Machine Learning Approaches for the Solution of the Riemann Problem in Fluid Dynamics:a Case Study

We present our results by using a machine learning(ML)approach for the solution of the Riemann problem for the Euler equations of fluid dynamics.The Riemann problem is an initial-value problem with piecewise-constant initial data and it represents a mathematical model of the shock tube.The solution of the Riemann problem is the building block for many numerical algorithms in computational fluid dynamics,such as finite-volume or discontinuous Galerkin methods.Therefore,a fast and accurate approximation of the solution of the Riemann problem and construction of the associated numerical fluxes is of crucial importance.The exact solution of the shock tube problem is fully described by the intermediate pressure and mathematically reduces to finding a solution of a nonlinear equation.Prior to delving into the complexities of ML for the Riemann problem,we consider a much simpler formulation,yet very informative,problem of learning roots of quadratic equations based on their coefficients.We compare two approaches:(i)Gaussian process(GP)regressions,and(ii)neural network(NN)approximations.Among these approaches,NNs prove to be more robust and efficient,although GP can be appreciably more accurate(about 30\%).We then use our experience with the quadratic equation to apply the GP and NN approaches to learn the exact solution of the Riemann problem from the initial data or coefficients of the gas equation of state(EOS).We compare GP and NN approximations in both regression and classification analysis and discuss the potential benefits and drawbacks of the ML approach.

Effects of Health Education with Problem-Based Learning Approaches on the Knowledge, Attitude, Practice and Coping Skills of Women with High-Risk Pregnancies in Plateau Areas

Objective: Given the unique cultural background, way of life, and physical environment of the Tibetan Plateau, this study aims to investigate the effects of health education using problem-based learning (PBL) approaches on the knowledge, attitude, practice, and coping skills of women with high-risk pregnancies in this region. Methods: 76 high-risk pregnancy cases were enrolled at Tibet’s Linzhi People’s Hospital between September 2023 and April 2024. 30 patients admitted between September 2023 and December 2023 were selected as the control group and were performed with regular patient education. 46 patients admitted between January 2024 and April 2024 were selected as the observation group and were performed regular patient education with problem-based learning approaches. Two groups’ performance on their health knowledge, attitude, practice and coping skills before and after interventions were evaluated, and patient satisfaction were measured at the end of the study. Results: There was no statistical significance (P P P Conclusions: Health education with problem-based learning approaches is worth promoting as it can help high-risk pregnant women in plateau areas develop better health knowledge, attitude and practice and healthier coping skills. Also, it can improve patient sanctification.

Impact of parenting styles on preschoolers’behaviors

In this editorial,I comment on the article“Association of preschool children behavior and emotional problems with the parenting behavior of both parents”which was published in the latest issue of“World Journal of Clinical Cases”that demonstrates the prevalence of behavioral disorders in preschool children.Therefore I am focused on parenting which is the most effective factor shown to affect the development and continuity of these behaviors.The management of child behavior problems is crucial.Children in early ages,especially preschoolers who are in the first 5 years of life,are influenced by dramatic changes in various aspects of development,such as social,emotional,and physical.Also,children experience many changes linked to different developmental tasks,such as discovering themselves,getting new friendships,and adapting to a new environment.In this period,parents have a critical role in supporting child development.If parents do not manage and overcome their child’s misbehavior,it could be transformed into psychosocial problems in adulthood.Parenting is the most powerful predictor in the social development of preschool children.Several studies have shown that to reduce the child’s emotional and behavioral problems,a warm relationship between parents and children is needed.In addition,recent studies have demonstrated significant relationships between family regulation factors and parenting,as well as with child behaviors.

Data-Driven Learning Control Algorithms for Unachievable Tracking Problems

For unachievable tracking problems, where the system output cannot precisely track a given reference, achieving the best possible approximation for the reference trajectory becomes the objective. This study aims to investigate solutions using the Ptype learning control scheme. Initially, we demonstrate the necessity of gradient information for achieving the best approximation.Subsequently, we propose an input-output-driven learning gain design to handle the imprecise gradients of a class of uncertain systems. However, it is discovered that the desired performance may not be attainable when faced with incomplete information.To address this issue, an extended iterative learning control scheme is introduced. In this scheme, the tracking errors are modified through output data sampling, which incorporates lowmemory footprints and offers flexibility in learning gain design.The input sequence is shown to converge towards the desired input, resulting in an output that is closest to the given reference in the least square sense. Numerical simulations are provided to validate the theoretical findings.

