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.

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.

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.

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Use of a Digital Image Correlation Technique for Measuring the Material Properties of Beetle Wing

Beetle wings are very specialized flight organs consisting of the veins and membranes.Therefore it is necessary from abionic view to investigate the material properties of a beetle wing experimentally.In the present study,we have used a DigitalImage Correlation (DIC) technique to measure the elastic modulus of a beetle wing membrane.Specimens were prepared bycarefully cutting a beetle hind wing into 3.0 mm by 7.0 mm segments (the gage length was 5 mm).We used a scanning electronmicroscope for a precise measurement of the thickness of the beetle wing membrane.The specimen was attached to a designedfixture to induce a uniform displacement by means of a micromanipulator.We used an ARAMISTM system based on the digitalimage correlation technique to measure the corresponding displacement of a specimen.The thickness of the beetle wing variedat different points of the membrane.The elastic modulus differed in relation to the membrane arrangement showing a structuralanisotropy;the elastic modulus in the chordwise direction is approximately 2.65 GPa,which is three times larger than the elasticmodulus in the spanwise direction of 0.84 GPa.As a result,the digital image correlation-based ARAMIS system was suc-cessfully used to measure the elastic modulus of a beetle wing.In addition to membrane’s elastic modulus,we considered thePoisson’s ratio of the membrane and measured the elastic modulus of a vein using an Instron universal tensile machine.Theresult reveals the Poisson’s ratio is nearly zero and the elastic modulus of a vein is about 11 GPa.

Impact of cognition-related single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease

Multiple single nucleotide polymorphisms may contribute to cognitive decline in Parkinson’s disease. However, the mechanism by which these single nucleotide polymorphisms modify brain imaging phenotype remains unclear. The aim of this study was to investigate the potential effects of multiple single nucleotide polymorphisms on brain imaging phenotype in Parkinson’s disease. Forty-eight Parkinson’s disease patients and 39 matched healthy controls underwent genotyping and 7 T magnetic resonance imaging. A cognitive-weighted polygenic risk score model was designed, in which the effect sizes were determined individually for 36 single nucleotide polymorphisms. The correlations between polygenic risk score, neuroimaging features, and clinical data were analyzed. Furthermore, individual single nucleotide polymorphism analysis was performed to explore the main effects of genotypes and their interactive effects with Parkinson’s disease diagnosis. We found that, in Parkinson’s disease, the polygenic risk score was correlated with the neural activity of the hippocampus, parahippocampus, and fusiform gyrus, and with hippocampal-prefrontal and fusiform-temporal connectivity, as well as with gray matter alterations in the orbitofrontal cortex. In addition, we found that single nucleotide polymorphisms in α-synuclein(SNCA) were associated with white matter microstructural changes in the superior corona radiata, corpus callosum, and external capsule. A single nucleotide polymorphism in catechol-O-methyltransferase was associated with the neural activities of the lingual, fusiform, and occipital gyri, which are involved in visual cognitive dysfunction. Furthermore, DRD3 was associated with frontal and temporal lobe function and structure. In conclusion, imaging genetics is useful for providing a better understanding of the genetic pathways involved in the pathophysiologic processes underlying Parkinson’s disease. This study provides evidence of an association between genetic factors, cognitive functions, and multi-modality neuroimaging biomarkers in Parkinson’s disease.

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.

Identity Issue and Mysterious Images in the Bonesetter's Daughter

This paper is going to do a research on the book The Bonesetter's Daughter and will make an analysis of mysterious images appear in the novel which can be considered as symbols that reflect the culture of orient. And it also looks into the identity issue of Chinese American women from postcolonial perspective.

