The quality of light is an important abiotic factor that affects the growth and development of photosynthetic organisms.In this study,we exposed the unicellular green alga Dunaliella salina to red(660 nm)and blue(450 ...The quality of light is an important abiotic factor that affects the growth and development of photosynthetic organisms.In this study,we exposed the unicellular green alga Dunaliella salina to red(660 nm)and blue(450 nm)light and analyzed the cell growth,total carotenoid content,and transcriptomes.The growth of D.salina was enhanced by illumination with red light,whereas blue light was not able to promote the algal growth.In contrast,the total carotenoid content increased under both red and blue light.The RNA of D.salina was sequenced and the transcriptomic response of algal cells to red and blue light was investigated.Six transcripts encoding for the blue light receptor cryptochrome were identified,and transcripts involved in the carotenoid metabolism were up-regulated under both red and blue light.Transcripts encoding for photoprotective enzymes related to the scavenging of reactive oxygen species were up-regulated under blue light.The present transcriptomic study provides a more comprehensive understanding of carotenoid biosynthesis in D.salina under different wavelengths of light.展开更多
为了进一步增强视频图像超分辨率重建的效果,研究利用卷积神经网络的特性进行视频图像的空间分辨率重建,提出了一种基于卷积神经网络的视频图像重建模型。采取预训练的策略用于重建模型参数的初始化,同时在多帧视频图像的空间和时间维...为了进一步增强视频图像超分辨率重建的效果,研究利用卷积神经网络的特性进行视频图像的空间分辨率重建,提出了一种基于卷积神经网络的视频图像重建模型。采取预训练的策略用于重建模型参数的初始化,同时在多帧视频图像的空间和时间维度上进行训练,提取描述主要运动信息的特征进行学习,充分利用视频帧间图像的信息互补进行中间帧的重建。针对帧间图像的运动模糊,采用自适应运动补偿加以处理,对通道进行优化输出得到高分辨率的重建图像。实验表明,重建视频图像在平均客观评价指标上均有较大提升(PSNR+0. 4 d B/SSIM+0. 02),并且有效减少了图像在主观视觉效果上的边缘模糊现象。与其他传统算法相比,在图像评价的客观指标和主观视觉效果上均有明显的提升,为视频图像的超分辨率重建提供了一种基于卷积神经网络的新颖架构,也为进一步探索基于深度学习的视频图像超分辨率重建方法提供了思路。展开更多
基金Supported by the National Natural Science Foundation of China(No.41506188)the China Nantong Municipal Applied Basic Research Program(No.MS12017025-2)the Tianjin Demonstration Project for Innovative Development of Marine Economy(No.BHSF2017-21)
文摘The quality of light is an important abiotic factor that affects the growth and development of photosynthetic organisms.In this study,we exposed the unicellular green alga Dunaliella salina to red(660 nm)and blue(450 nm)light and analyzed the cell growth,total carotenoid content,and transcriptomes.The growth of D.salina was enhanced by illumination with red light,whereas blue light was not able to promote the algal growth.In contrast,the total carotenoid content increased under both red and blue light.The RNA of D.salina was sequenced and the transcriptomic response of algal cells to red and blue light was investigated.Six transcripts encoding for the blue light receptor cryptochrome were identified,and transcripts involved in the carotenoid metabolism were up-regulated under both red and blue light.Transcripts encoding for photoprotective enzymes related to the scavenging of reactive oxygen species were up-regulated under blue light.The present transcriptomic study provides a more comprehensive understanding of carotenoid biosynthesis in D.salina under different wavelengths of light.
文摘为了进一步增强视频图像超分辨率重建的效果,研究利用卷积神经网络的特性进行视频图像的空间分辨率重建,提出了一种基于卷积神经网络的视频图像重建模型。采取预训练的策略用于重建模型参数的初始化,同时在多帧视频图像的空间和时间维度上进行训练,提取描述主要运动信息的特征进行学习,充分利用视频帧间图像的信息互补进行中间帧的重建。针对帧间图像的运动模糊,采用自适应运动补偿加以处理,对通道进行优化输出得到高分辨率的重建图像。实验表明,重建视频图像在平均客观评价指标上均有较大提升(PSNR+0. 4 d B/SSIM+0. 02),并且有效减少了图像在主观视觉效果上的边缘模糊现象。与其他传统算法相比,在图像评价的客观指标和主观视觉效果上均有明显的提升,为视频图像的超分辨率重建提供了一种基于卷积神经网络的新颖架构,也为进一步探索基于深度学习的视频图像超分辨率重建方法提供了思路。