As the most critical part of post-graduate education,the Chinese government launched Standard Resident Training in 2013 to solve the regional inequality of medical quality and meet the increasing social requirement fo...As the most critical part of post-graduate education,the Chinese government launched Standard Resident Training in 2013 to solve the regional inequality of medical quality and meet the increasing social requirement for better medical service.We integrated problem-based learning(PBL)and case-based learning(CBL)in the Endodontics Standard Resident Training.By evaluating with objective parameters including theoretical knowledge and clinical practice skill,and subjective parameters including questionnaire,it was found that PBL+CBL played a positive role in endodontic resident training with a significant difference(P<0.05).This combined training model is instructive for China’s resident training,and this result can provide a rudimentary reference to current postgraduate teaching reform.展开更多
In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytic...In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.展开更多
Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL...Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.展开更多
Humans achieve cognitive development through continuous interaction with their environment,enhancing both perception and behavior.However,current robots lack the capacity for human-like action and evolution,posing a b...Humans achieve cognitive development through continuous interaction with their environment,enhancing both perception and behavior.However,current robots lack the capacity for human-like action and evolution,posing a bottleneck to improving robotic intelligence.Existing research predominantly models robots as one-way,static mappings from observations to actions,neglecting the dynamic processes of perception and behavior.This paper introduces a novel approach to robot cognitive learning by considering physical properties.We propose a theoretical framework wherein a robot is conceptualized as a three-body physical system comprising a perception-body(P-body),a cognition-body(C-body),and a behavior-body(B-body).Each body engages in physical dynamics and operates within a closed-loop interaction.Significantly,three crucial interactions connect these bodies.The C-body relies on the Pbody's extracted states and reciprocally offers long-term rewards,optimizing the P-body's perception policy.In addition,the C-body directs the B-body's actions through sub-goals,and subsequent P-body-derived states facilitate the C-body's cognition dynamics learning.At last,the B-body would follow the sub-goal generated by the C-body and perform actions conditioned on the perceptive state from the P-body,which leads to the next interactive step.These interactions foster the joint evolution of each body,culminating in optimal design.To validate our approach,we employ a navigation task using a four-legged robot,D'Kitty,equipped with a movable global camera.Navigational prowess demands intricate coordination of sensing,planning,and D'Kitty's motion.Leveraging our framework yields superior task performance compared with conventional methodologies.In conclusion,this paper establishes a paradigm shift in robot cognitive learning by integrating physical interactions across the P-body,C-body,and B-body,while considering physical properties.Our framework's successful application to a navigation task underscores its efficacy in enhancing robotic intelligence.展开更多
Partial Differential Equations(PDEs)are model candidates of soft sensing for aero-engine health management units.The existing Physics-Informed Neural Networks(PINNs)have made achievements.However,unmeasurable aero-eng...Partial Differential Equations(PDEs)are model candidates of soft sensing for aero-engine health management units.The existing Physics-Informed Neural Networks(PINNs)have made achievements.However,unmeasurable aero-engine driving sources lead to unknown PDE driving terms,which weaken PINNs feasibility.To this end,Physically Informed Hierarchical Learning followed by Recurrent-Prediction Term(PIHL-RPT)is proposed.First,PIHL is proposed for learning nonhomogeneous PDE solutions,in which two networks NetU and NetG are constructed.NetU is for learning solutions satisfying PDEs;NetG is for learning driving terms to regularize NetU training.Then,we propose a hierarchical learning strategy to optimize and couple NetU and NetG,which are integrated into a data-physics-hybrid loss function.Besides,we prove PIHL-RPT can iteratively generate a series of networks converging to a function,which can approximate a solution to well-posed PDE.Furthermore,RPT is proposed for prediction improvement of PIHL,in which network NetU-RP is constructed to compensate for information loss caused by data sampling and driving sources’immeasurability.Finally,artificial datasets and practical vibration process datasets from our wear experiment platform are used to verify the feasibility and effectiveness of PIHL-RPT based soft sensing.Meanwhile,comparisons with relevant methods,discussions,and PIHL-RPT based health monitoring example are given.展开更多
Similar to many fields of sciences,recent deep learning advances have been applied extensively in geosciences for both small-and large-scale problems.However,the necessity of using large training data and the’black ...Similar to many fields of sciences,recent deep learning advances have been applied extensively in geosciences for both small-and large-scale problems.However,the necessity of using large training data and the’black box’nature of learning have limited them in practice and difficult to interpret.Furthermore,including the governing equations and physical facts in such methods is also another challenge,which entails either ignoring the physics or simplifying them using unrealistic data.To address such issues,physics informed machine learning methods have been developed which can integrate the governing physics law into the learning process.In this work,a 1-dimensional(1 D)time-dependent seismic wave equation is considered and solved using two methods,namely Gaussian process(GP)and physics informed neural networks.We show that these meshless methods are trained by smaller amount of data and can predict the solution of the equation with even high accuracy.They are also capable of inverting any parameter involved in the governing equation such as wave velocity in our case.Results show that the GP can predict the solution of the seismic wave equation with a lower level of error,while our developed neural network is more accurate for velocity(P-and S-wave)and density inversion.展开更多
Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 vali...Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 valid questionnaires were returned,for an effective return rate of 86.4%.Some 54.4%of the students learned that PBL was a pedagogical method from teachers,and 27.8%of the students had participated in PBL courses.Almost all of students(97.6%)were interested in PBL,and 66.7%of survey participants believed that students who were not good at solving problems would have difficulty in PBL courses.Conclusion:Nursing educators should guide students to adapt to new learning approaches,and encourage students to participate in the teaching reform to promote students’autonomous learning ability,innovation ability,and comprehensive ability.展开更多
This study proposes a supervised learning method that does not rely on labels.We use variables associated with the label as indirect labels,and construct an indirect physics-constrained loss based on the physical mech...This study proposes a supervised learning method that does not rely on labels.We use variables associated with the label as indirect labels,and construct an indirect physics-constrained loss based on the physical mechanism to train the model.In the training process,the model prediction is mapped to the space of value that conforms to the physical mechanism through the projection matrix,and then the model is trained based on the indirect labels.The final prediction result of the model conforms to the physical mechanism between indirect label and label,and also meets the constraints of the indirect label.The present study also develops projection matrix normalization and prediction covariance analysis to ensure that the model can be fully trained.Finally,the effect of the physics-constrained indirect supervised learning is verified based on a well log generation problem.展开更多
Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known e...Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known education methods that can be integrated into ophthalmology education to improve students' competence level and promote active learning. Methods: We used a mixed teaching methodology that integrated a FC and PBL into a 1-week ophthalmology clerkship for 72 fourth-year medical students. The course includes two major sessions: FC session and PBL session, relying on clinical and real-patient cases. Written examinations were set up to assess students' academic performance and questionnaires were designed to evaluate their perceptions. Results: The post-course examination results were higher than the pre-course results, and many students gained ophthalmic knowledge and learning skills to varying levels. Comparison of pre-and post-course questionnaires indicated that interests in ophthalmology increased and more students expressed desires to be eye doctors. Most students were satisfied with the new method, while some suggested the process should be slower and the communication with their teacher needed to strengthen.Conclusions: FC and PBL are complementary methodologies. Utilizing the mixed teaching meth of FC and PBL was successful in enhancing academic performance, student satisfactions and promoting active learning.展开更多
Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and cou...Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.展开更多
Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effectiv...Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effective PBL problems.The purpose of this paper is to provide a possible solution to the formulation of PBL problems for computer science courses,which is to reimplement open-source projects(ROSP).A case is demonstrated by showing how ROSP was adopted in a practical intercourse-level PBL course module.This paper contributes to a new PBL problem formulation method for promoting PBL in a practical way for Chinese universities.展开更多
In this article, a physics aware deep learning model is introduced for multiphase flow problems. The deep learning model is shown to be capable of capturing complex physics phenomena such as saturation front, which is...In this article, a physics aware deep learning model is introduced for multiphase flow problems. The deep learning model is shown to be capable of capturing complex physics phenomena such as saturation front, which is even challenging for numerical solvers due to the instability. We display the preciseness of the solution domain delivered by deep learning models and the low cost of deploying this model for complex physics problems, showing the versatile character of this method and bringing it to new areas. This will require more allocation points and more careful design of the deep learning model architectures and residual neural network can be a potential candidate.展开更多
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 M...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.展开更多
