Thesis (M.S.)--West Virginia University, 1999. / Title from document title page. "April 1998." Document formatted into pages; contains vi, 70 p. : ill. (some col.) Includes abstract. Includes bibliographical references (p. 45-46).

Thesis (Ph. D.)--University of Cambridge, 1998. / Includes bibliographical references (p. 197-201).

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xviii, 126 p.; also includes graphics (some col.) Includes bibliographical references (p. 121-126). Available online via OhioLINK's ETD Center

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 262-263). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 262-263). Also available on the Internet.

Thesis (M.Eng.)--Memorial University of Newfoundland, 2004. / Bibliography: leaves 134-138.

Thesis (Ph. D.)--University of Oregon, 2006. / Typescript. Includes vita and abstract. Includes bibliographical references (leaves 174-183). Also available for download via the World Wide Web; free to University of Oregon users.

There is great need of robust and high throughput techniques for accurately measuring the concentration of nanoparticles in a solution. Microarray imaging techniques using widely used to quantify the binding of labeled analytes to a functionalized surface. However, most approaches require the combined output of many individual binding events to produce a measurable signal, which limits the sensitivity of such assays at low sample concentrations. Although a number of high-NA optical techniques have demonstrated the capability of imaging individual nanoparticles, these approaches have not been adopted for diagnostics due complex instrumentation and low assay throughput. Alternatively, interferometric imaging techniques based on light scattering have demonstrated the potential for single nanoparticle detection on a robust and inexpensive platform. This dissertation focuses on the development of methods and infrastructure to enable the development of diagnostic assays using the Single Particle Interferometric Imaging Sensor (SP-IRIS). SP-IRIS uses a bright-field reflectance microscope to image microarrays immobilized on a simple reflective substrate, which acts as a common-path homodyne interferometer to enhance the visibility of nanoparticles captured near its surface. This technique can be used to detect natural nanoparticles (such as viruses and exosomes) as well as molecular analytes (proteins and nucleic acid sequences) which have been tagged with metallic nanoparticle in a sandwich assay format. Although previous research efforts have demonstrated the potential for SP-IRIS assays in a variety of applications, these studies have largely been focused on demonstrating theoretical proof of concept in a laboratory setting. In contrast, the effective use of SP-IRIS as a clinical diagnostic platform will require significant functional improvements in automation of assay incubation, instrument control, and image analysis. In this dissertation, we discuss the development of instrumentation and software to support the translation of SP-IRIS from manual laboratory technique into an automated diagnostic platform. We first present a collection of mechanical solutions to enable the real-time, in-solution imaging of nanoparticles in disposable microfluidic cartridges. Next, we present image analysis techniques for the detection of nanoparticle signatures within digital images, and discuss solutions to the unique obstacles presented by the ill-defined focal properties of homodyne interferometry. Finally, we present a particle tracking algorithm for residence time analysis of nanoparticle binding in real-time datasets. Collectively, these improvements represent significant progress towards the use of SP-IRIS as a robust and automated diagnostic platform. / 2019-07-02T00:00:00Z

The ability to synthesize recordings from surface data as if they had come from subsurface sources has allowed geophysicists to estimate subsurface properties. Either in the form of classical seismic migration which creates structural maps of the subsurface, to the more recent seismic interferometry which turns seismic sources into receivers and vice-versa, this ability has provided a rich trove of methods with which to probe the Earth's interior. While powerful, both of these techniques suffer from well-known issues. Standard migration requires data without multiply-scattered waves (multiples). Seismic interferometry, on the other hand, can be applied to full recorded data (containing multiples and other wave types), but requires sources (receivers) to be physically placed at the location from (to) one wishes to estimate responses. The Marchenko method, developed recently for the seismic setting, circumvents both of these restrictions: it creates responses from virtual subsurface sources as if measured at the surface. It requires only single-sided surface data, and a smooth estimate of the subsurface velocities. Initially developed for acoustic media, this thesis contributes the first elastic formulation of the Marchenko method, providing a more suitable setting for applications for the solid Earth. In another development, this thesis shows how the obtained virtual recordings may be used for migration. With these two contributions, this thesis shows that for elastic surface seismic data, the main drawbacks of migration and interferometry can be overcome using the Marchenko method: multiples do not harm migrated images, and sources (receivers) need not be physically placed in the medium for their responses to be accessible. In addition to the above methods, generating images devoid of multiple-related artifacts can be achieved in several other different ways. Two approaches to this are the use of a post-imaging filter, and attenuation of internal multiples in the data itself. This thesis contributes one new method using each of these approaches. First, a form of Marchenko imaging is known to create spurious reflectors, as also occurs in standard reverse-time migration (RTM). However, these artifacts usually appear at different locations in RTM and this form of Marchenko imaging. Using this insight, this thesis presents a way to combine pairs of seismic images in such a way that their differences (e.g. artifacts) are attenuated, while similarities (e.g. true reflectors) are preserved. Applying this to RTM and Marchenko-derived images markedly improves image quality. Second, this thesis presents a method to estimate multiples in the data. Multiples can either be migrated on their own to aid in interpretation, or be adaptatively removed from the data to improve image quality. However, because of the nature of adaptive subtraction, this second method may harm primary energy. To avoid this problem, this thesis develops a final method to directly image using only primary energy in the recorded data using only a small number of virtual points. This method bypasses the need for multiple removal and the estimation of subsurface responses at every depth location. In addition, primaries from particular reflectors may be particularly selected such that they can be imaged individually. Overall this thesis provides several new ways to use surface seismic data in such a way that multiples do not hamper the end product of seismic data processing: the seismic image. It demonstrates this use on synthetic and real data, proving their effectiveness.

Modern optical measurement techniques have  developed rapidly in recent years. One of the  measurement technologies  is polarization interferometry that can be used  for roughness evaluation, deformation measurement,  and vibration analysis of objects. based on LabVIEW and MATLAB, this project  introduces the technique of virtual  instruments into the field of modern optical  measurements. The optical phase images  have been captured by LabVIEW and processed  by MATLAB to acquire the surface structures. The main research work in the project involves:  (1) Introduction of the virtual instrument  technique to capture and process optical phase  images; (2) Processing of phase  images acquired with different wavelengths using  MATLAB to reveal show the 2D and 3D  surface structures.