The national image is a comprehensive concept with a distinct political feature,including the international image presented to the outside world,and also encompassing the national identity of the people.With the devel...The national image is a comprehensive concept with a distinct political feature,including the international image presented to the outside world,and also encompassing the national identity of the people.With the development of globalization,international cultural communication has become a crucial part of shaping the national image,and the opening ceremony of the Beijing Winter Olympics has become an important opportunity for China to showcase its national image to the world in the post-pandemic era.Based on Forceville’s multimodal metaphor theory,this paper examines the metaphorical phenomena contained in the performance and their functions,effects,and purposes in the construction of the national image.It is found that there are many scenes,images,and narratives in the opening ceremony,including war metaphor,competition metaphor,personification metaphor,and other conceptual metaphors.The focus of this paper is on multimodal metaphor in a broad sense,mainly encompassing auditory and visual modes.Through the use of these multimodal metaphors,the opening ceremony of the Winter Olympics builds an image of a vibrant,peace-loving,and responsible country,which not only demonstrates China’s cultural self-confidence,but also expresses the Chinese people’s beautiful vision for the early reunification of the motherland.展开更多
The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern ...The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern to reach the required optimum sizes. Nevertheless, there is no mature model to predict fragmentation distribution to date that can be used in various open pit mines. Therefore, a new framework to evaluate and predict fragmentation distribution is presented based on the image analysis approach. For this purpose, the data collected from Jajarm bauxite mine in Iran were used as the sources in this study. The image analysis process was performed by Split-Desktop software to find out fragmentation distribution, uniformity index and average size of the fragmented rocks. Then, two different approaches including the multivariate regression method and the decision-making trial and evaluation laboratory(DEMATEL) technique were incorporated to develop new models of the uniformity index and the average size to improve the Rosin-Rammler function. The performances of the proposed models were evaluated in four blasting operation sites. The results obtained indicate that the regression model possesses a better performance in prediction of the uniformity index and the average size and subsequently the fragmentation distribution in comparison with DEMATEL and conventional Rosin-Rammler models.展开更多
Magnetic resonance imaging(MRI)is considered the gold standard for the evaluation of anal fistulas.There is sufficient literature available outlining the interpretation of fistula MRI before performing surgery.However...Magnetic resonance imaging(MRI)is considered the gold standard for the evaluation of anal fistulas.There is sufficient literature available outlining the interpretation of fistula MRI before performing surgery.However,the interpretation of MRI becomes quite challenging in the postoperative period after the surgery of fistula has been undertaken.Incidentally,there are scarce data and no set guidelines regarding analysis of fistula MRI in the postoperative period.In this article,we discuss the challenges faced while interpreting the postoperative MRI,the timing of the postoperative MRI,the utility of MRI in the postoperative period for the management of anal fistulas,the importance of the active involvement and experience of the treating clinician in interpreting MRI scans,and the latest advancements in the field.展开更多
An adaptive optics(AO) system based on a stochastic parallel gradient descent(SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the con...An adaptive optics(AO) system based on a stochastic parallel gradient descent(SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briey and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array(LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image con-trast shows improvement from 10-3 to 10-4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.展开更多
Established in 1989, the Open Laboratory ofPalaeobiology & Stratigraphy is a department-spon-sored experimental entity and the only one of its kindin China. At present, it has become a research basefor disciplinar...Established in 1989, the Open Laboratory ofPalaeobiology & Stratigraphy is a department-spon-sored experimental entity and the only one of its kindin China. At present, it has become a research basefor disciplinary studies of Palaeobiology &Stratigraphy. It is noted for its innovative work incarrying out such projects as "Early life evolution &Cambrian biota explosion," "Global stratotypes of theOrdovician series and stage boundaries," "展开更多
Objective: To investigate the potential of superparamagnetic iron oxide particles (SPIO) in MR imaging for the differentiation between hyperplastic and metastatic lymph node. Methods: Animal models of malignant lymph ...Objective: To investigate the potential of superparamagnetic iron oxide particles (SPIO) in MR imaging for the differentiation between hyperplastic and metastatic lymph node. Methods: Animal models of malignant lymph node metastasis were established in 6 New-Zealand rabbits by a unilateral intra-muscular injection of VX2 carcinoma cells, and models of hyperplastic lymph nodes were induced in another 6 rabbits by a unilateral intra-muscular injection of egg yolk emulsion. MR images of the lymph nodes were obtained before and 12 h after interstitial injection of SPIO. Image results were analyzed and compared with pathological findings. Results: On unenhanced images, the signal intensity of hyperplastic and metastatic lymph nodes did not differ significantly. After administration of SPIO, the signal intensity of both hyperplastic and metastatic lymph nodes remained unchanged on T1-weighted SE images. On T2-weighted SE images, the signal intensity of hyperplastic lymph nodes decreased heterogeneously, while that of all metastatic ones remained unchanged. On T2-weighted GRE images, the signal intensity of hyperplastic lymph nodes decreased significantly and homogeneously, while that of 4 metastatic ones remained unchanged and that of the rest 2 decreased heterogeneously. Conclusion: SPIO-enhanced MR imaging may enable the differentiation between the hyperplastic and metastatic lymph nodes.展开更多