Interplay between the glymphatic system and neurotoxic proteins in Parkinson’s disease and related disorders:current knowledge and future directions

Parkinson’s disease is a common neurodegenerative disorder that is associated with abnormal aggregation and accumulation of neurotoxic proteins,includingα-synuclein,amyloid-β,and tau,in addition to the impaired elimination of these neurotoxic protein.Atypical parkinsonism,which has the same clinical presentation and neuropathology as Parkinson’s disease,expands the disease landscape within the continuum of Parkinson’s disease and related disorders.The glymphatic system is a waste clearance system in the brain,which is responsible for eliminating the neurotoxic proteins from the interstitial fluid.Impairment of the glymphatic system has been proposed as a significant contributor to the development and progression of neurodegenerative disease,as it exacerbates the aggregation of neurotoxic proteins and deteriorates neuronal damage.Therefore,impairment of the glymphatic system could be considered as the final common pathway to neurodegeneration.Previous evidence has provided initial insights into the potential effect of the impaired glymphatic system on Parkinson’s disease and related disorders;however,many unanswered questions remain.This review aims to provide a comprehensive summary of the growing literature on the glymphatic system in Parkinson’s disease and related disorders.The focus of this review is on identifying the manifestations and mechanisms of interplay between the glymphatic system and neurotoxic proteins,including loss of polarization of aquaporin-4 in astrocytic endfeet,sleep and circadian rhythms,neuroinflammation,astrogliosis,and gliosis.This review further delves into the underlying pathophysiology of the glymphatic system in Parkinson’s disease and related disorders,and the potential implications of targeting the glymphatic system as a novel and promising therapeutic strategy.

Efficient image encryption scheme with synchronous substitution and diffusion based on double S-boxes

Single or multiple S-boxes are widely used in image encryption schemes, and in many image encryption schemes the asynchronous encryption structure is utilized, which separates the processes of substitution and diffusion. In this paper, we analyze the defects of this structure based on the example of an article and crack it using a simpler method. To address the defects of the asynchronous encryption structure, a novel encryption scheme is proposed, in which the structure of synchronous substitution and diffusion based on double S-boxes is utilized, so the processes of substitution and diffusion are combined together and the attackers cannot crack the cryptosystem by any of the processes. The simulation results and security analysis show that the proposed encryption scheme is safer and more efficient to expediently use in the real-time system.

A novel pseudo-random coupled LP spatiotemporal chaos and its application in image encryption

In this paper, first, we investigate a novel one-dimensional logistic-PWLCM(LP) modulation map which is derived from the logistic and PWLCM maps. Second, we propose a novel PCLML spatiotemporal chaos in pseudo-random coupling method that can accelerate the system behavior of the fully spatial chaos. Here, because the better chaotic properties include a wide range of parameter settings and better ergodicity than a logistic map, the LP is used in PCLML as f(x). The Kolmogorov–Sinai entropy density and universality and the bifurcation diagram are employed to investigate the chaotic behaviors of the proposed PCLML model. Finally, we apply the LP and PCLML chaotic systems to image encryption to improve the effectiveness and security of the encryption scheme. By combining self-generating matrix model M and dynamic substitution box(S-Box) methods, we design a new image encryption algorithm. Numerical simulations and security analysis have been carried out to demonstrate that the proposed algorithm has a high security level and can efficiently encrypt several different kinds of images into random-like images.

A Comparative Image Study of two Love Songs——The Sun Rising by John Donne and The Love Song of J.Alfred Prufrock by T.S Eliot

The Sun Rising is one of the most famous metaphysical poems of John Donne.The Love Song of J.Alfred Prufrock is known as the first Modernist poem of T.S Eliot.This paper mainly aims to analyze the strikingly unconventional images use in the two poems,and make comments on their effect on expressing the poet emotions.

Neural stem cell-derived exosomes promote mitochondrial biogenesis and restore abnormal protein distribution in a mouse model of Alzheimer's disease

Mitochondrial dysfunction is a hallmark of Alzheimer’s disease.We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of AP P/PS1 mice.Because Alzheimer’s disease affects the entire brain,further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole.Here,we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing,immunostaining,and lightsheet imaging to clarify their spatial distribution.Additionally,to clarify whether the sirtuin 1(SIRT1)-related pathway plays a regulatory role in neural stem cell-de rived exosomes interfering with mitochondrial functional changes,we generated a novel nervous system-SIRT1 conditional knoc kout AP P/PS1mouse model.Our findings demonstrate that neural stem cell-de rived exosomes significantly increase SIRT1 levels,enhance the production of mitochondrial biogenesis-related fa ctors,and inhibit astrocyte activation,but do not suppress amyloid-βproduction.Thus,neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer’s disease that activates the SIRT1-PGC1αsignaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis.In addition,we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer’s disease,and that neural stem cell-derived exosome treatment can reverse this effect,indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Spectrometer of hard X-ray imager payload onboard the ASO-S mission

