National Image Construction from the Perspective of Multimodal Metaphor-A Case Study of the Opening Ceremony of the Beijing Winter Olympics

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.

Tourism Image Plan for Wunvfeng National Forest Park

After the introduction of tourist resources in Wunvfeng National Forest Park, the paper had planed its overall image from the perspectives of concept design, visual identity, behavioral norms and audio identity. The slogan of Wunvfeng National Forest Park had been identified as "tour of nature and mythology-Wunvfeng", and the park's emblem, symbolic mascots, spokesman of tourism image and tourist souvenirs had been set, so as to better display tourist advantages of Wunvfeng National Forest Park and create more economic and social benefits.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Imaging characteristics of brain microstructure and cerebral perfusion in Crohn’s disease patients with anxiety: A prospective comparative study

BACKGROUND Anxiety is a common comorbidity in patients with Crohn’s disease(CD).Data on the imaging characteristics of brain microstructure and cerebral perfusion in CD with anxiety are limited.AIM To compare the imaging characteristics of brain microstructure and cerebral perfusion among CD patients with or without anxiety and healthy individuals.METHODS This prospective comparative study enrolled consecutive patients with active CD and healthy individuals who visited the study hospital between January 2022 and January 2023.Anxiety was measured using the Hospital Anxiety and Depression Scale-Anxiety.The imaging characteristics of brain microstructure and cerebral perfusion were measured by diffusion kurtosis imaging and intravoxel incoherent motion.RESULTSA total of 57 participants were enrolled. Among the patients with active CD, 16 had anxiety. Compared withhealthy individuals, patients with active CD demonstrated significantly lower radial kurtosis values in the rightcerebellar region 6, lower axial kurtosis (AK) values in the right insula, left superior temporal gyrus, and rightthalamus, and higher slow and fast apparent diffusion coefficients (ADCslow and ADCfast) in the bilateral frontal lobe,bilateral temporal lobe, and bilateral insular lobe (all P < 0.05). Compared with patients with CD without anxiety,patients with CD and anxiety exhibited significantly higher ADCslow values in the left insular lobe and lower AKvalues in the right insula and right anterior cuneus (all P < 0.05).CONCLUSIONThere are variations in brain microstructure and perfusion among CD patients with/without anxiety and healthyindividuals, suggesting potential use in assessing anxiety-related changes in active CD.

Pervasive Attentive Neural Network for Intelligent Image Classification Based on N-CDE’s

The utilization of visual attention enhances the performance of image classification tasks.Previous attentionbased models have demonstrated notable performance,but many of these models exhibit reduced accuracy when confronted with inter-class and intra-class similarities and differences.Neural-Controlled Differential Equations(N-CDE’s)and Neural Ordinary Differential Equations(NODE’s)are extensively utilized within this context.NCDE’s possesses the capacity to effectively illustrate both inter-class and intra-class similarities and differences with enhanced clarity.To this end,an attentive neural network has been proposed to generate attention maps,which uses two different types of N-CDE’s,one for adopting hidden layers and the other to generate attention values.Two distinct attention techniques are implemented including time-wise attention,also referred to as bottom N-CDE’s;and element-wise attention,called topN-CDE’s.Additionally,a trainingmethodology is proposed to guarantee that the training problem is sufficiently presented.Two classification tasks including fine-grained visual classification andmulti-label classification,are utilized to evaluate the proposedmodel.The proposedmethodology is employed on five publicly available datasets,including CUB-200-2011,ImageNet-1K,PASCAL VOC 2007,PASCAL VOC 2012,and MS COCO.The obtained visualizations have demonstrated that N-CDE’s are better appropriate for attention-based activities in comparison to conventional NODE’s.

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification

Hyperspectral image classification stands as a pivotal task within the field of remote sensing,yet achieving highprecision classification remains a significant challenge.In response to this challenge,a Spectral Convolutional Neural Network model based on Adaptive Fick’s Law Algorithm(AFLA-SCNN)is proposed.The Adaptive Fick’s Law Algorithm(AFLA)constitutes a novel metaheuristic algorithm introduced herein,encompassing three new strategies:Adaptive weight factor,Gaussian mutation,and probability update policy.With adaptive weight factor,the algorithmcan adjust theweights according to the change in the number of iterations to improve the performance of the algorithm.Gaussianmutation helps the algorithm avoid falling into local optimal solutions and improves the searchability of the algorithm.The probability update strategy helps to improve the exploitability and adaptability of the algorithm.Within the AFLA-SCNN model,AFLA is employed to optimize two hyperparameters in the SCNN model,namely,“numEpochs”and“miniBatchSize”,to attain their optimal values.AFLA’s performance is initially validated across 28 functions in 10D,30D,and 50D for CEC2013 and 29 functions in 10D,30D,and 50D for CEC2017.Experimental results indicate AFLA’s marked performance superiority over nine other prominent optimization algorithms.Subsequently,the AFLA-SCNN model was compared with the Spectral Convolutional Neural Network model based on Fick’s Law Algorithm(FLA-SCNN),Spectral Convolutional Neural Network model based on Harris Hawks Optimization(HHO-SCNN),Spectral Convolutional Neural Network model based onDifferential Evolution(DE-SCNN),SpectralConvolutionalNeuralNetwork(SCNN)model,and SupportVector Machines(SVM)model using the Indian Pines dataset and PaviaUniversity dataset.The experimental results show that the AFLA-SCNN model outperforms other models in terms of Accuracy,Precision,Recall,and F1-score on Indian Pines and Pavia University.Among them,the Accuracy of the AFLA-SCNN model on Indian Pines reached 99.875%,and the Accuracy on PaviaUniversity reached 98.022%.In conclusion,our proposed AFLA-SCNN model is deemed to significantly enhance the precision of hyperspectral image classification.

