Happening @ Michigan https://events.umich.edu/list/rss RSS Feed for Happening @ Michigan Events at the University of Michigan. Dissertation Defense: Advanced Predictive Control Strategies for More Electric Aircraft (February 21, 2019 10:00am) https://events.umich.edu/event/61053 61053-15024938@events.umich.edu Event Begins: Thursday, February 21, 2019 10:00am
Location: Lurie Robert H. Engin. Ctr
Organized By: Aerospace Engineering

William Dunham

Dissertation Committee:
Professor Ilya Kolmanovsky (co-chair)
Associate Professor Anouck Girard (co-chair)
Dr Brandon Hencey, Air Force Research Laboratory
Professor Jing Sun, Naval Architecture and Marine Engineering (Cognate)

Presentation Info:
February 21st, 2019
GM Conference Room, Lurie Engineering Center

Next generation aircraft designs are incorporating more extensive electrical distributions that cover a broader range of applications, increasing the power levels to be met and the complexity of their operation. The expansion of the electrical grid cascades out into the engine, where the generators extract power from. This dissertation develops advanced predictive control strategies that account for the interactions between the subsystems in order to enable the potential benefits of a More Electric Aircraft (MEA), such as improved efficiency and reliability.

First, models representing the engine and power subsystems of the MEA, including their interactions, are developed. The control objective in this MEA system is to actuate the engine and power subsystem inputs to satisfy demands for thrust and power loads while enforcing constraints on compressor surge
and bus voltage deviations.

Second, model predictive control (MPC) strategies incorporating disturbance rejection, coordination between the subsystems, and anticipation of the changes in the power loads are shown to be effective in the MEA.

Third, a Distributed MPC is formulated that accounts for separately developed subsystems through controller privacy and differences in update rates.

Finally, a Scenario Based MPC is proposed to handle stochastic transitions in the thrust and power load references.

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Presentation Mon, 11 Feb 2019 11:54:16 -0500 2019-02-21T10:00:00-05:00 2019-02-21T11:30:00-05:00 Lurie Robert H. Engin. Ctr Aerospace Engineering Presentation will
Write Togethers (for grad students) (February 25, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491990@events.umich.edu Event Begins: Monday, February 25, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-02-25T09:00:00-05:00 2019-02-25T12:00:00-05:00 North Quad Sweetland Center for Writing Other flyer
Rackham/Sweetland Workshops: Structuring Content (February 26, 2019 4:00pm) https://events.umich.edu/event/60155 60155-14840471@events.umich.edu Event Begins: Tuesday, February 26, 2019 4:00pm
Location: North Quad
Organized By: Sweetland Center for Writing

What kinds of arguments can you use a dissertation to make, and how can you frame or position those arguments? Once you've committed to an argument, how do you arrange your dissertation to best serve it? How can you think about the overall shape of what you're doing and making? The Structuring Content workshop will present graduate students an opportunity to consider these questions, learn about some of the common components of dissertations in the humanities and social sciences, and ask questions about how to scaffold and build out their dissertation topics and projects.

Register at https://lsa.umich.edu/sweetland/graduates/sweetland-rackham-workshops.html

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Workshop / Seminar Mon, 21 Jan 2019 15:35:18 -0500 2019-02-26T16:00:00-05:00 2019-02-26T17:30:00-05:00 North Quad Sweetland Center for Writing Workshop / Seminar North Quad
PhD Defense: Yiling Zhang (March 1, 2019 9:00am) https://events.umich.edu/event/61586 61586-15150260@events.umich.edu Event Begins: Friday, March 1, 2019 9:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Yiling Zhang

CHAIR(s): Siqian Shen, Ruiwei Jiangl

TITLE OF DISSERTATION: Convex Nonlinear and Integer Programming Approaches for Distributionally Robust Optimization of Complex Systems

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Lecture / Discussion Mon, 25 Feb 2019 11:55:00 -0500 2019-03-01T09:00:00-05:00 2019-03-01T11:00:00-05:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Yiling Zhang
Write Togethers (for grad students) (March 11, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491991@events.umich.edu Event Begins: Monday, March 11, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-03-11T09:00:00-04:00 2019-03-11T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
PhD Defense: Xiangkun Shen (March 11, 2019 2:00pm) https://events.umich.edu/event/61589 61589-15150262@events.umich.edu Event Begins: Monday, March 11, 2019 2:00pm
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Xiangkun Shen

DATE: Monday, March 11, 2019

CHAIR(s): Viswanath Nagarajan

TITLE OF DISSERTATION: Linear and Convex Programming based Algorithms for Network Design

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Lecture / Discussion Mon, 25 Feb 2019 11:54:05 -0500 2019-03-11T14:00:00-04:00 2019-03-11T16:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Xiangkun Shen
PhD Defense: Lauren Steimle (March 11, 2019 3:30pm) https://events.umich.edu/event/61590 61590-15150266@events.umich.edu Event Begins: Monday, March 11, 2019 3:30pm
Location: Lurie Robert H. Engin. Ctr
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Lauren Steimle

CHAIR(s): Brian Denton

TITLE OF DISSERTATION: Stochastic Dynamic Optimization Under Ambiguity

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Lecture / Discussion Mon, 25 Feb 2019 11:49:30 -0500 2019-03-11T15:30:00-04:00 2019-03-11T17:30:00-04:00 Lurie Robert H. Engin. Ctr U-M Industrial & Operations Engineering Lecture / Discussion Lauren Steimle
PhD Defense: Weidong Chen (March 14, 2019 3:00pm) https://events.umich.edu/event/61587 61587-15150261@events.umich.edu Event Begins: Thursday, March 14, 2019 3:00pm
Location: Lurie Robert H. Engin. Ctr
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Weidong Chen

PLACE: 1210 LEC (Lurie Engineering Center)

CHAIR(s): Cong Shi, Izak Duenyas

TITLE OF DISSERTATION: Online Learning Algorithms for Stochastic Inventory and Queueing Systems

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Lecture / Discussion Mon, 25 Feb 2019 11:54:37 -0500 2019-03-14T15:00:00-04:00 2019-03-14T17:00:00-04:00 Lurie Robert H. Engin. Ctr U-M Industrial & Operations Engineering Lecture / Discussion Weidong Chen
Write Togethers (for grad students) (March 18, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491992@events.umich.edu Event Begins: Monday, March 18, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-03-18T09:00:00-04:00 2019-03-18T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
Rackham/Sweetland Workshops: Writing Literature Reviews in the Natural Sciences (March 18, 2019 12:30pm) https://events.umich.edu/event/60373 60373-14866474@events.umich.edu Event Begins: Monday, March 18, 2019 12:30pm
Location: North Quad
Organized By: Sweetland Center for Writing

A literature review is a foundational component of the dissertation that provides important context for one's research and writing. It is also a challenging organizational project. In this workshop, we will explore the purpose and conventions of literature reviews in the natural sciences. The workshop will include a discussion of the genre of literature reviews, why they are important, and how they can be organized. Our ultimate goal will be to equip graduate students with both an understanding of different approaches to literature reviews as well as strategies for summarizing the literature and organizing content.

Register at https://lsa.umich.edu/sweetland/graduates/sweetland-rackham-workshops.html

Rackham / Sweetland Workshops, co-sponsored by the Rackham Graduate School

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Workshop / Seminar Thu, 24 Jan 2019 15:35:47 -0500 2019-03-18T12:30:00-04:00 2019-03-18T14:00:00-04:00 North Quad Sweetland Center for Writing Workshop / Seminar North Quad
PhD Defense: Crystal Green (March 19, 2019 10:00am) https://events.umich.edu/event/62197 62197-15311072@events.umich.edu Event Begins: Tuesday, March 19, 2019 10:00am
Location: Lurie Robert H. Engin. Ctr
Organized By: Nuclear Engineering and Radiological Sciences

Title: Automated Deformable Mapping Methods to Relate Corresponding Lesions in 3D X-ray and 3D Ultrasound Breast Images

Co-Chair: Prof. Mitchell Goodsitt
Co-Chair: Prof. Alex Bielajew

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Lecture / Discussion Fri, 15 Mar 2019 16:20:02 -0400 2019-03-19T10:00:00-04:00 2019-03-19T12:00:00-04:00 Lurie Robert H. Engin. Ctr Nuclear Engineering and Radiological Sciences Lecture / Discussion Crystal Green PhD defense flyer
Dissertation Defense: Enhancing Prediction Efficacy with High-Dimensional Input Via Structural Mixture Modeling of Local Linear Mapping (March 20, 2019 11:00am) https://events.umich.edu/event/62194 62194-15311061@events.umich.edu Event Begins: Wednesday, March 20, 2019 11:00am
Location: West Hall
Organized By: Department of Statistics

Regression is a widely used statistical tool to discover associations between variables. The estimated relationship can be further utilized for predicting new observations. Obtaining reliable prediction outcomes is a challenging task. When building a regression model, several difficulties such as high dimensionality in predictors, non-linearity of the associations and the unreliable results caused by outliers could deteriorate the results. Furthermore, the prediction error increases if the newly acquired data might not be processed carefully. In this dissertation, we aim at improving prediction performance by enhancing the model robustness at the training stage and duly handling the query data at the testing stage. We propose two methods to build robust models. One focuses on adopting a parsimonious model to limit the number of parameters and a refinement technique to enhance model robustness. We design the procedure to be carried out on parallel systems and further extend their abilities of handling complex and large-scale datasets. The other method restricts the parameter space to avoid the singularity issue and takes up the trimming techniques to limit the influence of outlying observations. We build both approaches by using the mixture-modeling principle to accommodating data heterogeneity without uncontrollably increasing model complexity. Both methods show their abilities to improve prediction performance, compared to existing approaches, in applications such as magnetic resonance vascular fingerprinting and source separation in single-channel polyphonic music, among others. To evaluate model robustness, we develop an efficient approach to generating adversarial samples, which could induce large prediction errors yet are difficult to detect visually. Finally, we propose a preprocessing system to detect and repair different kinds of abnormal testing samples for prediction efficacy, when testing samples are either corrupted or adversarially perturbed.

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Other Tue, 16 Jul 2019 14:26:50 -0400 2019-03-20T11:00:00-04:00 2019-03-20T13:00:00-04:00 West Hall Department of Statistics Other West Hall
PhD Defense: Bennett Williams (March 20, 2019 3:30pm) https://events.umich.edu/event/62264 62264-15337502@events.umich.edu Event Begins: Wednesday, March 20, 2019 3:30pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Nuclear Engineering and Radiological Sciences

Title: Applications of Principal Component Analysis for Position-Sensitive Semiconductor Detectors

Chair: Professor Zhong He

Abstract: Although the landscape of nuclear safeguards changes as new technologies emerge, gamma-ray spectroscopy remains a fundamental component of nuclear material detection and monitoring protocols. Systems that feature pixelated, large- volume CdZnTe detectors provide a viable option for gamma-ray spectrometers owing to their portability, room-temperature operation, imaging capabilities and high-performance energy resolution. Despite recent advances in data acquisition technology, CdZnTe detector systems fail to achieve comparable energy resolution to the industry-leading performance provided by high-purity germanium detectors. This limits the utility of CdZnTe systems in gamma-ray spectroscopy, as the confidence intervals of analyses pertinent to nuclear safeguards depend heavily on energy resolution.

In order to address this deficiency in CdZnTe detector technology, a fundamentally new approach for calibrating energy is proposed. Conventional calibration methods for position-sensitive semiconductor detectors rely heavily on theoretical models. Despite years of extensive study on charge transport properties in position-sensitive semiconductor detectors, the underlying models introduce systematic error in the energy reconstruction process. Under the proposed framework, predictive models are constructed via principal component analysis in an attempt to reduce the reliance on theoretical models and human intuition.

This work provides a practitioner's account of how one can leverage information extracted by principal component analysis to improve energy resolution for position-sensitive semiconductor detectors. This methodology is adapted to address unique challenges presented by a variety of events observed in position-sensitive detectors. For the detectors used in this work, single-pixel, two- pixel and three-pixel event energy resolution at 662 keV improve by approximately 10\% relative to the leading alternative. The proposed calibration procedure is generalized to accommodate event reconstruction for gamma-rays in the entire dynamic range.

Energy calibration via principal component analysis is intended to provide a practical alternative to conventional techniques. Calibration requirements and computational time are monitored closely to ensure that the application of the proposed technique does not become overly burdensome. Calibration measurements based on principal component analysis require no more time or data than conventional methods. The processing time per detection event is significantly reduced compared to computationally-intensive alternatives under this framework, enabling the processing speed necessary for a wide variety of nuclear safeguards applications.

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Lecture / Discussion Mon, 18 Mar 2019 15:21:16 -0400 2019-03-20T15:30:00-04:00 2019-03-20T17:30:00-04:00 Lurie Robert H. Engin. Ctr Nuclear Engineering and Radiological Sciences Lecture / Discussion Bennett Williams PhD Defense flyer
Local Learning at Literati: The Six Senses of Buddhism (March 20, 2019 7:00pm) https://events.umich.edu/event/59517 59517-14748076@events.umich.edu Event Begins: Wednesday, March 20, 2019 7:00pm
Location: Museum of Art
Organized By: University of Michigan Museum of Art (UMMA)

Buddhist experiences can engage six senses: taste, touch, sight, sound, smell, and thought. In this evening presentation that ranges from incense to hand-stitched vestments to meditation, get a peek into the concepts and concerns that inspired the University of Michigan Museum of Art exhibition The Six Senses of Buddhism with Susan Dine, UMMA curatorial fellow 2017-18 and exhibition curator. In the spirit of experience, be ready for some hands-on interaction. The incorporation of incense may trigger the scent sensitive.

Susan Dine is a doctoral candidate in the University of Michigan's History of Art department. She served as a curatorial fellow at the University of Michigan Museum of Art in 2017-2018 and has been a research fellow at the Smithsonian's Freer | Sackler for this academic year (2018-2019). Her dissertation explores representations of language in medieval Buddhist visual culture of Japan.

For more information about the Local Learning series at Literati Bookstore, visit www.literatibookstore.com.

Lead support for The Six Senses of Buddhism is provided by the Japan Business Society of Detroit Foundation and the University of Michigan Center for Japanese Studies.

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Other Wed, 06 Mar 2019 18:16:23 -0500 2019-03-20T19:00:00-04:00 2019-03-20T20:30:00-04:00 Museum of Art University of Michigan Museum of Art (UMMA) Other Museum of Art
PhD Defense: Victor Fuentes (March 21, 2019 11:00am) https://events.umich.edu/event/62037 62037-15276118@events.umich.edu Event Begins: Thursday, March 21, 2019 11:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Victor Fuentes

CHAIR: Jon Lee

TITLE OF DISSERTATION: On Computing Sparse Generalized Inverses
and Sparse-Inverse/Low-Rank Decompositions

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Lecture / Discussion Mon, 11 Mar 2019 15:46:50 -0400 2019-03-21T11:00:00-04:00 2019-03-21T13:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
Dissertation Defense: Debiased post selection inference (March 25, 2019 10:00am) https://events.umich.edu/event/62360 62360-15355259@events.umich.edu Event Begins: Monday, March 25, 2019 10:00am
Location: Randall Laboratory
Organized By: Department of Statistics

This dissertation concerns the post-selection bias issue in statistical inference on treatment effects when a large number of covariates are present in a linear or partially linear model. While the estimation bias in an under-fitted model is well understood, we address a lesser known bias that arises from an over-fitted model. We show that the over-fitting bias can be reduced or eliminated through data splitting, and more importantly, smoothing over random data splits or bootstrap-induced splits can be pursued to mitigate the efficiency loss. We also discuss some of the existing methods for debiased inference and provide insights into their intrinsic bias-variance trade-off, which leads to an improvement in bias controls. Based on these insights, we thoroughly study the connections between our current framework and average treatment effects estimation under the Neyman-Rubin causal model. A careful analysis shows that the post-selection bias issue can exist in a wider range of treatment effect estimation procedures. Under appropriate conditions, we show that our proposed estimators for the treatment effects are asymptotically normal and their variances can be well estimated. We discuss the pros and cons of various methods both theoretically and empirically, and show that the proposed methods are valuable options in post-selection inference.

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Other Tue, 16 Jul 2019 14:26:31 -0400 2019-03-25T10:00:00-04:00 2019-03-25T12:00:00-04:00 Randall Laboratory Department of Statistics Other flyer
PhD Defense: Hao Yuan (March 28, 2019 1:00pm) https://events.umich.edu/event/62038 62038-15276119@events.umich.edu Event Begins: Thursday, March 28, 2019 1:00pm
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Hao Yuan

CHAIR: Cong Shi

TITLE OF DISSERTATION: Data Driven Optimization:
Theory and Applications in Supply Chain Systems

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Lecture / Discussion Mon, 11 Mar 2019 15:46:26 -0400 2019-03-28T13:00:00-04:00 2019-03-28T15:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
Write Togethers (for grad students) (April 1, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491993@events.umich.edu Event Begins: Monday, April 1, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-04-01T09:00:00-04:00 2019-04-01T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
Dissertation Defense: Approaches for identifying biases in single-cell RNA-sequencing data (April 1, 2019 12:00pm) https://events.umich.edu/event/62523 62523-15397100@events.umich.edu Event Begins: Monday, April 1, 2019 12:00pm
Location: West Hall
Organized By: Department of Statistics

Single-cell RNA-sequencing (scRNA-seq) involves the measurement of gene expression from isolated single cells, with the potential to illuminate cellular heterogeneity within complex tissue samples. However, scRNA-seq data are subject to a large number of technical effects. In this work, we present two approaches that can be applied for removing technical effects from scRNA-seq data in downstream analyses. The first part introduces different concepts of stably expressed genes with respect to true biological expression. Different classes of stably expressed genes may capture different technical effects, assisting in the removal of these technical effects and increasing the biological interpretability of later results. We find that genes associated with the cytosolic ribosomal structure of cells are enriched with genes that are stably expressed in proportion to the total RNA content of a cell. The cytosolic ribosomal genes can serve as a foundation for a gene set incorporated into normalization procedures to remove some technical effects associated with cell size. The second part describes a procedure to analyze which genes are captured with more accuracy from scRNA-seq experiments. The number of reads captured for each unique molecular identifier (UMI) informs how well a specific gene is captured within a dataset. Reliably detectable genes can then be applied to downstream analyses, correcting for additional technical effects. Together, these two projects provide two approaches to identifying genes that capture technical effects in scRNA-seq data and can be applied to later normalization procedures.

