This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land sur...This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land surface dewfall, and describes several basic dewfall measurement methods. Moreover, the basic principles of these methods and instruments are interpreted, and their advantages, disadvantages, and applicability are analyzed. Recommendations for the further improvement of these observational instruments and the development of dewfall measuring methods are presented, and new technologies and scientific proposals for exploiting dewfall are elucidated.展开更多
Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution forma...Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution formation mechanism and developing prevention and control strategies.This paper outlined the development history of research on O_(3)formation sensitivity based on observational methods,described the principle and applicability of the methodology,summarized the relative application results in China and provided recommendations on the prevention and control of O_(3)pollution in China based on relevant study results,and finally pointed out the shortcomings and future development prospects in this field in China.The overview study showed that the O_(3)formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NO_(x)-limited regime due to the implementation of the O_(3)precursors emission reduction policies;O_(3)pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O_(3)pollution control measures should be improved.There are still some current deficiencies in the study field in China.Therefore,it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved;the atmospheric chemical mechanisms should be vigorously developed,and standardized methods for determining the O_(3)formation sensitivity should be established in China in the near future.展开更多
RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performa...RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.展开更多
As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and s...As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.展开更多
Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of un...Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.展开更多
Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of ...Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of diverse computational methods for RNA contact prediction,and a benchmark evaluation of these methods remains essential.In this work,we first classified RNA contact prediction methods into statistical inference-based and neural networkbased ones.We then evaluated eight state-of-the-art methods on three test sets:a sequencediverse set,a structurally non-redundant set and a CASP RNA targets set.Our evaluation shows that for identifying non-local and long-range contacts,neural network-based methods outperform statistical inference-based ones,with SPOT-RNA-2D achieving the best performance,followed by CoCoNet and RNAcontact.However,for identifying the long-range tertiary contacts,which are vital for stabilizing RNA tertiary structure,statistical inference-based methods exhibit superior performance with GREMLIN emerging as the top performer.This work provides a comprehensive benchmarking of RNA contact prediction methods,highlighting their strengths and limitations to guide further methodological improvements and applications in RNA structure modeling.展开更多
In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At prese...In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the nume...Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.展开更多
Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure...Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.展开更多
Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsist...Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsistent.It remains unclear whether these associations are causal.Methods We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia.Mendelian randomization(MR)analysis based on summary genome-wide association studies(GWASs)was performed.Genetic correlation and Bayesian colocalization analyses were used to provide robust genetic evidence.Results Ten observational studies involving 80,565,688 participants were included in this metaanalysis.IBD was significantly associated with dementia(risk ratio[RR]=1.36,95%CI=1.04-1.78;I2=84.8%)and VD(RR=2.60,95%CI=1.18-5.70;only one study),but not with AD(RR=2.00,95%CI=0.96-4.13;I^(2)=99.8%).MR analyses did not supported significant causal associations of IBD with dementia(dementia:odds ratio[OR]=1.01,95%CI=0.98-1.03;AD:OR=0.98,95%CI=0.95-1.01;VD:OR=1.02,95%CI=0.97-1.07).In addition,genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.Conclusion Our study did not provide genetic evidence for a causal association between IBD and dementia risk.The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.展开更多
Due to their high water content,stimulus responsiveness,and biocompatibility,hydrogels,which are functional materials with a three-dimensional network structure,are widely applied in fields such as biomedicine,environ...Due to their high water content,stimulus responsiveness,and biocompatibility,hydrogels,which are functional materials with a three-dimensional network structure,are widely applied in fields such as biomedicine,environmental monitoring,and flexible electronics.This paper provides a systematic review of hydrogel charac-terization methods and their applications,focusing on primary evaluation techniques for physical properties(e.g.,mechanical strength,swelling behavior,and pore structure),chemical properties(e.g.,composition,crosslink density,and degradation behavior),biocompatibility,and functional properties(e.g.,drug release,environmental stimulus response,and conductivity).It analyzes the challenges currently faced by characterization methods,such as a lack of standardization,difficulties in dynamic monitoring,an insufficient micro-macro correlation,and poor adaptability to complex environments.It proposes solutions,such as a hierarchical standardization system,in situ imaging technology,cross-scale characterization,and biomimetic testing platforms.Looking ahead,hydrogel characterization techniques will evolve toward intelligent,real-time,multimodal coupling and standardized approaches.These techniques will provide superior technical support for precision medicine,environmental restoration,and flexible electronics.They will also offer systematic methodological guidance for the performance optimization and practical application of hydrogel materials.展开更多
