Under the Crimson Flag: Fahle Burman's Two Trips to the Michigan Supreme Court

Erick Fahle Burman. a Swedish-born, Finnish-speaking labor and political activist, twice had cases argued on his behalf before the Michigan Supreme Court. In People vs. Burman, Burman, along with nine other defendants, had his conviction affirmed by the court and all ten were forced to pay a fine of $25 each for disturbing the peace. In People vs. Immonen, Burman and his co-defendant, Unto Immonen, had their convictions overturned because of improper evidence being admitted in their lower court trial. Though the conviction was overturned, the two men had already spent several months as prisoners at hard labor in Marquette State Prison located in Michigan's Upper Peninsula. Over twenty-five years separate Burman's two trips to Michigan's high court. On the first occasion, his arrest came less than five years after his arrival as an immigrant to the U. S. On the second occasion, his arrest came less than two years after his return to the state after being away for nearly two decades. On both occasions, Burman was arrested for his involvement with red flags. Though separated by decades, these cases, taken together, are important indicators of the state of Finnish-American radicalism in the years surrounding the red flag incidents and provide interesting insights into the delicacies of political suppression. Examination of these cases within the larger career of Fahle Burman points up his overlooked importance in the history of Finnish-American socialism and communism.

Genetic association studies under the population stratification, family pedigree and application to genome-wide association studies

This dissertation has three separate parts: the first part deals with the general pedigree association testing incorporating continuous covariates; the second part deals with the association tests under population stratification using the conditional likelihood tests; the third part deals with the genome-wide association studies based on the real rheumatoid arthritis (RA) disease data sets from Genetic Analysis Workshop 16 (GAW16) problem 1. Many statistical tests are developed to test the linkage and association using either case-control status or phenotype covariates for family data structure, separately. Those univariate analyses might not use all the information coming from the family members in practical studies. On the other hand, the human complex disease do not have a clear inheritance pattern, there might exist the gene interactions or act independently. In part I, the new proposed approach MPDT is focused on how to use both the case control information as well as the phenotype covariates. This approach can be applied to detect multiple marker effects. Based on the two existing popular statistics in family studies for case-control and quantitative traits respectively, the new approach could be used in the simple family structure data set as well as general pedigree structure. The combined statistics are calculated using the two statistics; A permutation procedure is applied for assessing the p-value with adjustment from the Bonferroni for the multiple markers. We use simulation studies to evaluate the type I error rates and the powers of the proposed approach. Our results show that the combined test using both case-control information and phenotype covariates not only has the correct type I error rates but also is more powerful than the other existing methods. For multiple marker interactions, our proposed method is also very powerful. Selective genotyping is an economical strategy in detecting and mapping quantitative trait loci in the genetic dissection of complex disease. When the samples arise from different ethnic groups or an admixture population, all the existing selective genotyping methods may result in spurious association due to different ancestry distributions. The problem can be more serious when the sample size is large, a general requirement to obtain sufficient power to detect modest genetic effects for most complex traits. In part II, I describe a useful strategy in selective genotyping while population stratification is present. Our procedure used a principal component based approach to eliminate any effect of population stratification. The paper evaluates the performance of our procedure using both simulated data from an early study data sets and also the HapMap data sets in a variety of population admixture models generated from empirical data. There are one binary trait and two continuous traits in the rheumatoid arthritis dataset of Problem 1 in the Genetic Analysis Workshop 16 (GAW16): RA status, AntiCCP and IgM. To allow multiple traits, we suggest a set of SNP-level F statistics by the concept of multiple-correlation to measure the genetic association between multiple trait values and SNP-specific genotypic scores and obtain their null distributions. Hereby, we perform 6 genome-wide association analyses using the novel one- and two-stage approaches which are based on single, double and triple traits. Incorporating all these 6 analyses, we successfully validate the SNPs which have been identified to be responsible for rheumatoid arthritis in the literature and detect more disease susceptibility SNPs for follow-up studies in the future. Except for chromosome 13 and 18, each of the others is found to harbour susceptible genetic regions for rheumatoid arthritis or related diseases, i.e., lupus erythematosus. This topic is discussed in part III.

