Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a ...Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.展开更多
This work correlated the detailed work zone location and time data from the Wis LCS system with the five-min inductive loop detector data. One-sample percentile value test and two-sample Kolmogorov-Smirnov(K-S) test w...This work correlated the detailed work zone location and time data from the Wis LCS system with the five-min inductive loop detector data. One-sample percentile value test and two-sample Kolmogorov-Smirnov(K-S) test were applied to compare the speed and flow characteristics between work zone and non-work zone conditions. Furthermore, we analyzed the mobility characteristics of freeway work zones within the urban area of Milwaukee, WI, USA. More than 50% of investigated work zones have experienced speed reduction and 15%-30% is necessary reduced volumes. Speed reduction was more significant within and at the downstream of work zones than at the upstream.展开更多
The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to s...The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to solve this problem,a novel nonlinear fuzzy membership function was presented to adjust the upper and lower limit of target acceleration adaptively,and then the validity of the new algorithm for feeblish maneuvering target was proved in theory.At last,the computer simulation experiments indicated that the new algorithm has a great advantage over the basic"current"statistical model and adaptive algorithm.展开更多
The model that two two level atoms interact with a singel mode cavity is studied. The exact solution of the time evolution operator for the two atom Jaynes Cummings model is presented by the bare states approach. Furt...The model that two two level atoms interact with a singel mode cavity is studied. The exact solution of the time evolution operator for the two atom Jaynes Cummings model is presented by the bare states approach. Furthermore, we investigate the dynamical properties of the photon statistics of the cavity field, and obtain a number of novel features.展开更多
This paper developed a statistical damage constitutive model for deep rock by considering the effects of external load and thermal treatment temperature based on the distortion energy.The model parameters were determi...This paper developed a statistical damage constitutive model for deep rock by considering the effects of external load and thermal treatment temperature based on the distortion energy.The model parameters were determined through the extremum features of stress−strain curve.Subsequently,the model predictions were compared with experimental results of marble samples.It is found that when the treatment temperature rises,the coupling damage evolution curve shows an S-shape and the slope of ascending branch gradually decreases during the coupling damage evolution process.At a constant temperature,confining pressure can suppress the expansion of micro-fractures.As the confining pressure increases the rock exhibits ductility characteristics,and the shape of coupling damage curve changes from an S-shape into a quasi-parabolic shape.This model can well characterize the influence of high temperature on the mechanical properties of deep rock and its brittleness-ductility transition characteristics under confining pressure.Also,it is suitable for sandstone and granite,especially in predicting the pre-peak stage and peak stress of stress−strain curve under the coupling action of confining pressure and high temperature.The relevant results can provide a reference for further research on the constitutive relationship of rock-like materials and their engineering applications.展开更多