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Other Tue, 16 Jul 2019 14:26:14 -0400 2019-04-01T12:00:00-04:00 2019-04-01T14:00:00-04:00 West Hall Department of Statistics Other flyer
Write Togethers (for grad students) (April 8, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491994@events.umich.edu Event Begins: Monday, April 8, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-04-08T09:00:00-04:00 2019-04-08T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
Write Togethers (for grad students) (April 15, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491995@events.umich.edu Event Begins: Monday, April 15, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-04-15T09:00:00-04:00 2019-04-15T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
EEB dissertation defense: Disentangling species boundaries and the evolution of habitat specialization for the ecologically diverse mite family Acaridae (April 17, 2019 10:00am) https://events.umich.edu/event/62843 62843-15483789@events.umich.edu Event Begins: Wednesday, April 17, 2019 10:00am
Location: Rackham Graduate School (Horace H.)
Organized By: Ecology and Evolutionary Biology

Pamela presents her dissertation defense

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Presentation Mon, 15 Apr 2019 11:11:51 -0400 2019-04-17T10:00:00-04:00 2019-04-17T11:00:00-04:00 Rackham Graduate School (Horace H.) Ecology and Evolutionary Biology Presentation Tyrophagus, commonly called mould or cheese mite
PhD Defense: Haining Zhou (April 18, 2019 11:00am) https://events.umich.edu/event/63190 63190-15587265@events.umich.edu Event Begins: Thursday, April 18, 2019 11:00am
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Sparse Functional Expansion Based Method for Solving High-dimensional Uncertainty Quantification Problems and Its Application to the Nuclear Transient Test Reactor (TREAT)

Chair: Prof. Thomas Downar

Abstract: The uncertainty quantification (UQ) in computational calculations is to quantitatively characterize the uncertainties in the quantities of interest resulted from input parameter uncertainties. UQ is essential in computational analysis since it predicts the range and the likelihood of possible model outcomes when some model parameters are not known as exact values. It is also usually the case that UQ is computationally intensive when the models are sophisticated, and the random space can have high dimensionality as it often requires multiple model evaluations. The effort in developing UQ methods that requires fewer sample evaluations includes the development of adjoint-based methods and the design of efficient sampling schemes. However, to apply these methods to specific models of interest, users must have either specialty in the modeling of the responses or must adopt some assumptions on the distribution of the model responses prior to the analysis. Methods to effectively reduce the number of sample evaluations required while being able to extract the detailed distribution information of the responses of interest remains a critical challenge facing researchers in the UQ community.
In this thesis, we propose a lasso regularization-based data-driven adaptive algorithm for finding a sparse solution of the generalized polynomial chaos expansion of a response of interest. The sparsity in the functional expansion solution determines the reduction in the dimensionality of the uncertainty space in the system that can be achieved. This makes it possible to effectively reduce the necessary number of sample evaluations without compromising the UQ analysis. The terms “data-driven” and “adaptive” mean that the sparsity in the provided solution is a model property that is inherent in the design of the algorithm. The algorithm automatically estimates the importance of the random parameters in the system and decides on the active set of orthogonal polynomials to use in the resulting expansion. Hence our method is very general, and users do not have to adopt model-based assumptions or make intrusive modifications to their deterministic program in order to apply it.

The development of the algorithm was inspired by the high-dimensional and computationally expensive UQ problems that are encountered while modeling the TREAT reactor. In this application we developed the algorithm for the uncertainty quantification of the modeling of the transient tests that were previously performed with the TREAT reactor. Results show that our algorithm can effectively reduce the number of sample evaluations for high-dimensional UQ problems while providing functional expansion solutions that are stable and that can accurately predict a wide range of responses of interest.

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Lecture / Discussion Tue, 16 Apr 2019 17:00:37 -0400 2019-04-18T11:00:00-04:00 2019-04-18T13:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion Flyer of Haining Zhou defense
PhD Defense: Jipu Wang (April 18, 2019 1:30pm) https://events.umich.edu/event/63189 63189-15587264@events.umich.edu Event Begins: Thursday, April 18, 2019 1:30pm
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Application of the Method of Manufactured Solutions to Verify the Method of Characteristics for Reactor Analysis

Chair(s): Prof. Bill Martin, Prof. Benjamin Collins

Abstract: The purpose of this study is to theoretically analyze the error of the method of characteristics (MOC) with respect to different independent variables and to develop the methodology to apply the method of manufactured solutions (MMS) to verify an MOC-based code system for reactor analysis. The MMS methodology has been applied to fixed source problems, criticality eigenvalue problems, as well as multiphysics problems coupling neutronics with other physics essential to reactor analysis. Theoretical predictions for the order of accuracy as a function of mesh spacing (spatial and angular meshes) are compared with numerical results with MMS. The coupling of spatial and angular errors obscured the convergence with the spatial mesh, and a method for removing the angular error from the numerical solution was developed, resulting in excellent agreement between theory and numerical results for the spatial order of accuracy. The application of MMS to the criticality eigenvalue problem yields an inhomogeneous eigenvalue problem, which does not have a unique solution. This was addressed by adding a constraint to the application code eigenvalue solver. An alternative method for applying MMS to the criticality eigenvalue problem was developed, based on modifying the fission cross section, and this avoids the inhomogeneous eigenvalue problem. Both methods yielded numerical results for the order of accuracy that were in excellent agreement with theory. The MMS methodology was also applied to the C5G7 benchmark problem, a seven-group small core with realistic geometry, and the numerical solution reproduced the assumed MMS solution everywhere to within negligible error.
The findings and conclusions are that MMS is a powerful, flexible and rigorous tool for reactor code verification, which is an essential step in developing a complex scientific computing code. This study contributes to reactor analysis by quantifying and removing errors associated with certain numerical approximations, revealing the rate of convergence with respect to the refined variable and providing a verification methodology for both reactor physics and coupled multiphysics applications.

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Lecture / Discussion Tue, 28 May 2019 10:21:18 -0400 2019-04-18T13:30:00-04:00 2019-04-18T15:30:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion Flyer for Jipu Wang defense
Robotics PhD Defense: Josh Mangelson (April 19, 2019 9:30am) https://events.umich.edu/event/62856 62856-15483804@events.umich.edu Event Begins: Friday, April 19, 2019 9:30am
Location: Michigan Memorial Phoenix Project
Organized By: Michigan Robotics

In manufacturing, teams of robotics systems, working in coordination with one another, have led to dramatic increases in safety, efficiency, and profit. Collaborative teams of robotic vehicles working together in unstructured environments have the potential to yield similar gains in a variety of application areas including automatic inspection of underwater structures. However, autonomous collaboration in real-world environments is significantly more difficult than in the factory. The main reason for this is because in an unstructured environment, fundamental information such as the position of the robotic agent, its relationship to other agents, and a model of the robot's surroundings all have to be estimated by the robotic vehicle online, while their estimation can be simplified or engineered out of the problem in a structured one. This is further complicated by the fact that in underwater environments, failure of a navigation or perception algorithm that estimates the above quantities can result in significant damage or the loss of a vehicle. Moreover, existing algorithms for navigation and mapping in unstructured environments, tend to fail in the presence of outlier measurements, when given a bad initialization, or when using an inaccurate characterization of pose uncertainty.

In this thesis, we propose four methods that bring us closer to robust and consistent multi-agent autonomous inspection. The first is a method for handling outlier measurements when merging maps generated by two agents collaboratively inspecting a structure. The proposed method uses graph theory to enforce that the selected set of measurements are consistent with one another resulting in more consistent maps than existing methods. The second is an initialization agnostic method for aligning robot trajectories based on low-dimensional data. The third is a way of formulating the simultaneous localization and mapping (SLAM) problem as a convex polynomial optimization problem. This enables us to guarantee that the trajectory estimated by the robotic vehicle is the true solution to the posed optimization problem. Finally, the fourth is method that uses Lie group theory and the Lie algebra to accurately characterize the uncertainty of jointly correlated poses. We evaluate the proposed methods and show that they outperform existing state-of-the-art algorithms.

We conclude with a discussion of "reliable autonomy" by describing a set of additional problems that need to be solved to enable reliable, large-scale, fully-autonomous, multi-agent inspection of underwater structures.

Joshua Mangelson is a Ph.D. Candidate in Robotics at the University of Michigan. His interests lie in the development of navigation, mapping, and perception algorithms that enable the design of reliable field robotic systems that can operate consistently in unstructured environments. He is especially interested in the development of large-scale multi-agent teams for autonomous inspection of underwater structures. He is the recipient of the IEEE ICRA Best Multi-Robot Paper Award and the IEEE OCEANS Best Poster Award both in 2018.

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Presentation Fri, 12 Apr 2019 11:33:03 -0400 2019-04-19T09:30:00-04:00 2019-04-19T11:30:00-04:00 Michigan Memorial Phoenix Project Michigan Robotics Presentation Mangelson with underwater robot
Write Togethers (for grad students) (April 22, 2019 9:00am) https://events.umich.edu/event/58376 58376-14491996@events.umich.edu Event Begins: Monday, April 22, 2019 9:00am
Location: North Quad
Organized By: Sweetland Center for Writing

Write Together sessions provide structure, space, and time for graduate writers working on papers, theses, and dissertations. These Monday Write Together sessions (from 9am-noon) bring graduate writers into common quiet space to work. Sweetland will offer short presentations on writing and work productivity, distribute writing support and information, and provide coffee, tea, and refreshments.

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Other Tue, 11 Dec 2018 11:46:28 -0500 2019-04-22T09:00:00-04:00 2019-04-22T12:00:00-04:00 North Quad Sweetland Center for Writing Other flyer
EEB dissertation defense: Drivers of epidemic timing and size in a natural aquatic system (April 23, 2019 2:00pm) https://events.umich.edu/event/62169 62169-15308869@events.umich.edu Event Begins: Tuesday, April 23, 2019 2:00pm
Location: Biological Sciences Building
Organized By: Ecology and Evolutionary Biology

Clara presents her dissertation defense

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Presentation Mon, 15 Apr 2019 15:24:21 -0400 2019-04-23T14:00:00-04:00 2019-04-23T15:00:00-04:00 Biological Sciences Building Ecology and Evolutionary Biology Presentation Daphnia
Ph.D. Defense: Kunal Rambhia (April 24, 2019 12:00pm) https://events.umich.edu/event/63081 63081-15653093@events.umich.edu Event Begins: Wednesday, April 24, 2019 12:00pm
Location:
Organized By: Biomedical Engineering

The purpose of this dissertation is to advance the development of a drug-loaded polymeric scaffold for bone tissue engineering as a promising synthetic substitute for autologous bone grafts. While still considered the reference standard for treatment of large volume bone injuries, autologous grafts are limited in their clinical applications by donor site morbidity, limited tissue availability, and potential for graft failure. The clinical use of bone morphogenetic proteins (BMP) as bone graft substitutes has resulted in serious side effects due in part to the supraphysiologic dose of BMP required for adequate healing. New approaches to treating these large volume injuries are needed. Our proposed strategy utilizes tissue engineering and drug delivery concepts to develop synthetic drug-loaded biomimetic scaffolds for bone regeneration.

To enhance the osteogenic potential of synthetic scaffolds, we sought to simultaneously deliver two growth factors: recombinant human BMP-7 and recombinant human basic fibroblast growth factor (FGF-2). We first established an in vitro cell culture model using rabbit mesenchymal stem cells to evaluate and optimize the dose and duration of FGF-2 treatment in combination with BMP-7 as a basis for our in vivo studies. We subsequently encapsulated the growth factors in poly (lactic-co-glycolic acid) (PLGA) nanospheres with tailored release patterns for each factor. Low molecular weight PLGA was used to encapsulate FGF-2 in fast releasing nanospheres while high molecular weight PLGA was used to encapsulate BMP-7 in slow releasing nanospheres. We found that FGF-2 augmented BMP-7-directed ectopic bone formation in a subcutaneous mouse model, and that the synergistic effect was dependent on the dose and duration of FGF-2 treatment. We also found that FGF-2 may contribute to enhanced bone formation due to its effects on cell migration and proliferation, as well as its angiogenic and osteogenic effects.

We then established an in vitro model to evaluate human mesenchymal stem cells in 2D monolayer and 3D culture on novel nanofibrous spongy microsphere scaffold (NF-SMS). We used a similar PLGA-based drug delivery system to control the release kinetics of FGF-2 and BMP-7 and conjugated drug-loaded PLGA nanospheres to the injectable NF-SMS scaffold. In a critical size cranial defect mouse model, low dose FGF-2 combined with BMP-7 enhanced bone regeneration over BMP-7 alone.

Lastly, we sought to better understand the crosstalk between the FGF-2 and BMP-7 signaling pathways through a series of experiments to measure the effect of FGF-2 on canonical BMP signaling in mouse calvarial osteoblasts. We identified a potential new link between these signaling pathways and propose a new mechanism by which FGF-2 signaling modulates BMP receptor activity, enhancing the phosphorylation of R-Smad1/5/9 proteins.

This research elucidates the criteria for achieving synergy between BMP-7 and FGF-2 through relevant in vitro and in vivo models. It provides guidelines for future development of biomimetic scaffolds with controlled release of multiple relevant biological cues to stimulate healing and tissue regeneration.

Chair: Peter X. Ma

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Presentation Wed, 24 Apr 2019 12:49:45 -0400 2019-04-24T12:00:00-04:00 2019-04-24T13:00:00-04:00 Biomedical Engineering Presentation Biomedical Engineering
Dissertation Defense: Design and Analysis of Sequential Randomized Trials with Applications to Mental Health and Online Education (April 25, 2019 12:00pm) https://events.umich.edu/event/63227 63227-15595499@events.umich.edu Event Begins: Thursday, April 25, 2019 12:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Dynamic treatment regimes, also called adaptive interventions, guide sequential treatment decision-making in a variety of fields, including healthcare and education. Dynamic treatment regimes accommodate differences between individuals and changes in individuals over time. Sequential randomized trials are a specific type of trial design useful for developing high-quality dynamic treatment regimes. Sequential randomized trials utilize re-randomization of individuals over time in order to discover how to sequence, time, and personalize treatments. Two of the most commonly used sequential randomized trial designs are sequential multiple assignment randomized trials and micro-randomized trials.

In this thesis, we contribute to both the design and analysis of sequential randomized trials. We describe design considerations for sequential randomized trials in online education. We present the design and analysis for a sequential randomized trial developed to reduce dropout in a massively open online course. We also develop statistical methodology and sample size formulae for sequential multiple assignment randomized trial designs which include cluster-level randomization. The techniques are inspired by a trial aiming to develop high-quality dynamic treatment regimes for mental health clinics. Lastly, we illustrate the design, describe the analysis, and present results of a large micro-randomized trial aiming to develop mobile health interventions for improving medical interns' mental health.

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Other Tue, 16 Jul 2019 14:25:45 -0400 2019-04-25T12:00:00-04:00 2019-04-25T14:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
Dissertation Defense: Scalable classification methods with applications to healthcare claims and automotive dealership data (April 25, 2019 3:00pm) https://events.umich.edu/event/63305 63305-15634623@events.umich.edu Event Begins: Thursday, April 25, 2019 3:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

With technology advances in recent years, sensing and media storage capabilities have enabled the generation of enormous amounts of information, often in the form of large data sets in different scientific fields such as biology, marketing and medicine. As this vast amount of data has opened a wealth of opportunities for data analysis, computationally scalable methods become increasingly important for statistical modeling. This thesis focuses on developing scalable classification methods and their applications to automotive dealerships and healthcare problems.

The first project studies parameter estimation of customers' and dealerships' consumption preference for the automotive market, which determines the manufacturers' profits. Most existing methods assume that the dealerships are rational and hence aim to maximize profits, which conflicts with observations. We propose a structural Bayesian model for customers’ and dealerships’ preference which aims to maximize a flexible utility function. Further we develop an MCMC algorithm utilizing parallel computing to estimate model parameters. The model is calibrated to data from a manufacturer, and the estimates are used in a simulation model to design optimal financial incentive offers to maximize profits.

The second project focuses on the two-class classification problem based on the area under the receiver operating curve (AUC), which is often considered as a more comprehensive measure for the performance of a classifier comparing with the misclassification error. Maximizing the empirical AUC directly, however, is computationally challenging as naive computation of the AUC requires quadratic time complexity, while computing the misclassification error only requires linear time complexity. Further, the optimization involves indicator functions and it is NP-hard. In this project, we propose a non-convex differentiable surrogate function for the AUC, and further develop a scalable algorithm to optimize this surrogate loss function. The proposed algorithm takes advantage of the selection tree data structure and also uses a truncated Newton strategy so that the computational complexity of the optimization scales at the quasilinear time. In the setting of linear classification, we also show that the estimated coefficients enjoy theoretical asymptotic consistency. Finally, we evaluate the performance of the proposed method using both simulation studies and two data sets, one for normal/abnormal vertebral column classification and the other for behaving/not-behaving network visit classification, and show that the proposed method outperforms the support vector machine (SVM) in terms of the AUC.

The last project is motivated by the problem of predicting midterm mortality of patients using the Ninth Revision, International Classification of Diseases (ICD-9) codes, which is relevant for healthcare and clinical research. The ICD-9 contains a list of standard six-character alphanumeric codes recording useful clinical information including patient diagnoses and procedures. However, the number of ICD-9 codes in a specific study is often large, on the order of thousands or tens of thousands, and the dependence structure among ICD-9 codes is complicated, which pose statistical challenges for using the ICD-9 codes. To address these challenges, we develop a supervised embedding method that combines an unsupervised criterion for learning latent representations of ICD-9 codes and a Deep Set neural network model for classification, which is invariant with respect to the ordering of the ICD-9 codes. The proposed supervised embedding method has the advantage of modeling the inter-relationship within ICD-9 codes and the nonlinear relationship between codes and the outcome variable simultaneously, and it can also be naturally extended to the semi-supervised learning setting. The model is trained using the stochastic gradient descent (SGD) approach, which allows the entire database to be stored on multiple computing nodes and hence makes the method suitable for analyzing large data sets. We have applied the proposed method to 1-year mortality prediction using the Medical Information Mart for Incentive Care III (MIMIC-III) database and achieved superior performance in comparison with several benchmark models.

