEGF promoter had no significant effect on luciferase production induced by M-CSF stimulation. Further analysis revealed that M-CSF induced VEGF through the MAPK/ERK signaling pathway via the transcription factor, Sp1. Thus, inhibition of either ERK or Sp1 suppressed M-CSF-induced VEGF at the mRNA and protein level. M-CSF also induced the nuclear localization of Sp1, which was blocked by ERK inhibition. Finally, mutating the Sp1 binding sites within the VEGF promoter or inhibiting ERK decreased VEGF promoter activity in M-CSF-treated human monocytes. To evaluate the biological significance of M-CSF induced VEGF production, we used an in vivo angiogenesis model to illustrate the ability of M-CSF to recruit mononuclear phagocytes, increase VEGF levels, and enhance angiogenesis. Importantly, the addition of a neutralizing VEGF antibody abolished M-CSF-induced blood vessel formation. CONCLUSION: These data delineate an ERK- and Sp1-dependent mechanism of M-CSF induced VEGF production and demonstrate for the first time the ability of M-CSF to induce angiogenesis via VEGF in vivo

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)