Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

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.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

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.

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.

基于感觉统合理论的听障儿童PSST沉浸式学习空间设计

特殊教育作为国家教育体系的重要组成部分,对实现中国式教育现代化具有重要意义。信息技术的有效应用是提升特殊教育质量的手段之一,如充分发挥信息技术的多感知觉刺激作用,在听障儿童的认知智能教育早有广泛的实践应用,然而现有的学习空间还不足以支持听障儿童技能有效发展,缺乏理论框架以支撑、引导相关的学习实践。基于此,文章以感觉统合理论(Sensory Integration Theory,SIT)为指导,强调统合外部环境与听障儿童内在感受,提出针对听障儿童特殊认知特征的沉浸式学习空间PSST框架,以实现“教育”“社会”“空间”“技术”四要素的深度融合,并依据此框架面向聋校3~6年级学生设计了“购买商品”沉浸式学习案例,以期为听障儿童感知觉能力的发展提供技术解决方案,并为同类研究提供实践参考。

近十年我国幼儿学习品质研究热点与启示──基于CiteSpace可视化分析

以中国知网(CNKI)数据库为文献来源,借助CiteSpace文献计量可视化软件绘制关键词共现知识图谱,对我国近十年来幼儿学习品质研究进行分析,发现我国幼儿学习品质研究热点领域主要为幼儿学习品质与幼儿发展、幼儿学习品质的影响因素、幼儿学习品质的培养。展望未来,幼儿学习品质研究应关注幼儿多元发展,深入探析因果关系;明确学习品质内涵,修正幼儿教师观念;拓宽研究对象范围,关注处境不利儿童;重视整体系统培养,促进学习品质发展。

A Comparison of the lexical processing in Children's Word Acquisition and in Adults' Word Learning

Children can acquire knowledge of their mother tongue easily in a relatively short time,whereas adults are too inferior to bear the comparison in learning a second language.This paper sets out to study the background and process of children's and adults' language learning,make comparison and contrast,and find out an effective way to promote adults' second language learning.

Decoding degeneration:the implementation of machine learning for clinical detection of neurodegenerative disorders

Machine learning represents a growing subfield of artificial intelligence with much promise in the diagnosis,treatment,and tracking of complex conditions,including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases.While no definitive methods of diagnosis or treatment exist for either disease,researchers have implemented machine learning algorithms with neuroimaging and motion-tracking technology to analyze pathologically relevant symptoms and biomarkers.Deep learning algorithms such as neural networks and complex combined architectures have proven capable of tracking disease-linked changes in brain structure and physiology as well as patient motor and cognitive symptoms and responses to treatment.However,such techniques require further development aimed at improving transparency,adaptability,and reproducibility.In this review,we provide an overview of existing neuroimaging technologies and supervised and unsupervised machine learning techniques with their current applications in the context of Alzheimer’s and Parkinson’s diseases.

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.

Comparison and development of machine learning for thalidomideinduced peripheral neuropathy prediction of refractory Crohn’s disease in Chinese population

BACKGROUND Thalidomide is an effective treatment for refractory Crohn’s disease(CD).However,thalidomide-induced peripheral neuropathy(TiPN),which has a large individual variation,is a major cause of treatment failure.TiPN is rarely predictable and recognized,especially in CD.It is necessary to develop a risk model to predict TiPN occurrence.AIM To develop and compare a predictive model of TiPN using machine learning based on comprehensive clinical and genetic variables.METHODS A retrospective cohort of 164 CD patients from January 2016 to June 2022 was used to establish the model.The National Cancer Institute Common Toxicity Criteria Sensory Scale(version 4.0)was used to assess TiPN.With 18 clinical features and 150 genetic variables,five predictive models were established and evaluated by the confusion matrix receiver operating characteristic curve(AUROC),area under the precision-recall curve(AUPRC),specificity,sensitivity(recall rate),precision,accuracy,and F1 score.RESULTS The top-ranking five risk variables associated with TiPN were interleukin-12 rs1353248[P=0.0004,odds ratio(OR):8.983,95%confidence interval(CI):2.497-30.90],dose(mg/d,P=0.002),brainderived neurotrophic factor(BDNF)rs2030324(P=0.001,OR:3.164,95%CI:1.561-6.434),BDNF rs6265(P=0.001,OR:3.150,95%CI:1.546-6.073)and BDNF rs11030104(P=0.001,OR:3.091,95%CI:1.525-5.960).In the training set,gradient boosting decision tree(GBDT),extremely random trees(ET),random forest,logistic regression and extreme gradient boosting(XGBoost)obtained AUROC values>0.90 and AUPRC>0.87.Among these models,XGBoost and GBDT obtained the first two highest AUROC(0.90 and 1),AUPRC(0.98 and 1),accuracy(0.96 and 0.98),precision(0.90 and 0.95),F1 score(0.95 and 0.98),specificity(0.94 and 0.97),and sensitivity(1).In the validation set,XGBoost algorithm exhibited the best predictive performance with the highest specificity(0.857),accuracy(0.818),AUPRC(0.86)and AUROC(0.89).ET and GBDT obtained the highest sensitivity(1)and F1 score(0.8).Overall,compared with other state-of-the-art classifiers such as ET,GBDT and RF,XGBoost algorithm not only showed a more stable performance,but also yielded higher ROC-AUC and PRC-AUC scores,demonstrating its high accuracy in prediction of TiPN occurrence.CONCLUSION The powerful XGBoost algorithm accurately predicts TiPN using 18 clinical features and 14 genetic variables.With the ability to identify high-risk patients using single nucleotide polymorphisms,it offers a feasible option for improving thalidomide efficacy in CD patients.