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Other Tue, 16 Jul 2019 14:25:06 -0400 2019-04-25T15:00:00-04:00 2019-04-25T17:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Justin Haney (April 26, 2019 9:00am) https://events.umich.edu/event/62633 62633-15414529@events.umich.edu Event Begins: Friday, April 26, 2019 9:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Justin Haney

TITLE OF DISSERTATION: Modeling Hand Movements in a Sequential Reach Task with Continuous Material

CHAIR(s): Clive D'Souza

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Lecture / Discussion Wed, 27 Mar 2019 11:04:00 -0400 2019-04-26T09:00:00-04:00 2019-04-26T11:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
Dissertation Defense: Statistical Learning for Networks with Node Features (April 26, 2019 1:00pm) https://events.umich.edu/event/63262 63262-15603740@events.umich.edu Event Begins: Friday, April 26, 2019 1:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Network data represent connectivity relationships between individuals of interest and are common in many scientific fields, including biology, sociology, medicine and healthcare. Often, additional node features are also available together with the data on relationships. Both types of data contain important information about individual characteristics and the population structure. This thesis focuses on developing statistical machine learning methods and theory for network data with node features.

We first study the problem of community detection for networks with node features using a model-based approach. Most existing models make strong conditional independence assumptions between the network, features and community memberships, which limits the applicability of the model. In our work, we develop a general statistical framework to describe the dependence structure between the link structure, node features and communities. Further, we propose two families of models that are the most general under this framework with the least conditional independence assumptions between the three components. We have established mild conditions for model identifiability and developed variational EM algorithms to estimate model parameters and community memberships. Extensive simulation studies and application to a food web and a lawyer friendship network indicate that the proposed methods work well.

The second project focuses on the problem of node classification using both individual features and the network. In a classical setting, data points are assumed independent and identically distributed, and a data point is classified using only its own features. When a network between the data points is available, it often contains additional information about class memberships and can be utilized to improve classification performance. In this work, we develop a general statistical framework for network augmented classification. Under this framework, we derive the optimal Bayes classifiers for two general families of distributions incorporating node features and networks. Further, we establish asymptotic consistency results for plug-in classifiers with respect to the optimal ones under the two families. We have also applied these general approaches to specific models and developed effective classifiers for practical use. The proposed methods have been evaluated using both simulation studies and a teenage friendship network, and show promising results.

The final contribution of this thesis is on link prediction for incomplete network data. Most existing link prediction methods require at least partial observation of connections for every node. In real-world networks, however, there often exist nodes that do not have any link information, and it is of interest to make link predictions for them using only their node features. We consider a general setup in which a network consists of three types of nodes, nodes only having feature information, nodes only having link information, and nodes having both. Our goal is to make link predictions for nodes having only feature information. Under this setting, we have proposed a family of generative models for incomplete networks with node features, and we have developed a variational auto-encoder algorithm for model estimation and link prediction and investigated different encoder structures. We have also designed a cross-validation scheme under the problem setting for model selection. The proposed method has been evaluated on an online social network and two citation networks and achieves superior performance comparing with existing methods.

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Other Tue, 16 Jul 2019 14:25:25 -0400 2019-04-26T13:00:00-04:00 2019-04-26T15:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
Ph.D. Defense: Hina Aftab Khan (April 30, 2019 9:00am) https://events.umich.edu/event/63402 63402-15669549@events.umich.edu Event Begins: Tuesday, April 30, 2019 9:00am
Location: Lurie Biomedical Engineering (formerly ATL)
Organized By: Biomedical Engineering

Ovarian cancer is the most lethal gynecologic malignancy among women in the US, responsible for 14,000 deaths per year, and five-year survival rate of 25%. Within the primary and metastatic microenvironments in the ovary, peritoneal ascites and omentum, the ovarian cancer cells are subject to several mechanical stresses, including compressive stresses generated by uncontrolled cell growth in a confining space, increased tissue stiffness due to tumor cell extracellular matrix (ECM) remodeling, and increased interstitial fluid pressure due to the angiogenic growth of new leaky blood vessels. However, current models to study these stimuli within the ovarian tumor microenvironment are lacking in biophysical cues, relevant extracellular matrix dynamics and the ability to consistently sustain cells through the detachment process. The absence of consistent optimization of matrix composition and degradation mechanics also leads to occurrences of increased cytolysis during in vitro experimentation. In order to meet this critical unmet need, my Master’s thesis is focused on developing extracellular matrices that feature comparable consistent compositional, structural and mechanical cues. Additionally, these matrices facilitate biophysical modulation to be applicable over a wider range in a manner that allows for improved experimental precision. Given the range of matrix stiffness, permeability and porosity, I have developed and characterized hydrogels for designing extracellular mimics for ovarian cancer mechanotransduction studies.

In this work, I highlight the need for optimization of interpenetrating network (IPN) hydrogels’ homogeneity, thereby providing uniform adhesion during mechano-transduction experiments. Further, I optimized cell harvesting via thorough cell detachment without causing cytolysis for downstream analysis including, flow cytometry on detached cells. Moreover, I have characterized the rheologic, transport and structural properties of IPN hydrogels, and demonstrate how these can account for variation in experimental results. Overall, my thesis provides insight into the significance of hydrogel matrix composition when constructing cell scaffolds for specific cellular microenvironments.

Owing to their success as natural hydrogel scaffolds, I utilized alginate and agarose to design the ovarian cancer extracellular matrices. Within these networks, collagen served as the second component of the IPN network, providing an anchoring fibrillar network for the cells within the otherwise non-fibrillar material, and further enhancing the biocompatibility of the scaffold. I varied the IPN hydrogel composition to demonstrate a relevant range structural and mechanical properties. Further, I characterized the homogeneity, morphology, fiber structure, stiffness, gelation time, permeability and porosity of IPN hydrogels. Lastly, I evaluated ovarian cancer cells for cellular function post-harvest from IPN hydrogels, to demonstrate successful detachment and degradation of the surrounding matrix.

The results of this study enable tailoring of the IPN hydrogel extracellular matrices according to required mechanical, structural, and biophysical parameters for not only ovarian cancer, but also other originating tissues for improved robustness and reliability of the in vitro cancer bioengineering models.

Chair: Dr. Geeta Mehta

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Presentation Fri, 26 Apr 2019 13:27:56 -0400 2019-04-30T09:00:00-04:00 2019-04-30T10:00:00-04:00 Lurie Biomedical Engineering (formerly ATL) Biomedical Engineering Presentation Biomedical Engineering
PhD Defense: Ece Sanci (April 30, 2019 10:00am) https://events.umich.edu/event/62592 62592-15407993@events.umich.edu Event Begins: Tuesday, April 30, 2019 10:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Ece Sanci

TITLE OF DISSERTATION: Strategies for Disaster Preparedness and Disruption Risk Mitigation

CHAIR(s): Mark Daskin

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Lecture / Discussion Wed, 27 Mar 2019 11:04:21 -0400 2019-04-30T10:00:00-04:00 2019-04-30T12:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
Ph.D. Defense: Riley Doherty (April 30, 2019 1:00pm) https://events.umich.edu/event/63350 63350-15653092@events.umich.edu Event Begins: Tuesday, April 30, 2019 1:00pm
Location: Industrial and Operations Engineering Building
Organized By: Biomedical Engineering

Human skin plays vital roles in both the sensory system and thermoregulation, and also provides an important line of defense for the body from the external environment. However, experimental methods that enable in vivo characterization of this multi-layered organ are currently lacking. Soft tissue artificial phantoms can be used to diagnose certain skin diseases or to validate the efficacy of medical procedures. This study proposes a non-invasive method to obtain three-dimensional displacement measurements of soft tissue using suction and digital image correlation. We developed a measurement device capable of applying suction loading while capturing images of the full-field deformation of the area of interest. Soft tissue phantoms were fabricated, and a temporary speckle pattern was applied to each surface to provide unique features required for image correlation. A soft tissue phantom with less stiff inclusions of various diameters and a 3D printed ellipsoid was prepared. Analysis was performed using an open-source software, DICe, and both peak displacement and pressure were further parameterized for comparison metrics. The stiffness of each material was validated by comparison to each other and a hard surface. The softer inclusions were not detected, however, the material with inclusions behaved differently than the control, indicating an overall change in material properties. Preliminary results support the use of the parameterizations as comparison metrics and demonstrate the successful application of 3D-DIC to measure deformation of a surface under suction loading. The device can be modified in the future to enable measurement of surfaces with larger contours or smaller regions of interest. The compact design of the instrument permits data collection in a range of environmental conditions outside of the lab, facilitating experiments that are currently not possible.

Chair: Deanna Gates

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Presentation Wed, 24 Apr 2019 12:46:53 -0400 2019-04-30T13:00:00-04:00 2019-04-30T14:00:00-04:00 Industrial and Operations Engineering Building Biomedical Engineering Presentation Biomedical Engineering
EEB dissertation defense: The genetic architecture of speciation in a primate hybrid zone (May 1, 2019 12:00pm) https://events.umich.edu/event/62947 62947-15520074@events.umich.edu Event Begins: Wednesday, May 1, 2019 12:00pm
Location: Rackham Graduate School (Horace H.)
Organized By: Ecology and Evolutionary Biology

Marcella presents her dissertation defense.

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Presentation Mon, 15 Apr 2019 11:12:31 -0400 2019-05-01T12:00:00-04:00 2019-05-01T13:00:00-04:00 Rackham Graduate School (Horace H.) Ecology and Evolutionary Biology Presentation Rackham Graduate School (Horace H.)
PhD Defense: Ke Liu (May 1, 2019 1:00pm) https://events.umich.edu/event/62636 62636-15414532@events.umich.edu Event Begins: Wednesday, May 1, 2019 1:00pm
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Ke Liu

TITLE OF DISSERTATION: Measuring and quantifying driver workload on limited access roads

CHAIR(s): Paul Green, Yili Liu

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Lecture / Discussion Wed, 27 Mar 2019 11:03:14 -0400 2019-05-01T13:00:00-04:00 2019-05-01T15:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
PhD Defense: Sol Lim (May 2, 2019 8:00am) https://events.umich.edu/event/62635 62635-15414530@events.umich.edu Event Begins: Thursday, May 2, 2019 8:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Sol Lim

TITLE OF DISSERTATION: Combining Inertial Sensing and Predictive Modeling for Ergonomic Exposure Assessment in Non-Repetitive Work

CHAIR(s): Clive D'Souza

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Lecture / Discussion Wed, 27 Mar 2019 11:03:37 -0400 2019-05-02T08:00:00-04:00 2019-05-02T10:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Industrial and Operations Engineering Building
Dissertation Defense: Uniform Consistency of Spectral Embeddings (May 2, 2019 10:00am) https://events.umich.edu/event/63316 63316-15636689@events.umich.edu Event Begins: Thursday, May 2, 2019 10:00am
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Spectral methods are a staple of modern statistics. For statistical learning tasks such as clustering or classification, one can featurize the data with spectral methods and then perform the task on the features. Despite the success and wide use of spectral methods, certain theoretical properties of spectral methods are not well-understood. In this oral defense, we investigate the uniform convergence (as opposed to convergence in an ``average'' sense) of the spectral embeddings obtained from the leading eigenvectors of certain similarity matrices to their population counterparts. We will first introduce necessary preliminaries and review existing results on this topic, and then explain the motivations and benefits for studying the convergence in a uniform sense. After that, we present the two main results in our work. The first result is a general perturbation result for orthonormal bases of invariant subspaces that can serve as a general recipe for establishing uniform consistency type results. The second result in an application of the first result to normalized spectral clustering---by tapping into the rich literature of Sobolev spaces and exploiting some concentration results in Hilbert spaces, we are able to prove a finite sample error bound on the uniform consistency error of the spectral embeddings in normalized spectral clustering.

The material in this oral defense is based on the first chapter of Ruofei Zhao's thesis "Convergence and Consistency Results in Spectral Clustering and Gaussian Mixture Models".

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Other Tue, 16 Jul 2019 14:24:43 -0400 2019-05-02T10:00:00-04:00 2019-05-02T12:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Selman Mujovic (May 3, 2019 3:00pm) https://events.umich.edu/event/63461 63461-15710555@events.umich.edu Event Begins: Friday, May 3, 2019 3:00pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Nuclear Engineering and Radiological Sciences

Title: The Plasma Water Reactor: A Geometric Approach to Scale Discharges for Water Treatment

Chair: Prof. John Foster

Abstract: Pollution, overdevelopment, population growth, and climate change excessively stress our freshwater quantity and quality. Conventional water treatment systems are poorly adapting to the presence of contaminants of emerging concern (CECs). CECs are: persistent, prevalent, recalcitrant, irregularly monitored, and potentially toxic at low concentrations. The inability to identify and assess CECs prior to entering the environment requires robust treatment technologies, particularly advanced oxidation processes (AOPs). AOPs are established disinfection methods that can remove CECs by producing hydroxyl radicals (•OH) in situ. Usually combinations of hydrogen peroxide (H2O2), ozone (O3), and ultraviolet (UV) light, traditional AOPs can significantly contribute to the cost of water.

Plasma interacting with liquid water can generate additional AOPs and transient radicals in solution while eliminating consumables and conversion efficiencies. Subsequently, in principle, plasma-based AOPs should be considerably cheaper and more effective than conventional AOPs. Although the plasma-water interface can facilitate vital kinetics through various pathways, approaches to date fail to scale-up due to limited oxidant transport. In this work, the Plasma Water Reactor (PWR) is proposed as a scalable high-throughput system that advantageously uses flowing water to enhance plasma formation and propagation. The PWR utilizes a close-packed lattice of water jets to mimic packed bed dielectric barrier discharges where water streams serve as the dielectric media.

The PWR was assessed in pure or single-CEC-spiked distilled water matrices. Pulser parametric kinetic studies were performed by measuring power and species concentrations while varying the pulse voltage, width, and frequency. In exclusively distilled water, H2O2 and O3 were measured for different combinations of pulser parameters. Though the pulser was power- limited, the PWR revealed relevant oxidant concentrations and variations in [H2O2]/[O3] based on chemical probes. For a given set of pulser parameters that corresponded to high oxidant dose, methylene blue, methyl tert-butyl ether, and 1,4-dioxane were decomposed. These indicator compounds demonstrated effective flow rates on the order of 0.1—0.75 gal/min for 90% removal. Since 1,4-dioxane exhibited the slowest destruction, the PWR was optimized using this compound. In addition to 1,4-dioxane, two transformation products, formate and acetate, and a plasma byproduct, nitrate, were measured. For three different pulser configurations, 1,4-dioxane kinetics were analyzed and the PWR achieved at least 0.5-log reduction, which implies sufficient oxidation. 1,4-dioxane decay displayed different order of reaction rates and real-time oxidant measurements confirmed [H2O2]/[O3] spanned several orders of magnitude. Thus, the PWR demonstrated the ability to vary kinetics.

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Lecture / Discussion Wed, 01 May 2019 15:01:03 -0400 2019-05-03T15:00:00-04:00 2019-05-03T17:00:00-04:00 Lurie Robert H. Engin. Ctr Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer for Selman Mujovic PhD Defense
Ph.D. Defense: Susannah Engdahl (May 9, 2019 9:00am) https://events.umich.edu/event/63349 63349-15653091@events.umich.edu Event Begins: Thursday, May 9, 2019 9:00am
Location: Central Campus Recreation Building (Bell Pool)
Organized By: Biomedical Engineering

Despite the significant functional limitations imposed by upper limb loss, little research has focused on quantifying the functional success and satisfaction of prosthesis users. Most existing evidence comes from surveys, rather than experimental outcomes. Without a quantitative baseline, it is difficult to know where to focus attention for improvement in future prosthesis designs or to demonstrate whether new designs offer advantages over existing technologies. Thus, the goal of this dissertation was to quantify how functional outcomes and satisfaction relate to the type of prosthesis used.

The first aim was to determine if prosthesis type affects embodiment, or the extent to which prosthesis users perceived their prosthesis to be part of their body. We quantified embodiment for body-powered (BP) and myoelectric (MYO) prosthesis users based on a survey and two objective measurements of body schema and peripersonal space. Although BP users reported a stronger sense of agency over their prostheses in comparison to MYO users, other measures did not consistently differentiate experiences of embodiment based on prosthesis type. However, measurements of body schema varied depending on the cause of limb loss.

The second aim was to determine if prosthesis type impacts movement quality during activities of daily living. As an initial step for this aim, we quantified the reliability of movement quality metrics (three measures of smoothness and one measure of straightness) in healthy adults performing a variety of different tasks. Based on these findings, we then compared movement quality in BP and MYO prosthesis users during a subset of tasks (moving a can from a low shelf to a high shelf, placing a pill in a pillbox, and placing a pushpin in a bulletin board) using the metrics that had the highest reliability. All movements were slower when performed with MYO prostheses, except for the reaching phase of the pill task. Object manipulation movements were consistently less smooth when performed with MYO prostheses. However, differences in curvature of the reaching movements between the prosthesis types varied across tasks.

The third aim was to determine if prosthesis type affects kinematic compensations during activities of daily living. We quantified lateral lean, axial rotation, and flexion of the trunk during the same three activities of daily living. The range of motion was greater in all directions for BP prostheses during each task—except axial rotation and flexion during the pin task, which were greater for MYO prostheses.

The fourth aim was to explore the factors associated with interest in noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. An online survey collected opinions from 232 individuals with upper limb loss on the interfaces. Relationships between interest in the interfaces and demographics, limb loss characteristics, and prosthesis use history were defined using bivariate analysis and logistic regression. There was increased interest in the invasive interfaces among individuals who were younger, had unilateral limb loss, or had acquired limb loss.

Taken together, these aims suggest that BP prostheses may promote embodiment and smooth movement, while MYO prostheses may minimize compensatory movement. Although emerging prosthesis technologies requiring surgical intervention may not be accepted by all individuals with upper limb loss, functional outcomes with these technologies should be compared to outcomes with existing BP and MYO prostheses to demonstrate the relative merits of each design.