The diversity of software and hardware forces programmers to spend a great deal of time optimizing their source code,which often requires specific treatment for each platform.The problem becomes critical on embedded d...The diversity of software and hardware forces programmers to spend a great deal of time optimizing their source code,which often requires specific treatment for each platform.The problem becomes critical on embedded devices,where computational and memory resources are strictly constrained.Compilers play an essential role in deploying source code on a target device through the backend.In this work,a novel backend for the Open Neural Network Compiler(ONNC)is proposed,which exploits machine learning to optimize code for the ARM Cortex-M device.The backend requires minimal changes to Open Neural Network Exchange(ONNX)models.Several novel optimization techniques are also incorporated in the backend,such as quantizing the ONNX model’s weight and automatically tuning the dimensions of operators in computations.The performance of the proposed framework is evaluated for two applications:handwritten digit recognition on the Modified National Institute of Standards and Technology(MNIST)dataset and model,and image classification on the Canadian Institute For Advanced Research and 10(CIFAR-10)dataset with the AlexNet-Light model.The system achieves 98.90%and 90.55%accuracy for handwritten digit recognition and image classification,respectively.Furthermore,the proposed architecture is significantly more lightweight than other state-of-theart models in terms of both computation time and generated source code complexity.From the system perspective,this work provides a novel approach to deploying direct computations from the available ONNX models to target devices by optimizing compilers while maintaining high efficiency in accuracy performance.展开更多
In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant fo...In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant for each label,which leads to the gradient variation con-centrating on the boundary.Thus,the dense deformation field(DDF)is gathered on the boundary and there even appears folding phenomenon.In order to fully leverage the label information,the morphological opening and closing information maps are introduced to enlarge the non-zero gradi-ent regions and improve the accuracy of DDF estimation.The opening information maps supervise the registration model to focus on smaller,narrow brain regions.The closing information maps supervise the registration model to pay more attention to the complex boundary region.Then,opening and closing morphology networks(OC_Net)are designed to automatically generate open-ing and closing information maps to realize the end-to-end training process.Finally,a new registra-tion architecture,VM_(seg+oc),is proposed by combining OC_Net and VoxelMorph.Experimental results show that the registration accuracy of VM_(seg+oc) is significantly improved on LPBA40 and OASIS1 datasets.Especially,VM_(seg+oc) can well improve registration accuracy in smaller brain regions and narrow regions.展开更多
A computer vision approach through Open AI’s CLIP, a model capable of predicting text-image pairs, is used to create an AI agent for Dixit, a game which requires creative linking between images and text. This paper c...A computer vision approach through Open AI’s CLIP, a model capable of predicting text-image pairs, is used to create an AI agent for Dixit, a game which requires creative linking between images and text. This paper calculates baseline accuracies for both the ability to match the correct image to a hint and the ability to match up with human preferences. A dataset created by previous work on Dixit is used for testing. CLIP is utilized through the comparison of a hint to multiple images, and previous hints, achieving a final accuracy of 0.5011 which surpasses previous results.展开更多
文摘The national image is a comprehensive concept with a distinct political feature,including the international image presented to the outside world,and also encompassing the national identity of the people.With the development of globalization,international cultural communication has become a crucial part of shaping the national image,and the opening ceremony of the Beijing Winter Olympics has become an important opportunity for China to showcase its national image to the world in the post-pandemic era.Based on Forceville’s multimodal metaphor theory,this paper examines the metaphorical phenomena contained in the performance and their functions,effects,and purposes in the construction of the national image.It is found that there are many scenes,images,and narratives in the opening ceremony,including war metaphor,competition metaphor,personification metaphor,and other conceptual metaphors.The focus of this paper is on multimodal metaphor in a broad sense,mainly encompassing auditory and visual modes.Through the use of these multimodal metaphors,the opening ceremony of the Winter Olympics builds an image of a vibrant,peace-loving,and responsible country,which not only demonstrates China’s cultural self-confidence,but also expresses the Chinese people’s beautiful vision for the early reunification of the motherland.