改进YOLOX-s的密集垃圾检测方法

针对密集堆放的多种类垃圾检测存在识别率低、定位不够准确和待测目标被误检、漏检问题,提出了一种融合多头自注意力机制改进YOLOX-s的垃圾检测方法。在特征提取网络嵌入SwinTransformer模块,引入基于滑窗操作的多头自注意力机制,使得网络兼顾全局特征信息和重点特征信息,减少误检现象;在预测输出网络中使用可变形卷积,对初始预测框进行精细化处理,提高定位精度;在EIoU损失的基础上引入加权系数,提出加权IoU-EIoU损失,自适应调整训练时不同阶段不同损失的关注程度,进一步加快训练网络的收敛速度。在公开204类垃圾检测数据集中进行测试,结果表明,所提改进算法的平均精度均值分别可达80.5%和92.5%,优于当前流行目标检测算法,且检测速度快,满足实时性需求。

Implicit Continuous User Authentication for Mobile Devices based on Deep Reinforcement Learning

The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like,fingerprint or face.Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session.However,divergent issues remain unaddressed.This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called,Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s(GWCK-CC).First,a Gaussian Weighted Non-local Mean Filter Preprocessing model is applied for reducing the noise pre-sent in the raw input face images.Cauchy Kriging Regression function is employed to reduce the dimensionality.Finally,Continuous Czekanowski’s Clas-sification is utilized for proficient classification between the genuine user and attacker.By this way,the proposed GWCK-CC method achieves accurate authen-tication with minimum error rate and time.Experimental assessment of the pro-posed GWCK-CC method and existing methods are carried out with different factors by using UMDAA-02 Face Dataset.The results confirm that the proposed GWCK-CC method enhances authentication accuracy,by 9%,reduces the authen-tication time,and error rate by 44%,and 43%as compared to the existing methods.

Risk Factors of Learning Disabilities in Chinese Children in Wuhan

Objective To investigate prevalence rate of learning disabilities (LD) in Chinese children, and to explore related risk factors, and to provide theoretical basis for preventing such disabilities. Methods One thousand and one hundred fifty one children were randomly selected in primary schools. According to criteria set by ICD-10, 118 children diagnosed as LD were classified into the study group. Four hundred and ninety one children were classified into the normal control group. Five hundred and forty two children were classified into the excellent control group. The study instruments included PRS (The pupil rating scale revised screening for learning disabilities), Conners' children behavior check-list taken by parents and YG-WR character check-list. Results The prevalence rate of LD in Chinese children was 10.3%. Significant differences were observed between LD and normally learning children, and between the LD group and the excellent group, in terms of scores of Conners' behavior check-list (P<0.05). The study further showed that individual differences in character between the LD group and the control groups still existed even after controlling individual differences in age, IQ, and gender. Some possible causal explanations contributing to LD were improper teaching by parents, low educational level of the parents, and children's characteristics and social relationships. Conclusion These data underscore the fact that LD is a serious national public health problem in China. LD is resulted from a number of factors. Good studying and living environments should be created for LD children.