树脂传递模塑成型(Resin transfer molding,RTM)工艺仿真对于提高成型质量,降低RTM工艺成本至关重要。将人工智能方法引入RTM工艺仿真中,可以不必求解复杂的多尺度渗流模型就能够获得对RTM模具设计的指导性意见。本文综述了以遗传算法...树脂传递模塑成型(Resin transfer molding,RTM)工艺仿真对于提高成型质量,降低RTM工艺成本至关重要。将人工智能方法引入RTM工艺仿真中,可以不必求解复杂的多尺度渗流模型就能够获得对RTM模具设计的指导性意见。本文综述了以遗传算法和机器学习方法为主的人工智能方法在RTM工艺仿真中的研究现状,并讨论了该领域存在的问题及发展方向。遗传算法主要被应用于注胶口及流道配置优化方面,但在复杂问题中收敛性较差,与其他局部搜索算法结合的方法展现出解决复杂问题的潜力;机器学习方法的应用研究处于起步阶段,目前主要被应用于注射压力、浸渍质量、渗透率预测等方面,只对简单二维充模问题进行了研究;其他人工智能方法通常计算成本低,但难以验证最优性。人工智能方法的问题集中在迭代/训练所需的数据集的获取成本方面。其在三维复杂几何结构及非均匀渗透率制件方面的应用是未来的重要发展方向。展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address ...Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.展开更多
The fabrication of efficient and stable flexible perovskite solar modules(F-PSMs)using poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)remains a significant challenge due to its hydrophobic properties and the mis...The fabrication of efficient and stable flexible perovskite solar modules(F-PSMs)using poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)remains a significant challenge due to its hydrophobic properties and the mismatch in interface energy-level alignment.Here,we introduced[2-(3,6-dimethoxy-9H-carba zol-9-yl)ethyl]phosphonic acid(MeO-2PACz)to modify the PTAA layer,which effectively suppressed surface potential fluctuations and aligned energy levels at the interface of PTAA/perovskite.Additionally,MeO-2PACz enhanced the hydrophilicity of PTAA,facilitating the fabrication of dense,uniform,and pinhole-free perovskite films on large-area flexible substrates.As a result,we achieved an F-PSM with a power conversion efficiency(PCE)of 16.6% and an aperture area of 64 cm^(2),which is the highest reported value among F-PSMs with an active area exceeding 35 cm^(2)based on PTAA.Moreover,the encapsulated module demonstrated outstanding long-term operational stability,retaining 90.2% of its initial efficiency after 1000 bending cycles(5 mm radius),87.2% after 1000 h of continuous illumination,and 80.3% under combined thermal and humid conditions(85℃ and 85% relative humidity),representing one of the most stable F-PSMs reported to date.展开更多
Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differe...Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differences between single types of modification modules,neglecting the impact of steric-hindrance effect caused by chemical structure.Herein,single-tailed modification module with low-steric-hindrance effect and two-tailed modification module with high-steric-hindrance effect were selected to construct paclitaxel prodrugs(P-LA_(C18)and P-BAC18),and the in-depth insights of the sterichindrance effect on prodrug nanoassemblies were explored.Notably,the size stability of the two-tailed prodrugs was enhanced due to improved intermolecular interactions and steric hindrance.Single-tailed prodrug nanoassemblies were more susceptible to attack by redox agents,showing faster drug release and stronger antitumor efficacy,but with poorer safety.In contrast,two-tailed prodrug nanoassemblies exhibited significant advantages in terms of pharmacokinetics,tumor accumulation and safety due to the good size stability,thus ensuring equivalent antitumor efficacy at tolerance dose.These findings highlighted the critical role of steric-hindrance effect of the modification module in regulating the structureactivity relationship of prodrug nanoassemblies and proposed new perspectives into the precise design of self-assembled prodrugs for high-performance cancer therapeutics.展开更多
文摘树脂传递模塑成型(Resin transfer molding,RTM)工艺仿真对于提高成型质量,降低RTM工艺成本至关重要。将人工智能方法引入RTM工艺仿真中,可以不必求解复杂的多尺度渗流模型就能够获得对RTM模具设计的指导性意见。本文综述了以遗传算法和机器学习方法为主的人工智能方法在RTM工艺仿真中的研究现状,并讨论了该领域存在的问题及发展方向。遗传算法主要被应用于注胶口及流道配置优化方面,但在复杂问题中收敛性较差,与其他局部搜索算法结合的方法展现出解决复杂问题的潜力;机器学习方法的应用研究处于起步阶段,目前主要被应用于注射压力、浸渍质量、渗透率预测等方面,只对简单二维充模问题进行了研究;其他人工智能方法通常计算成本低,但难以验证最优性。人工智能方法的问题集中在迭代/训练所需的数据集的获取成本方面。其在三维复杂几何结构及非均匀渗透率制件方面的应用是未来的重要发展方向。
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
