The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based ...The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.展开更多
BACKGROUND: Small-for-size syndrome is a widely recognized clinical complication after living donor liver transplantation or extended hepatectomy due to inadequate liver mass. The purpose of this study was to investig...BACKGROUND: Small-for-size syndrome is a widely recognized clinical complication after living donor liver transplantation or extended hepatectomy due to inadequate liver mass. The purpose of this study was to investigate the role of splenectomy in rats after massive hepatectomy, a surrogate model of small-for-size graft. METHODS: Rats were divided into eight groups, each with 20 animals: 50% hepatectomy (50% Hx), 50% hepatectomy+ splenectomy (50% Hx+Sp), 60% Hx, 60% Hx+Sp, 70% Hx, 70% Hx+Sp, 90% Hx and 90% Hx+Sp. The following parameters were evaluated: liver function tests (ALT, AST and TBIL), liver regeneration ratio, DNA synthesis, proliferation cell nuclear antigen, hepatic oxygen delivery (HDO(2)) and hepatic oxygen consumption (HVO(2)). RESULTS: The liver regeneration ratio was enhanced in the Hx+Sp groups (P < 0.05). In addition, compared with the Hx groups, the Hx+Sp groups had better liver functions (P < 0.05). DNA synthesis and proliferation cell nuclear antigen were also increased in the Hx+Sp groups compared with the Hx groups (P < 0.05). Furthermore, in the Hx+Sp groups, HDO(2) and HVO(2) were increased over those in the Hx groups (P < 0.05), and were positively correlated with the liver regeneration ratio. CONCLUSIONS: Splenectomy significantly improved liver function, and enhanced DNA synthesis and proliferation cell nuclear antigen after massive hepatectomy in rats. This operation could be mediated through increased HDO(2), and HVO(2) which facilitate liver regeneration. (Hepatobiliary Pancreat Dis Int 2012;11:60-65)展开更多
基金financially supported by the National Natural Science Foundation of China (Nos.51974023 and52374321)the funding of State Key Laboratory of Advanced Metallurgy,University of Science and Technology Beijing,China (No.41620007)。
文摘The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.
基金supported by grants from the National Natural Science Foundation of China (30772094)the State Scholarship Foundation of China (2009659015)
文摘BACKGROUND: Small-for-size syndrome is a widely recognized clinical complication after living donor liver transplantation or extended hepatectomy due to inadequate liver mass. The purpose of this study was to investigate the role of splenectomy in rats after massive hepatectomy, a surrogate model of small-for-size graft. METHODS: Rats were divided into eight groups, each with 20 animals: 50% hepatectomy (50% Hx), 50% hepatectomy+ splenectomy (50% Hx+Sp), 60% Hx, 60% Hx+Sp, 70% Hx, 70% Hx+Sp, 90% Hx and 90% Hx+Sp. The following parameters were evaluated: liver function tests (ALT, AST and TBIL), liver regeneration ratio, DNA synthesis, proliferation cell nuclear antigen, hepatic oxygen delivery (HDO(2)) and hepatic oxygen consumption (HVO(2)). RESULTS: The liver regeneration ratio was enhanced in the Hx+Sp groups (P < 0.05). In addition, compared with the Hx groups, the Hx+Sp groups had better liver functions (P < 0.05). DNA synthesis and proliferation cell nuclear antigen were also increased in the Hx+Sp groups compared with the Hx groups (P < 0.05). Furthermore, in the Hx+Sp groups, HDO(2) and HVO(2) were increased over those in the Hx groups (P < 0.05), and were positively correlated with the liver regeneration ratio. CONCLUSIONS: Splenectomy significantly improved liver function, and enhanced DNA synthesis and proliferation cell nuclear antigen after massive hepatectomy in rats. This operation could be mediated through increased HDO(2), and HVO(2) which facilitate liver regeneration. (Hepatobiliary Pancreat Dis Int 2012;11:60-65)
