临床上处方剂量计算时要考虑百分深度剂量(PDD)和总散射校正因子(S_c,p)的影响。本研究中利用蒙特卡罗程序(BEAMnrc和DOSXYZnrc)模拟SIEMENS Primus Plus直线加速器6MV能量的电子束,计算各照射范围内总散射校正因子和百分深度剂量值,并...临床上处方剂量计算时要考虑百分深度剂量(PDD)和总散射校正因子(S_c,p)的影响。本研究中利用蒙特卡罗程序(BEAMnrc和DOSXYZnrc)模拟SIEMENS Primus Plus直线加速器6MV能量的电子束,计算各照射范围内总散射校正因子和百分深度剂量值,并与指形电离室测量值比较,同时计算了总散射校正因子(S_c,p)随照射范围和深度的变化。计算结果表明:总散射校正因子随着照射范围的增加而增大,当照射范围>10cm×10cm时,总散射校正因子随着深度的增加而增大;当照射范围<10cm×10cm时,总散射校正因子随着深度的增加而减小。利用蒙特卡罗方法可以建立全面准确的散射校正因子资料,为临床放射治疗提供质量保证和质量控制。展开更多
Soil salinity is a serious land degradation issue in agriculture.It is a major threat to agriculture productivity.Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form ...Soil salinity is a serious land degradation issue in agriculture.It is a major threat to agriculture productivity.Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation water.For the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)rate.The relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)rate.ML-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity level.The proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)determination.The validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm day-1.The applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.展开更多
文摘临床上处方剂量计算时要考虑百分深度剂量(PDD)和总散射校正因子(S_c,p)的影响。本研究中利用蒙特卡罗程序(BEAMnrc和DOSXYZnrc)模拟SIEMENS Primus Plus直线加速器6MV能量的电子束,计算各照射范围内总散射校正因子和百分深度剂量值,并与指形电离室测量值比较,同时计算了总散射校正因子(S_c,p)随照射范围和深度的变化。计算结果表明:总散射校正因子随着照射范围的增加而增大,当照射范围>10cm×10cm时,总散射校正因子随着深度的增加而增大;当照射范围<10cm×10cm时,总散射校正因子随着深度的增加而减小。利用蒙特卡罗方法可以建立全面准确的散射校正因子资料,为临床放射治疗提供质量保证和质量控制。
基金funded by the Deanship of Scientific Research(DSR),King AbdulAziz University,Jeddah,Saudi Arabia under Grant No.(RG-11-611-43).
文摘Soil salinity is a serious land degradation issue in agriculture.It is a major threat to agriculture productivity.Extra irrigation water is applied to leach down the salts from the root zone of the plants in the form of a Leaching fraction(LF)of irrigation water.For the leaching process to be effective,the LF of irriga-tion water needs to be adjusted according to the environmental conditions and soil salinity level in the form of Evapotranspiration(ET)rate.The relationship between environmental conditions and ET rate is hard to be defined by a linear relationship and data-driven Machine learning(ML)based decisions are required to determine the calibrated Evapotranspiration(ETc)rate.ML-assisted ETc is pro-posed to adjust the LF according to the ETc and soil salinity level.A regression model is proposed to determine the ETc rate according to the prevailing tempera-ture,humidity,and sunshine,which would be used to determine the smart LF according to the ETc and soil salinity level.The proposed model is trained and tested against the Blaney Criddle method of Reference evapotranspiration(ETo)determination.The validation of the model from the test dataset reveals the accu-racy of the ML model in terms of Root mean squared errors(RMSE)are 0.41,Mean absolute errors(MAE)are 0.34,and Mean squared errors(MSE)are 0.28 mm day-1.The applications of the proposed solution in a real-time environ-ment show that the LF by the proposed solution is more effective in reducing the soil salinity as compared to the traditional process of leaching.
