Markov Chain Monitoring

In networking applications, one often wishes to obtain estimates about the number of objects at different parts of the network (e.g., the number of cars at an intersection of a road network or the number of packets expected to reach a node in a computer network) by monitoring the traffic in a small number of network nodes or edges. We formalize this task by defining the 'Markov Chain Monitoring' problem. Given an initial distribution of items over the nodes of a Markov chain, we wish to estimate the distribution of items at subsequent times. We do this by asking a limited number of queries that retrieve, for example, how many items transitioned to a specific node or over a specific edge at a particular time. We consider different types of queries, each defining a different variant of the Markov chain monitoring. For each variant, we design efficient algorithms for choosing the queries that make our estimates as accurate as possible. In our experiments with synthetic and real datasets we demonstrate the efficiency and the efficacy of our algorithms in a variety of settings.Comment: 13 pages, 10 figures, 1 tabl

Annotated Bibliography: Understanding Ambulatory Care Practices in the Context of Patient Safety and Quality Improvement.

The ambulatory care setting is an increasingly important component of the patient safety conversation. Inpatient safety is the primary focus of the vast majority of safety research and interventions, but the ambulatory setting is actually where most medical care is administered. Recent attention has shifted toward examining ambulatory care in order to implement better health care quality and safety practices. This annotated bibliography was created to analyze and augment the current literature on ambulatory care practices with regard to patient safety and quality improvement. By providing a thorough examination of current practices, potential improvement strategies in ambulatory care health care settings can be suggested. A better understanding of the myriad factors that influence delivery of patient care will catalyze future health care system development and implementation in the ambulatory setting

ADAPTIVE GRAVITY BALANCING ARM SYSTEMS

Upadhyay, Harshal. M.S.M.E., Purdue University, May 2016. Adaptive Gravity-Balancing Arm Systems. Major Professor: Justin Seipel, School of Mechanical Engineering

Functional Characterization of a Drosophila Transgenic Line Expressing a Chimeric Flightin: Implications on Flight Muscle Structure and Mating Behavior

The asynchronous, indirect flight muscles (IFM) of Drosophila are characterized by their remarkable crystalline myofilament lattice structure that has been proposed to have evolved to power skilled flight for survival, and to produce male courtship song, a sexually selected pre-mating behavior for reproduction. It is not known how physiologically and genetically IFM generates two distinct behaviors under separate evolutionary schemes. Flightin, a 20kDa myofibrillar myosin-binding protein that in Drosophila is exclusively expressed in the IFM, is required for muscle structural integrity and flight. The flightin N-terminal sequence (~65 aa in D. melanogaster) is highly variable among Drosophila species, unlike the rest of the Drosophila protein. Using electron microscopy, fourier image analyses, flight and wing beat frequency tests, I explored the hypothesis that the sequence of amino acids in flightin’s N-terminal region has a strong influence on myofilament lattice spacing and crystallinity. This is investigated by the creation of two independent D.melanogaster transgenic fly lines expressing a D.virilis-D.melanogaster chimeric flightin, both of which exhibit larger myofillament lattice spacing compared to the full length transgenic and D.virilis control fly lines, along with an intermediate wing beat frequency and an equal and/or improved flight ability compared to the control full length transgenic line. These results suggest the N-terminal region is under evolutionary pressures to optimize crystalline lattice structure