Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics ...Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.展开更多
Magnetic/dielectric@porous carbon composites,derived from metal–organic frameworks(MOFs)with adjustable composition ratio,have attracted wide attention due to their unique magnetoelectric properties.In addition,MOFs-...Magnetic/dielectric@porous carbon composites,derived from metal–organic frameworks(MOFs)with adjustable composition ratio,have attracted wide attention due to their unique magnetoelectric properties.In addition,MOFs-derived porous carbon-based materials can meet the needs of lightweight feature.This paper reports a simple process for synthesizing stacked CoxNiy@C nanosheets derived from CoxNiy-MOFs nanosheets with multiple interfaces,which is good to the microwave response.The CoxNiy@C with controllable composition can be obtained by adjusting the ratio of Co^2+ and Ni^2+.It is supposed that the increased Co content is benefit to the dielectric and magnetic loss.Additionally,the bandwidth of CoNi@C nanosheets can take up almost the whole Ku band.Moreover,this composite has better environmental stability in air,which characteristic provides a sustainable potential for the practical application.展开更多
DNA barcoding is an increasingly prevalent molecular biological technology which uses a short and conserved DNA fragment to facilitate rapid and accurate species identification. Kalidium species are distributed i...DNA barcoding is an increasingly prevalent molecular biological technology which uses a short and conserved DNA fragment to facilitate rapid and accurate species identification. Kalidium species are distributed in saline soil habitat throughout Southeast Europe and Northwest Asia, and used mainly as forage grass in China. The discrimination of Ka-lidium species was based only on morphology-based identification systems and limited to recognized species. Here, we tested four DNA candidate loci, one nuclear locus （ITS, internal transcribed spacer） and three plastid loci （rbcL9 matK and ycflb）, to select potential DNA barcodes for identifying different Kalidium species. Results showed that the best DNA barcode was ITS locus, which displayed the highest species discrimination rate （100%）, followed by matK （33.3%）,ycflb （16.7%）, and rbcL （16.7%）. Meanwhile, four loci clearly identified the variant species, Kalidium cuspidatum （Ung.-Stemb.） Gmb.var.A. J. Li,as a single species in Kalidium.展开更多
Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling fac...Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling factors.To preserve the accuracy of depth discontinuity,a novel joint bilateral depth super-resolution with intensity guidance method is proposed.Particularly,the fast local intensity classification is exploited to estimate depth coefficients in joint bilateral up-sampling for depth maps,so as to eliminate depth discontinuity edge misalignment.Additionally,the proposed method is accelerated on graphic processing units(GPUs)to meet the requirement of realtime application.Experiments demonstrate that our method can preserve the accuracy of depth discontinuity edges after super resolution,leveraging the visual quality of synthesized image in 3D image warping.展开更多
Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an eff...Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an efficient method to solve this problem.Because of the complexity of cloud shapes,the task of modeling the cloud from a single image remains in the development phase.Methods In this study,a deep learning-based method was developed to address the problem of modeling 3D cumulus clouds from a single image.The method employs a three-dimensional autoencoder network that combines the variational autoencoder and the generative adversarial network.First,a 3D cloud shape is mapped into a unique hidden space using the proposed autoencoder.Then,the parameters of the decoder are fixed.A shape reconstruction network is proposed for use instead of the encoder part,and it is trained with rendered images.To train the presented models,we constructed a 3D cumulus dataset that included 2003D cumulus models.These cumulus clouds were rendered under different lighting parameters.Results The qualitative experiments showed that the proposed autoencoder method can learn more structural details of 3D cumulus shapes than existing approaches.Furthermore,some modeling experiments on rendering images demonstrated the effectiveness of the reconstruction model.Conclusion The proposed autoencoder network learns the latent space of 3D cumulus cloud shapes.The presented reconstruction architecture models a cloud from a single image.Experiments demonstrated the effectiveness of the two models.展开更多
Porous three-dimensional Si C/melamine-derived carbon foam(3 D-Si C/MDCF)composite with an original open pore structure was fabricated by the heat treatment of the commercial melamine foam(MF),carbonization of the sta...Porous three-dimensional Si C/melamine-derived carbon foam(3 D-Si C/MDCF)composite with an original open pore structure was fabricated by the heat treatment of the commercial melamine foam(MF),carbonization of the stable MF,and chemical vapor deposition of the ultra-thin Si C coating.Scanning electron microscopy(SEM)and X-ray diffraction(XRD)were employed to detect the microstructure and morphology of the as-prepared composites.The results indicated that the 3 D-Si C/MDCF composites with the coating structure were prepared successfully.The obtained minimum reflection loss was–29.50 d B when the frequency and absorption thickness were 11.36 GHz and 1.75 mm,respectively.Further,a novel strategy was put forward to state that the best microwave absorption property with a thin thickness of 1.65 mm was gained,where the minimum reflection loss was–24.51 d B and the frequency bandwidth was 3.08 GHz.The excellent electromagnetic wave absorption ability resulted from the specific cladding structure,which could change the raw dielectric property to acquire excellent impedance matching.This present work had a certain extend reference meaning for the potential applications of the lightweight wave absorption materials with target functionalities.展开更多
Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, ...Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, particularly geometric distortions induced by object dis-occlusion. Ensuring the quality of synthetic images is critical to maintaining adequate system service. However, traditional 2 D image quality metrics are ineffective for evaluating synthetic images as they are not sensitive to geometric distortion. In this paper, we propose a novel no-reference image quality assessment method for synthetic images based on convolutional neural networks, introducing local image saliency as prediction weights. Due to the lack of existing training data, we construct a new DIBR synthetic image dataset as part of our contribution. Experiments were conducted on both the public benchmark IRCCyN/IVC DIBR image dataset and our own dataset. Results demonstrate that our proposed metric outperforms traditional 2 D image quality metrics and state-of-the-art DIBR-related metrics.展开更多
How to address the impact of genome editing on human rights is a global challenge.The World Health Organization(WHO)recently developed a governance framework for human genome editing to provide global recommendations ...How to address the impact of genome editing on human rights is a global challenge.The World Health Organization(WHO)recently developed a governance framework for human genome editing to provide global recommendations for establishing appropriate governance mechanisms for human genome editing.This article suggests that a human rights-respecting approach should be explicitly recognized in the framework and other relevant endeavors.Such recognition has significant implications not only on clarifying the duty of States but also on the responsibility of non-State actors,particularly biotech enterprises,to orient this technology towards respect for human rights.To implement this approach,the United Nations Guiding Principles on Business and Human Rights(UNGPs)provide helpful guidance for States,biotech enterprises,and other stakeholders to raise awareness and enhance responsible practices in the field.展开更多
基金Supported by the National Key R&D Program of China (No:2018YFB1403202)the National Natural Science Foundation of China(62172366)。
文摘Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.
基金Financial supports from the National Nature Science Foundation of China(No.51971111)the foundation of Jiangsu Provincial Key Laboratory of Bionic Functional Materials are gratefully acknowledged.
文摘Magnetic/dielectric@porous carbon composites,derived from metal–organic frameworks(MOFs)with adjustable composition ratio,have attracted wide attention due to their unique magnetoelectric properties.In addition,MOFs-derived porous carbon-based materials can meet the needs of lightweight feature.This paper reports a simple process for synthesizing stacked CoxNiy@C nanosheets derived from CoxNiy-MOFs nanosheets with multiple interfaces,which is good to the microwave response.The CoxNiy@C with controllable composition can be obtained by adjusting the ratio of Co^2+ and Ni^2+.It is supposed that the increased Co content is benefit to the dielectric and magnetic loss.Additionally,the bandwidth of CoNi@C nanosheets can take up almost the whole Ku band.Moreover,this composite has better environmental stability in air,which characteristic provides a sustainable potential for the practical application.
基金supported by the Program for New Century Excellent Talents in the Ministry of Education in China(NCET-09-0446)lzujbky-2012-k22 to Yu Xia Wu
文摘DNA barcoding is an increasingly prevalent molecular biological technology which uses a short and conserved DNA fragment to facilitate rapid and accurate species identification. Kalidium species are distributed in saline soil habitat throughout Southeast Europe and Northwest Asia, and used mainly as forage grass in China. The discrimination of Ka-lidium species was based only on morphology-based identification systems and limited to recognized species. Here, we tested four DNA candidate loci, one nuclear locus （ITS, internal transcribed spacer） and three plastid loci （rbcL9 matK and ycflb）, to select potential DNA barcodes for identifying different Kalidium species. Results showed that the best DNA barcode was ITS locus, which displayed the highest species discrimination rate （100%）, followed by matK （33.3%）,ycflb （16.7%）, and rbcL （16.7%）. Meanwhile, four loci clearly identified the variant species, Kalidium cuspidatum （Ung.-Stemb.） Gmb.var.A. J. Li,as a single species in Kalidium.
基金Supported by the National Natural Science Foundation of China(61572058)
文摘Depth discontinuity edge affects the visual quality of synthesized images in 3D image warping.However,it suffers from accuracy degradation when up-sampled from low-resolution depth maps,especially at large scaling factors.To preserve the accuracy of depth discontinuity,a novel joint bilateral depth super-resolution with intensity guidance method is proposed.Particularly,the fast local intensity classification is exploited to estimate depth coefficients in joint bilateral up-sampling for depth maps,so as to eliminate depth discontinuity edge misalignment.Additionally,the proposed method is accelerated on graphic processing units(GPUs)to meet the requirement of realtime application.Experiments demonstrate that our method can preserve the accuracy of depth discontinuity edges after super resolution,leveraging the visual quality of synthesized image in 3D image warping.
