Thesis (doctoral)--Universität Bonn.

Thesis (M.S.)--Rowan University, 2009. / Typescript. Includes bibliographical references.

Thesis (M.S.)--Rowan University, 2009. / Typescript. Includes bibliographical references.

The purpose of this thesis is to compare the S.A. law of enrichment with the German BGB, to answer the question whether both systems are so similar that in both of them a general enrichment action could exist. Before this question can be answered in the affirmative, it has to be investigated whether, first of all, a basic structural similarity of these two Romanistic legal systeas exist and (secondly), whether the BGB recognizes a general enrichment action. The coaparison would be fairly easy if one could say that at least the basic principles of each system were of a firmly developed and undisputed nature. But this is far from true! Voluminous works have been written not only concerning the law of enrichment in general, but even concerning each specific element of enrichment liability. I do not intend to add another compendium to this huge number. Nor do I intend to discuss the actio negotiorum gestorum. This thesis is aimed at giving a short outline of both systems of unjustified enrichment, and elaborating basic principles of enrichment liability; thereafter the difference between the two systems will be highlighted by examples and, finally, special attention will be paid to the problem of a general enrichment action.

Annotation Enrichment Analysis is a widely used analytical methodology to process data generated by high-throughput genomic and proteomic experiments such as gene expression microarrays. The analysis uncovers and summarizes discriminating background information for sets of genes identified by the previous processing stages (e.g., a set of differentially expressed genes, a cluster). Enrichment analysis algorithms attach annotations to the genes and then discover statistical fluctuations of individual annotation terms in a given gene subset. The annotation terms represent different aspects of biological knowledge and come from databases such as GO, BIND, KEGG. Typical statistical models used to detect enrichments or depletions of annotation terms are hypergeometric, binomial and X2. At the end, the discovered information is utilized by human experts to find biological interpretations of the experiments. The main drawback of AEA is that it isolates and tests for overrepresentation of isolated individual annotation terms or groups of similar terms. As a result, AEA is limited in its ability to uncover complex phenomena involving relationships between multiple annotation terms from various knowledge bases. Also, AEA assumes that annotations describe the whole object of interest, which makes it difficult to apply it to sets of compound objects (e.g., sets of protein-protein interactions) and to sets of objects having an internal structure (e.g., protein complexes). To overcome this shortcoming, we propose a novel logic-based Annotation Concept Synthesis and Enrichment Analysis (ACSEA) approach. In this approach, the source annotation information, experimental data and uncovered enriched annotations are represented as First-Order Logic (FOL) statements. ACSEA uses the fusion of inductive logic reasoning with statistical inference to uncover more complex phenomena captured by the experiments. The proposed paradigm allows a synthesis of enriched annotation concepts that better describe the observed biological processes. The methodological advantage of Annotation Concept Synthesis and Enrichment Analysis is six-fold. Firstly, it is easier to represent complex, structural annotation information. Information already captured and formalized in OWL and RDF knowledge bases can be directly utilized. Secondly, it is possible to synthesize and analyze complex annotation concepts. Thirdly, it is possible to perform the enrichment analysis for sets of aggregate objects (such as sets of genetic interactions, physical protein-protein interactions or sets of protein complexes). Fourthly, annotation concepts are straightforward to interpret by a human expert. Fifthly, the logic data model and logic induction are a common platform that can integrate specialized analytical tools (e.g. tools for numerical, structural and sequential analysis). Sixthly, used statistical inference methods are robust on noisy and incomplete data, scalable and trusted by human experts in the field. In this thesis we developed and implemented the ACSEA approach. We evaluate it on large-scale datasets from several microarray experiments and on a clustered genome-wide genetic interaction network using different biological knowledge bases. Also, we define a statistical model of experimental and annotation data and evaluate ACSEA on synthetic datasets. The discovered interpretations are more enriched in terms of P- and Q-values than the interpretations found by AEA, are highly integrative in nature, and include analysis of quantitative and structured information present in the knowledge bases. The results suggest that ACSEA can significantly boost the effectiveness of the processing of high-throughput experiment data.

The field of sample enrichment is currently receiving a large amount of attention because it is essential to reduce the time required for many laboratory processes. Dielectrophoresis, or the motion of a polarized particle in the presence of a non-uniform electric field, has emerged as a promising method for biological sample concentration. By relying upon electrical properties that are intrinsic to a cell or microparticle, dielectrophoretic concentration avoids the need for sample preparation procedures which can greatly reduce the throughput of a system. Contactless Dielectrophoresis (cDEP) is a promising manifestation of dielectrophoresis in which the electrode structures that provide the non-uniform electric field are physically separated from the sample by a thin dielectric barrier. This work presents two methods for providing the high-voltage and high-frequency signal necessary to generate a non-uniform electric field in the sample channel of a cDEP device. The first method, an oscillator-based system, was able to produce DEP trapping and pearl-chaining of THP-1 and MCF-7 breast cancer cells in a cDEP device. The second method presented here utilizes an amplifier and transformer combination to generate very high voltages over a wide range of frequencies. Finally, electrorotation, or the spin imparted to a particle due to a rotating electric field has proven to be an extremely useful analysis of a cell's dielectric properties. A wideband, computer controlled function generator, outputting four sinusoidal waveforms in quadrature is presented. This device was able to produce outputs with the proper alignment over the range of 10 Hz to 100MHz. / Master of Science

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No description available.

The purpose of this study was to determine if participation in a marriage enrichment program had an impact on couple's relationships in the areas of regard, empathy, congruence, dyadic adjustment and self esteem. Seven independent variables were also analyzed to see if they had any impact on the five outcome measures. A survey was given at four different time periods (pretest, immediately before the enrichment experience; posttest, immediately after the enrichment experience; three months following; and six months following the enrichment experience) to determine if change did occur and if it was maintained over time. There was no control group and the experimenta l group had an N of 36 , or 18 couples . The results showed a significant increase in regard , empathy, congruence, and dyadic adjustment from pretest to posttest. Self esteem increased slightly but not 8t a significant level. From posttest to the three-month followup, regard, empathy, congruence and dyadic adjustment declined significantly and self-esteem increased significantly. From the three-month followup to the six-month followup there was no significant difference indicating a stablizing effect. A~e and dyadic adjustment were significantly related. The older the coup le, the better the mari tal adjustment. (Number of child ren approached significance in explaining level of re~Sar d .) This relationship was negati ve , meaning the l ower the number of the children the higher the level of rega rd. None of the other independent variables had any impact on the outcome measures. Although the mean scores for the five outcome measures signif icantly declined from posttest to six- month followup, they were still hi gher t han pretest mean scores .