An Unsupervised Deep Learning Approach for Scenario Forecasts

In this paper, we propose a novel scenario forecasts approach which can be applied to a broad range of power system operations (e.g., wind, solar, load) over various forecasts horizons and prediction intervals. This approach is model-free and data-driven, producing a set of scenarios that represent possible future behaviors based only on historical observations and point forecasts. It first applies a newly-developed unsupervised deep learning framework, the generative adversarial networks, to learn the intrinsic patterns in historical renewable generation data. Then by solving an optimization problem, we are able to quickly generate large number of realistic future scenarios. The proposed method has been applied to a wind power generation and forecasting dataset from national renewable energy laboratory. Simulation results indicate our method is able to generate scenarios that capture spatial and temporal correlations. Our code and simulation datasets are freely available online.Comment: Accepted to Power Systems Computation Conference 2018 Code available at https://github.com/chennnnnyize/Scenario-Forecasts-GA

MEMS-Based Endomicroscopes for High Resolution in vivo Imaging

Intravital microscopy is an emerging methodology for performing real time imaging in live animals. This technology is playing a greater role in the study of cellular and molecular biology because in vitro systems cannot adequately recapitulate the microenvironment of living tissues and systems. Conventional intravital microscopes use large, bulky objectives that require wide surgical exposure to image internal organs and result in terminal experiments. If these instruments can be reduced sufficiently in size, biological phenomena can be observed in a longitudinal fashion without animal sacrifice. The epithelium is a thin layer of tissue in hollow organs, and is the origin of many types of human diseases. In vivo assessment of biomarkers expressed in the epithelium in animal models can provide valuable information of disease development and drug efficacy. The overall goal of this work is to develop miniature imaging instruments capable of visualizing the epithelium in live animals with subcellular resolution. The dissertation is divided into four projects, where each contains an imaging system developed for small animal imaging. These systems are all designed using laser beam scanning technology with tiny mirrors developed with microelectromechanical systems (MEMS) technology. By using these miniature scanners, we are able to develop endomicroscopes small enough for hollow organs in small animals. The performance of these systems has been demonstrated by imaging either excised tissue or colon of live mice. The final version of the instrument can collect horizontal/oblique plane images in the mouse colon in real time (>10 frames/sec) with sub-micron resolution (<1 um), deep tissue penetration (~200 um) and large field of view (700 x 500 um). A novel side-viewing architecture with distal MEMS scanning was developed to create clear and stable image in the mouse colon. With the use of the instrument, it is convenient to pinpoint location of interest and create a map of the colon using image mosaicking. Multispectral fluorescence images can by collected at excitation wavelength ranging from 445 nm to 780 nm. The instruments have been used to 1) validate specific binding of a cancer targeting agent in the mouse colon and 2) study the tumor development in a mouse model with endogenous fluorescence protein expression. We use these studies to show that we have developed an enabling technology which will allow biologist to perform longitudinal imaging in animal models with subcellular resolution.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136954/2/dxy_1.pd

Exploring Plant Innate Immune Signaling Network: Layered Post-translational Modifications in Play

