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BACKGROUND: Since Shiraz Transplant Center is one of the major transplant centers in Iran and the Middle East, this study was conducted to evaluate outcomes of the applied policies on COVID-19 detection and management. METHODS: During 4 months from March to June 2020, patient's data diagnosed with the impression of COVID-19 were extracted and evaluated based on demographic and clinical features, along with the length of hospital stay and expenses. RESULTS: Our data demonstrated that a total of 190 individuals, with a median age of 58, were diagnosed with COVID-19 during the mentioned period. Among these, 21 patients had a positive PCR test and 56 patients had clinical symptoms in favor of COVID-19. Also, 113 (59%) patients were classified as mild based on clinical evidence and were treated on an outpatient basis. Furthermore, 81 out of 450 cases (18%) of the healthcare workers at our center had either PCR of clinical features in favor of COVID-19. The mortality rate of our study was 11% and diabetes mellitus, hypertension were considered risk factors for obtaining COVID-19 infection. The direct cost of treatment and management of patients with COVID-19 amounted to 2,067,730,919 IRR, which considering the 77 patients admitted to Gary Zone per capita direct cost of treatment each patient was 26,853,648 IRR. CONCLUSION: We demonstrated that the COVID-19 pandemic had a noticeable influence on our transplant center in aspects of delaying surgery and increased hospital costs and burden. However, by implanting proper protocols, we were able to was able to provide early detection for COVID-19 and apply necessary treatment and prevention protocols to safeguard the patients under its coverage, especially immunocompromised patients.
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Concrete corrosion is one of the most significant failure mechanisms of sewer pipes, and can reduce the sewer service life significantly. To facilitate the management and maintenance of sewers, it is essential to obtain reliable prediction of the expected service life of sewers, especially if that is based on limited environmental conditions. Recently, a long-term study was performed to identify the controlling factors of concrete sewer corrosion using well-controlled laboratory-scale corrosion chambers to vary levels of H2S concentration, relative humidity, temperature and in-sewer location. Using the results of the long-term study, three different data-driven models, i.e. multiple linear regression (MLR), artificial neural network (ANN), and adaptive neuro fuzzy inference system (ANFIS), as well as the interaction between environmental parameters, were assessed for predicting the corrosion initiation time (ti) and corrosion rate (r). This was performed using the sewer environmental factors as the input under 12 different scenarios after allowing for an initiation corrosion period. ANN and ANFIS models showed better performance than MLR models, with or without considering the interactions between environmental factors. With the limited input data available, it was observed that ti prediction by these models is quite sensitive, however, they are more robust for predicting r as long as the H2S concentration is available. Using the H2S concentration as a single input, all three data driven models can reasonably predict the sewer service life.
Assuntos
Materiais de Construção , Redes Neurais de Computação , Corrosão , Concentração de Íons de Hidrogênio , TemperaturaRESUMO
Water equivalent ratio (WER) was calculated for different proton energies in polymethyl methacrylate (PMMA), polystyrene (PS) and aluminum (Al) using FLUKA and SRIM codes. The results were compared with analytical, experimental and simulated SEICS code data obtained from the literature. The biggest difference between the codes was 3.19%, 1.9% and 0.67% for Al, PMMA and PS, respectively. FLUKA and SEICS had the greatest agreement (≤0.77% difference for PMMA and ≤1.08% difference for Al, respectively) with the experimental data.