文摘Target occlusion poses a significant challenge in computer vision,particularly in agricultural applications,where occlusion of crops can obscure key features and impair the model’s recognition performance.To address this challenge,a mushroom recognition method was proposed based on an erase module integrated into the EL-DenseNet model.EL-DenseNet,an extension of DenseNet,incorporated an erase attention module designed to enhance sensitivity to visible features.The erase module helped eliminate complex backgrounds and irrelevant information,allowing the mushroom body to be preserved and increasing recognition accuracy in cluttered environments.Considering the difficulty in distinguishing similar mushroom species,label smoothing regularization was employed to mitigate mislabeling errors that commonly arose from human observers.This strategy converted hard labels into soft labels during training,reducing the model’s overreliance on noisy labels and improving its generalization ability.Experimental results showed that the proposed EL-DenseNet,when combined with transfer learning,achieved a recognition accuracy of 96.7%for mushrooms in occluded and complex backgrounds.Compared with the original DenseNet and other classic models,this approach demonstrated superior accuracy and robustness,providing a promising solution for intelligent mushroom recognition.
基金financially supported by the Key Fund of Tianjin Natural Science Foundation,China Project of Tianjin Natural Science Foundation(24JCZDJC00510)the National Natural Science Foundation of China,China(22475147)the Fundamental Research Funds for the Central Universities,China。
文摘The fabrication of efficient and stable flexible perovskite solar modules(F-PSMs)using poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine](PTAA)remains a significant challenge due to its hydrophobic properties and the mismatch in interface energy-level alignment.Here,we introduced[2-(3,6-dimethoxy-9H-carba zol-9-yl)ethyl]phosphonic acid(MeO-2PACz)to modify the PTAA layer,which effectively suppressed surface potential fluctuations and aligned energy levels at the interface of PTAA/perovskite.Additionally,MeO-2PACz enhanced the hydrophilicity of PTAA,facilitating the fabrication of dense,uniform,and pinhole-free perovskite films on large-area flexible substrates.As a result,we achieved an F-PSM with a power conversion efficiency(PCE)of 16.6% and an aperture area of 64 cm^(2),which is the highest reported value among F-PSMs with an active area exceeding 35 cm^(2)based on PTAA.Moreover,the encapsulated module demonstrated outstanding long-term operational stability,retaining 90.2% of its initial efficiency after 1000 bending cycles(5 mm radius),87.2% after 1000 h of continuous illumination,and 80.3% under combined thermal and humid conditions(85℃ and 85% relative humidity),representing one of the most stable F-PSMs reported to date.
基金supported by the National Natural Science Foundation of China,(Nos.82272151,82204318)Liaoning Revitalization Talents Program(No.XLYC2203083)+2 种基金Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program(No.RC220389)Postdoctoral Fellowship Program of CPSF(No.GZC20231732)China Postdoctoral Science Foundation(Nos.2023TQ0222,2023MD744229).
文摘Self-assembled prodrug nanomedicine has emerged as an advanced platform for antitumor therapy,mainly comprise drug modules,response modules and modification modules.However,existing studies usually compare the differences between single types of modification modules,neglecting the impact of steric-hindrance effect caused by chemical structure.Herein,single-tailed modification module with low-steric-hindrance effect and two-tailed modification module with high-steric-hindrance effect were selected to construct paclitaxel prodrugs(P-LA_(C18)and P-BAC18),and the in-depth insights of the sterichindrance effect on prodrug nanoassemblies were explored.Notably,the size stability of the two-tailed prodrugs was enhanced due to improved intermolecular interactions and steric hindrance.Single-tailed prodrug nanoassemblies were more susceptible to attack by redox agents,showing faster drug release and stronger antitumor efficacy,but with poorer safety.In contrast,two-tailed prodrug nanoassemblies exhibited significant advantages in terms of pharmacokinetics,tumor accumulation and safety due to the good size stability,thus ensuring equivalent antitumor efficacy at tolerance dose.These findings highlighted the critical role of steric-hindrance effect of the modification module in regulating the structureactivity relationship of prodrug nanoassemblies and proposed new perspectives into the precise design of self-assembled prodrugs for high-performance cancer therapeutics.