目的:研究2005—2020年中国(暂未包含我国台湾地区、香港地区和澳门地区)≥60岁老年人群肺结核疾病负担在不同区域、城乡、年龄的变化趋势和轨迹。方法:基于“结核病信息管理系统”“全国疾病监测系统”和“中国疾病预防控制信息系统”2...目的:研究2005—2020年中国(暂未包含我国台湾地区、香港地区和澳门地区)≥60岁老年人群肺结核疾病负担在不同区域、城乡、年龄的变化趋势和轨迹。方法:基于“结核病信息管理系统”“全国疾病监测系统”和“中国疾病预防控制信息系统”2005—2020年中国≥60岁老年人群肺结核的发病、死亡和人口数据,计算由肺结核造成的伤残调整寿命年(disability-adjusted life years,DALYs)变化趋势。将数据按照区域、城乡、年龄分层后,应用轨迹模型分析DALYs率的变化趋势。结果:不同年龄组老年人群肺结核DALYs率轨迹模型拟合为2组,组1包含60~64岁组老年人群(t=―5.484,P<0.001),组2包含其余年龄分组老年人群(t=―16.464,P<0.001),均为下降趋势;不同地区老年人群肺结核标化DALYs率轨迹模型拟合组别数为2组,组1包含东部地区老年人群(t=―3.395,P=0.001),组2包含中部和西部地区老年人群(t=―8.863,P<0.001),均为下降趋势。将老年人群按年龄组、地区和城乡进行分层,共得到36种组合,其肺结核DALYs率轨迹模型拟合组别数为3组,组1呈下降趋势(模型1次项t=110971.711、2次项t=―17438254.240、3次项t=150665.213,P值均<0.001),包含东部地区所有老年人群,中部和西部地区60~64岁组、65~69岁组城市老年人群,以及中部地区60~64岁组农村老年人群;组2呈线性下降趋势(t=―22.210,P<0.001),趋势较组1更为明显,包含中部和西部城市地区除组1以外的所有老年人群,以及西部60~64岁组和≥85岁组老年人群;组3呈现下降趋势(t=―14.923,P<0.001),在3个轨迹拟合组中DALYs率最高,包含西部地区农村剩余组别的老年人群。结论:2005—2020年中国≥60岁老年人群肺结核疾病负担呈下降趋势,但不同组别的下降趋势存在异质性。应重点关注高龄、农村及西部地区的老年人群,针对不同亚组的特点,制定更加精准的防控策略和措施。展开更多
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
基金Project(52274096)supported by the National Natural Science Foundation of ChinaProject(WS2023A03)supported by the State Key Laboratory Cultivation Base for Gas Geology and Gas Control,China。
文摘Accurate assessment of coal brittleness is crucial in the design of coal seam drilling and underground coal mining operations.This study proposes a method for evaluating the brittleness of gas-bearing coal based on a statistical damage constitutive model and energy evolution mechanisms.Initially,integrating the principle of effective stress and the Hoek-Brown criterion,a statistical damage constitutive model for gas-bearing coal is established and validated through triaxial compression tests under different gas pressures to verify its accuracy and applicability.Subsequently,employing energy evolution mechanism,two energy characteristic parameters(elastic energy proportion and dissipated energy proportion)are analyzed.Based on the damage stress thresholds,the damage evolution characteristics of gas bearing coal were explored.Finally,by integrating energy characteristic parameters with damage parameters,a novel brittleness index is proposed.The results demonstrate that the theoretical curves derived from the statistical damage constitutive model closely align with the test curves,accurately reflecting the stress−strain characteristics of gas-bearing coal and revealing the stress drop and softening characteristics of coal in the post-peak stage.The shape parameter and scale parameter represent the brittleness and macroscopic strength of the coal,respectively.As gas pressure increases from 1 to 5 MPa,the shape parameter and the scale parameter decrease by 22.18%and 60.45%,respectively,indicating a reduction in both brittleness and strength of the coal.Parameters such as maximum damage rate and peak elastic energy storage limit positively correlate with coal brittleness.The brittleness index effectively captures the brittleness characteristics and reveals a decrease in brittleness and an increase in sensitivity to plastic deformation under higher gas pressure conditions.
基金Project(61620106002)supported by the National Natural Science Foundation of ChinaProject(2016YFB0100906)supported by the National Key R&D Program in China+1 种基金Project(2015364X16030)supported by the Information Technology Research Project of Ministry of Transport of ChinaProject(2242015K42132)supported by the Fundamental Sciences of Southeast University,China
文摘This work correlated the detailed work zone location and time data from the Wis LCS system with the five-min inductive loop detector data. One-sample percentile value test and two-sample Kolmogorov-Smirnov(K-S) test were applied to compare the speed and flow characteristics between work zone and non-work zone conditions. Furthermore, we analyzed the mobility characteristics of freeway work zones within the urban area of Milwaukee, WI, USA. More than 50% of investigated work zones have experienced speed reduction and 15%-30% is necessary reduced volumes. Speed reduction was more significant within and at the downstream of work zones than at the upstream.