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Presentation Wed, 24 Apr 2019 12:39:22 -0400 2019-05-09T09:00:00-04:00 2019-05-09T10:00:00-04:00 Central Campus Recreation Building (Bell Pool) Biomedical Engineering Presentation Biomedical Engineering
Robotics PhD Defense: Ross Hartley (May 10, 2019 4:00pm) https://events.umich.edu/event/63476 63476-15718784@events.umich.edu Event Begins: Friday, May 10, 2019 4:00pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Michigan Robotics

Ross is a PhD student working on biped robot control and is advised by Professor Jessy Grizzle. He received a Bachelor's degree in Electrical Engineering from the University of Louisiana at Lafayette. His research interests include control systems, legged robots, and computer vision.

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Presentation Thu, 09 May 2019 06:35:37 -0400 2019-05-10T16:00:00-04:00 2019-05-10T18:00:00-04:00 Lurie Robert H. Engin. Ctr Michigan Robotics Presentation ross with MARLO
Ph.D. Defense: Jared Houghtaling (May 13, 2019 10:00am) https://events.umich.edu/event/63458 63458-15710552@events.umich.edu Event Begins: Monday, May 13, 2019 10:00am
Location: Lurie Biomedical Engineering
Organized By: Biomedical Engineering

Molecular diagnosis has proven to be a powerful tool for early detection of neurodegenerative disease, but research in this field is still relatively nascent. In Alzheimer’s Disease specifically, levels of microtubule associated protein tau and amyloid-beta1-42 in cerebrospinal fluid are becoming reliable pathological indicators. The current gold standard for detecting these biomarkers is an enzyme-linked immunosorbent assay, and while this method has a limit of detection on the order of pg mL-1, it lacks the ability to provide information about aggregation extent and structure on a per-protein basis. From a disease standpoint, neurological pathologies are often extremely complex in their biological manifestation, and precise mechanisms for many of these diseases are still being discovered and revised. A thorough understanding of in situ structure and properties of neurological disease-related proteins would likely help clarify some of these complicated mechanisms. Resistive-pulse methods may be useful in this effort, as they can determine specific biomarker concentrations and can also unveil multiple physical qualities of single proteins or protein aggregates in an aqueous sample. The latter capability is critical and could allow for both earlier diagnoses and a stronger mechanistic understanding of neurological disease progression.

The work presented in this dissertation, therefore, represents broad efforts toward developing a nanopore-based system able to characterize amyloids and protein complexes related to neurodegenerative disease. These efforts range from upstream fabrication and characterization of nanopores in synthetic substrates to downstream techniques for optimizing the accuracy and efficiency of analyses on resistive pulses. Single proteins rotating and translating while tethered to the surface of a nanopore provide rich information during transit through the pore that makes it possible to determine their ellipsoidal shape, volume, dipole moment, charge, and rotational diffusion coefficient in a time frame of just a few hundred microseconds. This five-dimensional protein fingerprint, however, requires chemical modification of each protein and is thus not ideal for studying protein dynamics or transient protein complexes, both of which are relevant when characterizing amyloids. Transitioning to low-noise nanopore substrates and high-bandwidth recordings enables label-free identification and quantification of unperturbed, natively-folded proteins and protein complexes in solution – no chemical tags, tethers, or fluorescent labels are needed. Such a transition is nontrivial; proteins passing uninhibited through the strong electric field inside of a nanopore rotate and translocate rapidly, posing a challenge to time-resolve their various orientations adequately while circumventing adhesion to nanopore walls. Furthermore, during their translocation through the nanopore, untethered, native proteins diffuse laterally, generating asymmetric disturbances of the electric field and larger-than-expected resistive pulse magnitudes. Known as off-axis effects, these latter phenomena add a noise-like element to the electrical recordings. We evaluate, both computationally and experimentally, the influence of such label-free complications on resulting parameter estimates, and place these results in the context of developing future iterations of nanopore-based protein sensors.

In light of the spectacular recent success of nanopore-based nucleic acid sequencing, it is likely that the next frontier for nanopore-based analysis is the characterization of single proteins and, in particular, the characterization of protein aggregates such as amyloids. The experiments and results presented here enable future particle-by-particle analysis of amyloids with nanopores to rapidly reconstruct their heterogeneity in size and shape, both of which are correlated with the neurotoxicity of amyloid samples and are being investigated as biomarkers for neurodegenerative disease.

Co-Chairs: Michael Mayer and David Sept

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Presentation Wed, 01 May 2019 12:44:40 -0400 2019-05-13T10:00:00-04:00 2019-05-13T11:00:00-04:00 Lurie Biomedical Engineering Biomedical Engineering Presentation Biomedical Engineering
Dissertation Defense: Just-In-Time Adaptive Interventions: Experiment, Inference and Online Learning (May 13, 2019 1:00pm) https://events.umich.edu/event/63520 63520-15773891@events.umich.edu Event Begins: Monday, May 13, 2019 1:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

The use and development of mobile interventions are experiencing rapid growth. Ideally, mobile devices can be used to provide treatment/support whenever needed and to adapt treatment to the context of the user. Just-in-time Adaptive Interventions (JITAIs) are composed of decision rules that map a user’s context (e.g., user's behaviors, location, current time, social activity, stress and urges to smoke) to a treatment that is delivered to the user via the mobile device in near real-time. Advancements in mobile health engineering and technology (e.g., passive stress sensing) continue to bring us closer to being able to provide interventions in this way. However, a number of important gaps in data science must be addressed before mobile devices can be used to deliver on the promise of JITAIs. First, there is a need for experimental designs to collect data that can be used to assess the effectiveness of the sequence of treatments delivered by a mobile device on health outcomes in order to support the development of JITAIs. Second, there is a need for data-driven methods to inform the construction of efficacious JITAIs. In the vast majority of currently deployed JITAIs, the decision rules underpinning JITAIs are formulated using domain expertise and clinical experience, with very limited use of data evidence.

In this dissertation, we make several contributions by tackling the above mentioned data science barriers to effective JITAI development in mobile health. First, we propose a micro-randomized trial (MRT) design and develop the primary analysis for assessing the proximal causal effect of treatments. In addition, we develop stratified micro-randomized trials for the setting where there is a time-varying, discrete variable and the primary analysis focuses on how the effectiveness of interventions changes with this variable. We also develop a novel algorithm to design randomization scheme for this setting when there is an average constraint on the number of times interventions that should be sent in a certain time interval. Second, we develop a semi-parametric model to estimate the long-term average of health outcomes that would accrue should a given JITAI be followed. We derive asymptotic theory for the consistency and asymptotic normality of the proposed estimator. Third, we develop an online learning algorithm that continuously learns and improves the JITAI as the data is collected from the user. The proposed algorithm introduces a proxy of future outcomes based on a dosage variable to capture the delayed effect of sending the interventions due to the treatment burden.

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Other Tue, 16 Jul 2019 14:24:15 -0400 2019-05-13T13:00:00-04:00 2019-05-13T15:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Alexander Englesbe (May 14, 2019 1:00pm) https://events.umich.edu/event/63605 63605-15808604@events.umich.edu Event Begins: Tuesday, May 14, 2019 1:00pm
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Charge Dynamics in Femtosecond Laser Filaments

Co-Chair: Prof. Karl Krushelnick
Co-Chair: Dr. Andreas Schmitt-Sody

Abstract: When a high intensity, ultrashort laser pulse propagates in the atmosphere, it drives competing intensity-dependent effects that simultaneously try to collapse and defocus the beam. The balance of these effects leads to a transversely confined, high intensity structure called a filament that can persist for long distances. The self-focusing effect is counterbalanced by ionization of the air, and the resulting plasma channel has many interesting and poorly understood properties. One of these is the ability of the plasma to generate and radiate short pulses of microwaves.
Microwave frequencies lie in the range of 1-300 GHz. Radiation of this type from plasmas generated by laser filamentation has not been studied closely before. The nanosecond timescale of the current density variation which causes the observed emission is much slower than that of known charged particle motions in the plasma. The experiments described in the dissertation make substantial progress toward explaining the microwave generation mechanism. They show that large scale longitudinal changes in the current density on the order of the plasma size are reflected in the frequency spectrum of the radiation.
The frequency range of the short-duration microwave pulses is large enough that it was necessary to develop a new measurement technique in order to characterize their frequency spectrum. It relies on absolute calibration of a microwave receiver over many adjacent frequency bands, so that measurements made in each band can be presented as a continuous spectrum. It is then applied to several laser produced plasmas in atmosphere over a frequency range of 2-70 GHz.
The dependence of the microwave radiation on the electron-neutral collision rate is investigated by changing the air pressure. Its dependence on the average electron energy is examined by comparing the radiation resulting from air plasmas generated at different laser wavelengths in the mid-infrared versus the near-infrared. The plasma due to a laser pulse composed the fundamental wavelength and its second harmonic is shown to enhance or suppress the microwave radiation depending on the relative phase of the laser harmonics. Finally, the microwave field strength can be optimized by iteratively changing the transverse laser intensity profile in the focal region using a deformable mirror whose shape is controlled with a genetic algorithm.
The sensitivity of the microwave radiation to the conditions of the laser-plasma interaction indicates that it might be employed as new non- perturbing diagnostic for filament plasmas. This has been a longstanding challenge in the field, because plasmas resulting from filamentation are relatively diffuse, cold, and typically have submillimeter diameters. Determination of the low electron densities and temperatures by conventional means is typically intractable. The microwave measurements may contribute a solution that would enable a deeper understanding of the evolution of the filament plasma.

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Presentation Mon, 13 May 2019 15:54:53 -0400 2019-05-14T13:00:00-04:00 2019-05-14T15:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Presentation flyer for Alexander Englesbe PhD Defense
Dissertation Defense: Statistical Tools for Samples of Weighted Networks with Applications to Neuroimaging (May 15, 2019 10:00am) https://events.umich.edu/event/63584 63584-15806547@events.umich.edu Event Begins: Wednesday, May 15, 2019 10:00am
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Neuroimaging data on functional connections in the brain are frequently represented by weighted networks. These networks share the same set of labeled nodes corresponding to a fixed atlas of the brain, while each subject’s network has their own edge weights. This thesis focuses on developing statistical tools for analyzing samples of weighted networks with applications to neuroimaging.

We first propose a method for modeling such brain networks via linear mixed effects models, which takes advantage of the community structure, or functional regions, known to be present in the brain. The model allows for comparing two populations, such as patients and healthy controls, globally, at functional systems level, and at individual edge level, with systems-level inference in particular allowing for a biologically meaningful interpretation. We incorporate correlation between edge weights into the model by allowing for a general variance structure, and show this leads to much more accurate inference. A thorough study comparing schizophrenics to healthy controls illustrates the full potential of our methods, and obtains results consistent with the medical literature on schizophrenia.

While we focus on networks as the main object of analysis, auxillary information about subjects is frequently available. The subject’s age is a particularly important covariance, since studying how the brain changes over time can lead to insights about brain development in children and adolescents and the effects of aging for older subjects. A typical neuroimaging study, however, is cross-sectional rather than longitudinal, meaning we measure subjects of many different ages, but only once. We developed two methods for analyzing such samples of multiple, time-stamped networks. One is a parametric approach utilizing a linear mixed effects model with age included as a covariate; the other one is a nonparametric method which can be viewed as a network version of principal component analysis, where we look for components that explain age-related trends and vary smoothly with age. Both approaches take network community structure into account and allow for concise and interpretable representation of the data by obtaining developmental curves for functional regions of the brain that vary smoothly with age. We apply the methods to fMRI data of subjects who are 8 to 22 years old, and extract developmental curves consistent with the current understanding of brain maturation in neuroscience.

Clustering is of special interest in neuroimaging studies of mental illness, because psychiatrists believe that many psychiatric conditions present in multiple distinct and not yet identified subtypes. Clustering brain connectivity networks of patients with a certain disorder can lead to discovering these subtypes, and ideally identifying the differences in connectivity patterns that distinguish between subtypes. Clustering with a large number of features is challenging in itself, and the network nature of the observations presents additional difficulties. Our goal is to develop a clustering method that respects the network nature of the data, allows for feature selection, and scales well to high dimensions. One general method for clustering and feature selection in high dimensions is sparse K-means, which performs feature selection by minimizing the K-means objective function plus a lasso penalty. Here we develop network-aware sparse K-means, using a network-induced penalty for simultaneously clustering weighted networks and performing feature selection. We also develop a Gaussian mixture model version of the algorithm, particularly useful when features are highly correlated, which is the case in neuroimaging. We illustrate the method on simulated networks and an fMRI dataset of youth.

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Other Tue, 16 Jul 2019 14:23:52 -0400 2019-05-15T10:00:00-04:00 2019-05-15T12:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Xiao Wu (May 16, 2019 12:00pm) https://events.umich.edu/event/63698 63698-15824937@events.umich.edu Event Begins: Thursday, May 16, 2019 12:00pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Nuclear Engineering and Radiological Sciences

Title: Tritium Control and Mitigation for Advanced Nuclear Reactors

Chair: Prof. Xiaodong Sun

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Presentation Wed, 15 May 2019 17:34:19 -0400 2019-05-16T12:00:00-04:00 2019-05-16T14:00:00-04:00 Lurie Robert H. Engin. Ctr Nuclear Engineering and Radiological Sciences Presentation Lurie Robert H. Engin. Ctr
Dissertation Defense: Group Sparsity in Regression and PCA (May 20, 2019 1:00pm) https://events.umich.edu/event/63733 63733-15839172@events.umich.edu Event Begins: Monday, May 20, 2019 1:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

In the field of high-dimensional statistics, it is commonly assumed that only a small subset of the variables are relevant and sparse estimators are pursued to exploit this assumption. Sparse estimation methodologies are often straightforward to construct, and indeed there is a full spectrum of sparse algorithms covering almost all statistical learning problems. In contrast, theoretical developments are more limited and often focus on asymptotic theories. In applications, non-asymptotic results may be more relevant.

The goal of this work is to show how non-asymptotic statistical theory can be developed for sparse estimation problems that assume group sparsity. We discuss three different problems: principal component analysis (PCA), sliced inverse regression (SIR) and multivariate regression. For PCA, we study a two-stage thresholding algorithm and provide theories that go beyond the common spiked-covariance model. SIR is then related to PCA in some special settings, and it is shown that the theory of sparse PCA can be modified to work for SIR. Regression represents another important research direction in high-dimensional analysis. We study a linear regression model in which both the response and predictors are grouped, as an extension of group Lasso.

Despite the distinctions in these problems, the proofs of consistency and support recovery share some common elements: concentration inequalities and union probability bounds, which are also the foundation of most existing sparse estimation theories. The proofs are presented in modules in order to clearly reveal how most sparse estimators can be theoretically justified. Moreover, we identify those modules that are possibly not optimized to show the limitation of the existing proof techniques and how they could be extended.

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Other Tue, 16 Jul 2019 14:23:24 -0400 2019-05-20T13:00:00-04:00 2019-05-20T15:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Tony Shin (May 22, 2019 9:00am) https://events.umich.edu/event/63768 63768-15871559@events.umich.edu Event Begins: Wednesday, May 22, 2019 9:00am
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Fast-Neutron Multiplicity Counting Techniques for Nuclear Safeguards Applications

Chair: Prof. Sara Pozzi

Abstract: Nuclear safeguards inspections are performed in accessible facilities of Nonnuclear Weapons States by international inspectorates such as the International Atomic Energy Agency. The objective of the safeguards inspections is to detect diversion of significant quantities of fissile material, defined as 8 kg plutonium and 25 kg of highly enriched uranium. The fidelity of detecting clandestine diversion of fissile material depends on the speed, precision, and accuracy of characterizing pertinent physical properties. Special nuclear materials emit multiplets of correlated neutrons that exhibit characteristic signatures. Traditional neutron multiplicity counting is a well- established method that uses an array of capture-based neutron detectors embedded in polyethylene to measure the emitted time-correlated neutrons. However, traditional systems are only sensitive to the emitted neutron multiplicity distribution as the polyethylene thermalizes the emitted neutrons and modulates the initial angular and energy information.
Organic scintillators are scatter-based detectors that directly detect the emitted fast neutrons and therefore measured quantities are closely related to the emitted neutron properties. The time-correlated response of an array of organic scintillators can be used to measure portions of the emitted neutron multiplicity, energy, and angular distribution simultaneously, offering a unique capability unavailable to capture-based systems. The absence of polyethylene allows time-correlation analysis to be implemented on much shorter time scales, which improves measurement precision benefiting the speed and precision of detecting mass diversions.
This dissertation summarizes the feasibility and improvements of a fast-neutron multiplicity counting system for nondestructive assay of special nuclear material. Experimental results of passive (Pu-bearing material) and active (U-bearing material) nondestructive assay are presented, demonstrating the system capability for estimating fissile mass and detecting fissile mass diversions. New point kinetics equations for analytic estimation of the fissile mass were derived to account for the inherent phenomena of neutron cross-talk, where a single neutron enters and registers counts in multiple detectors adversely increasing the observed multiplicity counts. The newly derived equations are verified with experimental results showing improved accuracy of estimating fissile mass when accounting for the spurious cross-talk counts. This work also summarizes experiments performed to characterize angular and energy-angle correlations of special nuclear material in relevant configurations to investigate additional capabilities unavailable to traditional systems. Experimental results are presented for the first time that relate the observed neutron-neutron angular and energy-angle correlations as a function of fissile material physical properties (i.e., leakage multiplication, α-ratio).

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Lecture / Discussion Tue, 21 May 2019 10:56:47 -0400 2019-05-22T09:00:00-04:00 2019-05-22T11:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer of Tony Shin PhD defense
Dissertation Defense: Large Data Approaches to Thresholding Problems (May 22, 2019 10:30am) https://events.umich.edu/event/64296 64296-16282455@events.umich.edu Event Begins: Wednesday, May 22, 2019 10:30am
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Advances in computational hardware has greatly expanded the power to collect and store data. With collection of greater data sets, comes greater difficulties in estimation, warranting more analysis and novel methods to handle. This is still true in threshold estimation, the estimation of discontinuities. To this end we present this body of work in thresholding problems in long data sequences and data with growing dimensions. The former setting, more commonly known as the change point problem, we introduce and analyze a method which can estimate change points with greater computational efficiency than existing procedures, without compromising the accuracy of the estimators. For the latter problem, also known as the change plane problem, we will study the case when the dimension of the problem grows with the sample size, a setting not well-studied in existing literature, and lay the groundwork with asymptotic results.