Introduction: Nursing students’ experiences during the pandemic provoked social isolation, the way to learn and every context increasing their stress and anxiety leading to drug use and abuse, among others. Problem-b...Introduction: Nursing students’ experiences during the pandemic provoked social isolation, the way to learn and every context increasing their stress and anxiety leading to drug use and abuse, among others. Problem-based learning (PBL) is a pedagogic strategy to strengthen significant learning;then the objective was to establish PBL influence in nursing students’ experiences on drug use and abuse during COVID-19 contingency. Methods: Qualitative, phenomenological and descriptive paradigm, 12 female and male nursing students aged 20 - 24 years old from the 5<sup>th</sup> and 6<sup>th</sup> semesters participated. Information collection was through semi-structured interview and a deep one in four cases. A guide of questions about: How the pandemic impacted your life? How did you face it? And what did you learn during this process? Those questions were used. Qualitative data analysis was based on De Souza Minayo, and signed informed consent was obtained from participants. Results: Students’ experiences allowed four categories to emerge, with six sub-categories. Category I. Students’ experiences on drug use and abuse facing the sanitary contingency;Category II. Students’ skills development to identify a problem and design of appropriate solutions;Category III. Developing skills to favor interpersonal relationships;Category IV. Influence of PBL in nursing students’ experiences on drug use and abuse during the COVID-19 contingency. Conclusion: PBL favored analysis and thoughts in nursing students’ experiences on drug use and abuse during the COVID-19 contingency, they worked collaboratively, developed resilience to daily life situations, and implemented stress coping strategies with their significant learning, which diminished their risk behavior.展开更多
Background:Recently,WeChat application has been widely applied in the field of nursing education in China.Among them,WeChat as a platform combined with problem-based learning(PBL)teaching method is a commonly used met...Background:Recently,WeChat application has been widely applied in the field of nursing education in China.Among them,WeChat as a platform combined with problem-based learning(PBL)teaching method is a commonly used method in nursing teaching,however,no unanimous consensus on the effectiveness of the application of nursing teaching.Purpose:The purpose of this meta-analysis is to systematically evaluate the effectiveness of WeChat as a platform combined with PBL teaching method in nursing teaching for Chinese nursing students from four aspects:nursing students'performance,ability,learning interest and teaching satisfaction.Methods:The following English and Chinese databases were searched for relevant articles:PubMed,Embase,Cochrane library,Web of Science,China National Knowledge Infrastructure(CNKI),WanFang Database,VIP Database and Chinese Biomedical Literature Database(CBM).The search timeframe was set fromthe establishment of these databaseto August 2021.Two reviewers separately screened records,abstracted data,and assessed risk of bias in trials included.Review Manager Software 5.3 was used to analyze data.Results:A total of 11 randomized controlled trials(RCTs)were included.The results of this meta-analysis showed that WeChat combined with PBL teaching method can significantly improve theory examination(SMD=2.50,95%CI:1.69 to 3.30,P<0.001),operation skill(SMD=2.32,95%CI:1.47 to 3.18,P<0.001),comprehensive ability(SMD=3.18,95%CI:1.59 to 4.76,P<0.001),and learning interest(SMD=3.08,95%CI:1.44 to 4.72,P<0.001)in Chinese nursing students,and increase nursing students on teachers'teaching satisfaction(SMD=2.64,95%CI:0.39 to 4.89,P<0.001).Conclusion:WeChat combined with PBL teaching method can significantly enhance Chinese nursing students'knowledge mastery and application,improve their comprehensive ability and learning interest,and improve classroom teaching effect.College nursing educators should consider adopting WeChat combined with PBL teaching method in nursing education to fully demonstrate its application value.展开更多
Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our ho...Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.展开更多
This quasi-experimental study aimed at looking into the effectiveness of PBL （problem-based learning） in improving the performance in Navigation 3 （terrestrial and coastal navigation） of BSMT （Bachelor of Science...This quasi-experimental study aimed at looking into the effectiveness of PBL （problem-based learning） in improving the performance in Navigation 3 （terrestrial and coastal navigation） of BSMT （Bachelor of Science in Marine Transportation） second year students at JBLFMU-Arevalo during the first semester of school year 2016-2017. The respondents of this research were the two sections comparable with each other who was enrolled in the subject Navigation 3. There were 60 student respondents composed of 30 in the experimental group and 30 in the control group. A validated three item teacher-made problem solving test with 10 points for each correct answer was used as an instrument. The dependent variable was the scores in Navigation 3 and independent variable was the PBL approach. The statistical tools used were mean, standard deviation, Mann-Whitney test, and Wilcoxon-Signed ranks test set at 0.05 level of significance. The effect size was computed to determine the effectiveness of the PBL approach in terms of students＇ performance in Navigation 3. Results showed that in the pretest, though the experimental group had a higher mean than the control group, the Mann-Whitney test showed that the mean scores of the two groups were comparable because the significant value was greater than 0.05. When the treatment was introduced, findings showed that there were significant differences in the Navigation 3 performance in the pretest and posttest of experimental and control groups as well as in the posttests of both groups. It could be inferred that the better performance of the experimental group could be attributed to the intervention where the students were actively involved in the learning process.展开更多
基金supported by the Teaching Reform Project of Stomatology College of Chongqing Medical University(KQJ202215,KQJ202204)the Teaching Reform Project of Chongqing Medical University(JY20220317).