The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and e...The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.展开更多
Dairy wastewater,a kind of high concentration organic wastewater,is produced in large quantities and difficult to treat,and has a negative impact on the ecological environment.In this study,the source,composition,wate...Dairy wastewater,a kind of high concentration organic wastewater,is produced in large quantities and difficult to treat,and has a negative impact on the ecological environment.In this study,the source,composition,water quality characteristics of dairy wastewater and its impact on the ecological environment were analyzed,and the treatment methods of dairy wastewater at home and abroad in recent years were summarized,in order to provide a reference for the treatment of dairy wastewater.展开更多
Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has bee...Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has been extensively studied,there is still no consensus on the correlation between acoustic attenuation coefficient and sediment physical properties.Predicting the acoustic attenuation coefficient remains a challenging issue in sedimentary acoustic research.In this study,we propose a prediction method for the acoustic attenuation coefficient using machine learning algorithms,specifically the random forest(RF),support vector machine(SVR),and convolutional neural network(CNN)algorithms.We utilized the acoustic attenuation coefficient and sediment particle size data from 52 stations as training parameters,with the particle size parameters as the input feature matrix,and measured acoustic attenuation as the training label to validate the attenuation prediction model.Our results indicate that the error of the attenuation prediction model is small.Among the three models,the RF model exhibited the lowest prediction error,with a mean squared error of 0.8232,mean absolute error of 0.6613,and root mean squared error of 0.9073.Additionally,when we applied the models to predict the data collected at different times in the same region,we found that the models developed in this study also demonstrated a certain level of reliability in real prediction scenarios.Our approach demonstrates that constructing a sediment acoustic characteristics model based on machine learning is feasible to a certain extent and offers a novel perspective for studying sediment acoustic properties.展开更多
The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical procedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sam...The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical procedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sample processing,instruments,energy consumed,and the quantities of hazardous materials and waste generated during analytical procedures,need to be considered in the evaluation of the greenness of analytical assays.In this study,we propose a greenness evaluation metric for analytical methods(GEMAM).The new greenness metric is simple,flexible,and comprehensive.The evaluation criteria are based on both the 12 principles of GAC(SIGNIFICANCE)and the 10 factors of sample preparation,and the results are presented on a 0–10 scale.The GEMAM calculation process is easy to perform,and its results are easy to interpret.The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.展开更多
Erratum to:Research Methods Used for Developing Academic Wordlists:A Systematic Review of Studies Published Between 2000 and 2020,Chinese Journal of Applied Linguistics,Volume 48,Issue 3,2025,pp.425-450,doi:10.1515/CJ...Erratum to:Research Methods Used for Developing Academic Wordlists:A Systematic Review of Studies Published Between 2000 and 2020,Chinese Journal of Applied Linguistics,Volume 48,Issue 3,2025,pp.425-450,doi:10.1515/CJAL-2025-0210.展开更多
With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application ...With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application of Manim in the course of Mathematical Methods for Physics.Taking the visualization of Fourier series,complex numbers,and other content as examples,it improves students’understanding of complex and abstract mathematical physics concepts through dynamic and visual teaching methods.The teaching effect shows that Manim helps to enhance students’learning experience,improve teaching efficiency and effectiveness,and has a positive impact on students’active learning ability.The research in this paper can provide references and inspiration for the educational digitalization of higher education.展开更多
基金supported by the National Science Foundation of China (Grant Nos. 40830957 and 40575006)
文摘This paper systematically summarizes previous measuring methods and observational instruments for the magnitude of dewfall on land surface, analyzes the characteristics of common observational instruments for land surface dewfall, and describes several basic dewfall measurement methods. Moreover, the basic principles of these methods and instruments are interpreted, and their advantages, disadvantages, and applicability are analyzed. Recommendations for the further improvement of these observational instruments and the development of dewfall measuring methods are presented, and new technologies and scientific proposals for exploiting dewfall are elucidated.
