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.

Appendicitis combined with Meckel’s diverticulum obstruction, perforation, and inflammation in children: Three case reports

BACKGROUND Meckel’s diverticulum is a common congenital malformation of the small intestine,with the three most common complications being obstruction,per-foration,and inflammation.To date,only a few cases have been reported world-wide.In children,the clinical symptoms are similar to appendicitis.As most of the imaging features are nonspecific,the preoperative diagnosis is not precise.In addition,the clinical characteristics are highly similar to pediatric acute appendicitis,thus special attention is necessary to distinguish Meckel’s diver-ticulum from pediatric appendicitis.Patients with poor disease control should undergo laparoscopic exploration to avoid serious complications,including intestinal necrosis,intestinal perforation and gastrointestinal bleeding.CASE SUMMARY This report presents three cases of appendicitis in children combined with intestinal obstruction,which was caused by fibrous bands(ligaments)arising from the top part of Meckel's diverticulum,diverticular perforation,and diver-ticular inflammation.All three patients,aged 11-12 years,had acute appendicitis as their initial clinical presentation.All were treated by laparoscopic surgery with a favorable outcome.A complete dataset including clinical presentation,dia-gnostic imaging,surgical information,and histopathologic findings was also provided.CONCLUSION Preoperative diagnosis of Meckel’s diverticulum and its complications is challenging because its clinical signs and complications are similar to those of appendicitis in children.Laparoscopy combined with laparotomy is useful for diagnosis and treatment.

Relationship between Authoritative Parenting Style and Preschool Children’s Emotion Regulation:A Moderated Mediation Model

An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies.However,little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship.Based on family system theory,this study attempts to better understand the relationship between authoritative parenting style and emotion regulation.Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits,their authoritative parenting styles,and children’s emotion regulation.A total of 531 children participated in this study.Results showed that authoritative parenting was positively associated with emotional regulation.Sleep problems mediated the effects of authoritative parenting style on emotion regulation.The child’s sibling status moderated the mediating effects of sleep problems in authoritative parenting and emotion regulation relationships.Specifically,the relationship between the authoritative parenting style and sleep problems was significant for only children,while birth order had no significant influence on the authoritative parenting style and sleep problems in two-child families.These findings suggest that a lowauthoritative parenting style predicts low emotion regulation through sleep problems,and this depends on the child’s sibling status,indicating that children without siblings may impair emotion regulation due to increased sleep problems.

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.

On Translation of Children’s Literature Based on Reception Aesthetics:A Case Study of The Secret Garden

Grounded in reader-centered theories,Reception Aesthetics prioritizes the active engagement and acceptance of target readers.This study examines the translation of children’s literature through the lens of Reception Aesthetics,using Li Wenjun’s rendition of The Secret Garden as a case study.The objective is to scrutinize various aspects of the translation-including vocabulary,syntax,rhetorical devices,and cultural nuances-and to discern how the adaptation and application of diverse translation strategies cater to the aesthetic expectations.

Reflections on Conducting Kindergarten Language Education Activities Based on Children’s Literature

In early childhood education,language education is a crucial component,yet in kindergarten teaching,there often exists issues such as“emphasis on knowledge and neglect of practice.”To address this problem,teachers need to incorporate children’s literature in a reasonable manner to create a conducive environment for language education for young children.This article analyzes and discusses the significance of integrating children’s literature into kindergarten language education activities,and proposes strategies for addressing the current issues in kindergarten language education activities and conducting them based on children’s literature.

The Market Development of Children’s Go Training and the Difficulty and Countermeasure Analysis of Go Training

The children’s Go training market is experiencing vigorous growth but also faces several challenges.As the importance of Go in cultural education increases,the market expands,with growing demand and involvement from training and educational institutions.However,the market encounters difficulties such as a shortage of high-quality Go coaches,uniformity in training content and methods,and high training costs.To address these issues,measures can be taken to strengthen the team of Go coaches,diversify training content and methods,and optimize the training cost structure,thereby promoting the healthy development of the children’s Go training market.

A Study of Health Prescribing for Children with Tourette’s Disorders in Children’s Health Education Specialty Care Clinics

Objective:This study designs and implements the health prescription of children’s health education specialized nursing clinic based on the physical and mental characteristics of children with Tourette’s syndrome.Methods:Applying the evidence-based nursing model and nursing intervention theory based on the survey research by searching China Knowledge Network,Wanfang Database and Wipro Chinese Science and Technology Journal Database,the study collected the literature on the health prescription intervention research in children’s Tourette’s disorders health education in children’s health education of specialized nursing outpatient clinic for review and combined with the specialty characteristics to formulate“Children’s Tourette’s Disorder Health Education Prescription.”Results:Tourette’s syndrome in children is a common pediatric neurological disorder,mainly manifested as involuntary,rapid and repeated muscle twitching and vocal tics,which brings serious psychological pressure and life disturbance to the affected children.Conclusion:For children with Tourette’s syndrome,healthcare professionals should give enough care and understanding to the children and their parents,provide timely and effective health education to them,help them improve their bad behavioral habits,establish correct cognitive attitudes,enhance self-confidence,improve patient compliance,reduce the frequency of recurrence,reduce the incidence of complications and promote children’s physical and mental health development.