文摘As the most critical part of post-graduate education,the Chinese government launched Standard Resident Training in 2013 to solve the regional inequality of medical quality and meet the increasing social requirement for better medical service.We integrated problem-based learning(PBL)and case-based learning(CBL)in the Endodontics Standard Resident Training.By evaluating with objective parameters including theoretical knowledge and clinical practice skill,and subjective parameters including questionnaire,it was found that PBL+CBL played a positive role in endodontic resident training with a significant difference(P<0.05).This combined training model is instructive for China’s resident training,and this result can provide a rudimentary reference to current postgraduate teaching reform.
文摘In order to gain insight into the current research status and development trend of problem-based learning(PBL)in colleges and universities,this study employs the bibliometric method to conduct statistical and analytical studies based on the examination of journal papers and review papers within the Web of Science(WOS)database.The objective is to provide a reference point for research in related fields.The findings indicate a sustained expansion in PBL research output at universities,with the United States accounting for most documents in the field,while European research institutions such as Aalborg University and Maastricht University are at the forefront.Nevertheless,the density of collaborative networks between authors is relatively low,and cross-institutional and interdisciplinary collaboration still requires further strengthening.The majority of research results are published in academic journals such as Academic Medicine and the International Journal of Sustainability in Higher Education.Presently,the focal point of PBL research in colleges and universities is undergoing a transition from a“single-discipline focus”to an“interdisciplinary integration.”This integration is profoundly intertwined with the nascent fields of modern educational technology and education for sustainable development,thereby offering a novel avenue for the advancement of pedagogical approaches and educational equity.
基金supported by National Natural Science Foundation of China(62227818,12204239,62275121)Youth Foundation of Jiangsu Province(BK20220946)+1 种基金Fundamental Research Funds for the Central Universities(30923011024)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202201).
文摘Deep learning(DL)is making significant inroads into biomedical imaging as it provides novel and powerful ways of accurately and efficiently improving the image quality of photoacoustic microscopy(PAM).Off-the-shelf DL models,however,do not necessarily obey the fundamental governing laws of PAM physical systems,nor do they generalize well to scenarios on which they have not been trained.In this work,a physics-embedded degeneration learning(PEDL)approach is proposed to enhance the image quality of PAM with a self-attention enhanced U-Net network,which obtains greater physical consistency,improves data efficiency,and higher adaptability.The proposed method is demonstrated on both synthetic and real datasets,including animal experiments in vivo(blood vessels of mouse's ear and brain).And the results show that compared with previous DL methods,the PEDL algorithm exhibits good performance in recovering PAM images qualitatively and quantitatively.It overcomes the challenges related to training data,accuracy,and robustness which a typical data-driven approach encounters,whose exemplary application envisions to provide a new perspective for existing DL tools of enhanced PAM.