基金supported by the National Research Program for Key Issues in Air Pollution Control(No.DQGG202121)the Beijing Municipal Science&Technology Commission(No.Z181100005418015)+1 种基金National Natural Science Foundation of China(No.42075094)the National Research Program for Key Issue in Air Pollution Control(No.DQGG2021101)。
文摘Observation-based method for O_(3)formation sensitivity research is an important tool to analyze the causes of ground-level O_(3)pollution,which has broad application potentials in determining the O_(3)pollution formation mechanism and developing prevention and control strategies.This paper outlined the development history of research on O_(3)formation sensitivity based on observational methods,described the principle and applicability of the methodology,summarized the relative application results in China and provided recommendations on the prevention and control of O_(3)pollution in China based on relevant study results,and finally pointed out the shortcomings and future development prospects in this field in China.The overview study showed that the O_(3)formation sensitivity in some urban areas in China in recent years presented a gradual shifting tendency from the VOC-limited regime to the transition regime or the NO_(x)-limited regime due to the implementation of the O_(3)precursors emission reduction policies;O_(3)pollution control strategies and precursor control countermeasures should be formulated based on local conditions and the dynamic control capability of O_(3)pollution control measures should be improved.There are still some current deficiencies in the study field in China.Therefore,it is recommended that a stereoscopic monitoring network for atmospheric photochemical components should be further constructed and improved;the atmospheric chemical mechanisms should be vigorously developed,and standardized methods for determining the O_(3)formation sensitivity should be established in China in the near future.
基金supported by grants from the National Science Foundation of China(Grant Nos.12375038 and 12075171 to ZJT,and 12205223 to YLT).
文摘RNAs have important biological functions and the functions of RNAs are generally coupled to their structures, especiallytheir secondary structures. In this work, we have made a comprehensive evaluation of the performances of existingtop RNA secondary structure prediction methods, including five deep-learning (DL) based methods and five minimum freeenergy (MFE) based methods. First, we made a brief overview of these RNA secondary structure prediction methods.Afterwards, we built two rigorous test datasets consisting of RNAs with non-redundant sequences and comprehensivelyexamined the performances of the RNA secondary structure prediction methods through classifying the RNAs into differentlength ranges and different types. Our examination shows that the DL-based methods generally perform better thanthe MFE-based methods for RNAs with long lengths and complex structures, while the MFE-based methods can achievegood performance for small RNAs and some specialized MFE-based methods can achieve good prediction accuracy forpseudoknots. Finally, we provided some insights and perspectives in modeling RNA secondary structures.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grants(52275471 and 52120105008)the Beijing Outstanding Young Scientist Program,and the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.
基金supported by the National Natural Science Foundation of China(No.92252201)the Fundamental Research Funds for the Central Universitiesthe Academic Excellence Foundation of Beihang University(BUAA)for PhD Students。
文摘Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over.
基金supported by grants from the National Natural Science Foundation of China(Grant No.12205223 to YLT,Grant No.12375038 to ZJT and Grant No.11605125 to YZS)the Department of Education of Hubei Province(Grant No.Q20221705 to YLT)。
文摘Ribonucleic Acid(RNA)contact prediction holds great significance for modeling RNA 3D structures and further understanding RNA biological functions.The rapid growth of RNA sequencing data has driven the development of diverse computational methods for RNA contact prediction,and a benchmark evaluation of these methods remains essential.In this work,we first classified RNA contact prediction methods into statistical inference-based and neural networkbased ones.We then evaluated eight state-of-the-art methods on three test sets:a sequencediverse set,a structurally non-redundant set and a CASP RNA targets set.Our evaluation shows that for identifying non-local and long-range contacts,neural network-based methods outperform statistical inference-based ones,with SPOT-RNA-2D achieving the best performance,followed by CoCoNet and RNAcontact.However,for identifying the long-range tertiary contacts,which are vital for stabilizing RNA tertiary structure,statistical inference-based methods exhibit superior performance with GREMLIN emerging as the top performer.This work provides a comprehensive benchmarking of RNA contact prediction methods,highlighting their strengths and limitations to guide further methodological improvements and applications in RNA structure modeling.
