FDG PET/CT Findings of Recurrent Respiratory Papillomatosis With Malignant Degeneration in the Lung.

Recurrent respiratory papillomatosis is a rare benign disease caused by HPV-6 or HPV-11. The tumors may rarely undergo malignant degeneration. We performed FDG PET/CT in a patient experiencing recurrent respiratory papillomatosis who had pulmonary involvement. Although squamous cell carcinoma was detected in one of the pulmonary masses, squamous metaplasia with dysplasia were detected in the other one. Intensity modulated radiation therapy was performed to treat the malignancy. Second FDG PET/CT was performed 15 months after radiotherapy.

Fuzzy-logic modeling of Fenton's strong chemical oxidation process treating three types of landfill leachates.

Three multiple input and multiple output-type fuzzy-logic-based models were developed as an artificial intelligence-based approach to model a novel integrated process (UF-IER-EDBM-FO) consisted of ultrafiltration (UF), ion exchange resins (IER), electrodialysis with bipolar membrane (EDBM), and Fenton's oxidation (FO) units treating young, middle-aged, and stabilized landfill leachates. The FO unit was considered as the key process for implementation of the proposed modeling scheme. Four input components such as H(2)O(2)/chemical oxygen demand ratio, H(2)O(2)/Fe(2+) ratio, reaction pH, and reaction time were fuzzified in a Mamdani-type fuzzy inference system to predict the removal efficiencies of chemical oxygen demand, total organic carbon, color, and ammonia nitrogen. A total of 200 rules in the IF-THEN format were established within the framework of a graphical user interface for each fuzzy-logic model. The product (prod) and the center of gravity (centroid) methods were performed as the inference operator and defuzzification methods, respectively, for the proposed prognostic models. Fuzzy-logic predicted results were compared to the outputs of multiple regression models by means of various descriptive statistical indicators, and the proposed methodology was tested against the experimental data. The testing results clearly revealed that the proposed prognostic models showed a superior predictive performance with very high determination coefficients (R (2)) between 0.930 and 0.991. This study indicated a simple means of modeling and potential of a knowledge-based approach for capturing complicated inter-relationships in a highly non-linear problem. Clearly, it was shown that the proposed prognostic models provided a well-suited and cost-effective method to predict removal efficiencies of wastewater parameters prior to discharge to receiving streams.