The advances in mass spectrometry (MS) instrumentation have rendered MS an indispensable tool for structure elucidation, quantification, and assessment of the biological consequences of DNA modifications. DNA encodes genetic information that is used in the development and functioning of essentially all known organisms. Changes in DNA could give rise to compromised transmission of genetic information. Abnormal modifications are generally harmful to cells and will be converted to permanent genetic damage if they evade DNA repair, whereas epigenetic DNA modifications are regulators of cell function that influence chromatin structure and control the levels of gene expression. The emphasis of this dissertation is on the application of MS, together with biological techniques, for assessing the occurrence and biological consequences of these two major types of DNA modifications.

After an introduction presented in Chapter 1, Chapter 2 focuses on monitoring the enzymatic removal of 8-methoxypsoralen-induced DNA interstrand cross-links (ICLs) in cultured mammalian cells by using an HPLC coupled with tandem-MS approach. With genetic depletion of DNA repair proteins, we also pinpointed the role of nucleotide excision repair pathway in removing DNA ICLs. Chapters 3 and 4 discuss the development of an HPLC-MS/MS/MS method, along with the isotope dilution technique, for accurate measurements of 5-hydroxymethyl, 5-formyl and 5-carboxyl derivatives of 2'-deoxycytidine and 5-hydroxymethyl-2'-deoxyuridine (5-hmdU) in genomic DNA of cultured human cells, mammalian tissues and plant tissues. This is the first direct quantitative comparison between the levels of multiple 5-mdC derivatives in mammalian tissues and the first report of their presence in the model plant Arabidopsis. Chapter 5 describes the combination of this method with other bioanalytical techniques for studying the mechanisms of arsenic epigenotoxicity. We found that arsenite could bind directly to the zinc fingers of Tet proteins and substantially impair the catalytic efficiency of Tet proteins in oxidizing 5-mC both in vitro and in cells. In Chapter 6, we report the application of LC-MS/MS for quantifying β-D-glucosyl-5-hydroxymethyl- 2'-deoxyuridine (dJ) in Trypanosoma brucei. The results provide evidence that dJ binding proteins play an important role in oxidizing thymidine to form 5-hmdU, which then facilitates the generation of dJ.

Biological and solid-state nanopore sensors have proven their capability of high-throughput electrical single molecule sensing and potential in DNA/RNA sequencing. On the other hand, optofluidics, the combination of integrated optics and microfluidics, has drawn extensive attention over the past decade. The combination of nanopore technology and optofluidics is bound to bring impressive features and superiority. In this work, we innovatively integrated the solid-state nanopore into an optofluidic device, anti-resonant reflecting optical waveguides (ARROWs), to form an electro-opto-fluidic sensing platform, and demonstrate for the first time correlated electro-optical detection of single biological nanoparticles.

In order to successfully fabricate the solid-state nanopore in the semiconductor based ARROWs, we developed different fabrication methods, which are either based on standard semiconductor processes, or require the help of a focused ion beam milling. Solid-state nanopores fabricated with these methods were thoroughly characterized, analyzed, and compared using cross section analysis, energy dispersive X-ray analysis, and finite element simulation. We demonstrated that the fabrication dependent geometric shape of the pore determines the electrical blockade signal.

Afterwards, our nanopore-optofluidic device was used for the correlated electro-optical detection of single synthesized nanoparticles, single viruses, and single DNA molecules. The nanopore functions as a smart gate for sequential introduction of single nanoparticles for optical analysis. We proved that the electrical signals and the optical signals of individual nanoparticles can be clearly detected and cross correlated with a fidelity of up to 100%. On top of that, the electrical signal and the optical signal were used together to distinguish and identify different particles which could not be differentiated using either one of the signals. Moreover, information about the flow velocity, the particle-nanopore interaction, and the particle's fine structure could be extracted by analyzing electrical and optical signals. Furthermore, the combined analysis of optical signal intensity distribution and the simulated particle locations in the flow assisted us to find out the optical mode location.

Both the results and the theoretical analysis show that our novel electro-opto-fluidic platform is promising for further scientific research and clinical applications.

