TEMPERATURE DEPENDENCE OF THE GROWTH MODE DURING HOMOEPITAXY ON PATTERNED GALLIUM ARSENIDE (001); ATOMIC-SCALE MECHANISMS FOR UNSTABLE GROWTH.

ABSTRACT Title of Document: TEMPERATURE DEPENDENCE OF THE GROWTH MODE DURING HOMOEPITAXY ON PATTERNED GALLIUM ARSENIDE (001); ATOMIC-SCALE MECHANISMS FOR UNSTABLE GROWTH. Tabassom Tadayyon-Eslami, Doctor of Philosophy, 2006 Directed By: Professor Raymond J. Phaneuf, Department of Materials Science and Engineering In this thesis we present an extensive investigation of instability in molecular beam epitaxial growth of GaAs(001) over a range of pattern periods, cell sizes, growth temperature and As2 flux. We find very good agreement with predictions of the continuum models of Sun, Guo and Grant [Phys. Rev. A 40, 6763(1989)] for the growth above ~540ºC and Lai and Das Sarma [Phys. Rev. Lett. 66, 2348 (1991)] for the growth below this temperature. Changing the growth temperature to lower than 540 ºC leads to the formation of ring-like protrusions in the [110] direction around pits patterned on the initial substrate, which are absent for growth at higher temperature. This change in growth mode occurs in the temperature range within in which both pre-roughening transition and surface reconstruction transition (β2(2x4) to c(4x4)) also occur. We rule out the possibility of preroughening and the change in surface reconstruction as the reason for this growth mode change, based on the As2 flux dependence of the growth mode transition temperature. Based on our atomic force microcopy characterization of the surface morphology during early the stage of growth, we propose a physically based model for the growth, which involves a competition between decreased adatom collection efficiency during growth on small terraces and a small anisotropic multiple step Ehrlich-Schwoebel barrier at the pit edge. This provides a physical basis for the nonlinear term in the continuum models proposed by Sun et. al., and Lai and Das Sarma, whose predictions qualitatively describe our experimental observations

Fractionation of the insoluble brain proteins with acrylamide electrophoresis

A method for fractionating the insoluble proteins of the brain with polyacrylamide electrophoresis is described. The procedure consists of dissolving the membrane proteins in a solution of urea, alkali, mercapto-ethanol, and Triton, and then conducting the separation in gels containing urea and Triton in discontinuous acidic buffers. As many as 30 sharp bands are discernable in the gel out of an insoluble brain fraction. The reproducibility of the band pattern is demonstrable in a gel slab system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/32783/1/0000156.pd

Advances in functional assemblies for regenerative medicine

The ability to synthesise bioresponsive systems and selectively active biochemistries using polymer-based materials with supramolecular features has led to a surge in research interest directed towards their development as next generation biomaterials for drug delivery, medical device design and tissue engineering

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

© 2017 The Author(s). This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic

Chronic kidney disease associated cardiovascular disease: scope and limitations of animal models

Chronic kidney disease (CKD) is a heterogeneous range of disorders affecting up to 11% of the world’s population. The majority of patients with CKD die of cardiovascular disease (CVD) before progressing to end-stage renal disease. CKD patients have an increased risk of atherosclerotic disease as well as a unique cardiovascular phenotype. There remains no clear aetiology for these issues and a better understanding of the pathophysiology of CKD-associated CVD is urgently needed. Although nonanimal studies can provide insights into the nature of disease, the wholeorganism nature of CKD-associated CVD means that highquality animal models, at least for the immediate future, are likely to remain a key tool in improving our understanding in this area. We will discuss the methods used to induce renal impairment in rodents and the methods available to assess cardiovascular phenotype and in each case describe the applicability to humans

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis

Classifying and Grouping Mammography Images into Communities Using Fisher Information Networks to Assist the Diagnosis of Breast Cancer

© 2020, Springer Nature Switzerland AG. The aim of this paper is to build a computer based clinical decision support tool using a semi-supervised framework, the Fisher Information Network (FIN), for visualization of a set of mammographic images. The FIN organizes the images into a similarity network from which, for any new image, reference images that are closely related can be identified. This enables clinicians to review not just the reference images but also ancillary information e.g. about response to therapy. The Fisher information metric defines a Riemannian space where distances reflect similarity with respect to a given probability distribution. This metric is informed about generative properties of data, and hence assesses the importance of directions in space of parameters. It automatically performs feature relevance detection. This approach focusses on the interpretability of the model from the standpoint of the clinical user. Model predictions were validated using the prevalence of classes in each of the clusters identified by the FIN

Transport properties of copper phthalocyanine based organic electronic devices

Ambipolar charge carrier transport in Copper phthalocyanine (CuPc) is studied experimentally in field-effect transistors and metal-insulator-semiconductor diodes at various temperatures. The electronic structure and the transport properties of CuPc attached to leads are calculated using density functional theory and scattering theory at the non-equilibrium Green's function level. We discuss, in particular, the electronic structure of CuPc molecules attached to gold chains in different geometries to mimic the different experimental setups. The combined experimental and theoretical analysis explains the dependence of the mobilityand the transmission coefficient on the charge carrier type (electrons or holes) and on the contact geometry. We demonstrate the correspondence between our experimental results on thick films and our theoretical studies of single molecule contacts. Preliminary results for fluorinated CuPc are discussed.Comment: 18 pages, 16 figures; to be published in Eur. Phys. J. Special Topic