文摘The main purpose of blasting in open pit mines is to produce the feed for crushing stage with the optimum dimensions from in situ rocks. The size distribution of muck pile indicates the efficiency of blasting pattern to reach the required optimum sizes. Nevertheless, there is no mature model to predict fragmentation distribution to date that can be used in various open pit mines. Therefore, a new framework to evaluate and predict fragmentation distribution is presented based on the image analysis approach. For this purpose, the data collected from Jajarm bauxite mine in Iran were used as the sources in this study. The image analysis process was performed by Split-Desktop software to find out fragmentation distribution, uniformity index and average size of the fragmented rocks. Then, two different approaches including the multivariate regression method and the decision-making trial and evaluation laboratory(DEMATEL) technique were incorporated to develop new models of the uniformity index and the average size to improve the Rosin-Rammler function. The performances of the proposed models were evaluated in four blasting operation sites. The results obtained indicate that the regression model possesses a better performance in prediction of the uniformity index and the average size and subsequently the fragmentation distribution in comparison with DEMATEL and conventional Rosin-Rammler models.
文摘Magnetic resonance imaging(MRI)is considered the gold standard for the evaluation of anal fistulas.There is sufficient literature available outlining the interpretation of fistula MRI before performing surgery.However,the interpretation of MRI becomes quite challenging in the postoperative period after the surgery of fistula has been undertaken.Incidentally,there are scarce data and no set guidelines regarding analysis of fistula MRI in the postoperative period.In this article,we discuss the challenges faced while interpreting the postoperative MRI,the timing of the postoperative MRI,the utility of MRI in the postoperative period for the management of anal fistulas,the importance of the active involvement and experience of the treating clinician in interpreting MRI scans,and the latest advancements in the field.
基金Supported by the National Natural Science Foundation of China(Grant Nos. 10873024 and 11003031)supported by the National Science Foundation under Grant ATM-0841440
文摘An adaptive optics(AO) system based on a stochastic parallel gradient descent(SPGD) algorithm is proposed to reduce the speckle noises in the optical system of a stellar coronagraph in order to further improve the contrast. The principle of the SPGD algorithm is described briey and a metric suitable for point source imaging optimization is given. The feasibility and good performance of the SPGD algorithm is demonstrated by an experimental system featured with a 140-actuator deformable mirror and a Hartmann-Shark wavefront sensor. Then the SPGD based AO is applied to a liquid crystal array(LCA) based coronagraph to improve the contrast. The LCA can modulate the incoming light to generate a pupil apodization mask of any pattern. A circular stepped pattern is used in our preliminary experiment and the image con-trast shows improvement from 10-3 to 10-4.5 at an angular distance of 2λ/D after being corrected by SPGD based AO.