基金jointly funded by the National Science and Technology Major Project of the Ministry of Science and Technology of China(2018AAA0102900)the"New Generation Artificial Intelligence"Key Field Research and Development Plan of Guangdong Province(2021B0101410002)。
文摘Humans achieve cognitive development through continuous interaction with their environment,enhancing both perception and behavior.However,current robots lack the capacity for human-like action and evolution,posing a bottleneck to improving robotic intelligence.Existing research predominantly models robots as one-way,static mappings from observations to actions,neglecting the dynamic processes of perception and behavior.This paper introduces a novel approach to robot cognitive learning by considering physical properties.We propose a theoretical framework wherein a robot is conceptualized as a three-body physical system comprising a perception-body(P-body),a cognition-body(C-body),and a behavior-body(B-body).Each body engages in physical dynamics and operates within a closed-loop interaction.Significantly,three crucial interactions connect these bodies.The C-body relies on the Pbody's extracted states and reciprocally offers long-term rewards,optimizing the P-body's perception policy.In addition,the C-body directs the B-body's actions through sub-goals,and subsequent P-body-derived states facilitate the C-body's cognition dynamics learning.At last,the B-body would follow the sub-goal generated by the C-body and perform actions conditioned on the perceptive state from the P-body,which leads to the next interactive step.These interactions foster the joint evolution of each body,culminating in optimal design.To validate our approach,we employ a navigation task using a four-legged robot,D'Kitty,equipped with a movable global camera.Navigational prowess demands intricate coordination of sensing,planning,and D'Kitty's motion.Leveraging our framework yields superior task performance compared with conventional methodologies.In conclusion,this paper establishes a paradigm shift in robot cognitive learning by integrating physical interactions across the P-body,C-body,and B-body,while considering physical properties.Our framework's successful application to a navigation task underscores its efficacy in enhancing robotic intelligence.
基金supported in part by the National Science and Technology Major Project of China(No.2019-I-0019-0018)the National Natural Science Foundation of China(Nos.61890920,61890921,12302065 and 12172073).
文摘Partial Differential Equations(PDEs)are model candidates of soft sensing for aero-engine health management units.The existing Physics-Informed Neural Networks(PINNs)have made achievements.However,unmeasurable aero-engine driving sources lead to unknown PDE driving terms,which weaken PINNs feasibility.To this end,Physically Informed Hierarchical Learning followed by Recurrent-Prediction Term(PIHL-RPT)is proposed.First,PIHL is proposed for learning nonhomogeneous PDE solutions,in which two networks NetU and NetG are constructed.NetU is for learning solutions satisfying PDEs;NetG is for learning driving terms to regularize NetU training.Then,we propose a hierarchical learning strategy to optimize and couple NetU and NetG,which are integrated into a data-physics-hybrid loss function.Besides,we prove PIHL-RPT can iteratively generate a series of networks converging to a function,which can approximate a solution to well-posed PDE.Furthermore,RPT is proposed for prediction improvement of PIHL,in which network NetU-RP is constructed to compensate for information loss caused by data sampling and driving sources’immeasurability.Finally,artificial datasets and practical vibration process datasets from our wear experiment platform are used to verify the feasibility and effectiveness of PIHL-RPT based soft sensing.Meanwhile,comparisons with relevant methods,discussions,and PIHL-RPT based health monitoring example are given.
文摘Similar to many fields of sciences,recent deep learning advances have been applied extensively in geosciences for both small-and large-scale problems.However,the necessity of using large training data and the’black box’nature of learning have limited them in practice and difficult to interpret.Furthermore,including the governing equations and physical facts in such methods is also another challenge,which entails either ignoring the physics or simplifying them using unrealistic data.To address such issues,physics informed machine learning methods have been developed which can integrate the governing physics law into the learning process.In this work,a 1-dimensional(1 D)time-dependent seismic wave equation is considered and solved using two methods,namely Gaussian process(GP)and physics informed neural networks.We show that these meshless methods are trained by smaller amount of data and can predict the solution of the equation with even high accuracy.They are also capable of inverting any parameter involved in the governing equation such as wave velocity in our case.Results show that the GP can predict the solution of the seismic wave equation with a lower level of error,while our developed neural network is more accurate for velocity(P-and S-wave)and density inversion.
文摘Purpose:To investigate nursing students’knowledge of and attitudes about problem-based learning(PBL).Methods:A total of 1200 students were surveyed at eight nursing colleges in Hunan Province.Results:In all,1037 valid questionnaires were returned,for an effective return rate of 86.4%.Some 54.4%of the students learned that PBL was a pedagogical method from teachers,and 27.8%of the students had participated in PBL courses.Almost all of students(97.6%)were interested in PBL,and 66.7%of survey participants believed that students who were not good at solving problems would have difficulty in PBL courses.Conclusion:Nursing educators should guide students to adapt to new learning approaches,and encourage students to participate in the teaching reform to promote students’autonomous learning ability,innovation ability,and comprehensive ability.
