DNA水凝胶具有序列可编程性、分子识别能力、刺激响应性、生物相容性和生物降解性等独特性质,广泛应用于材料科学与生物医用领域。滚环扩增(rolling circle amplification,RCA)反应是一种简单高效的等温酶促扩增策略,可合成具有大量重...DNA水凝胶具有序列可编程性、分子识别能力、刺激响应性、生物相容性和生物降解性等独特性质,广泛应用于材料科学与生物医用领域。滚环扩增(rolling circle amplification,RCA)反应是一种简单高效的等温酶促扩增策略,可合成具有大量重复功能单元的超长DNA单链。基于RCA技术,研究人员构建了一系列智能DNA水凝胶材料,具有广阔的生物医学应用前景。本文综述了通过RCA反应制备具有多功能的智能DNA水凝胶的方法,含多聚适配体的DNA水凝胶和生物颗粒的特异性识别与分离,及其后续在疾病诊疗领域的应用研究。展开更多
Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the...Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the monolithic counterpart,the sub-mirrors must maintain precise co-phasing.Piston error critically degrades segmented mirror imaging quality,necessitating efficient and precise detection.To ad-dress the limitations that the conventional circular-aperture diffraction with two-wavelength algorithm is sus-ceptible to decentration errors,and the traditional convolutional neural networks(CNNs)struggle to capture global features under large-range piston errors due to their restricted local receptive fields,this paper pro-poses a method that integrates extended Young’s interference principles with a Vision Transformer(ViT)to detect piston error.By suppressing decentration error interference through two symmetrically arranged aper-tures and extending the measurement range to±7.95μm via a two-wavelength(589 nm/600 nm)algorithm.This approach exploits ViT’s self-attention mechanism to model global characteristics of interference fringes.Unlike CNNs constrained by local convolutional kernels,the ViT significantly improves sensitivity to inter-ferogram periodicity.The simulation results demonstrate that the proposed method achieves a measurement accuracy of 5 nm(0.0083λ0)across the range of±7.95μm,while maintaining an accuracy exceeding 95%in the presence of Gaussian noise(SNR≥15 dB),Poisson noise(λ≥9 photons/pixel),and sub-mirror gap er-ror(Egap≤0.2)interference.Moreover,the detection speed shows significant improvement compared to the cross-correlation algorithm.This study establishes an accurate,robust framework for segmented mirror error detection,advancing high-precision astronomical observation.展开更多
文摘DNA水凝胶具有序列可编程性、分子识别能力、刺激响应性、生物相容性和生物降解性等独特性质,广泛应用于材料科学与生物医用领域。滚环扩增(rolling circle amplification,RCA)反应是一种简单高效的等温酶促扩增策略,可合成具有大量重复功能单元的超长DNA单链。基于RCA技术,研究人员构建了一系列智能DNA水凝胶材料,具有广阔的生物医学应用前景。本文综述了通过RCA反应制备具有多功能的智能DNA水凝胶的方法,含多聚适配体的DNA水凝胶和生物颗粒的特异性识别与分离,及其后续在疾病诊疗领域的应用研究。
文摘Due to the inability of manufacturing a single monolithic mirror at the 10-meter scales,segmented mirrors have become indispensable tools in modern astronomical research.However,to match the imaging performance of the monolithic counterpart,the sub-mirrors must maintain precise co-phasing.Piston error critically degrades segmented mirror imaging quality,necessitating efficient and precise detection.To ad-dress the limitations that the conventional circular-aperture diffraction with two-wavelength algorithm is sus-ceptible to decentration errors,and the traditional convolutional neural networks(CNNs)struggle to capture global features under large-range piston errors due to their restricted local receptive fields,this paper pro-poses a method that integrates extended Young’s interference principles with a Vision Transformer(ViT)to detect piston error.By suppressing decentration error interference through two symmetrically arranged aper-tures and extending the measurement range to±7.95μm via a two-wavelength(589 nm/600 nm)algorithm.This approach exploits ViT’s self-attention mechanism to model global characteristics of interference fringes.Unlike CNNs constrained by local convolutional kernels,the ViT significantly improves sensitivity to inter-ferogram periodicity.The simulation results demonstrate that the proposed method achieves a measurement accuracy of 5 nm(0.0083λ0)across the range of±7.95μm,while maintaining an accuracy exceeding 95%in the presence of Gaussian noise(SNR≥15 dB),Poisson noise(λ≥9 photons/pixel),and sub-mirror gap er-ror(Egap≤0.2)interference.Moreover,the detection speed shows significant improvement compared to the cross-correlation algorithm.This study establishes an accurate,robust framework for segmented mirror error detection,advancing high-precision astronomical observation.
