Communications Engineer

Exposure to estrogens has been associated with an increased risk of developing breast cancer. Breast biopsy tissues from 49 women without breast cancer (controls) and 28 with breast carcinoma (cases) were analyzed by HPLC with electrochemical detection for 31 estrogen metabolites and catechol estrogen quinone±glutathione conjugates. The levels of estrone and estradiol were higher in cases. More 2-catechol estrogen (CE) than 4-CE was observed in controls, but the 4-CE were three times higher than 2-CE in cases. In addition, the 4-CE were nearly four times higher in cases than in controls. Less O-methylation was observed for the CE in cases. The level of catechol estrogen quinone conjugates in cases was three times that in controls, suggesting in the cases a higher probability for the quinones to react with DNA and generate mutations that may initiate cancer. The levels of 4-CE and quinone conjugates were highly significant predictors of breast cancer. These results suggest that some catechol estrogen metabolites and conjugates could serve as biomarkers to predict risk of breast cancer.

Miniature miicrostrip stepped impedance resonator bandpass filters and diplexers for satellite mobile communications have been developed. A very high dielectric constant substrate (~~3 8 9 and h=2mm) is used. Experimental results show that an unloaded half wave resonator quality factor as high as 400 at 1.5 GHz, with such substrate, may be possible. The merit of this circuit lies in the simplicity of design procedure, the possibility of developing this filter with quite ;i variety of high dielectric constant substrate materials and the simplicity of simulation with most commercial software packages. A four resonator bandpass filter with 35 MHz bandwidth at 1.55 GHz was designed and implemented with this substrate. Based on this filter, a diplexer which meets satellite mobile communications performance has been developed. Experimental results are in good agreement with theoretical predictions

Dietary n-6 polyunsaturated fatty acids (PUFAs) promote rat mammary cancer while n-3 PUFAs are inhibitory. The purpose of this study was to determine whether the fats exert their effects by altering the expression of genes that affect cancer development. Therefore, we have examined the effect of PUFAs on the expression of the cyclooxygenase (COX) 1 and 2 genes that are involved in prostaglandin biosynthesis. We also investigated the effect of dietary PUFAs on the expression of the p21 ras protein and Ha-ras mRNA. Rats were fed either low-(7%; LF) or high-(21%; HF) fat diets that were rich in either n-6 PUFAs (safflower oil, S) or n-3 PUFAs (menhaden oil, M) for 3 weeks. COX-1 mRNA levels were approximately the same in groups fed diets containing either level of menhaden oil, but were increased by~30% in the LFS and HFS groups (P Ͻ 0.05). Transcripts of the inducible COX-2 gene were not detectable in the menhaden oil groups, but this gene was expressed in animals fed either level of safflower oil and in the HFS group was associated with increased levels of COX enzymatic activity and production of PGE 2 . Animals fed safflower oil had elevated levels of p21 ras protein compared to animals fed menhaden oil. Ha-ras mRNA was increased by~35% in animals fed HFS compared to the group fed HFM (P < 0.05). These results demonstrate that dietary n-6 PUFAs upregulate COX-2 and, to some extent, COX-1 expression. There was a concomitant increase in COX enzyme activity and PG synthesis in the mammary glands of rats fed high levels of n-6 PUFAs. Together with associated changes in p21 ras expression, these results may explain, at least in part, the promoting effects of dietary n-6 PUFAs on mammary carcinogenesis. *Abbreviations: PUFAs, polyunsaturated fatty acids; PG, prostaglandin; NSAIDs, non-steroidal anti-inflammatory drugs; LA, linoleic acid; EPA, eicosapentaenoic acid; DHA, docosahexaenoic acid; COX, cyclooxygenase; AA, arachidonic acid; LFM, low fat menhaden; HFM, high fat menhaden; HFS, high fat safflower; LFS, low fat safflower.

Defining the project estimated cost, duration and maintenance effort early in the development life cycle is a valuable goal to be achieved for software projects. Many model structures evolved in the literature. These model structures consider modeling software effort as a function of the developed line of code (DLOC). Building such a function helps project managers to accurately allocate the available resources for the project. In this study, we present two new model structures to estimate the effort required for the development of software projects using Genetic Algorithms (GAs). A modified version of the famous COCOMO model provided to explore the effect of the software development adopted methodology in effort computation. The performance of the developed models were tested on NASA software project dataset .The developed models were able to provide a good estimation capabilities.

In this paper, neural networks have been proposed as an alternative technique to build software reliability growth models. A feedforward neural network was used to predict the number of faults initially resident in a program at the beginning of a test/debug process. To evaluate the predictive capability of the developed model, data sets from various projects were used. A comparison between regression parametric models and neural network models is provided