A transfer learning enhanced physics-informed neural network for parameter identification in soft materials

Soft materials,with the sensitivity to various external stimuli,exhibit high flexibility and stretchability.Accurate prediction of their mechanical behaviors requires advanced hyperelastic constitutive models incorporating multiple parameters.However,identifying multiple parameters under complex deformations remains a challenge,especially with limited observed data.In this study,we develop a physics-informed neural network(PINN)framework to identify material parameters and predict mechanical fields,focusing on compressible Neo-Hookean materials and hydrogels.To improve accuracy,we utilize scaling techniques to normalize network outputs and material parameters.This framework effectively solves forward and inverse problems,extrapolating continuous mechanical fields from sparse boundary data and identifying unknown mechanical properties.We explore different approaches for imposing boundary conditions(BCs)to assess their impacts on accuracy.To enhance efficiency and generalization,we propose a transfer learning enhanced PINN(TL-PINN),allowing pre-trained networks to quickly adapt to new scenarios.The TL-PINN significantly reduces computational costs while maintaining accuracy.This work holds promise in addressing practical challenges in soft material science,and provides insights into soft material mechanics with state-of-the-art experimental methods.

An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

Artificial rabbits optimization(ARO)is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature.However,for solving optimization problems,the ARO algorithm shows slow convergence speed and can fall into local minima.To overcome these drawbacks,this paper proposes chaotic opposition-based learning ARO(COARO),an improved version of the ARO algorithm that incorporates opposition-based learning(OBL)and chaotic local search(CLS)techniques.By adding OBL to ARO,the convergence speed of the algorithm increases and it explores the search space better.Chaotic maps in CLS provide rapid convergence by scanning the search space efficiently,since their ergodicity and non-repetitive properties.The proposed COARO algorithm has been tested using thirty-three distinct benchmark functions.The outcomes have been compared with the most recent optimization algorithms.Additionally,the COARO algorithm’s problem-solving capabilities have been evaluated using six different engineering design problems and compared with various other algorithms.This study also introduces a binary variant of the continuous COARO algorithm,named BCOARO.The performance of BCOARO was evaluated on the breast cancer dataset.The effectiveness of BCOARO has been compared with different feature selection algorithms.The proposed BCOARO outperforms alternative algorithms,according to the findings obtained for real applications in terms of accuracy performance,and fitness value.Extensive experiments show that the COARO and BCOARO algorithms achieve promising results compared to other metaheuristic algorithms.

The Practice and Exploration of Applying EBM to Bilingual Teaching of Medical Genetics at OSBCM

In the process of teaching medical genetics of undergraduate clinical medicine, the practice and exploration of applying EBM to the bilingual teaching of OSBCM medical genetics are carried out. Using CBL and PBL as the carrier can make up for the shortcomings of a single teaching mode, synthesize the advantages of multiple teaching modes. It starts from integrating the basic theoretical knowledge of medicine and clinical practice knowledge, improving students’ bilingual level of medical genetics, cultivating students’ literature retrieval ability, and promoting early clinical, multi-clinical and repeated clinical consciousness for medical students. Therefore, it is more conducive to cultivate students’ ability to learn independently, accurately analyze and solve problems, improve medical students’ clinical thinking ability and scientific research awareness, improve medical students’ ability of international communication, and lay a solid foundation for improving medical students’ future post competence, innovative spirit and lifelong learning ability.

