How should legal benefit restoration be positioned within the criminal law system?This question reveals a rare opportunity for theoretical innovation:embedding legal benefit restoration into the evaluation of illegali...How should legal benefit restoration be positioned within the criminal law system?This question reveals a rare opportunity for theoretical innovation:embedding legal benefit restoration into the evaluation of illegality,and thereby driving a functional shift in illegality theory.In constructing a functional illegality theory,two layers of illegality are involved:meriting punishment and necessitating punishment.The former is anchored in the legitimacy of declaring an act illegal;the latter focuses on the immediate necessity of such a declaration.The two layers exhibit clear differences in the content of assessment,sequence of verification,and evaluative direction,creating a collaborative relationship of mutual supplementation and restriction.The functional illegality theory not only systematically incorporates functional thinking but also clearly demarcates different dimensions of functional evaluation,harmonizing them with the hierarchical structure of criminal theory.展开更多
Traditional hyperspectral imaging(HI)systems are constrained by a limited depth of field(DoF),necessitating refocusing for any out-of-focus objects.This requirement not only slows down the imaging speed but also compl...Traditional hyperspectral imaging(HI)systems are constrained by a limited depth of field(DoF),necessitating refocusing for any out-of-focus objects.This requirement not only slows down the imaging speed but also complicates the system architecture.It is challenging to trade off among speed,resolution,and DoF within an ultrasimple system.While some studies have reported advancements in extending DoF,the improvements remain insufficient.To address this challenge,we propose a novel,to our knowledge,differentiable framework that integrates an extended DoF(E-DoF)wave propagation model and an achromatic hyperspectral reconstructor powered by deep learning.Through rigorous experimental validation,we have demonstrated that the compact HI system is capable of snapshot capturing of high-fidelity images with an exceptional DoF reaching approximately 5 m,marking a significant improvement of over three orders of magnitude.Additionally,the system achieves over 90%spectral accuracy without aberration,nearly doubling the accuracy performance of existing methods.An asymmetric freeform surface design is introduced for diffractive optical elements,enabling dual functionality with design freedom and E-DoF.The sparse prior conditions for spatial texture and spectral features of hyperspectral cubic data are integrated into the reconstruction network,effectively mitigating texture blurring and chromatic aberration.It foresees that the optimal strategy for achromatic E-DoF can be adopted into other optical systems such as polarization imaging and depth measurement.展开更多
文摘How should legal benefit restoration be positioned within the criminal law system?This question reveals a rare opportunity for theoretical innovation:embedding legal benefit restoration into the evaluation of illegality,and thereby driving a functional shift in illegality theory.In constructing a functional illegality theory,two layers of illegality are involved:meriting punishment and necessitating punishment.The former is anchored in the legitimacy of declaring an act illegal;the latter focuses on the immediate necessity of such a declaration.The two layers exhibit clear differences in the content of assessment,sequence of verification,and evaluative direction,creating a collaborative relationship of mutual supplementation and restriction.The functional illegality theory not only systematically incorporates functional thinking but also clearly demarcates different dimensions of functional evaluation,harmonizing them with the hierarchical structure of criminal theory.
基金Youth Innovation Promotion Association of the Chinese Academy of Sciences(2022246)Shanghai Sailing Program(22YF1454800,20YF145480)。
文摘Traditional hyperspectral imaging(HI)systems are constrained by a limited depth of field(DoF),necessitating refocusing for any out-of-focus objects.This requirement not only slows down the imaging speed but also complicates the system architecture.It is challenging to trade off among speed,resolution,and DoF within an ultrasimple system.While some studies have reported advancements in extending DoF,the improvements remain insufficient.To address this challenge,we propose a novel,to our knowledge,differentiable framework that integrates an extended DoF(E-DoF)wave propagation model and an achromatic hyperspectral reconstructor powered by deep learning.Through rigorous experimental validation,we have demonstrated that the compact HI system is capable of snapshot capturing of high-fidelity images with an exceptional DoF reaching approximately 5 m,marking a significant improvement of over three orders of magnitude.Additionally,the system achieves over 90%spectral accuracy without aberration,nearly doubling the accuracy performance of existing methods.An asymmetric freeform surface design is introduced for diffractive optical elements,enabling dual functionality with design freedom and E-DoF.The sparse prior conditions for spatial texture and spectral features of hyperspectral cubic data are integrated into the reconstruction network,effectively mitigating texture blurring and chromatic aberration.It foresees that the optimal strategy for achromatic E-DoF can be adopted into other optical systems such as polarization imaging and depth measurement.