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Other Tue, 16 Jul 2019 14:21:22 -0400 2019-05-22T10:30:00-04:00 2019-05-22T12:30:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
Dissertation Defense: Local Structure of Random Fields - Properties and Inference (May 28, 2019 1:00pm) https://events.umich.edu/event/63807 63807-15890343@events.umich.edu Event Begins: Tuesday, May 28, 2019 1:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Advances in data collection and computation tools popularize localized modeling on temporal or spatial data. Similar to the connection between derivatives and smooth functions, one approach to studying the local structure of a random field is to look at the tangent field, which is a stochastic random field obtained as a limit of suitably normalized increment of the random field at any fixed location. This thesis develops theories for tangent fields of any order and new statistical tools for their inference.

Our first project focuses on various properties of tangent fields. In particular, we show that tangent fields are self-similar and intrinsically stationary. Those two properties, along with the assumption of mean-square continuity, allow us to fully characterize a tangent field via a spectral representation, which provides a systematic way to obtain useful models. Our extension of the spectral theory to abstract spaces, including function spaces, can be of interest on its own. We also connect our theories with common models in spatial statistics including the Mat\'ern model and its variations. Preliminary inference methods are proposed along with simulation studies.

An important example of random fields with tangent fields is the multifractional Brownian motion which has been studied extensively. Our second project focuses on a wide range of issues concerning the estimation of the Hurst function of a multifractional Brownian motion when the process is observed on a regular grid. A theoretical lower bound for the minimax risk of this inference problem is established for a wide class of smooth Hurst functions. We also propose nonparametric estimators and show they are rate optimal. Implementation issues including how to overcome the presence of a nuisance parameter and choose the tuning parameter from data have also been included. An extensive numerical study is conducted to compare our approach with other approaches. Some explorations about nongrid observations and nonconstant variances are also included.

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Other Tue, 16 Jul 2019 14:22:57 -0400 2019-05-28T13:00:00-04:00 2019-05-28T15:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
PhD Defense: Tom Logan (June 5, 2019 10:00am) https://events.umich.edu/event/63501 63501-15759485@events.umich.edu Event Begins: Wednesday, June 5, 2019 10:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Tom Logan

TITLE OF DISSERTATION: Integrating risk science and urban planning:
Mitigating hazards and protecting our communities.

CHAIR: Seth Guikema

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Lecture / Discussion Tue, 07 May 2019 13:43:31 -0400 2019-06-05T10:00:00-04:00 2019-06-05T12:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Tom Logan
PhD Defense: Donald Richardson (June 19, 2019 11:00am) https://events.umich.edu/event/63911 63911-15987731@events.umich.edu Event Begins: Wednesday, June 19, 2019 11:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Donald Richardson

CHAIR(s): Amy Cohn

TITLE OF DISSERTATION: Operations Research Frameworks for Improving Make-ahead Drug Policies at Outpatient Chemotherapy Infusion Centers

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Lecture / Discussion Mon, 01 Jul 2019 11:26:48 -0400 2019-06-19T11:00:00-04:00 2019-06-19T13:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Donald Richardson
EEB dissertation defense: Rodent population connectivity in coffee agroecosystems (July 5, 2019 11:00am) https://events.umich.edu/event/64165 64165-16171658@events.umich.edu Event Begins: Friday, July 5, 2019 11:00am
Location: Rackham Graduate School (Horace H.)
Organized By: Ecology and Evolutionary Biology

Bea presents her dissertation defense

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Presentation Tue, 23 Jul 2019 16:38:30 -0400 2019-07-05T11:00:00-04:00 2019-07-05T12:00:00-04:00 Rackham Graduate School (Horace H.) Ecology and Evolutionary Biology Presentation image of rodent and of a coffee farm
PhD Defense: Karmel Shehadeh (July 10, 2019 10:00am) https://events.umich.edu/event/63790 63790-15873609@events.umich.edu Event Begins: Wednesday, July 10, 2019 10:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

TITLE OF DISSERTATION: Stochastic Optimization Approaches for Outpatient Appointment Scheduling under Uncertainty

CHAIR(s): Amy Cohn & Ruiwei Jiang

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Lecture / Discussion Tue, 21 May 2019 16:52:23 -0400 2019-07-10T10:00:00-04:00 2019-07-10T12:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion Karmel Shehadeh
PhD Defense: Steven Exelby (July 15, 2019 9:00am) https://events.umich.edu/event/64299 64299-16284445@events.umich.edu Event Begins: Monday, July 15, 2019 9:00am
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Design, Development, and Experiments on the Recirculating Planar Crossed-Field Amplifier

Chair: Prof. Ronald Gilgenbach

Abstract: The Recirculating Planar Crossed-Field Amplifier (RPCFA) is an adaptation of the Recirculating Planar Magnetron (RPM) that has been the focus of research at the University of Michigan’s Plasma, Pulsed Power and Microwave Laboratory for nearly a decade.1 The RPM is a high power microwave (HPM) source that utilizes an innovative geometry to overcome the high power generating limitations of existing magnetrons while maintaining the characteristic high efficiencies of these devices. The large planar cathode emits higher currents, leading to higher power, than a rod cathode at charge limited densities due to its increased emitting surface area. The recirculating interaction space effectively recycles the electron beam, which preserves the electronic efficiency of the device. The RPCFA utilizes a geometry similar to the RPM and is likewise expected to hold the same advantages over traditional CFAs that the RPM holds over traditional magnetrons. Additionally, the planar amplifying structure permits the injection and extraction ports be placed physical far away. This allows the Brillouin hub to demodulate over a long distance which minimizes feedback, a primary power limiting mechanism in cylindrical CFAs. The focus of this experiment is to design and test a prototype RPCFA which demonstrates these features.

The slow wave structure (SWS) is the key component to a magnetron and CFA which is responsible for promoting the synchronous interaction between the RF wave and the Brillouin hub. The SWS in a CFA is designed with the following criteria: First, the SWS must act as a transmission line over the band of frequencies (typically around 10% bandwidth) the device is expected to amplify. The transmission should minimize radiative and resistive losses and minimize reflection and any point in the RF circuit. Thus, the SWS should be inherently low Q. Second, the SWS must generate periodic fringing RF fields in response to an excitation in the amplification band. Finally, the phase velocity of these fringing fields must be slowed to the speed of the Brillouin hub, in this application that will be approximately 0.2 to 0.3c. Using Ansys HFSS driven modal simulation, a SWS was designed that satisfied the criteria listed. This SWS was reproduced using the particle-in- cell code, MAGIC, to simulate operation.2 MAGIC simulation showed the device could generate amplification of a 1.3 MW signal at 3 GHz to a steady state output power of 29 MW, a gain of nearly 13.5 dB. MAGIC simulation also predicted approximately 13% bandwidth, zero drive stability (meaning output power was dependent on the presence of an input signal), and nearly linear amplification in the range of testable input powers.

The RPCFA was then prototyped, employing the "lost wax" additive manufacturing technique to build the intricate SWS, and traditional machining techniques to fabricate the supporting components. The RPCFA was tested experimentally to reproduce the results of MAGIC simulation. Zero-Drive stability was observed and a minimum amplifiable power was established to be around 100 W. Moderate power (10’s of kW) input signals showed moderate levels of amplification, 7.87 dB with high levels of variability, σ = 2.74 dB. At moderate power the bandwidth was measured to be 15%, slightly exceeding the bandwidth predicted by simulation. At high power input drive (150+ kW) the RPCFA demonstrated much more consistent amplification and increased mean gain of 8.71 dB with σ = 0.63 dB. The RPCFA consistently reached peak output powers around 5 MW before exhibiting RF breakdown of the RF circuit. This RF breakdown is characterized by the abrupt termination of the transmitted RF signal. This RF breakdown represents the current limit for output power on the RPCFA. Future experiments will make attempts to remove this limitation, redesigning the S-band structure to accommodate high RF fields or moving to lower frequencies where features will be inherently larger.
[1] R.M. Gilgenbach, Y.Y. Lau, D.M. French, B.W. Hoff, J. Luginsland, and M. Franzi, "Crossed field device," U.S. Patent US 8 841 867B2, Sep. 23, 2014.
[2] Developed by Alliant Techsystems

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Lecture / Discussion Thu, 11 Jul 2019 13:23:54 -0400 2019-07-15T09:00:00-04:00 2019-07-15T11:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer for Steven Exelby PhD Defense
Dissertation Defense (July 16, 2019 10:00am) https://events.umich.edu/event/64259 64259-16268502@events.umich.edu Event Begins: Tuesday, July 16, 2019 10:00am
Location: Lorch Hall
Organized By: Department of Linguistics

Linguistics graduate student Hezao (Alan) Ke will defend his dissertation, "The syntax, semantics and processing of agreement and binding grammatical illusions," on Tuesday, July 16, at 10 a.m.

ABSTRACT
The overall goal of this dissertation is to establish a linking theory between the syntax and semantics and the processing of subject--verb agreement and reflexive binding. This dissertation develops a unified syntactic analysis of agreement, based on a formalization of minimal search. Such an analysis accounts for a variety of agreement patterns observed in various languages, including negative concord in Czech, inflection doubling in Norwegian, Frisian and Swedish, multiple agree in Japanese, cyclic agree in Georgian and Hindi Urdu, and subject-complementizer agreement in Lubukusu. The minimal search-based analysis is also extended to reflexive binding. The minimal search-based analysis of subject--verb agreement and reflexive binding captures the syntactic similarity between these two constructions.

This dissertation then argues that subject--verb agreement and reflexive binding have an important representational difference: the phi-features involved in subject--verb agreement and reflexive binding are essentially different in their semantic content. The phi-features on bound reflexives (and bound variables generally) have semantic content and are semantically interpretable, whereas those on agreeing verbs/T heads are not semantically interpretable.

The syntactic and semantic analyses of agreement and reflexive binding have crucial consequences for the sentence processing study of subject--agreement and reflexive binding. This dissertation proposes that the parser is less tolerant of mismatches of semantically interpretable retrieval cues (in reflexive binding) in cue-based retrieval, compared to those of phonological cues (in subject--verb agreement). Experimental results are provided to test how this asymmetry may underlie interesting dissociations with regard to grammatical illusions in subject--verb agreement and reflexive binding.

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Other Tue, 09 Jul 2019 15:54:09 -0400 2019-07-16T10:00:00-04:00 2019-07-16T12:00:00-04:00 Lorch Hall Department of Linguistics Other Lorch Hall
Dissertation Defense: Subgroup Analysis: Risk Quantification and Debiased Inference (July 16, 2019 2:00pm) https://events.umich.edu/event/64297 64297-16282456@events.umich.edu Event Begins: Tuesday, July 16, 2019 2:00pm
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

Subgroup analysis is frequently used to account for the treatment effect heterogeneity in clinical trials. When a promising subgroup is selected from existing trial data, a decision on whether an additional confirmatory trial for the selected subgroup is worth pursuing needs to be made. Unfortunately, the usual statistical analysis applied to the selected subgroup as if the subgroup is identified independently of the data often leads to overly optimistic evaluations. Any statistical analysis that ignores how the subgroup is selected tends to suffer from subgroup selection bias. In this dissertation, we propose two new statistical tools to evaluate the selected subgroup. The first is a risk index which can be used as a simple screening tool to reduce the risk of over-optimism in naive subgroup analysis and the second is debiased inference to answer the question of how good the selected subgroup really is. The proposed tools are model-free, easy-to-implement and adjust for the subgroup selection bias appropriately. We demonstrate the merit of the proposed tools by re-analyzing the MONET1 trial. An extension of the debiased inference method is also discussed for observational studies with potentially many confounders.

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Other Tue, 16 Jul 2019 14:06:33 -0400 2019-07-16T14:00:00-04:00 2019-07-16T16:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
EEB dissertation defense: Genetic drivers of diversification in the Conus adaptive radiation (July 18, 2019 2:00pm) https://events.umich.edu/event/64193 64193-16203860@events.umich.edu Event Begins: Thursday, July 18, 2019 2:00pm
Location: Biological Sciences Building
Organized By: Ecology and Evolutionary Biology

Andrew defends his dissertation.

Illustration: John Megahan

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Presentation Fri, 12 Jul 2019 14:11:47 -0400 2019-07-18T14:00:00-04:00 2019-07-18T15:00:00-04:00 Biological Sciences Building Ecology and Evolutionary Biology Presentation Illustration of 4 coneshells of different colors by John Megahan
PhD Defense: Yuanyuan Guo (July 19, 2019 10:00am) https://events.umich.edu/event/64250 64250-16266504@events.umich.edu Event Begins: Friday, July 19, 2019 10:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

TITLE OF DISSERTATION:
Data-Driven Distributionally Robust Optimization
on Power System Operations

CHAIR:
Ruiwei Jiang

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Presentation Tue, 09 Jul 2019 11:41:26 -0400 2019-07-19T10:00:00-04:00 2019-07-19T12:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Presentation Photo of Yuanyuan Guo
Brown Bag: "Cinema of Social Dreamers: Artists and Their Imaginations Return to the Caribbean" (July 22, 2019 12:00pm) https://events.umich.edu/event/63916 63916-15993697@events.umich.edu Event Begins: Monday, July 22, 2019 12:00pm
Location: William Clements Library
Organized By: William L. Clements Library

In this talk, Yasmine Espert will discuss her current research at the Clements Library as recipient of the inaugural Brian Leigh Dunnigan Fellowship in the History of Cartography. Her research this year is also supported by the Pierre and Maria-Gaetana Matisse Fellowship for 20th Century Art. A PhD candidate in Art History and Archaeology at Columbia University, her dissertation research explores how artists of African and Afro-Asian descent map their dreams of the Caribbean.

Attendees are welcome to bring a lunch and eat during the presentation.

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Workshop / Seminar Fri, 19 Jul 2019 16:54:11 -0400 2019-07-22T12:00:00-04:00 2019-07-22T13:00:00-04:00 William Clements Library William L. Clements Library Workshop / Seminar Caribbean map
PhD Defense: Wilmer Henao (August 8, 2019 1:00pm) https://events.umich.edu/event/64830 64830-16458980@events.umich.edu Event Begins: Thursday, August 8, 2019 1:00pm
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

TITLE OF DISSERTATION:
Bridging the Gap Between Intended and Delivered Doses in Volumetric Modulated Arc Therapy (Vmat) and Tomotherapy for Cancer Treatment

CHAIR:
Marina Epelman

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Presentation Fri, 02 Aug 2019 12:56:47 -0400 2019-08-08T13:00:00-04:00 2019-08-08T14:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Presentation "PhD Defense" Text and U-M Industrial & Operations Engineering logo
PhD Defense: Jiawei Xia (August 9, 2019 11:00am) https://events.umich.edu/event/65020 65020-16501321@events.umich.edu Event Begins: Friday, August 9, 2019 11:00am
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Interaction Reconstruction in Digital 3-D CdZnTe Under Various Circumstances

Chair: Zhong He

Abstract: Cadmium zinc telluride (CdZnTe) is a semiconductor material that has attracted wide attention in the field of radiation detector in recent years. With the improvements in crystal growth, electrode design and readout electronics, the performance of CdZnTe detectors has been improving and approaching HPGe detectors without the requirements of cryogenic cooling. This work attempts to extend the application of CdZnTe detectors in multiple dimensions by addressing different challenges.

The advancements in digital readout systems enables more accurate information extraction from the CdZnTe detectors. Improvements were made on the measurement of electron mobility-lifetime product in 3-D CdZnTe detectors using more suitable filtering methods.

Though CdZnTe detectors can be operated at room temperature, the front-end devices still need to be temperature-regulated because the electronic gain as well as the electron transport property changes with temperature. The regulation requires extra power consumption, and impedes development of hand-held CdZnTe detector devices. In this work, the effect of temperature change on digital CdZnTe systems was studied in detail. In addition, practical algorithms were developed to correct for the systematic changes with varying temperature in both material and electronics.
Fast neutron damage in high-performance, 3-D sensitive CdZnTe detectors were studied. 3-D CdZnTe detectors showed significant performance degradation after neutron damage. The annealing process of neutron damage was studied both at room temperature and 80 oC. The annealing was significantly accelerated at higher temperatures. The detectors' performance was recoverable after annealing.
The usage of digital CdZnTe detector systems was extended to measurement of gamma rays in the above-3 MeV range. Pair-production double-escape event peaks were clearly resolved. Resolution degradation mechanisms in 3-D CdZnTe for gamma-ray interactions in this energy range were studied.

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Lecture / Discussion Wed, 07 Aug 2019 16:23:10 -0400 2019-08-09T11:00:00-04:00 2019-08-09T13:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer of Jiawei Xia defense
AE Dissertation Defense: "Model Order Reduction for Aeroelastic Analysis of Very Flexible Aircraft" (August 12, 2019 1:00pm) https://events.umich.edu/event/64997 64997-16501298@events.umich.edu Event Begins: Monday, August 12, 2019 1:00pm
Location: Francois-Xavier Bagnoud Building
Organized By: Aerospace Engineering

Renato Rebouças de Medeiros

With increasing requirements for lower emissions and costs, next-generation transport aircraft are poised to deal with high aspect ratio wings. Long lightweight structures are very flexible, and this fact brings new challenges to the aeroelastic analysis. Time-domain simulation of these nonlinear systems is desirable to analyze their aeroelastic behavior over the flight envelope.

In the structural end, while simplified methods exist to model long wings with equivalent beams, essential details can only be captured with built-up finite element models. Unfortunately, these models are expensive and non-robust for extensive dynamic simulations. This dissertation builds upon previous efforts to develop nonlinear modal reduced-order models (ROMs). Training these models requires the fitting of nonlinear stiffness and displacements from static solutions. The newly introduced Enhanced Implicit Condensation and Expansion (EnICE) method accounts for the contribution of nonlinear motion to inertia forces during dynamic simulations.

The EnICE approach was integrated into the computational fluid dynamics code CFL3D for high-fidelity aeroelastic analyses. An aerodynamic ROM was developed based on convolution corrected by a nonlinear factor obtained from steady solutions. For additional speedup, the Method of Segments provides these correction factors. The aeroelastic tool arising from the two reduced-order models simulates large displacements, taking into account structural and aerodynamic nonlinearities.