Solving Geometry Problems via Feature Learning and Contrastive Learning of Multimodal Data

This paper presents an end-to-end deep learning method to solve geometry problems via feature learning and contrastive learning of multimodal data.A key challenge in solving geometry problems using deep learning is to automatically adapt to the task of understanding single-modal and multimodal problems.Existing methods either focus on single-modal ormultimodal problems,and they cannot fit each other.A general geometry problem solver shouldobviouslybe able toprocess variousmodalproblems at the same time.Inthispaper,a shared feature-learning model of multimodal data is adopted to learn the unified feature representation of text and image,which can solve the heterogeneity issue between multimodal geometry problems.A contrastive learning model of multimodal data enhances the semantic relevance betweenmultimodal features and maps them into a unified semantic space,which can effectively adapt to both single-modal and multimodal downstream tasks.Based on the feature extraction and fusion of multimodal data,a proposed geometry problem solver uses relation extraction,theorem reasoning,and problem solving to present solutions in a readable way.Experimental results show the effectiveness of the method.

Exploring the Relationship between Learning Styles and Proficiency in Verbal Communication

In the light of need to use learning styles to enhance verbal proficiency,this paper will explore the interconnectedness of learning styles and proficiency in verbal communication.It will first introduce the background of the study.This will be followed by an overview of the research on related literature and studies in the field.Lastly the paper concludes that foreign language teachers should give attention to the styles for languages learning and verbal proficiency since they are closely correlated.

Exploring the Application Effect of Flipped Classroom Combined with Problem-Based Learning Teaching Method in Clinical Skills Teaching of Standardized Training for Resident Doctors of Traditional Chinese Medicine

Objective: To explore the application effect of flipped classroom combined with problem-based learning teaching method in clinical skills teaching of standardized training for resident doctors of traditional Chinese Medicine. Methods: The study used the experimental control method. The study lasted from September to November 2022. The subjects of this study were 49 students of standardized training for resident doctors of traditional Chinese Medicine from grades 2020, 2021 and 2022 of Dazhou integrated TCM & Western Medicine Hospital. They were randomly divided into experiment group (25) and control group (24). The experiment group adopted flipped classroom combined with problem-based learning teaching method, and the control group adopted traditional teaching method. The teaching content was 4 basic clinical skill projects, including four diagnoses of traditional Chinese Medicine, cardiopulmonary resuscitation, dressing change procedure, acupuncture and massage. The evaluation method was carried out by comparing the students’ performance and a self-designed questionnaire was used to investigate the students’ evaluation of the teaching method. Results: The test scores of total scores in the experimental group (90.12 ± 5.89) were all higher than those in the control group (81.47 ± 7.96) (t = 4.53, P P Conclusions: The teaching process of the flipped classroom combined with problem-based learning teaching method is conducive to improving the efficiency of classroom teaching, cultivating students’ self-learning ability, and enhancing students’ willingness to learn.

Application of Learning Style Theory in an English-teaching Activity

Language teaching is demanding.The focus of language teachers nowadays has been extended to a broader area.In the TESOL context,the findings and research of learning style have raised the attention of language teachers,who have to take the responsibility to study how to improve the teaching results according to different learners.This essay attempts to demonstrate a language-teaching activity in a typical English class and discuss the application of learning style theory in it so as to improve the practical English teaching in China.

The Influence of Gender Differences on Language Learning Styles

Generally language learning styles are classified as sensory style and cognitive style. This thesis analyzes the different characteristics of male and female college students in their language learning styles,thus put forwards the strategy of teaching through individuality.

Investigation of the Relevance Between Electronic Courseware Implementation and Students’ Learning Styles

Currently many methods of implementation are available if we want the com＇seware to be used in e-learning interactivly with media rich. This paper focuses the attention to the relevance between various implementations in presentation adopted in the courseware and students＇ learning styles, in order to consider what kind of implemenation or description is preferable to what kind of students or order to support their leaming. We carded out the canonical correlation analysis for this purpose and investigated this relevance on the basis of the experiments. Main results of the experiment are given with detailed disoussion.

The Influence of Learning Style on Second Language Acquisition

Different theorists hold their own idea of learning style and thus lead to various models of learning style. Numerous studies in the field of second language acquisition has been done to prove whether there is a correlation between learning style and second language achievement. The bulk of research indicates that there is a strong relationship between learning styles and language learning outcomes. Learning style is of great importance in second language learning.