文摘The basic"current"statistical model and adaptive Kalman filter algorithm can not track a weakly maneuvering target precisely,though it has good estimate accuracy for strongly maneuvering target.In order to solve this problem,a novel nonlinear fuzzy membership function was presented to adjust the upper and lower limit of target acceleration adaptively,and then the validity of the new algorithm for feeblish maneuvering target was proved in theory.At last,the computer simulation experiments indicated that the new algorithm has a great advantage over the basic"current"statistical model and adaptive algorithm.
文摘The model that two two level atoms interact with a singel mode cavity is studied. The exact solution of the time evolution operator for the two atom Jaynes Cummings model is presented by the bare states approach. Furthermore, we investigate the dynamical properties of the photon statistics of the cavity field, and obtain a number of novel features.
基金Project(11272119)supported by the National Natural Science Foundation of China。
文摘This paper developed a statistical damage constitutive model for deep rock by considering the effects of external load and thermal treatment temperature based on the distortion energy.The model parameters were determined through the extremum features of stress−strain curve.Subsequently,the model predictions were compared with experimental results of marble samples.It is found that when the treatment temperature rises,the coupling damage evolution curve shows an S-shape and the slope of ascending branch gradually decreases during the coupling damage evolution process.At a constant temperature,confining pressure can suppress the expansion of micro-fractures.As the confining pressure increases the rock exhibits ductility characteristics,and the shape of coupling damage curve changes from an S-shape into a quasi-parabolic shape.This model can well characterize the influence of high temperature on the mechanical properties of deep rock and its brittleness-ductility transition characteristics under confining pressure.Also,it is suitable for sandstone and granite,especially in predicting the pre-peak stage and peak stress of stress−strain curve under the coupling action of confining pressure and high temperature.The relevant results can provide a reference for further research on the constitutive relationship of rock-like materials and their engineering applications.
文摘目的:研究2005—2020年中国(暂未包含我国台湾地区、香港地区和澳门地区)≥60岁老年人群肺结核疾病负担在不同区域、城乡、年龄的变化趋势和轨迹。方法:基于“结核病信息管理系统”“全国疾病监测系统”和“中国疾病预防控制信息系统”2005—2020年中国≥60岁老年人群肺结核的发病、死亡和人口数据,计算由肺结核造成的伤残调整寿命年(disability-adjusted life years,DALYs)变化趋势。将数据按照区域、城乡、年龄分层后,应用轨迹模型分析DALYs率的变化趋势。结果:不同年龄组老年人群肺结核DALYs率轨迹模型拟合为2组,组1包含60~64岁组老年人群(t=―5.484,P<0.001),组2包含其余年龄分组老年人群(t=―16.464,P<0.001),均为下降趋势;不同地区老年人群肺结核标化DALYs率轨迹模型拟合组别数为2组,组1包含东部地区老年人群(t=―3.395,P=0.001),组2包含中部和西部地区老年人群(t=―8.863,P<0.001),均为下降趋势。将老年人群按年龄组、地区和城乡进行分层,共得到36种组合,其肺结核DALYs率轨迹模型拟合组别数为3组,组1呈下降趋势(模型1次项t=110971.711、2次项t=―17438254.240、3次项t=150665.213,P值均<0.001),包含东部地区所有老年人群,中部和西部地区60~64岁组、65~69岁组城市老年人群,以及中部地区60~64岁组农村老年人群;组2呈线性下降趋势(t=―22.210,P<0.001),趋势较组1更为明显,包含中部和西部城市地区除组1以外的所有老年人群,以及西部60~64岁组和≥85岁组老年人群;组3呈现下降趋势(t=―14.923,P<0.001),在3个轨迹拟合组中DALYs率最高,包含西部地区农村剩余组别的老年人群。结论:2005—2020年中国≥60岁老年人群肺结核疾病负担呈下降趋势,但不同组别的下降趋势存在异质性。应重点关注高龄、农村及西部地区的老年人群,针对不同亚组的特点,制定更加精准的防控策略和措施。