Doctoral Comittee
Chair: Prof. Carlos E.S. Cesnik
Cognate Member: Prof. Bogdan I. Epureanu
Members: Peretz P. Friedmann, Prof Krzysztof Fidkowski

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Presentation Wed, 07 Aug 2019 13:27:58 -0400 2019-08-12T13:00:00-04:00 2019-08-12T16:30:00-04:00 Francois-Xavier Bagnoud Building Aerospace Engineering Presentation Francois-Xavier Bagnoud Building
Dissertation Defense: Unified Price Indices for Spatial Comparisons (August 16, 2019 8:00am) https://events.umich.edu/event/65067 65067-16509334@events.umich.edu Event Begins: Friday, August 16, 2019 8:00am
Location: West Hall
Organized By: Department of Statistics Dissertation Defenses

This thesis proposes a method to measure fine-grained spatial differences in prices using retail barcode scanner datasets. To avoid conflating spatial price differences with differences in consumer preferences for products sold in each area, it extends the framework proposed by Redding and Weinstein to adjust price indices for product turnover, from the temporal to the spatial context. In this extension, differences in spatial product availability are considered analogous to differences in product availability across time. It describes a method to estimate these "spatial UPI" indices, and the uncertainty associated with these estimates. It then applies this method to compare the food cost of living between different counties within the state of Michigan based on the Nielsen retail scanner database.

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Other Thu, 08 Aug 2019 15:46:49 -0400 2019-08-16T08:00:00-04:00 2019-08-16T10:00:00-04:00 West Hall Department of Statistics Dissertation Defenses Other flyer
AE Dissertation Defense: Propeller Effects on Very Flexible Aircraft (August 21, 2019 1:00pm) https://events.umich.edu/event/65233 65233-16557455@events.umich.edu Event Begins: Wednesday, August 21, 2019 1:00pm
Location: Francois-Xavier Bagnoud Building
Organized By: Aerospace Engineering

Patricia Teixeira, Aerospace PhD Candidate

Although many studies have been done in propeller-wing interaction, little has been explored about propeller effects on very flexible aircraft (VFA). Moreover, state-of-the-art nonlinear aeroelastic frameworks lack complete propeller modeling, just using simple concentrated forces to model its thrust.

This work aims to fill this gap by incorporating propeller aerodynamics and inertial effects into an aeroelastic framework. For that, the University of Michigan’s Nonlinear Aeroelastic Simulation Toolbox (UM/NAST) is enhanced with an Unsteady Vortex Lattice for the lifting surfaces and a Lifting Line coupled with Viscous Vortex Particle (LL/VVP) method to model the propeller aerodynamics. In addition, inertia effects associated with the rigid rotating blades are modeled. Verification tests demonstrate the accuracy of each new component added to the enhanced framework.

Using the new developments, investigations of propeller effects on the aeroelastic response and stability of a representative High Altitude Long Endurance (HALE) aircraft were performed. The results demonstrate that the presence of propellers can influence the aeroelastic response and stability of a VFA. Therefore, the additional propeller effects (besides just the incorporation of thrust) should not be neglected in aeroelastic simulations.

Dissertation Committee:

Chair: Prof. Carlos S. Cesnik
Cognate Member: Kevin J. Maki
Members: Prof. Peretz P. Friedmann and Prof. Daniel J. Inman

Publications:

Teixeira, P. C. and Cesnik, C. E. S., “Inclusion of Propeller Effects on Aeroelastic Behavior of Very Flexible Aircraft," International Forum on Aeroelasticity and Structural Dynamics, IFASD 2017 , Como, Italy, 25-28 June 2017.

Teixeira, P. C. and Cesnik, C. E. S., “Propeller Effects on the Dynamic Response of HALE Aircraft” 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, AIAA SciTech Forum, AIAA Paper 2018-1953, January 2018.

Ritter, M., Teixeira, P. C., and Cesnik, C. E. S., “Comparison of Nonlinear Aeroelastic Methods for Maneuver Simulation of Very Flexible Aircraft," 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, AIAA SciTech Forum, AIAA Paper 2018-1953, January 2018.

Teixeira, P. C. and Cesnik, C. E. S., “Propeller Influence on the Stability of HALE Aircraft," 31st Congress of the International Council of the Aeronautical Sciences (ICAS), Belo Horizonte, Brazil, 9-14 September 2018.

Teixeira, P. C. and Cesnik, C. E. S., Propeller Effects on the Response of High Altitude Long-Endurance Aircraft," AIAA Journal

del Carre, A., Teixeira, P. C., Palacios, R., and Cesnik, C. E. S., “Nonlinear Response of a Very Flexible Aircraft Under Lateral Gust," International Forum on Aeroelasticity and Structural Dynamics, IFASD, Savannah, Georgia, USA, Jun 2019.

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Lecture / Discussion Mon, 19 Aug 2019 10:21:51 -0400 2019-08-21T13:00:00-04:00 2019-08-21T14:00:00-04:00 Francois-Xavier Bagnoud Building Aerospace Engineering Lecture / Discussion XHALE Clamped and Particles
Dissertation Defense (August 26, 2019 2:30pm) https://events.umich.edu/event/65220 65220-16555449@events.umich.edu Event Begins: Monday, August 26, 2019 2:30pm
Location: Lorch Hall
Organized By: Department of Linguistics

Linguistics graduate student Dave Ogden will defend his dissertation, “Processing Fluency, Perceptual Adaptation, and Language Attitudes: Does Adaptation Improve Comprehension Ease and Attitudes Toward Non-Native Speakers?” on Monday, August 26, at 2:30 p.m. in room 473, Lorch Hall.

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Other Wed, 14 Aug 2019 08:32:05 -0400 2019-08-26T14:30:00-04:00 2019-08-26T16:30:00-04:00 Lorch Hall Department of Linguistics Other Lorch Hall
PhD Defense: Francisco Aldarondo (August 27, 2019 9:00am) https://events.umich.edu/event/65328 65328-16571522@events.umich.edu Event Begins: Tuesday, August 27, 2019 9:00am
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

TITLE OF DISSERTATION:
Design and Operational Analysis of Automated Guided Vehicle-Based Goods-to-Person Order Picking and Sortation Systems

CHAIR:
Yavuz Bozer

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Presentation Fri, 16 Aug 2019 10:45:02 -0400 2019-08-27T09:00:00-04:00 2019-08-27T11:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Presentation Francisco Aldarondo PhD Defense
PhD Defense: Nanjun Chen (August 30, 2019 9:00am) https://events.umich.edu/event/65924 65924-16670252@events.umich.edu Event Begins: Friday, August 30, 2019 9:00am
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

TITLE: Understanding of Ion-Solid Interaction and Defect Evolution in Zinc-Blende Structured Materials

CHAIR: Prof. Fei Gao

ABSTRACT: Zinc-blende structured materials have received considerable attentions due to their excellent performance in many fields. The major benefit has attributed to high power space energy systems and nuclear reactors. Their applications can expose to high energy radiation, including neutrons, ions and cosmic rays. Under these conditions, defects are generated in materials in amounts significantly exceeding their equilibrium concentrations. The accumulation of defects can lead to undesired consequences, which may alter the performance of the materials. Therefore, the fundamental understanding of ion-solid interaction and defect evolution is a key factor to the success of both nuclear and electronic materials. This thesis focuses on the study of zinc-blende materials, including GaAs, GaN, InAs, and SiC for their possible applications in both nuclear and space fields.
SiC has its unique capability in the applications of nuclear fuel, cladding and fusion structure materials. In tri-structural isotropic (TRISO) fuel particles, SiC coating is considered as a major barrier for the release of fission products (FPs). However, the release of some metallic FPs (i.e. Ag, Pd, Ru, and I) from fully intact fuel particles raises serious concern on the safety of high temperature gas-cooled reactors (HTGRs). This thesis first addresses atomistic process of FP diffusion in SiC. Ab initio calculations are used to determine the defects configurations, migration energy barriers and pathways of FPs in SiC. Based on the ab initio results, the interatomic potentials of FPs in SiC are developed and evaluated to serve as a link between the density functional theory (DFT) and next coarser level. Classical molecular dynamics (MD) simulations have been employed to investigate FP accommodation in SiC, interactions with point defects and grain boundaries, and their diffusion kinetics. These findings lead to a conclusion that the grain boundary diffusion of FPs is faster than bulk diffusion with a strong segregation at the GBs. Analysis of the radiation enhanced diffusion obtained by experiments and diffusion by modeling work for Ru and I has suggested that the interstitial migration is likely to be a major mechanism under irradiation condition. Moreover, the diffusivities can vary by grain boundary types, whereas high energetic grain boundaries can provide the fastest paths for FPs to diffuse. An elevation of 1.5 eV in GB energy can result in 2-3 orders of magnitude difference in Ag diffusion coefficient.
We have further explored the defect production, clustering, and its evolution in GaAs, GaN, InAs, and SiC, and determined non-ionizing energy loss (NIEL) that indicates a rate of degradation in electronic devices in space applications. Nonlinear defect production is observed with an increasing of primary knock-on (PKA) energy in GaAs and InAs. This effect, which corresponds to the direct-impact amorphization, is observed for PKA energy over 2 keV. Gallium nitride is however different and presents a pseudometallic behavior (PMB) resulting in a majority of surviving defects to be single interstitials or vacancies. SiC also has a limited number and size of defect clusters due to the formation of multiple subcascades with low energy density. With the damage density evaluated from MD simulations, a model to determine NIEL has been developed, which can be used to qualify the radiation degradation in space application. The NIELs for proton, alpha, and Xe particles are then predicted, and provide a pathway to evaluate the capabilities for the space applications of these materials. The comparisons of defect creation, density, and effective NIEL suggest that GaN may be the best candidate as a radiation hard material for space applications at high-energy regime. For low incident particle energies at which the NIEL ratio of InAs-to-GaN is less than 1, the performance of InAs may be superior to that of GaN.

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Lecture / Discussion Wed, 28 Aug 2019 16:04:55 -0400 2019-08-30T09:00:00-04:00 2019-08-30T11:00:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer of Nanjun Chen defense
Robotics PhD Defense: Mia Stevens (September 3, 2019 1:00pm) https://events.umich.edu/event/65320 65320-16571514@events.umich.edu Event Begins: Tuesday, September 3, 2019 1:00pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Michigan Robotics

As small unmanned aircraft systems (UAS) are utilized in an increasingly wide variety of commercial and civil applications, safety of flight within low altitude airspace can be improved through use of electronic geofence systems to partition the airspace. A geofence is defined as a volume of airspace with specific temporal, spatial, and permission constraints. This thesis develops geofencing as a tool for individual UAS and for managing airspace utilization through UAS Traffic Management (UTM). Permissions constraints determine which UAS may fly within each geofence. As a safety system, geofencing aims to keep the UAS within the airspace sectors (keep-in geofences) it has permission to access. Similarly, geofencing prevents the UAS from entering the airspace sectors it does not have permission to access (keep-out geofences). This thesis offers three specific contributions to geofencing.

First, a methodology is developed to enable the UTM system to build and manage the set of active geofences, ensuring a maximum of one geofence per volume of airspace at any given time. Spatial priority of geofences within the UTM system is awarded in order of request, with always active (static) geofences having top priority. Unlike static geofences, dynamic geofences appear and disappear at user-specified times and are spatially and temporally deconflicted to maximize authorized airspace volume. Polygon set operations are used to deconflict the horizontal boundaries of newly requested geofence sets from the existing UTM approved geofence set.

Second, a Triangle Weight Characterization with Adjacency (TWCA) algorithm is developed to efficiently determine whether a UAS is within a given geofence independent of the complexity of its boundary. This algorithm enables the UAS geofence module to quickly check whether the UAS is violating a geofence boundary by decomposing the horizontal boundary into triangles and tracking the occupied triangle over time through an adjacency graph. To test the performance of TWCA against the industry standard of Ray Casting, the run-time per query is calculated for randomly generated geofences and flight paths. The run-time of Ray Casting scales linearly with the number of geofence vertices while the average run-time of TWCA is constant independent of number of vertices. This time independence from geofence complexity is managed by a pre-processing step that enables real-time operation of this algorithm.

Third, to enable the UAS operator or geofence automation to intervene prior to a boundary violation, the geofence polygons are scaled to provide warning and override cues. This boundary layering algorithm utilizes a uniform and a directional buffer distance to scale keep-in geofences inward and keep-out geofences outward. The layering algorithm is designed to handle arbitrary concave polygons, with special cases identified and analyzed through Monte Carlo simulation. Multiple layering techniques are utilized in parallel to increase the likelihood of finding a scaled boundary solution. The statistical results show that the likelihood of success for inward and outward scaling decreases as buffer magnitude increases.

The contributions of this thesis are combined to form a full system simulation, from the request of a new geofence and access to an existing geofence through the prevention of the boundary violation by the UAS.

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Presentation Fri, 16 Aug 2019 08:11:12 -0400 2019-09-03T13:00:00-04:00 2019-09-03T15:00:00-04:00 Lurie Robert H. Engin. Ctr Michigan Robotics Presentation Geofenced North Campus
Dissertation Defense (September 4, 2019 2:00pm) https://events.umich.edu/event/66267 66267-16725779@events.umich.edu Event Begins: Wednesday, September 4, 2019 2:00pm
Location: Lorch Hall
Organized By: Department of Linguistics

Linguistics graduate student Marcus Berger will defend his dissertation, “The Syntax of Bora Subject Clitics” on Wednesday, September 4, at 2 p.m. in room 301, Lorch Hall. Committee chair: Acrisio Pires.

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Other Wed, 04 Sep 2019 08:57:58 -0400 2019-09-04T14:00:00-04:00 2019-09-04T16:00:00-04:00 Lorch Hall Department of Linguistics Other Lorch Hall
PhD Defense: Andrew McKelvey (September 4, 2019 2:30pm) https://events.umich.edu/event/66300 66300-16725816@events.umich.edu Event Begins: Wednesday, September 4, 2019 2:30pm
Location: Lurie Robert H. Engin. Ctr
Organized By: Nuclear Engineering and Radiological Sciences

Title: Short-pulse Driven Transport Measurements in Dense Plasmas

Chair: Prof. Karl Krushelnick

Abstract: Accurate transport properties---such as opacity, and electrical & thermal conductivities---provide crucial input for the intricate physics models necessary to describe the dynamics of complex, high energy density (HED) systems. This includes stars, giant planets, and inertial confinement fusion plasmas. However, these theoretical transport models present challenges as the phase space often sits at the intersection of solid, liquid, gas, and plasma where many effects of comparable magnitude must be considered. Additionally, the transient nature of such high energy density materials complicates experimental measurement, and many theories remain sparsely benchmarked by data.
In the laboratory, HED material must be created via some combination of material compression to very high densities or by adding large amounts of energy to the material in a very short time. This thesis focuses on experiments utilizing the second technique. X-ray free-electron lasers (tau<100 fs) or short-pulse lasers (tau<1 ps) are capable of heating materials from room temperature to tens or even many hundreds of eV while keeping densities at appreciable fractions of their ambient value. This allows for the probing of material properties before hydrodynamics phenomena become dominant.
First, an experimental platform designed to constrain thermal conductivity models in warm dense matter is presented. Its basis relies on differentially heating multilayer targets (one high-Z layer and one low- to mid-Z layer) to generate a thermal gradient. This concept was first demonstrated using the Titan laser at the Jupiter Laser Facility, creating an intense proton beam to heat a gold/aluminum multilayer target. The temperature, reflectivity, and expansion of the rear surface were observed with time-resolved diagnostics as the thermal energy from the hot gold layer reached the coldest part of the aluminum layer. The data were compared with hydrodynamics models that self-consistently used the electrical and thermal conductivities to calculate observables. Measured temperatures were too low relative to predictions, possibly indicating the need to decrease tested conductivity models. This experiment was repeated using an X-ray free-electron laser at the Linac Coherent Light Source (LCLS) with gold/iron targets. Data are presented for this work along with calculations and a discussion of how the different drivers impact the experimental design and data quality.
Finally, data from a platform designed to measure opacities using short- pulse lasers at the Orion Laser Facility are presented. Spectroscopic measurements of silicon's K-shell that are both temporally and angularly resolved are benchmarked against the radiation transfer code Cretin. The validity of the commonly-used escape factor approximation is tested against the full solution of the radiation transfer equation and found to be in good agreement for presented experimental conditions. An analysis of the effects of radial gradients on spectroscopically inferred temperatures is found to lead to errors in the peak temperature as large as 50% as well as incorrect cooling rates. This emphasizes the importance of absolute emissivity calibrations and spatially resolved spot size measurements.

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Lecture / Discussion Wed, 04 Sep 2019 11:43:56 -0400 2019-09-04T14:30:00-04:00 2019-09-04T16:30:00-04:00 Lurie Robert H. Engin. Ctr Nuclear Engineering and Radiological Sciences Lecture / Discussion AndrewMcKelvey PhD defense flyer
AE Dissertation Defense: "Development and Application of a Comprehensive Simulation for Modeling Helicopter Ship Landing" (September 6, 2019 1:30pm) https://events.umich.edu/event/65898 65898-16670220@events.umich.edu Event Begins: Friday, September 6, 2019 1:30pm
Location: Francois-Xavier Bagnoud Building
Organized By: Aerospace Engineering

A comprehensive simulation framework for modeling helicopter ship landing was developed. The framework includes high-fidelity models for: 1) vehicle flight dynamics, 2) Wind Over Deck (WOD), 3) ground effect, 4) ship deck motion, and 5) a robust flight control system.

Approach simulations were performed to assess the influence of WOD and ground effect on the UH-60A helicopter response. The WOD velocities were obtained from Detached Eddy Simulation of flow over a SFS2 ship. A gain scheduled LQR controller was used to track the approach trajectory. The WOD resulted in high frequency oscillations in the CG position coordinates and attitude angles. Oblique WOD conditions required greater control effort than the headwind case. Ground effect, modeled using a simple scaling factor, caused an 11.3% decrease in rotor power consumption.

A finite-state ground effect model was subsequently implemented to study the influence of inclined and moving decks. Hover and landing simulations were performed with a deck inclined at constant roll and pitch angles, and a deck undergoing isolated sinusoidal motion. Static deck roll produced an increase in the lateral inflow coefficient and the longitudinal cyclic input to the main rotor. Power requirements were significantly affected by heaving deck motion, highlighting the importance of modeling dynamic ground effect.