A spaceborne hard X-ray spectrometer, composed of an array of 99 scintillation detectors and associated readout electronics, has been developed for the hard X-ray imager(HXI). The HXI is one of the three payloads onboard the advanced space-based solar observatory(ASO-S), which is scheduled to be launched in early 2022 as the first Chinese solar satellite. LaBr3 scintillators and photomultiplier tubes with a super bialkali cathode are used to achieve an energy resolution better than 20% at 30 keV.Further, a new multi-channel charge-sensitive readout application-specific integrated circuit guarantees high-frequency data acquisition with low power consumption. This paper presents a detailed design of the spectrometer for the engineering model of the HXI and discusses its noise and linearity performance.

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 algorithm 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 neighborhood 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.

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.

The Images in The Rime of the Ancient Mariner

The paper mainly talks about the background of S. T. Coleridge and the images of The Rime of the AncientMariner. As for the images, the wind, the albatross and the snake will be thoroughly discussed. There are manydifferent images which also have different meanings and connotations in the context. What＇s more, the poemexpresses the theme of the metabolic relationships between men and nature： harmony, conflict or compromise.

采用DenseNet模型的AD自动分类方法

为研究深度学习算法对阿尔茨海默病分类的准确性,提出密集卷积神经网络方法,对阿尔茨海默病进行分类.利用预处理后的数据训练密集卷积神经网络结构,并分类阿尔茨海默病和认知正常者.测试结果表明,文中方法获得的分类准确率为98.91%,分类阿尔茨海默病和轻度认知障碍的准确率为94.54%,准确率较其他算法有一定提升,为阿尔茨海默病的精准分类提供了一种有效的解决方案.

A Content-Based Parallel Image Retrieval System on Cluster Architectures

We propose a content-based parallel image retrieval system to achieve high responding ability. Our system is developed on cluster architectures. It has several retrieval servers to supply the service of content-based image retrieval. It adopts the Browser/Server (B/S) mode. The users could visit our system though web pages. It uses the symmetrical color-spatial features (SCSF) to represent the content of an image. The SCSF is effective and efficient for image matching because it is independent of image distortion such as rotation and flip as well as it increases the matching accuracy. The SCSF was organized by M-tree, which could speedup the searching procedure.Our experiments show that the image matching is quickly and efficiently with the use of SCSF. And with the support of several retrieval servers, the system could respond to many users at mean time.

The Mixture Japanese and Western Style in the Image of theGovernor-General’s Residence of Taiwan Under Japanese Rule 1

This paper focused on Japan who was as a new colonial government in Taiwan under Japanese rule,during the period of which took official buildings or urban planning mainly of a series of Western European-style architecture as a ruler’s cultural identity and a modern Taiwan policy.However,in the context of East Asian modernity,the basic colonial not only mixed Eurocentric,but also included Japan Center and the interaction between the two.Therefore,the scope of research and discussion shall have regarded to the non-Western,non-white nature of the Japanese Empire,and its colonial/modernity construction is another new model.Taiwan Governor-General’s Residence as the Governor-General’s residence for Japanese government combined administrative office,daily living,and social life,showing a symbol of Japan’s colonial ruling class,and a hostel to greet Japanese royal family and the nobility from time to time.As a mansion of both Western Baroque and Japanese style,its architectural design has class meaning,therefore it featured with a class-separation building,also combined the leisure of Western high society.The associated festivals at that time included tea party,fairs and royal family welcoming pilgrimage,the part of which with a strong political implication.This paper mainly uses the images of the Taiwan Governor-General’s Residence during the Japanese rule period and the literature at that time to restore the mixed taste and Japanese-Western style of Taiwan at that time.The Japanese colonists ruled the complex interactions of different ethnic groups in Taiwan.