Nitrogen is essential for plant growth and development,with the ratio of ammonium(NH_(4)^(+))to nitrate(NO_(3)^(-))critically influencing physiological efficiency.This study investigated the effects of different NH_(4...Nitrogen is essential for plant growth and development,with the ratio of ammonium(NH_(4)^(+))to nitrate(NO_(3)^(-))critically influencing physiological efficiency.This study investigated the effects of different NH_(4)^(+)-N/NO_(3)^(-)-N mass ratios(0︰1,3︰7,1︰1,7︰3,1︰0)and a no-nitrogen control on Zanthoxylum planispinum var.dintanensis seedlings,using NH_(4)Cl and NaNO_(3) as nitrogen sources.Key results revealed that a 3︰7 NH_(4)^(+)︰NO_(3)^(-)ratio(T2)significantly enhanced stomatal conductance(G_(s)),amino acid content,root tip number,and the photochemical quenching parameters q_(P),q_(L),ETR,and F_(v)/F_(m).This treatment also maximized ground diameter increment,chlorophyll content,intercellular CO_(2)concentration(C_(i)),transpiration rate(T_(r)),ribulose-1,5-bisphosphate carboxylase(Rubisco)activity,nitrate reductase(NR)activity,and soluble protein content.Conversely,a 7︰3 ratio(T4)yielded the highest net photosynthetic rate(Pn)and fructose-1,6-bisphosphate aldolase(FBA)activity.Overall,the T4 treatment exhibited the second most effective promotion of Z.planispinum var.dintanensis seedling growth and development,after T2.In summary,mixed NH_(4)^(+)-N/NO_(3)^(-)-N nutrition markedly enhances seedling performance,with the 3︰7 ratio optimal for growth,photosynthesis,and nitrogen assimilation.Sole nitrogen sources,particularly pure NH_(4)^(+)-N,exert inhibitory effects.展开更多
An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale...An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.展开更多
文摘Nitrogen is essential for plant growth and development,with the ratio of ammonium(NH_(4)^(+))to nitrate(NO_(3)^(-))critically influencing physiological efficiency.This study investigated the effects of different NH_(4)^(+)-N/NO_(3)^(-)-N mass ratios(0︰1,3︰7,1︰1,7︰3,1︰0)and a no-nitrogen control on Zanthoxylum planispinum var.dintanensis seedlings,using NH_(4)Cl and NaNO_(3) as nitrogen sources.Key results revealed that a 3︰7 NH_(4)^(+)︰NO_(3)^(-)ratio(T2)significantly enhanced stomatal conductance(G_(s)),amino acid content,root tip number,and the photochemical quenching parameters q_(P),q_(L),ETR,and F_(v)/F_(m).This treatment also maximized ground diameter increment,chlorophyll content,intercellular CO_(2)concentration(C_(i)),transpiration rate(T_(r)),ribulose-1,5-bisphosphate carboxylase(Rubisco)activity,nitrate reductase(NR)activity,and soluble protein content.Conversely,a 7︰3 ratio(T4)yielded the highest net photosynthetic rate(Pn)and fructose-1,6-bisphosphate aldolase(FBA)activity.Overall,the T4 treatment exhibited the second most effective promotion of Z.planispinum var.dintanensis seedling growth and development,after T2.In summary,mixed NH_(4)^(+)-N/NO_(3)^(-)-N nutrition markedly enhances seedling performance,with the 3︰7 ratio optimal for growth,photosynthesis,and nitrogen assimilation.Sole nitrogen sources,particularly pure NH_(4)^(+)-N,exert inhibitory effects.
基金supported by Yunnan Power Grid Co.,Ltd.Science and Technology Project:Research and application of key technologies for graphical-based power grid accident reconstruction and simulation(YNKJXM20240333).
文摘An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.