The Role of Moral Intelligence and Identity Styles in Prediction of Mental Health Problems in Healthcare Students

Background: Assessment of healthcare students’ mental health problems is an important aspect of health promotion. This study examined the roles of moral intelligence (MI) and identity styles in prediction of mental health problems in healthcare students. Methods: In a correlation study, two hundred healthcare students (100 girls, 100 boys) of Medicine, Density, and Paramedicine Colleges of Bobol University of Medical Sciences were selected. The subjects filled out three questionnaires;General Health Questionnaire (GHQ-28), Moral Competency Inventory (MCI), and Identity Style Inventory (ISI), and General Health Questionnaire (GHQ-28). Pearson correlation, multivariate analysis variance model (MANOVA), and multivariate regression used to analyze the data. Results: Boys and girls did not have a meaningful difference in the mean of total GHQ, MCI, normative and informational identity. Girls had significantly higher mean level of diffused-avoidant identity than boys. There was a positive and significant relationship between moral intelligence, normative identity and mental health problems of students. Also, there was a negative relationship (p < 0.05) between diffused-avoidant identity and mental health problems of students. Moral intelligence, informational and normative identity predicted 25.8% of the variance in mental health problems for girls’ students. Normative and diffused-avoidant identity predicted 21.6% of the variance in mental health problems for girls’ students. Conclusions: This study demonstrated that moral intelligence and identity status contributed to the mental health problems of healthcare students. University administrators should adopt strategies that strengthen the moral intelligence and identity maturity associated with university students’ mental health.

An Analysis of the Impact of Language Learning Styles on Learning Strategy Preferences

This study is designed to explore the impact of LLS （Language Learning Styles） on learning strategy preferences through questionnaire and data analysis. The aim of the study is to make an through investigation of Chinese non-English majors＇ learning styles and their learning strategies in English study, and to analyze the impact of learning styles on learning strategy preferences statistically so as to provide empirical evidence in this field, and then present some implications for college English teaching and learning in Chinese context. This study has significance for pedagogy. Teachers should make language learners aware of their own learning styles and strategy preferences and help them select strategies matching their own style preferences in second language learning. It is hoped that this study can benefit language teachers, learners, and researchers to some extent and can spark more teaching research in the future.

The Influence of Learning Style on English Writing Strategy Training

Learning style is defined as one’s natural,habitual,and preferred ways of absorbing,processing and retaining new information and skills.In language learning process,learners’learning style may help or hinder the mastery of new language.Based on the influential power,learning style should be carefully noticed in the way of strategy training.This paper focuses on the English writing strategy training and aims to put forward some suggestions,putting the influence of learning style at a prominent position.

The Relationship of Learning Strategies and Styles on Language Learning

This study investigates the relationship of learning strategies and styles on language learning and shows how different learning materials according to students＇ adoptions of them. And it especially focuses on analyzing and understanding how M.I. （Multiple Intelligences）, as a strategy, influence on language learning. For research method, this study adopts the observations of the classroom teachings and interviews with the students. As a result, the findings show that first, there are not enough clear explanation on relationship of strategies and styles, but overall, certain factors as verbal-linguistic and interpersonal intelligences help language learners improve their language ability. Second, the use of learning strategies has a positive effect on language learning. Third, the use of learning strategies can be trained and encouraged in language classrooms. Fourth, the appropriate learning materials should be selected according to learners＇ strategies and styles so that learning is more effective and successful. Finally, the implications of these findings are discussed.

Research of the Learning Problems of Contemporary University Students

With the rapid development of China＇s higher education, higher education, popularization of increasingly rapid pace, the future number of people receiving higher education will grow exponentially. In the rapidly growing scale of higher education at the same time, the quality of higher education has been a cause for concern This paper analyzes the current problems in the study of college students exist, and improvement measures put forward their own proposals.

Research of the Learning Problems of Contemporary University Students

With the rapid development of China＇s higher education, higher education, popularization of increasingly rapid pace, the future number of people receiving higher education will grow exponentially. In the rapidly growing scale of higher education at the same time, the quality of higher education has been a cause for concern~ This paper analyzes the current problems in the study of college students exist, and improvement measures put forward their own proposals.