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SummaryBackground:Simultaneous or consequent development of multiple solid tumors might be faced in some patients, especially the young. These tumors might be related to certain hereditary cancer syndromes or certain genetic predispositions.Case Report:We present the case of a 19-year-old woman with metastatic breast cancer to the contralateral axillary lymph node, associated with simultaneous osteosarcoma of the left lower femur. As she did not fit into any of the familial cancer syndromes, genetic predisposition was suspected. We detected MLH1 and MSH2 promotor methylation (PM), microsatellite instability (MSI), and different mutational events in both tumors. BRCA1 gene mutations were detected in the breast tumor, with reduced mRNA expression of BRCA1&2. ERCC1, MLH1 and MSH2, especially in OS, and RRM1 was overexpressed in both tumors.Conclusions:Aberrations in MMR genes could explain simultaneous or consequent development of multiple solid tumors, especially in a young patient. We recommend detecting these defects, close follow-up for those patients, and genetic counseling for their family members. Further studies in a larger population are essential to support our results.

This paper focuses on the service life of slag concrete, where the time to corrosion initiation for a given chloride threshold value of 0.3% by mass of cement and different surface chloride concentrations (C s ), (1%, 3%, and 5%) was calculated using the error function solution to Fick's second law of diffusion as a service life model, where the chloride diffusion coefficients of different OPC/slag mixes were collected from literature.To gain improved understanding of the above-mentioned aspect, this research presents an experimental investigation to elucidate the impacts of local by-product water cooled slag (WCS) on the microstructure of OPC cement paste mixes using thermo-gravimetric analysis and de-sorption approaches.A partial replacement of OPC with 50% WCS in OPC paste mixes resulted in an increase in the amount of calcium silicate hydrate (CSH) by 57%, a decrease in the amount of calcium hydroxide (CH) by 66%, and a decrease in the amount of capillary pores by 57%, compared to those in the pure OPC matrix. In addition, the research results demonstrate that increasing C s from 1% to 5% resulted in dramatically decreasing the service life of OPC/slag concrete, where the amount of decreasing reaches about 71%. Also, the service life of concrete increases with increasing slag content.Ó 2013 Production and hosting by Elsevier B.V. on behalf of Ain Shams University.

3D computational fluid dynamics models using Fluent were developed to investigate the steel melt flow during waiting and arcing time. Both models were transient that analyzed 60 seconds to investigate the flow characteristics considering variation in steel melt thermo-physical parameters and operating conditions. The velocity of melt movement was high enough to make a turbulent flow (solved with realize k-ε turbulence model). It was found that the steel melt flow velocity increases by a combined effect of the steel melt temperature and composition, and slag pressure. The slag pressure increases by a double effect of slag density and height, and the steel melt fluid flow velocity changes with the slag pressure. The effect of the slag thickness is more significant than the effect of thermo-physical properties of steel melt. Although, the maximum steel melt velocity "during arcing time" may be as large as 0.67 m/s located at steel met outlet, the melt exhibits completely dead zones with minimum flow velocity distribution especially at the bottom and circumference areas. This indicates the importance of combined stirring and large reaction rates to achieve a complete homogeneous melt especially at bottom and circumference areas.

This paper focuses on the Artificial Neural Network (ANN) as an alternative approach to simulate the corrosion initiation time of slag concrete obtained from the error function solution to Fick's second law of diffusion. The adopted network architecture consists of four neurons in the input layer, which represents the values of concrete cover depth, apparent chloride diffusion coefficient, chloride threshold value and surface chloride concentration, and one neuron in the output layer, which represents the value of the corresponding corrosion initiation time. Back Propagation (BP) algorithm was employed for the ANN training in which a Tansig function was used as the nonlinear transfer function. The research results obtained from both ANN model and the error function solution to Fick's second law of diffusion demonstrate that the corrosion initiation time of slag concrete increases with increasing both the concrete cover and the chloride threshold value and decreases with increasing both the surface chloride concentration and the chloride diffusion coefficient. Through the comparison of the estimated results from ANN model and the error function solution to Fick's second law of diffusion, it was clear that there was a high correlation between the corrosion initiation time obtained from the error function solution to Fick's second law of diffusion and the corresponding corrosion initiation time predicted by the ANN model.

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