Establishment of Costume Design Database Based on Image Resources in Daur Nationality

Through collecting, summarizing and effectively classifying the image resources in Daur nationality,and applying the theories and methods of costume design,ethnology and computer science,it investigates into the retrieval method and indicator system of images resources in Daur nationality in the context of digitalization. The preliminarily established application model of Daur costume design database can search out all qualified image resources from the database quickly according to the prerequisites given by users so that they can obtain information promptly. In particular,costume designers can get inspirations of creation and enlightenment on their creative thinking. Therefore,the effective integration of art and scientific researches can be realized.

The Disillusionment of the National Ideal Image of China During the Reign of the Qing Dynasty

The author analyzed the subjective factors of the gradual disillusionment of China’s national image, which can be summed up as the increasingly conservative ruling policy of the Qing Dynasty, the increasingly extravagant and corrupt feudal ruling groups, the increasing diplomatic strategy of seclusion and the increasingly imprisoned ruling ideology. The root cause lay in the decline of agricultural civilization and the rise of industrial civilization. The seclusion of the Qing Dynasty caused China to miss the wave of industrial civilization development, and finally led to the reversal of the image of the West and China.

Chinese Overseas Enterprises and Construction of China＇ s National Image

National image is an important component of national interests and a key indicator of a country's comprehensive strength. National image is also an integral part of a country's foreign strategy. With further promotion of the going global strategy, Chinese overseas enterprises have become important participants in globalization and thus major actors shaping China's national image. However, several overseas enterprises have adversely affected China's national image due to lack of cooperation, lack of legal concepts, lack of environmental awareness, ignorance of social responsibility and cultural differences. To this end, the Chinese government should focus on raising awareness among overseas enterprises about national image, establishing a clear mechanism for the entry and exit of overseas enterprises, fostering publicity among overseas enterprises, strengthening the guidance of overseas enterprises in performing their duties, and guiding Chinese overseas enterprises to actively and effectively shape a responsible national image.

The Projection of China’s National Image in President Xi Jinping’s Speeches

In the 21st century, soft power has become an important element to evaluate a nation’s comprehensive strength. Meanwhile, as an indispensable part of soft power, national image receives more and more attention on the political stage. Since Chinese President Xi Jinping’s speeches have unique features and greatly reflect positive national images of China, many scholars start to analyze them from diversified perspectives. Based on Du Bois’ theory of “the Stance Triangle” and the Indexicality Principle, taking President Xi Jinping’s speech at the opening ceremony of the Belt and Road Forum for International Cooperation for example, this paper expounds how President Xi achieves the evaluation, position, and alignment between the subject and object by means of overt labeling, implicature and presupposition, covert evaluation statement, and ideology-laden linguistic structure, in order to establish China’s national image. Through the analysis, the author intends to figure out how national leaders use various persuasive methods to achieve their political purpose. And the author hopes this thesis can provide a new perspective for further analysis on national leaders’ speeches.

China’s National Image in Western Travel Writings in the Age of Discovery

Western travel writings about China provided material driving and theoretical guidance for the Age of Discovery, and became the main spiritual motive of the Westerners voyage to the East. In the Age of Discovery, the image of China in the eyes of Western envoys, merchants and missionaries begun to fade away from traditional mythological and psychedelic colors, and the image of cultural elements such as material, spirit and history become clear. These Western travelers tried to shape the image of China as a state of civilization and wisdom, a state of moral order, and a state of wealth and power. On the basis of the continued description of the kingship and wealth of the Middle Ages, they constructed an overall image of China as a powerful state of civilization and wealth, thus forming a new frame of reference for cognition of China.

Application of Tai Chi Cultural Semiotic Symbols in Chinese Construction of National Image

In recent years, a rapid growth of the global economy has strengthened the competition among nations. To be at a favorable international advantage under such an environment, a positive national image is necessary. As a result, this paper analyzes the application of Tai Chi cultural semiotic symbols in Chinese construction of national image under the discussion on the selection of culture symbol in Chinese construction of national image, as a base, through its positioning with an introduction of Tai Chi - Chinese unique culture symbol. Finally, this paper explains the application tactics in Chinese construction of national image by Tai Chi culture symbol, laying a good foundation for the improvement of Chinese international status.