Robot grasp planning has been extensively studied in the last decades often consisting of two different stages determining where to grasp an object and measuring the quality of a tentative grasp. Additionally, because these two processes are computationally demanding, form closure grasps are more widely used in practice than force closure grasps, even though the latter is, in many cases, preferable. In this dissertation, we introduce our framework to improve grasp quality evaluation by increasing the speed of evaluating a grasp and developing more informative metrics. Specifically, we accelerate the computation of the grasp wrench space, used to measure the grasp quality, by exploiting some geometric insights in the computation of a convex hull through identifying a cutoff sequence to terminate the convex hull calculation with guaranteed convergence to the quality measure. Furthermore, we go into detail about the metric improvement for the grasp quality. Specifically, we study how noise at each joint of the manipulator affects grasp quality and how different arm configurations will generate different noise distributions at the end-effector, which has a huge impact in the robustness of grasping. Moreover, we illustrate our method that evaluates arm configurations based on the probability of achieving a force closure grasp. Then we introduce our work taking into account the hand structure and the local geometry of the object to be grasped as the second aspect for improving grasp quality metrics. In particular, for concave objects, we exploit the fact that grasping the concave region can make the grasp more robust. These insights are explored through theory and then validated on an experimental platform. Finally, we present three grasp planners we developed. We constructed two planners taking advantage of the negative curvature feature. The first the planner uses the geometry model of the object and constructs a database for online use. The second planner does not require the model but instead, detects negative curvature features on the fly and calculates candidate grasps in real time. Lastly, our third grasp planner searches through the objects' surface, represented as a triangular mesh, and tries to find the global optimal grasp.

This dissertation consists of three chapters that study dealer's endogenous search effort in over-the-counter (OTC) financial markets and its effect on asset's liquidity risk in U.S. corporate bond markets. In Chapter 1, I study dealer's search intensity using a transaction-level data set on U.S. corporate bonds. The main target of this chapter is to test whether dealer's search intensity is endogenously determined by their idiosyncratic states and how search intensity affects market efficiency. Existing literatures commonly do not consider dealer's continuous adjustment of search intensity in search-and-match models and there is no paper using transaction-level data to estimate the dealer-level state-dependent search intensity. In this paper, I propose a search-and-match model with dealers' endogeneous and state-dependent search intensity and estimate it using the TRACE data for the U.S. corporate bond market. I find that: [1] if we rank all dealers by their private valuations for holding the bond, the dealer of the middle-level private valuation will choose the highest level of search intensity, and she works as the "dealer of dealers" to reallocate bond positions from the low-type dealers to the high-type dealers; [2] the estimated model gives us a quantitative evaluation of the inefficiency due to the decentralized market structure. At the average level across all sub-markets in our sample, the model estimates that dealers' search cost is 0.75% of bond's face value, and there is on average 8.64% of bond positions being misallocated, comparing with a counterfactual frictionless market. In conclusion, the decentralized market structure generates 8.96% welfare loss relative to the frictionless one.

In Chapter 2, I study the correlation between corporate bond's misallocation among dealers and liquidity risk. This chapter bridges the literature on search-and-match models and the literature on explaining the non-default component of corporate bond's credit spread variations. In this paper, I propose a measure of bond's misallocation among dealers. This measure is based on a structural search-and-match model, and is defined as the cross-sectional covariance of dealers' idiosyncratic private valuations for holding the bond and their actual inventory positions in the bond. Using the TRACE data for the U.S. corporate bond market, I construct a panel data which contains yearly series of empirical estimates of bond's misallocation and liquidity risk, and verify that: at the bond level, a higher magnitude of misallocation among the dealers is associated with a higher magnitude of liquidity risk. This finding gives a preliminary market microstructural evidence supporting that: the distribution of market maker's states correlates with the magnitude of asset's liquidity risk.

In Chapter 3, I theoretically study the social optimal policy function of dealer's meeting technology in over-the-counter markets. This chapter contributes to the existing literature by considering the dealer-level state-dependent meeting technology in a random search model and obtaining explicit-form solutions of the social optimal policy functions. In the model, I allow the agents (dealers) to freely adjust their meeting technologies based on two types of idiosyncratic states: asset position and liquidity need. I find that in the social optimal policy functions, there is no intermediation in the sense that no dealer will choose to search simultaneously on both the buy side and sell side of the market. This result applies for a general form of search-cost function.