文摘Established in 1989, the Open Laboratory ofPalaeobiology & Stratigraphy is a department-spon-sored experimental entity and the only one of its kindin China. At present, it has become a research basefor disciplinary studies of Palaeobiology &Stratigraphy. It is noted for its innovative work incarrying out such projects as "Early life evolution &Cambrian biota explosion," "Global stratotypes of theOrdovician series and stage boundaries," "
文摘Objective: To investigate the potential of superparamagnetic iron oxide particles (SPIO) in MR imaging for the differentiation between hyperplastic and metastatic lymph node. Methods: Animal models of malignant lymph node metastasis were established in 6 New-Zealand rabbits by a unilateral intra-muscular injection of VX2 carcinoma cells, and models of hyperplastic lymph nodes were induced in another 6 rabbits by a unilateral intra-muscular injection of egg yolk emulsion. MR images of the lymph nodes were obtained before and 12 h after interstitial injection of SPIO. Image results were analyzed and compared with pathological findings. Results: On unenhanced images, the signal intensity of hyperplastic and metastatic lymph nodes did not differ significantly. After administration of SPIO, the signal intensity of both hyperplastic and metastatic lymph nodes remained unchanged on T1-weighted SE images. On T2-weighted SE images, the signal intensity of hyperplastic lymph nodes decreased heterogeneously, while that of all metastatic ones remained unchanged. On T2-weighted GRE images, the signal intensity of hyperplastic lymph nodes decreased significantly and homogeneously, while that of 4 metastatic ones remained unchanged and that of the rest 2 decreased heterogeneously. Conclusion: SPIO-enhanced MR imaging may enable the differentiation between the hyperplastic and metastatic lymph nodes.
基金This work was supported in part by the Ministry of Science and Technology of Taiwan,R.O.C.,the Grant Number of project 108-2218-E-194-007.
文摘The diversity of software and hardware forces programmers to spend a great deal of time optimizing their source code,which often requires specific treatment for each platform.The problem becomes critical on embedded devices,where computational and memory resources are strictly constrained.Compilers play an essential role in deploying source code on a target device through the backend.In this work,a novel backend for the Open Neural Network Compiler(ONNC)is proposed,which exploits machine learning to optimize code for the ARM Cortex-M device.The backend requires minimal changes to Open Neural Network Exchange(ONNX)models.Several novel optimization techniques are also incorporated in the backend,such as quantizing the ONNX model’s weight and automatically tuning the dimensions of operators in computations.The performance of the proposed framework is evaluated for two applications:handwritten digit recognition on the Modified National Institute of Standards and Technology(MNIST)dataset and model,and image classification on the Canadian Institute For Advanced Research and 10(CIFAR-10)dataset with the AlexNet-Light model.The system achieves 98.90%and 90.55%accuracy for handwritten digit recognition and image classification,respectively.Furthermore,the proposed architecture is significantly more lightweight than other state-of-theart models in terms of both computation time and generated source code complexity.From the system perspective,this work provides a novel approach to deploying direct computations from the available ONNX models to target devices by optimizing compilers while maintaining high efficiency in accuracy performance.
基金supported by Shandong Provincial Natural Science Foundation(No.ZR2023MF062)the National Natural Science Foundation of China(No.61771230).
文摘In order to improve the registration accuracy of brain magnetic resonance images(MRI),some deep learning registration methods use segmentation images for training model.How-ever,the segmentation values are constant for each label,which leads to the gradient variation con-centrating on the boundary.Thus,the dense deformation field(DDF)is gathered on the boundary and there even appears folding phenomenon.In order to fully leverage the label information,the morphological opening and closing information maps are introduced to enlarge the non-zero gradi-ent regions and improve the accuracy of DDF estimation.The opening information maps supervise the registration model to focus on smaller,narrow brain regions.The closing information maps supervise the registration model to pay more attention to the complex boundary region.Then,opening and closing morphology networks(OC_Net)are designed to automatically generate open-ing and closing information maps to realize the end-to-end training process.Finally,a new registra-tion architecture,VM_(seg+oc),is proposed by combining OC_Net and VoxelMorph.Experimental results show that the registration accuracy of VM_(seg+oc) is significantly improved on LPBA40 and OASIS1 datasets.Especially,VM_(seg+oc) can well improve registration accuracy in smaller brain regions and narrow regions.
文摘A computer vision approach through Open AI’s CLIP, a model capable of predicting text-image pairs, is used to create an AI agent for Dixit, a game which requires creative linking between images and text. This paper calculates baseline accuracies for both the ability to match the correct image to a hint and the ability to match up with human preferences. A dataset created by previous work on Dixit is used for testing. CLIP is utilized through the comparison of a hint to multiple images, and previous hints, achieving a final accuracy of 0.5011 which surpasses previous results.
