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.

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.

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.

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.

Magnetic resonance imaging in children and adolescents with chronic inflammatory bowel disease

Inflammatory bowel diseases(IBD) represent challenges, both from a diagnostic, and therapeutic point of view. Deep-seated anatomic structures are difficult to assess by ultrasound technique alone. As radiation-free alternative cross-sectional imaging method, magnetic resonance imaging of the intestinal structures is costly and time-consuming. Examination of pediatric patients imply additional considerations: reduction of body motions in younger children and consideration of the most appropriate preparation, and examination technique. The demanding Sellink technique is the only means for appropriately distending the lesser intestine in order to detect small bowel strictures. Oral intake of contrast medium(CM) alone shows its limitations regarding distensibility. The need for intravenous contrast media application needs to be considered, too. Active inflammation of both intestinal wall, and mesentery can be demonstrated accurately. Nevertheless, viable alternatives to CM application is desirable, considering non-negligible adverse reactions. Recent data suggest diffusion weighted imaging might fill this diagnostic gap. Irrespective of sequence technique chosen, bowel movement remains a major obstacle. Antispasmolytics in their function as smooth muscle relaxants help in improving image quality, however, their use in children might be off-label. Optimal preparation for the examination and appropriate imaging technique allow for diagnosing typical patterns of changes in IBD, such as bowel wall thickening, ulcers, mural stratification, strictures, creeping fat, and comb sign, and lymphadenopathy. The article gives a detailed overview of current significance of magnetic resonance imaging pediatric patients suffering from IBD, considering indications, limitations, and safety aspects.

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.

Application of Preoperative CT/MRI Image Fusion in Target Positioning for Deep Brain Stimulation

Objective To explore the efficacy of target positioning by preoperative CT/MRI image fusion technique in deep brain stimulation.Methods We retrospectively analyzed the clinical data and images of 79 cases(68 with Parkinson's disease,11 with dystonia) who received preoperative CT/MRI image fusion in target positioning of subthalamic nucleus in deep brain stimulation.Deviation of implanted electrodes from the target nucleus of each patient were measured.Neurological evaluations of each patient before and after the treatment were performed and compared.Complications of the positioning and treatment were recorded.Results The mean deviations of the electrodes implanted on X,Y,and Z axis were 0.5 mm,0.6 mm,and 0.6 mm,respectively.Postoperative neurologic evaluations scores of unified Parkinson's disease rating scale(UPDRS) for Parkinson's disease and Burke-Fahn-Marsden Dystonia Rating Scale(BFMDRS) for dystonia patients improved significantly compared to the preoperative scores(P<0.001); Complications occurred in 10.1%(8/79) patients,and main side effects were dysarthria and diplopia.Conclusion Target positioning by preoperative CT/MRI image fusion technique in deep brain stimulation has high accuracy and good clinical outcomes.

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.

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.

Design of a Landscape Device for Children from the Perspective of Embodied Cognition in the New Era

In recent years,embodied cognition has ushered in a new research upsurge in the academic field,and has become a hot topic in the field of cognitive psychology.In this paper,from the perspective of embodied cognition,the interaction ways of a landscape device for children were discussed to achieve a more real and harmonious interaction between children and scenes.The research data of embodied cognition used by children was analyzed,and the drawbacks and breakthrough points of current landscape devices for children were discussed.The core characteristics of children’s growth period were extracted to establish children’s interaction model and summarize the interactive design methods of landscape devices for children.Embodied cognition has become the most intuitive way for children to know and understand the environment,and plays a pivotal role in children’s growth.Based on embodied cognition principle and interactive behavior mode,the interactive design of a landscape device for children was studied,and three interactive design modes,including simple and convenient interaction mode,multi-sensory interaction mode and game natural interaction mode were summarized.On the basis of this research,relevant design practice and research were carried out to bring a new vision to the design of children’s landscape.

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.

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.

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.

Research on the Influence of Family Education on Children’s Behavioral Habits

Under the background of the all-round deepening of quality education,the cultivation of comprehensive quality has become the main theme of contemporary education reform.Good behavior and habits are of great significance to children’s future learning,growth,and development.Through literature review and other methods,this paper analyzes the current situation of children’s family education and the influence of family education on the cultivation of children’s behavioral habits and provides some strategies for cultivating children’s good behavioral habits in family education.