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Lecture / Discussion Wed, 28 Aug 2019 12:19:01 -0400 2019-09-06T13:30:00-04:00 2019-09-06T15:00:00-04:00 Francois-Xavier Bagnoud Building Aerospace Engineering Lecture / Discussion Abhinav Sharma
Ph.D. Defense: Zachariah Sperry (September 11, 2019 9:00am) https://events.umich.edu/event/66181 66181-16717510@events.umich.edu Event Begins: Wednesday, September 11, 2019 9:00am
Location:
Organized By: Biomedical Engineering

Department of Biomedical Engineering Final Oral Examination

Zachariah Sperry

Neural Interfacing with Dorsal Root Ganglia: Anatomical Characterization and Electrophysiological Recordings with Novel Electrode Arrays

Dorsal root ganglia (DRG), the hubs of neurons conducting sensory information into the spinal cord, are promising targets for clinical and investigative neural interface technologies. DRG stimulation is currently a tertiary therapy for chronic pain patients, which has an estimated prevalence of up to 40% of adults in the United States. In pre-clinical studies, combined neural recording and stimulation at DRG has been used as part of novel closed-loop systems to drive activity of the limbs or the urinary system. This suggests a potential role for clinical DRG interfaces to assist, among other patient groups, the nearly 300,000 spinal cord injured patients in the United States.

To maximize the utility of DRG interfaces, however, there remains a strong need to improve our understanding of DRG structure. Neural interface technologies for both stimulation and recording rely heavily on the spatial organization of their neural targets. To record high-fidelity neural signals, a microelectrode must be placed within about 200 µm of a neural cell body. Likewise, effective neural stimulation is believed to act on a subset of DRG axons based on their size and location. The spatial organization of DRG, however, has not been previously quantified. In this thesis, I demonstrate a novel algorithm to transform histological cross-sections of DRG to a normalized circular region for quantifying trends across many samples. Using this algorithm on 26 lumbosacral DRG from felines, a common preclinical DRG model, I found that the highest density of neural cell bodies was in the outer 24% radially, primarily at the dorsal aspect. I extended this analysis to a semi-automated cross-DRG analysis in 33 lower lumbar DRG from 10 human donors. I found that the organization of human DRG was similar to felines, with the highest density of cell bodies found in the outer 20-25% of the DRG, depending on spinal level. I also found a trend toward lower small-axon density at the dorsal aspect of L5 DRG, a key region for stimulation applications.

To take advantage of this quantitative knowledge of DRG organization, future neural interfaces with DRG will require more advanced technologies. Standard silicon-based electrode arrays, while useful for short-term DRG recordings, ultimately fail in chronic use after several weeks as a result of mechanical mismatch with neural tissue. In this thesis, I demonstrate sensory recording from the surface and interior of sacral DRG during acute surgeries using a variety of flexible polyimide microelectrode arrays 4 μm thick with minimum site separation of 25 to 40 μm. Using these arrays, I recorded from bladder and somatic afferents with high fidelity. The high density of sites allowed for neural source localization from surface recordings to depths 25 to 107 µm. This finding supports the anatomical analysis suggesting a high density of cell bodies in the dorsal surface region where the surface array was applied. The high site density also allowed for the use of advanced signal processing to decrease analysis time and track neural sources during movement of the array which may occur during long-term behavioral experiments.

This thesis represents significant advances in our understanding of DRG and how to interface with them, particularly related to the ways anatomy can inform development of future technologies. Going forward, it will be important to expand the anatomical maps based on organ function and to test the novel flexible arrays in chronic implant experiments.

Date: Wednesday, September 11, 2019
Time: 9:00 AM
Location: NCRC Building 32 Auditorium
Chair: Dr. Tim Bruns

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Lecture / Discussion Tue, 03 Sep 2019 11:58:35 -0400 2019-09-11T09:00:00-04:00 2019-09-11T10:00:00-04:00 Biomedical Engineering Lecture / Discussion U-M BME Event
PhD Defense: Kenneth Engeling (September 11, 2019 1:30pm) https://events.umich.edu/event/66855 66855-16779052@events.umich.edu Event Begins: Wednesday, September 11, 2019 1:30pm
Location: Cooley Building
Organized By: Nuclear Engineering and Radiological Sciences

Title: Micro-Plasma in Porous Media and Dielectric Barrier Discharges with Advanced Agricultural Applications

Chair: Prof. John Foster

Abstract: A range of chemical processing applications feature the passage of process gas through porous media. Such media such as foams with interconnected pores or packed beds of aggregate media are desirable for chemical reactions since the reaction surface area to volume ratio is typically quite high. Applications of such reactors include the removal of volatile organic compounds from flues, plasma treatment of aggregate organic media such as seeds, and low temperature, efficient combustion. Conventional applications featuring packed bed media contain catalytic particles often at high temperature. The chemical reactivity of such porous media can be greatly enhanced non-thermally through the production of plasma in the pores. The plasma electrons drive non- equilibrium chemical reactions allowing for a high degree of reaction selectivity. Such plasmas are also the source of reactive radicals. The production and subsequent propagation of plasma within the pores of such media is not well understood. The goal of this thesis work is to understand the plasma production process in porous media and the subsequent propagation of the plasma through such media. This work also involves understanding the induced chemical reactivity induced by the propagating plasma. The ultimate goal is to obtain insight into how the plasma imparts reactivity to the flow through gas and how these effects can be controlled. This insight will serve as the basis for optimization of existing packed media plasma reactors and the development of new, novel sources for a range of applications including chemical processing. An application area of plasma packed bed reactors is also explored—the treatment of seeds. Here the propagation of plasma through packed beds of seeds and the subsequent germination and growth is studied. Such treatments have the potential to revolutionize agriculture by improving yields, increasing crop growing seasons and enhancing seed vigor. Such work supports food security particularly in light of pressures from overpopulation and climate change.

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Lecture / Discussion Tue, 10 Sep 2019 16:48:18 -0400 2019-09-11T13:30:00-04:00 2019-09-11T15:30:00-04:00 Cooley Building Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer of Kenneth Engeling defense
PhD Defense: Thomas Chen (September 30, 2019 1:00pm) https://events.umich.edu/event/67040 67040-16796468@events.umich.edu Event Begins: Monday, September 30, 2019 1:00pm
Location: Industrial and Operations Engineering Building
Organized By: U-M Industrial & Operations Engineering

CANDIDATE: Thomas Chen

CHAIR: Seth Guikema

TITLE OF DISSERTATION: Advancing Quantitative Risk Analysis for Critical Water Infrastructure

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Lecture / Discussion Thu, 12 Sep 2019 13:51:15 -0400 2019-09-30T13:00:00-04:00 2019-09-30T14:00:00-04:00 Industrial and Operations Engineering Building U-M Industrial & Operations Engineering Lecture / Discussion PhD Defense: Thomas Chen
PhD Defense: Dominique Smith (October 2, 2019 2:00pm) https://events.umich.edu/event/67289 67289-16831267@events.umich.edu Event Begins: Wednesday, October 2, 2019 2:00pm
Location: North Campus Research Complex Building 10
Organized By: Biomedical Engineering

Spinal cord injury (SCI) causes paralysis below the level of injury which, at the cellular level, results from neuron and oligodendrocyte cell death, axonal loss, demyelination, and critically, the limited capacity of spinal cord neurons to regenerate. Although central nervous system (CNS) tissue has the innate capacity to repair the local environment that develops after SCI lacks sufficient factors that promote regeneration and has an abundance of factors that inhibit regeneration. Many strategies have been attempted to aid in the regeneration of CNS tissue, yet re-entry into intact spared tissue remains inadequately low. This is due to the complexity of the spinal cord microenvironment post injury and the barriers that must be addressed to elicit adequate regeneration. The Shea lab has developed multi-channel poly (lactide-co-glycolide) (PLG) bridges to promote spinal cord regeneration and restore functional losses. These bridges are biodegradable and provide a temporary structure that promotes regeneration for between 2 and 6 months post-implantation. The bridges have an interconnected pore structure, that allows infiltration of endogenous cell populations, including macrophages, Schwann cells, oligodendrocytes. Additionally, the bridge mechanically stabilizes the injury with tissue ingrowth and reduces secondary injury and axonal dieback. Longitudinal channels encourage axons to regenerate into the bridge with cells aligned along this major axis. Both motor and sensory axons have been identified in bridge channels. These bridges also serve as a platform for delivery of therapeutics including drugs, cells, and notably lentivirus.

This dissertation investigated the use of lentiviral gene therapy from multi-channel bridges to barriers to regeneration during acute and chronic phases of SCI. We investigated myelination of regenerating axons by over-expression of platelet-derived growth factor-AA (PDGF) and noggin either alone or in combination in an acute mouse SCI model. The combination of noggin + PDGF enhanced total myelination of regenerating axons relative to either factor alone and importantly, enhanced functional recovery relative to the control condition. The increase in myelination was consistent with an increase in oligodendrocyte-derived myelin, which was also associated with a greater density of cells of an oligodendroglial lineage relative to each factor individually and control conditions. We investigated synergistic effects of anti-inflammatory and regenerative factors by bi-cistronic delivery of NT-3 and IL-10 using PLG bridges after acute SCI. The combination of IL-10+NT-3 enhanced axonal growth and oligodendrocyte myelinated axon density significantly over control This resulted in increased locomotor functional recovery compared to IL-10 or NT-3 alone but increased hypersensitivity compared to IL-10 alone. Furthermore, we observed a strong positive correlation between oligodendrocyte myelinated axon density and functional recovery. Lastly, we investigated regeneration using the multi-channel bridge implanted into a chronic SCI following surgical resection of necrotic tissue. We characterized the dynamic injury response and noted that scar formation decreased at 4 and 8 weeks post injury (wpi), yet macrophage infiltration increased between 4 and 8 wpi. Subsequently, scar tissue was resected and bridges were implanted at 4 and 8 wpi. We observed robust axon growth into the bridge and remyelination at 6 months post initial injury. Axon densities were increased for 8 week bridge implantation relative to 4 week bridge implantation, whereas greater myelination, particularly by Schwann cells, was observed with 4 week bridge implantation. Taken together, these results show the bridges as a great tool to manipulate and investigate the spinal cord microenvironment to improve functional outcomes.

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Lecture / Discussion Mon, 16 Sep 2019 16:38:05 -0400 2019-10-02T14:00:00-04:00 North Campus Research Complex Building 10 Biomedical Engineering Lecture / Discussion BME
PhD Defense: Daniel Nunez (October 23, 2019 2:00pm) https://events.umich.edu/event/68698 68698-17138820@events.umich.edu Event Begins: Wednesday, October 23, 2019 2:00pm
Location: Michigan Memorial Phoenix Project
Organized By: Nuclear Engineering and Radiological Sciences

Title: High-Resolution Experiments of Momentum and Buoyancy-Driven Flows for the Validation and Advancement of Computational Fluid Dynamics Codes

Abstract: Over the past decade, Computational Fluid Dynamics (CFD) has become an important simulation tool to properly predict 3D effects in nuclear power plant systems and reduce the uncertainty in design safety margins. Reynolds-Averaged Navier-Stokes (RANS) formulations are commonly used to predict fluid flows due to their robustness and their relatively low computational cost in comparison to higher fidelity models such as Large Eddy Simulation (LES). However, because of the various approximations at the basis of RANS turbulent models, validation for the specific applications need to be carried out to assess the models’ capabilities to predict a given phenomenon of interest.
The primary goal of this thesis is to develop a high-resolution high-fidelity experimental database for the development and improvement of CFD codes, and to gain physical insight into complex phenomena relevant to nuclear power applications. Two applications of interest are addressed: a) mixing and interaction of multiple jets in a uniform environment, and b) propagation of stratified fronts in presence of positive and negative density gradients. When assessing the performance of CFD models, it is important to determine whether, for the specific phenomenon of interest, the CFD predictions would lead to a conservative or non-conservative result. For example, in the case of a PWR Main Steam Line Break (MSLB) accident, an over-estimation of thermal stratification would lead to non-conservative results, since the resulting core reactivity insertion will be under-estimated.
High-resolution data collected from two experimental facilities designed and built to address jets interactions and propagation of stratified fronts will be discussed, together with CFD validation results. Shortcomings of the current RANS models and efforts to understand the reasons for the inaccuracy of the simulations will be summarized as well. The data presented consists of experiments and CFD simulations under constant and variable density conditions, and are accompanied with the uncertainties due to geometries, algorithms, reproducibility and repeatability of the measurements.

Chair(s): Prof. Annalisa Manera

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Lecture / Discussion Tue, 22 Oct 2019 14:25:50 -0400 2019-10-23T14:00:00-04:00 2019-10-23T16:00:00-04:00 Michigan Memorial Phoenix Project Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer for David Nunez defense
CDB Dissertation Defense: Ye Li (October 29, 2019 10:00am) https://events.umich.edu/event/68769 68769-17147156@events.umich.edu Event Begins: Tuesday, October 29, 2019 10:00am
Location: Medical Science Research Building 2
Organized By: Cell & Developmental Biology

“Exploring neuronal heterogeneity in the Drosophila nervous system with novel neurotechnologies.”

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Lecture / Discussion Wed, 23 Oct 2019 13:20:35 -0400 2019-10-29T10:00:00-04:00 2019-10-29T11:00:00-04:00 Medical Science Research Building 2 Cell & Developmental Biology Lecture / Discussion Ye Li Dissertation Seminar
Dissertation Defense (November 4, 2019 2:00pm) https://events.umich.edu/event/68870 68870-17186668@events.umich.edu Event Begins: Monday, November 4, 2019 2:00pm
Location: Lorch Hall
Organized By: Department of Linguistics

Linguistics graduate candidate Alicia Stevers will defend her dissertation, "The said construction: usage, change, and social meaning in English and Spanish," on Monday, November 4, at 2 p.m. in 473 Lorch Hall. All are welcome.

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Other Mon, 28 Oct 2019 11:39:52 -0400 2019-11-04T14:00:00-05:00 2019-11-04T16:00:00-05:00 Lorch Hall Department of Linguistics Other Lorch Hall
Ph.D. Defense: Dakota Crisp (November 6, 2019 2:00pm) https://events.umich.edu/event/68890 68890-17188749@events.umich.edu Event Begins: Wednesday, November 6, 2019 2:00pm
Location: North Campus Research Complex Building 10
Organized By: Biomedical Engineering

Epilepsy is characterized by spontaneously recurring seizures that severely disrupt quality of life and pose risks of injury and death. It is a highly heterogenous disease, with seizures seen in a wide range of other diseases (Alzheimer’s, autism, Down’s syndrome, etc.). Yet to date, there is no method of categorizing seizures that can help distinguish the link between pathology and seizures. The aim of this work is to validate and explore a method of categorizing seizures based on their fundamental dynamics to provide a framework for future research to better investigate the underlying mechanisms of seizures and therapeutic approaches to stop them.

The first study used predictions from a previously-published computational model to visually classify seizures using dynamical transition features in two large datasets (simulated and real human data). Machine learning was applied to raw signal features to verify the accuracy of the reviewer’s labels. It found that visual classification is consistent and supported by the signal feature analysis. We also investigate the model’s predictions in real human data, finding that most dynamic classifications were observed and patients can have varying seizure dynamics over time. A major unpublished aspect of this work is that the human data analysis was crucial in the original development of the model.

The second study used data mining and machine learning in a long-term rat model of epileptogenesis to investigate the viability of these same dynamic principles as a biomarker of epileptic brain state. It also applied the same rigor to an analysis of the response to electrical stimulation. We found that evoked responses can be used to predict if an injured brain would eventually develop seizures or not. Once seizures began manifesting, both evoked responses and seizure onset dynamics had strong correlation with the progression of epileptogenesis, suggesting they are independent biomarkers.

For the final study, we use the same principles of dynamics and machine learning to characterize differences between a low Mg2+ / high K+ mouse brain-slice seizure model with and without different anti-seizure drugs. It found that anti-seizure drugs can change the observed seizure dynamics, and each drug has a different effect on brain dynamics.

These three studies provide evidence that seizures can be categorized by their fundamental dynamics. These dynamics can provide mechanistic insights into current brain state, future brain states, and the response to anti-epileptic drugs. The results presented in this dissertation can be used as a framework to further investigate seizure mechanisms and personalize patient treatment and research.

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Lecture / Discussion Mon, 28 Oct 2019 15:41:55 -0400 2019-11-06T14:00:00-05:00 2019-11-06T15:00:00-05:00 North Campus Research Complex Building 10 Biomedical Engineering Lecture / Discussion BME Logo
Ph.D Defense: James R. Day (November 8, 2019 1:00pm) https://events.umich.edu/event/68888 68888-17188748@events.umich.edu Event Begins: Friday, November 8, 2019 1:00pm
Location: Taubman Biomedical Science Research Building
Organized By: Biomedical Engineering

Cancer patient survivorship has increased substantially over the past few decades due to advances in anticancer treatments. However, a common deleterious effect of these lifesaving treatments is premature ovarian insufficiency (POI), as they are gonadotoxic. POI leads to infertility and loss of ovarian endocrine function, which is particularly devastating for female cancer survivors who experience POI prior to puberty, as puberty is the most crucial physiological event in a female’s life. Lack of ovarian endocrine function and absence of puberty leads to long-term co-morbidities such as poor bone health, diminished metabolic turnover, impacted cognition, and high risk of cardiovascular events. Current treatment options such as hormone replacement therapy and ovarian auto-transplantation are associated with non-physiological delivery of hormones and risk of re-implanting cancerous cells. This thesis details the work to prove our hypothesis that allo-transplantation of donor ovarian tissue can be utilized to restore ovarian endocrine function without evoking an immune response. We hypothesized the concept of immuno-isolation could be utilized to protect encapsulated allogeneic ovarian tissue in murine and non-human primate models.

First, we developed a dual poly(ethylene glycol) (PEG) that was appropriate for both ovarian tissue transplantation and immuno-isolation. The Dual PEG capsule contained a proteolytically degradable core crosslinked via Michael-type addition which was conducive for the dynamic growth of ovarian tissue and a non-degradable PEG shell that would serve as the immuno-protective barrier. We demonstrated in an ovariectomized syngeneic murine model that ovarian tissue encapsulated in Dual PEG survived and functioned until removed 60 days after implantation, which was shown through resumption of cyclicity, restoration of the hypothalamic-pituitary-gonadal (HPG) axis, and presence of healthy developed follicles.