基金partially funded by the National Natural Science Foundation of China (Grants 51520105005 and U1663208)
文摘This study proposes a supervised learning method that does not rely on labels.We use variables associated with the label as indirect labels,and construct an indirect physics-constrained loss based on the physical mechanism to train the model.In the training process,the model prediction is mapped to the space of value that conforms to the physical mechanism through the projection matrix,and then the model is trained based on the indirect labels.The final prediction result of the model conforms to the physical mechanism between indirect label and label,and also meets the constraints of the indirect label.The present study also develops projection matrix normalization and prediction covariance analysis to ensure that the model can be fully trained.Finally,the effect of the physics-constrained indirect supervised learning is verified based on a well log generation problem.
基金supported by National Natural Science Foundation of China for Young Scientist (81200686, 81400426)Research Fund for the Doctoral Program of Higher Education of China (20120171120108)+1 种基金Natural Science Foundation of Guangdong Province, China(S2011040005378)Fundamental Research Funds for the Central Universities (11ykpy65, 15ykpy31)
文摘Background: Ophthalmology is an important medical science subject, but it is given with insufficient attention in undergraduate medical education. Flipped classroom(FC) and problem-based learning(PBL) are well-known education methods that can be integrated into ophthalmology education to improve students' competence level and promote active learning. Methods: We used a mixed teaching methodology that integrated a FC and PBL into a 1-week ophthalmology clerkship for 72 fourth-year medical students. The course includes two major sessions: FC session and PBL session, relying on clinical and real-patient cases. Written examinations were set up to assess students' academic performance and questionnaires were designed to evaluate their perceptions. Results: The post-course examination results were higher than the pre-course results, and many students gained ophthalmic knowledge and learning skills to varying levels. Comparison of pre-and post-course questionnaires indicated that interests in ophthalmology increased and more students expressed desires to be eye doctors. Most students were satisfied with the new method, while some suggested the process should be slower and the communication with their teacher needed to strengthen.Conclusions: FC and PBL are complementary methodologies. Utilizing the mixed teaching meth of FC and PBL was successful in enhancing academic performance, student satisfactions and promoting active learning.
基金supported by the National Key Research and Development Program (2022YFF0609504)the National Natural Science Foundation of China (61974126,51902273,62005230,62001405)the Natural Science Foundation of Fujian Province of China (No.2021J06009)
文摘Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.
基金This research was financially supported by the PBL Research and Application Project of Northeastern University(Grant No.PBL-JX2021yb029,PBL-JX2021yb027).
文摘Recently,Problem-Based Learning(PBL)has been regarded as a possible way towards effective educational changes in Chinese universities.However,problems have been exposed in the adoption of PBL,such as choosing effective PBL problems.The purpose of this paper is to provide a possible solution to the formulation of PBL problems for computer science courses,which is to reimplement open-source projects(ROSP).A case is demonstrated by showing how ROSP was adopted in a practical intercourse-level PBL course module.This paper contributes to a new PBL problem formulation method for promoting PBL in a practical way for Chinese universities.
文摘In this article, a physics aware deep learning model is introduced for multiphase flow problems. The deep learning model is shown to be capable of capturing complex physics phenomena such as saturation front, which is even challenging for numerical solvers due to the instability. We display the preciseness of the solution domain delivered by deep learning models and the low cost of deploying this model for complex physics problems, showing the versatile character of this method and bringing it to new areas. This will require more allocation points and more careful design of the deep learning model architectures and residual neural network can be a potential candidate.
文摘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.
文摘Introduction: Nursing students’ experiences during the pandemic provoked social isolation, the way to learn and every context increasing their stress and anxiety leading to drug use and abuse, among others. Problem-based learning (PBL) is a pedagogic strategy to strengthen significant learning;then the objective was to establish PBL influence in nursing students’ experiences on drug use and abuse during COVID-19 contingency. Methods: Qualitative, phenomenological and descriptive paradigm, 12 female and male nursing students aged 20 - 24 years old from the 5<sup>th</sup> and 6<sup>th</sup> semesters participated. Information collection was through semi-structured interview and a deep one in four cases. A guide of questions about: How the pandemic impacted your life? How did you face it? And what did you learn during this process? Those questions were used. Qualitative data analysis was based on De Souza Minayo, and signed informed consent was obtained from participants. Results: Students’ experiences allowed four categories to emerge, with six sub-categories. Category I. Students’ experiences on drug use and abuse facing the sanitary contingency;Category II. Students’ skills development to identify a problem and design of appropriate solutions;Category III. Developing skills to favor interpersonal relationships;Category IV. Influence of PBL in nursing students’ experiences on drug use and abuse during the COVID-19 contingency. Conclusion: PBL favored analysis and thoughts in nursing students’ experiences on drug use and abuse during the COVID-19 contingency, they worked collaboratively, developed resilience to daily life situations, and implemented stress coping strategies with their significant learning, which diminished their risk behavior.
