[pt] Este trabalho apresenta um algoritmo de construção de malhas em grafos conexos orientados definidos pela matriz de incidência. Se o grafo é planar e conexo é obtida a matriz de malhas, com o fim de permitir alternativa de análises, por nós ou malhas, de redes elétricas lineares ativas descritas apenas por seus nós. Foi desenvolvido também um algoritmo que realiza essas 2 análises e que aceita elementos ideais como fontes de tensão e corrente, controladas ou não, amplificadores operacionais ideais, indutâncias mútuas. A dimensão do programa foi reduzida pelo fato da representação de um elementos em um método ser igual a de seu dual em outro método. É feita também uma comparação entre os métodos de anos métodos de análise existente. / [en] An algorithm is presented that defines all the internal meshes of na oriented connected graph described by its incidence matrix. In the case of a planar, connected graph, a mesh matrix is obtained, which allows either nodal or mesh analysis of an active linear network described by its nodes. A further algorithm is developed ehich applies both these types of analysis to networks with ideal elements, such as controlled or uncontrolled current and voltage sources, operational amplifiers and mutual inductances. Owing to the fact that the representation of an element in one of these methods is identical to that of the dual element in the other, a program which performs nodal analysis may easily be adapted to perform mesh analysis. The methods are compared with existing methods of circuit analysis and some conclusions are drawn.

abstract: Cancer is a major public health challenge and the second leading cause of death in the United States. Large amount of effort has been made to achieve sensitive and specific detection of cancer, and to predict the course of cancer. Glycans are promising avenues toward the diagnosis and prognosis of cancer, because aberrant glycosylation is a prevalent hallmark of diverse types of cancer. A bottom-up “glycan node analysis” approach was employed as a useful tool, which captures most essential glycan features from blood plasma or serum (P/S) specimens and quantifies them as single analytical signals, to a lung cancer set from the Women Epidemiology Lung Cancer (WELCA) study. In addition, developments were performed to simplify a relatively cumbersome step involved in sample preparation of glycan node analysis. Furthermore, as a biomarker discovery research, one crucial concern of the glycan node analysis is to ensure that the specimen integrity has not been compromised for the employed P/S samples. A simple P/S integrity quality assurance assay was applied to the same sample set from WELCA study, which also afford the opportunity to evaluate the effects of different collection sites on sample integrity in a multisite clinical trial. Here, 208 samples from lung cancer patients and 207 age-matched controls enrolled in the WELCA study were analyzed by glycan node analysis. Glycan features, quantified as single analytical signals, including 2-linked mannose, α2‐6 sialylation, β1‐4 branching, β1‐6 branching, 4-linked GlcNAc, and outer-arm fucosylation, exhibited abilities to distinguish lung cancer cases from controls and predict survival in patients. To circumvent the laborious preparation steps for permethylation of glycan node analysis, a spin column-free (SCF) glycan permethylation procedure was developed, applicable to both intact glycan analysis or glycan node analysis, with improved or comparable permethylation efficiency relative to some widely-used spin column-based procedures. Biospecimen integrity of the same set of plasma samples from WELCA study was evaluated by a simple intact protein assay (ΔS-Cysteinylated-Albumin), which quantifies cumulative exposure of P/S to thawed conditions (-30 °C). Notable differences were observed between different groups of samples with various initial handling/storage conditions, as well as among the different collection sites. / Dissertation/Thesis / Doctoral Dissertation Biochemistry 2019

The expansive nature of water distribution system makes them susceptible to threats such as natural disasters and man-made destructions. Vulnerability assessment research efforts have increased since the passing of “Bioterrorism Preparedness and Response Act” in 2002 to harden WDS. This study aimed to develop a method that locates critical nodes without hydraulic analysis of every failure scenario, applicable for any size WDS, incorporates critical infrastructure, and capable of verifying method accuracy. The Flow Distribution method is the application of the gravity model, typically used to predict traffic flows in transportation engineering, to a distribution system. Flow distribution predicts the amount of demand and population that would be affected if any node in the system were disabled by solving for the distribution of each node’s outflow. Flow Distribution is applied to the hypothetical city, Anytown, USA using the computer simulation program WaterCAD to model two different disaster scenarios. Results were verified by analyzing sixteen failure scenarios (one for each node) to measure the actual demand and population effect, which was then compared to the nodes predicted by Flow Distribution. Flow Distribution predicted the critical nodes with 70% accuracy and can still be improved with future work.