基金the National Key R&D Program of China(2017YFB1002702).
文摘Background Cumulus clouds are important elements in creating virtual outdoor scenes.Modeling cumulus clouds that have a specific shape is difficult owing to the fluid nature of the cloud.Image-based modeling is an efficient method to solve this problem.Because of the complexity of cloud shapes,the task of modeling the cloud from a single image remains in the development phase.Methods In this study,a deep learning-based method was developed to address the problem of modeling 3D cumulus clouds from a single image.The method employs a three-dimensional autoencoder network that combines the variational autoencoder and the generative adversarial network.First,a 3D cloud shape is mapped into a unique hidden space using the proposed autoencoder.Then,the parameters of the decoder are fixed.A shape reconstruction network is proposed for use instead of the encoder part,and it is trained with rendered images.To train the presented models,we constructed a 3D cumulus dataset that included 2003D cumulus models.These cumulus clouds were rendered under different lighting parameters.Results The qualitative experiments showed that the proposed autoencoder method can learn more structural details of 3D cumulus shapes than existing approaches.Furthermore,some modeling experiments on rendering images demonstrated the effectiveness of the reconstruction model.Conclusion The proposed autoencoder network learns the latent space of 3D cumulus cloud shapes.The presented reconstruction architecture models a cloud from a single image.Experiments demonstrated the effectiveness of the two models.
基金supported by the National Natural Science Foundation of China(Grant Nos.51772151 and 51761145103)the Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Porous three-dimensional Si C/melamine-derived carbon foam(3 D-Si C/MDCF)composite with an original open pore structure was fabricated by the heat treatment of the commercial melamine foam(MF),carbonization of the stable MF,and chemical vapor deposition of the ultra-thin Si C coating.Scanning electron microscopy(SEM)and X-ray diffraction(XRD)were employed to detect the microstructure and morphology of the as-prepared composites.The results indicated that the 3 D-Si C/MDCF composites with the coating structure were prepared successfully.The obtained minimum reflection loss was–29.50 d B when the frequency and absorption thickness were 11.36 GHz and 1.75 mm,respectively.Further,a novel strategy was put forward to state that the best microwave absorption property with a thin thickness of 1.65 mm was gained,where the minimum reflection loss was–24.51 d B and the frequency bandwidth was 3.08 GHz.The excellent electromagnetic wave absorption ability resulted from the specific cladding structure,which could change the raw dielectric property to acquire excellent impedance matching.This present work had a certain extend reference meaning for the potential applications of the lightweight wave absorption materials with target functionalities.
基金sponsored by the National Key R&D Program of China (No. 2017YFB1002702)the National Natural Science Foundation of China (Nos. 61572058, 61472363)
文摘Depth-image-based rendering(DIBR) is widely used in 3 DTV, free-viewpoint video, and interactive 3 D graphics applications. Typically, synthetic images generated by DIBR-based systems incorporate various distortions, particularly geometric distortions induced by object dis-occlusion. Ensuring the quality of synthetic images is critical to maintaining adequate system service. However, traditional 2 D image quality metrics are ineffective for evaluating synthetic images as they are not sensitive to geometric distortion. In this paper, we propose a novel no-reference image quality assessment method for synthetic images based on convolutional neural networks, introducing local image saliency as prediction weights. Due to the lack of existing training data, we construct a new DIBR synthetic image dataset as part of our contribution. Experiments were conducted on both the public benchmark IRCCyN/IVC DIBR image dataset and our own dataset. Results demonstrate that our proposed metric outperforms traditional 2 D image quality metrics and state-of-the-art DIBR-related metrics.
基金supported by grants from the National Key Research and Development Program of China(Grant nos.2019YFA0904600 and 2020YFA0908600).
文摘How to address the impact of genome editing on human rights is a global challenge.The World Health Organization(WHO)recently developed a governance framework for human genome editing to provide global recommendations for establishing appropriate governance mechanisms for human genome editing.This article suggests that a human rights-respecting approach should be explicitly recognized in the framework and other relevant endeavors.Such recognition has significant implications not only on clarifying the duty of States but also on the responsibility of non-State actors,particularly biotech enterprises,to orient this technology towards respect for human rights.To implement this approach,the United Nations Guiding Principles on Business and Human Rights(UNGPs)provide helpful guidance for States,biotech enterprises,and other stakeholders to raise awareness and enhance responsible practices in the field.