Next, we demonstrated the capsule was immuno-isolating as allogeneic ovarian tissue encapsulated in Dual PEG and implanted in recipient mice did not evoke a significant allo-specific antibody response compared to controls and the capsule did not allow cellular infiltration; protecting the encapsulated allograft from the outside immune environment and leading to ovarian endocrine restoration. After we proved that the Dual PEG capsule can prevent cellular infiltration, we demonstrated that the capsule can also retain cells encapsulated within, which can possibly be applied towards ovarian tissue auto-transplantation through retention of cancerous cells present in the graft and preventing cancer spreading and metastasis. We then demonstrated that encapsulation of ovarian allografts in Dual PEG precludes sensitization of the host immune system which proves the capsule is immuno-isolating and the host immune system is not exposed to allo-antigens while the graft is encapsulating, possibly allowing multiple implantations of the capsule.

Lastly, we demonstrate that non-human primate ovarian tissue can survive and develop in the Dual PEG capsule restoring ovarian endocrine function, while being protected from an immune response as indicated by the lack of active, dividing T cells in a syngeneic and allogeneic NHP model. This proves the capsule can withstand the volumetric change present in NHP folliculogenesis, protecting the encapsulated allograft, which promotes graft survival and ovarian endocrine restoration. Taken together, this dissertation works towards allowing the implantation of allogeneic ovarian tissue to restore ovarian endocrine function in a physiological manner without the risk of immune rejection.

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Lecture / Discussion Mon, 28 Oct 2019 15:26:48 -0400 2019-11-08T13:00:00-05:00 2019-11-08T14:00:00-05:00 Taubman Biomedical Science Research Building Biomedical Engineering Lecture / Discussion BME Logo
PhD Defense: Cameron Miller (November 15, 2019 12:30pm) https://events.umich.edu/event/69389 69389-17316495@events.umich.edu Event Begins: Friday, November 15, 2019 12:30pm
Location: Michigan Memorial Phoenix Project
Organized By: Nuclear Engineering and Radiological Sciences

Title: Improved Active Interrogation Methods for Nuclear Nonproliferation Applications

Chair: Prof. Sara Pozzi

Abstract: Highly enriched uranium is arguably the most difficult material to detect in the realm of nuclear security and safeguards, but is of great concern for its possible role in developing nuclear weapons. Uranium-235 emits very few neutrons, and the low energy photons it emits are easily shielded, making passive detection of highly enriched uranium very difficult. Actively interrogating the material with neutron or photon sources can provide a much more prominent detection signal. These sources of radiation can be used to either induce detectable emissions in the material, or radiograph the material to distinguish it from possible shielding. Active interrogation presents detection challenges in signal quality and operational feasibility, especially because currently-available sources mostly emit photons that can be easily shielded and are below photonuclear energy thresholds. My research will focus on addressing these challenges by demonstrating advantages of photon interrogation based on recent enabling technologies, both from the perspective of the interrogating source and the detection system.

Inverse Compton scattering quasi-monoenergetic photon sources using a laser-driven plasma accelerator are a developing technology that has strong potential to advance photon interrogation methods. These sources use the laser wakefield phenomenon to accelerate electrons to very high energy. Photons from a secondary laser beam interact with these electrons through inverse Compton scattering, producing a photon source highly focused in energy and space. The energy of these photons can be tuned to penetrate shielding and induce photonuclear reactions. The work presented here is based on quasi-monoenergetic photon sources at the University of Nebraska Lincoln and the Lawrence Berkeley National Laboratory. Through Monte Carlo simulations, I have demonstrated the capability to image heavily shielded nuclear material, validated by experiment. These studies showed increased accuracy for hidden nuclear material detection over traditional bremsstrahlung sources.

A 9-MeV linac has been installed at UM, which outputs a high intensity of photons capable of inducing photonuclear reactions. This high photon intensity makes neutron detection and identification challenging, but we are developing methods to detect prompt neutrons in-pulse with organic scintillators. These methods incorporate high throughput data acquisition, active background reduction, and collaboratively developed neural-network based pulse discrimination and recovery. Initial experiments interrogating lead and tungsten surrogates for highly enriched uranium have identified elevated neutron counts for the cases with target present over active background.

Compared to a quasi-monoenergetic photon source, the bremsstrahlung source produces many low-energy photons that only contribute to surrounding dose rates. To demonstrate this dosimetric advantage, and verify shielding for the operation of various accelerators, a method for measuring dose rates was required. An organic scintillator based strategy was developed to provide a replicable and dual-particle dose rate detection method. This method has been used to simultaneously measure neutron and gamma dose rates from isotopic sources; these results show reasonable agreement with traditional instruments. Future experiments will demonstrate the method with active interrogation sources.

The results of my research will enable the use of organic scintillators and novel photon sources for use in an active interrogation scenario to prevent the spread of nuclear material.

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Lecture / Discussion Wed, 13 Nov 2019 10:48:33 -0500 2019-11-15T12:30:00-05:00 2019-11-15T14:30:00-05:00 Michigan Memorial Phoenix Project Nuclear Engineering and Radiological Sciences Lecture / Discussion flyer for PhD Defense of Cameron Miller
AE Dissertation Defense: "Investigation of the Hall Thruster Breathing Mode" (November 18, 2019 3:00pm) https://events.umich.edu/event/68875 68875-17188735@events.umich.edu Event Begins: Monday, November 18, 2019 3:00pm
Location: Francois-Xavier Bagnoud Building
Organized By: Aerospace Engineering

Hall thrusters can support a wide range of instabilities, many of which remain poorly understood but are known to play a critical role in the fundamental operation of these devices. In this work, the dominant low-frequency oscillations known as the “breathing mode” is investigated to provide a more analytically rigorous yet intuitive description of the instability. The new understanding of Hall thruster oscillations yielded by this effort can improve the reliability of these devices.

Time-resolved laser-induced fluorescence paired with an ion kinetic analysis is used to characterize the near-field and internal thruster plasma during breathing oscillations. A frequency scaling study indicates that several existing theories for the breathing mode are consistent with observed oscillation trends. However, an examination of the dynamic properties of the discharge reveals that these same theories are fundamentally inconsistent with the experimental data.

A novel physical process for the breathing mode is proposed and found to agree with the experimental findings. A model corresponding to this process is developed and shown to predict positive linear growth and realistic real frequencies. A simpler model is derived and used to produce simple analytical descriptions of the real frequency and growth of the breathing mode.

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Lecture / Discussion Mon, 28 Oct 2019 12:29:25 -0400 2019-11-18T15:00:00-05:00 2019-11-18T16:30:00-05:00 Francois-Xavier Bagnoud Building Aerospace Engineering Lecture / Discussion Ethan Dale
PhD Defense: Yadrianna Acosta-Sojo (December 5, 2019 3:00pm) https://events.umich.edu/event/67979 67979-16977563@events.umich.edu Event Begins: Thursday, December 5, 2019 3:00pm
Location: Michigan Memorial Phoenix Project
Organized By: U-M Industrial & Operations Engineering

TITLE OF DISSERTATION: Adaptation of sensory and motor rehabilitation procedures for stroke patients

CHAIR: Bernard Martin

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Presentation Mon, 25 Nov 2019 14:05:28 -0500 2019-12-05T15:00:00-05:00 2019-12-05T17:00:00-05:00 Michigan Memorial Phoenix Project U-M Industrial & Operations Engineering Presentation PhD Defense: Yadrianna Acosta-Sojo
EEB dissertation defense: Plant invasions and microbes: the interactive effects of plant-associated microbes on invasiveness of Phragmites australis (December 13, 2019 10:00am) https://events.umich.edu/event/68330 68330-17046009@events.umich.edu Event Begins: Friday, December 13, 2019 10:00am
Location: Rackham Graduate School (Horace H.)
Organized By: Ecology and Evolutionary Biology

Wes Bickford defends his doctoral dissertation.

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Presentation Thu, 12 Dec 2019 11:30:38 -0500 2019-12-13T10:00:00-05:00 2019-12-13T11:00:00-05:00 Rackham Graduate School (Horace H.) Ecology and Evolutionary Biology Presentation scene of phragmites growing on the shore of a lake
Dissertation Defense (December 13, 2019 12:00pm) https://events.umich.edu/event/70197 70197-17547230@events.umich.edu Event Begins: Friday, December 13, 2019 12:00pm
Location: Lorch Hall
Organized By: Department of Linguistics

Linguistics PhD candidate Kate Sherwood will defend her dissertation, "The Prosodic System of Southern Bobo Madare," on Friday, Dec. 13, at 12 p.m. Committee chair: Jelena Krivokapic.

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Other Wed, 11 Dec 2019 10:49:39 -0500 2019-12-13T12:00:00-05:00 2019-12-13T14:00:00-05:00 Lorch Hall Department of Linguistics Other Lorch Hall
Defense Dissertation: "Multidisciplinary Design Optimization of an Aircraft Considering Path-Dependent Performance" (December 16, 2019 2:00pm) https://events.umich.edu/event/70111 70111-17532718@events.umich.edu Event Begins: Monday, December 16, 2019 2:00pm
Location: Francois-Xavier Bagnoud Building
Organized By: Aerospace Engineering

John Jasa

Committee:
Co-Chair: Prof. Joaquim R.R.A. Martins
Co-Chair: Dr. Charles Mader
Cognate: Prof. Yin Lu Young
Members:
Prof. Kryzstof Fidkowski
Dr. Justin Gray

Aircraft are multidisciplinary systems that are challenging to design due to interactions between the subsystems. The relevant disciplines, such as aerodynamic, thermal, and propulsion systems, must be considered simultaneously using a path-dependent formulation to accurately assess aircraft performance. The overarching contribution of this work is the construction and exploration of a coupled aero-thermal-propulsive-mission multidisciplinary model to optimize supersonic aircraft considering their path-dependent performance.

First, the mission, thermal, and propulsion disciplines are examined in detail. The aerostructural design and mission of a morphing-wing aircraft is optimized before the optimal flight profile for a supersonic strike mission is investigated. Then a fuel thermal management system, commonly used to dissipate excess thermal energy from supersonic aircraft, is constructed and presented. Engine design is then investigated through two main applications: multipoint optimization of a variable-cycle engine and coupled thermal-engine optimization considering a bypass duct heat exchanger.

This culminates into a fully-coupled path-dependent mission optimization problem considering the aerodynamic, propulsion, and thermal systems. This large-scale optimization problem captures non-intuitive design trades that single disciplinary models and path-independent methods cannot resolve. Although the focal application is a supersonic aircraft, the methods presented here are applicable to any air or space vehicle and other path-dependent problems.

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Presentation Mon, 09 Dec 2019 13:30:37 -0500 2019-12-16T14:00:00-05:00 Francois-Xavier Bagnoud Building Aerospace Engineering Presentation John Jasa
BME Ph.D Defense: Xiaotian Tan (February 12, 2020 11:00am) https://events.umich.edu/event/72235 72235-17963874@events.umich.edu Event Begins: Wednesday, February 12, 2020 11:00am
Location: Cooley Building
Organized By: Biomedical Engineering

Biosensors are devices or systems that can be used to detect, quantify, and analyze targets with biological activities and functions. As one of the largest subsets of biosensors, biomolecular sensors are specifically developed and programmed to detect, quantify and analyze biomolecules in liquid samples.

Wide-ranging applications have made immunoassays increasingly popular for biomolecular detection and quantification. Among these, enzyme-linked immunosorbent assays (ELISA) are of particular interest due to high specificity and reproducibility. To some extent, ELISA has been regarded as a “gold standard” for quantifying analytes (especially protein analytes) in both clinical diagnostics and fundamental biological research. However, traditional (96-well plate-based) ELISA still suffers from several notable drawbacks, such as long assay time (4–6 hours), lengthy procedures, and large sample/reagent consumption (∼100 μL). These inherent disadvantages still significantly limit traditional ELISA's applicability to areas such as rapid clinical diagnosis of acute diseases (e.g., viral pneumonia, acute organ rejection), and biological research that requires accurate measurements with precious or low abundance samples (e.g., tail vein serum from a mouse). Thus, a bimolecular sensing technology that has high sensitivity, short assay time, and small sample/reagent consumption is still strongly desired.

In this dissertation, we introduce the development of a multifunctional and automated optofluidic biosensing platform that can resolve the aforementioned problems. In contrast to conventional plate-based ELISA, our optofluidic ELISA platform utilizes mass-producible polystyrene microfluidic channels with a high surface-to-volume ratio as the immunoassay reactors, which greatly shortens the total assay time. We also developed a low-noise signal amplification protocol and an optical signal quantification system that was optimized for the optofluidic ELISA platform.

Our optofluidic ELISA platform provides several attractive features such as small sample/reagent consumption (<8 µL), short total assay time (30-45 min), high sensitivity (~1 pg/mL for most markers), and a broad dynamic range (3-4 orders of magnitude). Using these features, we successfully quantified mouse FSH (follicle stimulating hormone) concentration with a single drop of tail vein serum. We also successfully monitored bladder cancer progression in orthotopic xenografted mice with only <50 µL of mouse urine. More excitingly, we achieved highly-sensitive exosome quantification and multiplexed immuno-profiling with <40 ng/mL of total input protein (per assay). These remarkable milestones could not be achieved with conventional plate-based ELISA but were enabled by our unique optofluidic ELISA.

As an emerging member of the bimolecular sensor family, our optofluidic ELISA platform provides a high-performance and cost-effective tool for a plethora of applications, including endocrinal, cancer animal model, cellular biology, and even forensic science research. In the future, this technology platform can also be renovated for clinical applications such as personalized cancer diagnosis/prognosis and rapid point-of-care diagnostics for infectious diseases.

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Lecture / Discussion Thu, 30 Jan 2020 09:28:04 -0500 2020-02-12T11:00:00-05:00 2020-02-12T12:00:00-05:00 Cooley Building Biomedical Engineering Lecture / Discussion Xiaotian Tan
EEB dissertation defense: When does gene flow stop? A mechanistic approach to the formation of phylogeographic breaks in nature (February 17, 2020 1:00pm) https://events.umich.edu/event/72023 72023-17914210@events.umich.edu Event Begins: Monday, February 17, 2020 1:00pm
Location: Biological Sciences Building
Organized By: Ecology and Evolutionary Biology

Iris defends her doctoral dissertation

Image credit: Alison Davis Rabosky and Christian Cox

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Presentation Thu, 06 Feb 2020 16:14:16 -0500 2020-02-17T13:00:00-05:00 2020-02-17T14:00:00-05:00 Biological Sciences Building Ecology and Evolutionary Biology Presentation Four sonora snakes curled up near each other, orange with black stripes, white with black stripes, a solid orange and a solid brown
BME Ph.D. Defense: Lauren L. Zimmerman (February 20, 2020 10:00am) https://events.umich.edu/event/72566 72566-18018159@events.umich.edu Event Begins: Thursday, February 20, 2020 10:00am
Location: Lurie Robert H. Engin. Ctr
Organized By: Biomedical Engineering

Department of Biomedical Engineering Final Oral Examination

Lauren L. Zimmerman

Investigating Neuromodulation as a Treatment for Female Sexual Dysfunction

Female sexual dysfunction (FSD) affects millions of women worldwide. FSD has a significant impact on quality of life and interpersonal relationships. The prevalence of at least one form of sexual dysfunction is 40-45% of adult women with 12% of women experiencing sexually related personal distress, yet there is no clear treatment option for a wide range of FSD deficits with high efficacy and low side effects.

Neuromodulation techniques using electrical stimulation of peripheral nerves have the potential to treat some forms of FSD. In clinical trials of sacral neuromodulation (SNM) and percutaneous tibial nerve stimulation (PTNS) for bladder dysfunction, women have reported that their sexual dysfunction symptoms improved as well. Even though this effect has been observed clinically, very little research has been done to examine the mechanisms or the optimal method of treatment specifically for women with FSD. This thesis aims to bridge that gap by investigating neuromodulation as a treatment for FSD through both preclinical and clinical studies.

The first aim of this thesis is to investigate a possible mechanism of the improvement to sexual functioning in response to tibial nerve stimulation by evaluating vaginal blood flow responses in rats. In 16 ketamine-anesthetized female rats, the tibial nerve was stimulated for 30 minutes while vaginal blood perfusion was recorded with laser Doppler flowmetry. A novel signal analysis and quantification metric was developed for this analysis. I found that tibial nerve stimulation could drive prolonged increases in vaginal blood perfusion, typically after 20-30 minutes of stimulation. This result suggests that clinical neuromodulation may be improving FSD symptoms by increasing genital blood flow.

One question yet to be investigated by neuromodulation studies is whether tibial nerve stimulation could be an on-demand treatment for FSD, such as Viagra is for men, or is more appropriate as a long-term treatment with improvements over time, such as PTNS for bladder dysfunction. In this thesis I address this question by evaluating the sexual motivation and receptivity of female rats both immediately after a single stimulation session as well as after long-term, repeated stimulation sessions. I found that tibial nerve stimulation led to modest increases in sexual motivation in the short term, and larger increases in sexual receptivity in the long-term.

Lastly, this thesis evaluates a pilot clinical study of transcutaneous stimulation of the dorsal genital and posterior tibial nerves in nine women with FSD. The women received stimulation once a week for 12 weeks and their sexual functioning was measured using the Female Sexual Function Index (FSFI) at baseline, after 6 weeks of stimulation, after 12 weeks of stimulation, and at 18 weeks (6 weeks after the last stimulation session). The average total FSFI score across all subjects significantly increased from baseline to each of the time points in the study. Significant FSFI increases were seen in the sub-domains of lubrication, arousal, and orgasm, each of which is related to genital arousal.

This thesis provides evidence that peripheral neuromodulation can be an effective treatment for FSD. The stimulation is likely driving increases in genital blood flow, with greater effects observed when stimulation is repeatedly applied over time. This treatment has the potential to help millions of women worldwide.

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Lecture / Discussion Wed, 05 Feb 2020 15:00:05 -0500 2020-02-20T10:00:00-05:00 2020-02-20T11:00:00-05:00 Lurie Robert H. Engin. Ctr Biomedical Engineering Lecture / Discussion BME Logo