文摘Background:Recently,WeChat application has been widely applied in the field of nursing education in China.Among them,WeChat as a platform combined with problem-based learning(PBL)teaching method is a commonly used method in nursing teaching,however,no unanimous consensus on the effectiveness of the application of nursing teaching.Purpose:The purpose of this meta-analysis is to systematically evaluate the effectiveness of WeChat as a platform combined with PBL teaching method in nursing teaching for Chinese nursing students from four aspects:nursing students'performance,ability,learning interest and teaching satisfaction.Methods:The following English and Chinese databases were searched for relevant articles:PubMed,Embase,Cochrane library,Web of Science,China National Knowledge Infrastructure(CNKI),WanFang Database,VIP Database and Chinese Biomedical Literature Database(CBM).The search timeframe was set fromthe establishment of these databaseto August 2021.Two reviewers separately screened records,abstracted data,and assessed risk of bias in trials included.Review Manager Software 5.3 was used to analyze data.Results:A total of 11 randomized controlled trials(RCTs)were included.The results of this meta-analysis showed that WeChat combined with PBL teaching method can significantly improve theory examination(SMD=2.50,95%CI:1.69 to 3.30,P<0.001),operation skill(SMD=2.32,95%CI:1.47 to 3.18,P<0.001),comprehensive ability(SMD=3.18,95%CI:1.59 to 4.76,P<0.001),and learning interest(SMD=3.08,95%CI:1.44 to 4.72,P<0.001)in Chinese nursing students,and increase nursing students on teachers'teaching satisfaction(SMD=2.64,95%CI:0.39 to 4.89,P<0.001).Conclusion:WeChat combined with PBL teaching method can significantly enhance Chinese nursing students'knowledge mastery and application,improve their comprehensive ability and learning interest,and improve classroom teaching effect.College nursing educators should consider adopting WeChat combined with PBL teaching method in nursing education to fully demonstrate its application value.
文摘Objective:To analyze the effect of using a problem-based(PBL)independent learning model in teaching cerebral ischemic stroke(CIS)first aid in emergency medicine.Methods:90 interns in the emergency department of our hospital from May 2022 to May 2023 were selected for the study.They were divided into Group A(45,conventional teaching method)and Group B(45 cases,PBL independent learning model)by randomized numerical table method to compare the effects of the two groups.Results:The teaching effect indicators and student satisfaction scores in Group B were higher than those in Group A(P<0.05).Conclusion:The use of the PBL independent learning model in the teaching of CIS first aid can significantly improve the teaching effect and student satisfaction.
文摘This quasi-experimental study aimed at looking into the effectiveness of PBL （problem-based learning） in improving the performance in Navigation 3 （terrestrial and coastal navigation） of BSMT （Bachelor of Science in Marine Transportation） second year students at JBLFMU-Arevalo during the first semester of school year 2016-2017. The respondents of this research were the two sections comparable with each other who was enrolled in the subject Navigation 3. There were 60 student respondents composed of 30 in the experimental group and 30 in the control group. A validated three item teacher-made problem solving test with 10 points for each correct answer was used as an instrument. The dependent variable was the scores in Navigation 3 and independent variable was the PBL approach. The statistical tools used were mean, standard deviation, Mann-Whitney test, and Wilcoxon-Signed ranks test set at 0.05 level of significance. The effect size was computed to determine the effectiveness of the PBL approach in terms of students＇ performance in Navigation 3. Results showed that in the pretest, though the experimental group had a higher mean than the control group, the Mann-Whitney test showed that the mean scores of the two groups were comparable because the significant value was greater than 0.05. When the treatment was introduced, findings showed that there were significant differences in the Navigation 3 performance in the pretest and posttest of experimental and control groups as well as in the posttests of both groups. It could be inferred that the better performance of the experimental group could be attributed to the intervention where the students were actively involved in the learning process.