Application of MFBD Algorithms to Image Reconstruction Under Anisoplanatic Conditions

All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. Both military and civilian surveillance, gun-sighting, and target identification systems are interested in terrestrial imaging over very long horizontal paths, but atmospheric turbulence can blur the resulting images beyond usefulness. My dissertation explores the performance of a multi-frame-blind-deconvolution technique applied under anisoplanatic conditions for both Gaussian and Poisson noise model assumptions. The technique is evaluated for use in reconstructing images of scenes corrupted by turbulence in long horizontal-path imaging scenarios and compared to other speckle imaging techniques. Performance is evaluated via the reconstruction of a common object from three sets of simulated turbulence degraded imagery representing low, moderate and severe turbulence conditions. Each set consisted of 1000 simulated, turbulence degraded images. The MSE performance of the estimator is evaluated as a function of the number of images, and the number of Zernike polynomial terms used to characterize the point spread function. I will compare the mean-square-error (MSE) performance of speckle imaging methods and a maximum-likelihood, multi-frame blind deconvolution (MFBD) method applied to long-path horizontal imaging scenarios. Both methods are used to reconstruct a scene from simulated imagery featuring anisoplanatic turbulence induced aberrations. This comparison is performed over three sets of 1000 simulated images each for low, moderate and severe turbulence-induced image degradation. The comparison shows that speckle-imaging techniques reduce the MSE 46 percent, 42 percent and 47 percent on average for low, moderate, and severe cases, respectively using 15 input frames under daytime conditions and moderate frame rates. Similarly, the MFBD method provides, 40 percent, 29 percent, and 36 percent improvements in MSE on average under the same conditions. The comparison is repeated under low light conditions (less than 100 photons per pixel) where improvements of 39 percent, 29 percent and 27 percent are available using speckle imaging methods and 25 input frames and 38 percent, 34 percent and 33 percent respectively for the MFBD method and 150 input frames. The MFBD estimator is applied to three sets of field data and the results presented. Finally, a combined Bispectrum-MFBD Hybrid estimator is proposed and investigated. This technique consistently provides a lower MSE and smaller variance in the estimate under all three simulated turbulence conditions.

Computer Aided Design Algorithmic Technique for Very Large Scale Integrated Circuit Design and Smart Home Embedded System Design

To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

Oligodeoxynucleotide synthesis using protecting groups and a linker cleavable under non-nucleophilic conditions

Oligodeoxynucleotides (ODNs) containing latent electrophilic groups can be highly useful in antisense drug development and many other applications such as chemical biology and medicine, where covalent cross-linking of ODNs with mRNA, protein and ODN is required. However, such ODN analogues cannot be synthesized using traditional technologies due to the strongly nucleophilic conditions used in traditional deprotection/cleavage process. To solve this long lasting and highly challenging problem in nucleic acid chemistry, I used the 1,3-dithian-2-yl-methoxycarbonyl (Dmoc) function to protect the exo-amino groups on the nucleobases dA, dC and dG, and to design the linker between the nascent ODN and solid support. These protecting groups and linker are completely stable under all ODN synthesis conditions, but can be readily cleaved under non-nucleophilic and nearly neutral conditions. As a result, the new ODN synthesis technology is universally useful for the synthesis of electrophilic ODNs. The dissertation is mainly comprised of two portions. In the first portion, the development of the Dmoc-based linker for ODN synthesis will be described. The construction of the dT-Dmoc-linker required a total of seven steps to synthesize. The linker was then anchored to the solid support―controlled pore glass (CPG). In the second portion, the syntheses of Dmoc-protected phosphoramidites ODN synthesis monomers including Dmoc-dC-amidite, Dmoc-dA-amidite, Dmoc-dG-amidite are described. The protection of dC and dA with 1,3-dithian-2-yl-methyl 4-nitrophenyl carbonate proceeded smoothly giving Dmoc-dC and Dmoc-dA in good yields. However, when the same acylation procedure was applied for the synthesis of Dmoc-dG, very low yield was obtained. This problem was later solved using a highly innovative and environmentally benign procedure, which is expected to be widely useful for the acylation of the exo-amino groups on nucleoside bases. The reactions to convert the Dmoc-protected nucleosides to phosphoramidite monomers proceeded smoothly with high yields. Using the Dmoc phosphoramidite monomers dA, dC, dG and the commercially available dT, and the Dmoc linker, four ODN sequences were synthesized. In all cases, excellent coupling yields were obtained. ODN deprotection/cleavage was achieved by using non-nucleophilic oxidative conditions. The new technology is predicted to be universally useful for the synthesis of ODNs containing one or more electrophilic functionalities.