Research on Children’s Game Activity Design Strategies Based on Embodied Cognition Theory

Edutainment,in the kindergarten education stage,emphasizes the game as the basic activity and combines the content of education with the form of the game,thus it also forms the educational method of gamification teaching.Through investigation and analysis,it is found that the current kindergarten game activity design has the problem of improper combination of educational content and game form.The current kindergarten game activity design has problems such as stereotypes,children’s lack of active learning opportunities in activities,teachers’insufficient theoretical understanding,inappropriate teacher guidance methods,and so on.Embodied cognition theory attaches importance to the important role of the body in the development of cognition,provides new guidance for classroom teaching,and opens up a new path for classroom teaching reform.Based on the perspective of embodied cognition theory,the concept of body and mind integration should be adhered to in kindergarten teaching with games as the basic activity,experiential teaching situation should be created,children’s subjective experience should be respected,and games and interactions should be designed to promote children’s physical and mental participation,thus laying a foundation for the realization of children’s individual freedom,autonomy,and all-round development.Therefore,this paper aims at the existing problems in the current kindergarten gamification teaching and discusses the design strategy of children’s game activities based on embodied cognition theory.

Effect of Social Media Celebrities on Children’s Satisfaction with Their Body Image

This study investigated the impact of social media and media on children’s body satisfaction in early childhood.The effect of social media and media on children’s body image and differences between girls’and boys’acceptance of their body image were explored.A questionnaire and an illustrated body satisfaction scale were distributed to a sample of 491 children in Saudi Arabia(246 girls,245 boys)aged 5-7 years.The results revealed differences between children’s responses to the illustrated body satisfaction scale and questionnaire.Questionnaire data revealed children were satisfied with their body image(91.4%,standard deviation[SD]0.53),skin color(91.2%,SD 0.53),and weight(79.6%)and did not want to change their shape(73.7%).However,the illustrated body satisfaction scale indicated many children wanted to be like social media celebrities(37.9%),television and film celebrities(32.6%),and famous singers(25.5%).No statistically significant differences were found between girls and boys in body satisfaction,although 66.9%of boys wanted the shape of their body to be more muscular,and girls wanted blue or green eyes and blond hair.This study also revealed Disney princesses had a major effect on girls compared with other media.The researcher recommends conducting longitudinal studies in Arab societies,particularly in Saudi Arabia,to explore the influence of celebrities on children as they age.Importantly,educational policymakers should include pictures of Arab children in the curricula instead of foreign children.

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.

基于MRI影像组学构建PD-1/PD-L1抑制剂治疗dMMR/MSI-H直肠癌疗效的预测模型

目的:探讨MRI影像组学模型在程序性细胞死亡蛋白-1(PD-1)/程序性细胞死亡-配体1(PD-L1)抑制剂联合全程新辅助治疗(TNT)局部进展期直肠癌(LARC)的疗效预测价值。方法:收集河南中医药大学第一附属医院PD-1/PD-L1抑制剂联合TNT治疗的80例错配修复基因缺陷(dMMR)/微卫星高度不稳定(MSI-H)基因型中低位LARC患者的临床和影像资料。将入组患者按7∶3比例分为训练集和测试集,提取影像组学特征,从中筛选并构建影像组学模型。描绘影像组学模型的Rad-score与病理金标准之间的受试者工作特征(ROC)曲线,计算曲线下面积(AUC),并评价模型的诊断效能。采用决策曲线分析(DCA)计算风险阈值的范围,并评估临床获益情况。收集湖南省人民医院25例dMMR/MSI-H基因型LARC患者的影像资料作为外部验证集。结果:训练集、测试集及外部验证集三者之间的临床特征无统计学差异(P>0.05)。经过降维处理、t检验及一致性检验以及LASSO交叉验证后,筛选出一阶偏度特征和体积2个特征构建影像组学模型。训练集、测试集和外部验证集的影像组学预测模型ROC曲线的AUC、灵敏度、特异度、阳性预测值和阴性预测值分别为0.920、97.1%、85.7%、91.9%、94.7%;0.885、80.0%、88.9%、92.3%、72.7%;0.875、87.5%、88.9%、93.3%、80.0%。DCA曲线显示,当风险阈值范围为0%~82%时,采用影像组学模型预测LARC患者为病理完全缓解(pCR)的获益大于将所有患者都视为pCR或者无病理完全缓解(npCR)。结论:基于MRI影像组学构建的dMMR/MSI-H型局部进展期直肠癌PD-1/PD-L1抑制剂联合全程新辅助放化疗疗效预测模型,有较大潜力为不同基因分型的直肠癌患者制定个体化治疗策略提供量化依据。

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.

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.

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.

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. Key words content-based image retrieval - cluster architecture - color-spatial feature - B/S mode - task parallel - WWW - Internet CLC number TP391 Foundation item: Supported by the National Natural Science Foundation of China (60173058)Biography: ZHOU Bing (1975-), male, Ph. D candidate, reseach direction: data mining, content-based image retrieval.

Group Psychological Intervention for Children with Hyperactivity Disorder

ADHD is a broad psychiatric disorder that affects children of normal or near-normal intelligence.It is character-ized by inattention,hyperactivity,and age-inappropriate impulsivity,and it is often accompanied by learning dif-ficulties,behavioral,emotional,and interpersonal problems.On the other hand,hyperactive tendencies in children with ADHD exhibit ADHD-like behaviors such as lack of self-control,inattention,hyperactivity,and emotional impulsivity.However,because their symptoms are less severe,they do not meet the diagnostic criteria for ADHD but are ADHD or at risk of developing ADHD.The purpose of this study is to alleviate and reduce children’s hyperactivity symptoms by investigating the current situation of the children studied,and systemati-cally intervening and educating children with ADHD through psychological group intervention.Research data shows that ADHD is most commonly diagnosed in school-age children,and in 70%–80%of children with ADHD,symptoms persist into adolescence and 30%into adulthood.Through the use of group psychological intervention in the experiment,the prevalence rate of children with hyperactivity disorder tendency has been effectively reduced.This shows that group psychological intervention training has a significant effect on improving hyper-activity symptoms in children with ADHD tendency.