Study on the Strategy of International Publicity Translation in Our Country from the Perspective of National Image

Along with the advent of the age of globalization, our country and international community are becoming more closely, and comprehensive national strength and infl uence is also greatly growing. Strengthening external propaganda has become a strategic task in the current development of our country. The translation work has been paid more and more attention, and it has an important role in shaping the image of our country. But from the current point of view, there are still some common problems. In this paper, from the perspective of the national image, we analyze the relationship between foreign publicity translation strategies and national image, and we also analyze the status quo of the translation of foreign propaganda in China, then we put forward the strategy of publicity translation.

National Memory—National Image—National Security——National Security Ideology and the Theoretical Model

National security faces the challenge of the "cross- national- sovereignty-management"model and the"commons"mode. Based on hypothesis,cross- regional security net is formed. As for China,it attaches importance to sovereign states and nations,pursuing the relatively stable evaluation of the international community. And based on the national memory and national communication,the state security awareness provides possibility for surpassing the so- called universal value of the West.

Koizumi's Yasukuni Visits,China-Japan Relations And Japan's International Image

Early on the morning of August 15, 2006, which was the 61st anniversary of Japan’s surrender in the Second World War, Junichiro Koizumi dressed himself up in a formal tuxedo jacket with coattails and paid his sixth and also the last visit to the Yasukuni Shrine in his official capacity as Japan’s prime minister. Koizumi’s deliberate action taken amidst the strong protests from people both in and outside Japan has

Analysis of the Tragic Female Images in Eugene O'Neill's Plays

Ruth and Mary are two heroines in Eugene O'Neill's plays Beyond the Horizon, and Long Day's Journey into Night. They have some similarities: when they are young, they are beautiful, native and full of hope towards the future life, but both make wrong choices; in the following years, both suffer a lot from these wrong choices, and feel regretful. This paper tries to explore these two tragic female images.

Image Segmentation of Brain MR Images Using Otsu’s Based Hybrid WCMFO Algorithm

In this study,a novel hybrid Water Cycle Moth-Flame Optimization(WCMFO)algorithm is proposed for multilevel thresholding brain image segmentation in Magnetic Resonance(MR)image slices.WCMFO constitutes a hybrid between the two techniques,comprising the water cycle and moth-flame optimization algorithms.The optimal thresholds are obtained by maximizing the between class variance(Otsu’s function)of the image.To test the performance of threshold searching process,the proposed algorithm has been evaluated on standard benchmark of ten axial T2-weighted brain MR images for image segmentation.The experimental outcomes infer that it produces better optimal threshold values at a greater and quicker convergence rate.In contrast to other state-of-the-art methods,namely Adaptive Wind Driven Optimization(AWDO),Adaptive Bacterial Foraging(ABF)and Particle Swarm Optimization(PSO),the proposed algorithm has been found to be better at producing the best objective function,Peak Signal-to-Noise Ratio(PSNR),Standard Deviation(STD)and lower computational time values.Further,it was observed thatthe segmented image gives greater detail when the threshold level increases.Moreover,the statistical test result confirms that the best and mean values are almost zero and the average difference between best and mean value 1.86 is obtained through the 30 executions of the proposed algorithm.Thus,these images will lead to better segments of gray,white and cerebrospinal fluid that enable better clinical choices and diagnoses using a proposed algorithm.

A hybrid quantum encoding algorithm of vector quantization for image compression

Many classical encoding algorithms of vector quantization （VQ） of image compression that can obtain global optimal solution have computational complexity O（N）. A pure quantum VQ encoding algorithm with probability of success near 100% has been proposed, that performs operations 45√N times approximately. In this paper, a hybrid quantum VQ encoding algorithm between the classical method and the quantum algorithm is presented. The number of its operations is less than √N for most images, and it is more efficient than the pure quantum algorithm.

Range anomaly suppression based on neighborhood pixels detection in ladar range images

Research on the range anomaly suppression algorithm in laser radar （ladar） range images is significant in the application and development of ladar. But most of existing algorithms cannot protect the edge and linear target well while suppressing the range anomaly. Aiming at this problem, the differences among the edge, linear target, and range anomaly are analyzed and a novel algo- rithm based on neighborhood pixels detection is proposed. Firstly, the range differences between current pixel and its neighborhood pixels are calculated. Then, the number of neighborhood pixels is detected by the range difference threshold. Finally, whether the current pixel is a range anomaly is distinguished by the neighbor- hood pixel number threshold. Experimental results show that the new algorithm not only has a better range anomaly suppression performance and higher efficiency, but also protects the edge and linear target preferably compared with other algorithms.