Prompt activation of pattern recognition receptors (PRRs) upon microbial infection is essential for hosts to defend against pathogen attacks. Plant Botrytis-induced kinase 1 (BIK1) family receptor-like cytoplasmic kinases are key immune regulators associated with multiple PRRs, including the flagellin receptor complex FLS2-BAK1 in arabidopsis (Arabidopsis thaliana). Upon flagellin perception, BAK1 directly phosphorylates BIK1, leading to BIK1 dissociation from the FLS2-BAK1 complex to relay immune signaling. How BIK1 activation is regulated and how the signal is transduced downstream remain largely elusive. In this dissertation, we found that flagellin perception triggers rapid monoubiquitination of BIK1 and its homolog PBL1 in planta. Time course and mutational analyses suggest that flagellin-induced BIK1 phosphorylation precedes BIK1 monoubiquitination. We further identified an RING-type E3 ligase LUCKY1 that interacts with BIK1 and monoubiquitinates BIK1 at multiple sites. Mass spectrometry and mutational analyses uncovered that the BIK1^9KR mutant with nine lysine residues mutated into arginine eliminated ubiquitination without sacrificing BIK1 kinase activity. Phenotypic analysis with transgenic plants expressing BIK1^9KR suggested that ubiquitination of BIK1 positively regulates BIK1 function as well as plant immune responses. Moreover, we found that flg22-triggered ubiquitination of BIK1 does not regulate BIK1 stability but controls ligand-induced BIK1 dissociation from receptor FLS2. Recognition of pathogen-associated molecular patterns (PAMPs) via PRRs triggers a transient spike of secondary messengers such as Ca^2+ and phosphatidic acid (PA) in plant. How lipid signaling is tightly controlled to modulate PA production in immunity remains largely unknown. Here we show a PA synthesis diacylglycerol kinase DGK5 functions positively in plant immunity and is differentially regulated by two phosphorylation events. Upon PAMP activation, the PRR-associated cytoplasmic kinase BIK1 directly interacts with DGK5 and phosphorylates DGK5 at Ser-506. In addition, PAMP-activated MAP kinase 4 (MPK4) phosphorylates DGK5 at Thr-446 independently of BIK1. Interestingly, phosphorylation at Ser-506 by BIK1 appears to positively regulate DGK5 function while MPK4-mediated Thr-446 phosphorylation possesses a negative impact. Our findings reveal a mechanism that how PRR complex activation directly switches on lipid signaling to orchestrate innate immunity

Solid-Solid Phase Transitions in Colloidal Matter

Phase transitions are ubiquitous in nature, and observed throughout everyday life from the melting of ice to the magnetization of iron. In particular, solid–solid phase transitions are important in many areas such as metallurgy, geosciences, and the design of reconfigurable materials. Following the recent initiative of using nano building blocks to design next generation materials, we answer fundamental questions about solid–solid phase transitions in colloidal matter and guide the design of ma- terials that can change phase. Using the “Digital Alchemy” framework, we extend thermodynamic ensembles to include particle shape as a thermodynamic variable. This framework enables us to study the effect of altering particle shape in solid–solid phase transitions. We first study the thermodynamic order of two different solid–solid phase tran- sitions (face-centered cubic (FCC)↔body-centered cubic (BCC) and BCC↔simple cubic (SC)) in hard-particle systems upon an instantaneous change in particle shape. By calculating the Landau free energy, we are able to determine the thermody- namic order of these two phase transitions. We find FCC↔BCC is first order while BCC↔SC is second order. This work is followed up by a more detailed investigation of the FCC↔BCC transition to explore whether it can be second order. We next study the design of pressure-induced solid–solid phase transitions. Here, we incorporate varying particle shape as a part of the Monte Carlo process to find the optimal shape for a given phase transition. We successfully designed pressure driven FCC→BCC and BCC→SC transitions using three different particle shape constraints. We also study the kinetic transition pathway between solid phases. Our results show that there are similarities of the pathways of an entropic system and an atom- istic system. This demonstrates that we can use entropic systems as a toy model to understand better how the transformations happen in an atomistic system. Results from this dissertation give insight into the fundamental nature of the most common, yet poorly understood phase transitions in nature, and provide new minimal models for understanding solid–solid transitions in atomic systems. Our findings also provide guidance for the next generation of materials design.PHDPhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146134/1/xiyudu_1.pd

Labor Migration in China: How Families Affect Migrant Workers

China’s huge economic growth over the past four decades has been observed by the world and oftentimes acknowledged as an economic miracle. One of the main factors of this extraordinary growth is the large labor population and comparatively cheap labor cost. With the introduction of the Economic Reform and Opening-Up in the late 1970s, a large proportion of the Chinese citizens started to seek better work opportunities outside their permanent residencies, which was not restricted prior to the reform. These people, commonly quoted as the migrant workers and consist more than 20% of the Chinese labor force, is being studied as a good indicator which reflects both the internal migration and the economic growth of China. This paper attempts to understand if family characteristics have any impact on individuals’ decisionmaking of becoming a migrant worker. The study finds that for each one extra person in the family, an individual’s likelihood of becoming a migrant worker will increase by 1.36%; whereas for each one extra child an individual has, the likelihood will decrease by 2.8%