Objective： To analyze the pattern over time （dynamics） of further recurrence and death after ipsilateral breast tumor recurrence （IBTR） in breast cancer patients undergoing breast conserving treatment （BCT）. Me...Objective： To analyze the pattern over time （dynamics） of further recurrence and death after ipsilateral breast tumor recurrence （IBTR） in breast cancer patients undergoing breast conserving treatment （BCT）. Methods： A total of 338 evaluable patients experiencing IBTR were extracted from a database of 3,293 patients undergoing BCT. The hazard rates for recurrence and mortality throughout 10 years of follow-up after IBTR were assessed and were compared to the analogous estimates associated to the primary treatment. Results： In a time frame with the time origin at the surgical treatment for IBTR, the hazard rate for further recurrence displays a bimodal pattern （peaks at the second and at the sixth year）. Patients receiving mastectomy for IBTR reveal recurrence and mortality dynamics similar to that of node positive （N＋） patients receiving mastectomy as primary surgery, apart from the first two-three years, when IBTR patients do worse. If the patients with time to IBTR longer than 2.5 years are considered, differences disappear. Conclusions： The recurrence and mortality dynamics following IBTR surgical removal is similar to the corresponding dynamics following primary tumor removal. In particular, patients with time to IBTR in excess of 2.5 years behave like N＋ patients following primary tumor removal. Findings may be suitably explained by assuming that the surgical manoeuvre required by IBTR treatment is able to activate a sudden growing phase for tumor foci most of which, as suggested by the systemic model of breast cancer, would have reached the clinical level according to their own dynamics.展开更多
Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employe...Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.展开更多
In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to t...In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.展开更多
文摘Objective： To analyze the pattern over time （dynamics） of further recurrence and death after ipsilateral breast tumor recurrence （IBTR） in breast cancer patients undergoing breast conserving treatment （BCT）. Methods： A total of 338 evaluable patients experiencing IBTR were extracted from a database of 3,293 patients undergoing BCT. The hazard rates for recurrence and mortality throughout 10 years of follow-up after IBTR were assessed and were compared to the analogous estimates associated to the primary treatment. Results： In a time frame with the time origin at the surgical treatment for IBTR, the hazard rate for further recurrence displays a bimodal pattern （peaks at the second and at the sixth year）. Patients receiving mastectomy for IBTR reveal recurrence and mortality dynamics similar to that of node positive （N＋） patients receiving mastectomy as primary surgery, apart from the first two-three years, when IBTR patients do worse. If the patients with time to IBTR longer than 2.5 years are considered, differences disappear. Conclusions： The recurrence and mortality dynamics following IBTR surgical removal is similar to the corresponding dynamics following primary tumor removal. In particular, patients with time to IBTR in excess of 2.5 years behave like N＋ patients following primary tumor removal. Findings may be suitably explained by assuming that the surgical manoeuvre required by IBTR treatment is able to activate a sudden growing phase for tumor foci most of which, as suggested by the systemic model of breast cancer, would have reached the clinical level according to their own dynamics.
基金Project(60634020) supported by the National Natural Science Foundation of China
文摘Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.
文摘In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.