文摘In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42122034,42075043,42330609)the Second Tibetan Plateau Scientific Expedition and Research program(2019QZKK0103)+2 种基金Key Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu(No.24ZYQA031)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2021427)West Light Foundation of the Chinese Academy of Sciences(xbzg-zdsys-202215)。
文摘Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.
文摘Objective:To investigate the distribution of health literacy(HL)levels and the association of HL with proactive personality in patients with permanent colostomy.Methods:A cross-sectional study was conducted to measure proactive personality and HL using validated scales.A total of 172 patients with permanent colostomy were selected from January 2021 to May 2022 in Yantai City,China.Descriptive statistics,t-test,ANOVA,Pearson correlation analysis,and multiple linear regression analysis techniques were used.Results:The results obtained from the study showed that the HL status of the participants was moderate.The correlation between participants’total HL scores and proactive personality scores was 0.417(P-value<0.001).In addition,HL showed statistically significant differences according to education level,place of residence,profession,and average monthly household income.Conclusions:This study showed that patients with higher proactive personality scores had higher HL.The key stakeholders require several positive strategies to improve the HL of patients with permanent colostomy by cultivating their proactive personalities,and these important policies will help to improve patient health and quality of life.
基金supported by the China Postdoctoral Science Foundation(Grant No.2021M703366)Shenzhen Science and Technology Program(Grant No.KQTD20190929172835662).
文摘Objective Observational studies have found associations between inflammatory bowel disease(IBD)and the risk of dementia,including Alzheimer’s dementia(AD)and vascular dementia(VD);however,these findings are inconsistent.It remains unclear whether these associations are causal.Methods We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia.Mendelian randomization(MR)analysis based on summary genome-wide association studies(GWASs)was performed.Genetic correlation and Bayesian colocalization analyses were used to provide robust genetic evidence.Results Ten observational studies involving 80,565,688 participants were included in this metaanalysis.IBD was significantly associated with dementia(risk ratio[RR]=1.36,95%CI=1.04-1.78;I2=84.8%)and VD(RR=2.60,95%CI=1.18-5.70;only one study),but not with AD(RR=2.00,95%CI=0.96-4.13;I^(2)=99.8%).MR analyses did not supported significant causal associations of IBD with dementia(dementia:odds ratio[OR]=1.01,95%CI=0.98-1.03;AD:OR=0.98,95%CI=0.95-1.01;VD:OR=1.02,95%CI=0.97-1.07).In addition,genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia.Conclusion Our study did not provide genetic evidence for a causal association between IBD and dementia risk.The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
文摘Due to their high water content,stimulus responsiveness,and biocompatibility,hydrogels,which are functional materials with a three-dimensional network structure,are widely applied in fields such as biomedicine,environmental monitoring,and flexible electronics.This paper provides a systematic review of hydrogel charac-terization methods and their applications,focusing on primary evaluation techniques for physical properties(e.g.,mechanical strength,swelling behavior,and pore structure),chemical properties(e.g.,composition,crosslink density,and degradation behavior),biocompatibility,and functional properties(e.g.,drug release,environmental stimulus response,and conductivity).It analyzes the challenges currently faced by characterization methods,such as a lack of standardization,difficulties in dynamic monitoring,an insufficient micro-macro correlation,and poor adaptability to complex environments.It proposes solutions,such as a hierarchical standardization system,in situ imaging technology,cross-scale characterization,and biomimetic testing platforms.Looking ahead,hydrogel characterization techniques will evolve toward intelligent,real-time,multimodal coupling and standardized approaches.These techniques will provide superior technical support for precision medicine,environmental restoration,and flexible electronics.They will also offer systematic methodological guidance for the performance optimization and practical application of hydrogel materials.
文摘The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.
文摘Dairy wastewater,a kind of high concentration organic wastewater,is produced in large quantities and difficult to treat,and has a negative impact on the ecological environment.In this study,the source,composition,water quality characteristics of dairy wastewater and its impact on the ecological environment were analyzed,and the treatment methods of dairy wastewater at home and abroad in recent years were summarized,in order to provide a reference for the treatment of dairy wastewater.
基金funded by the Basic Scientific Fund for National Public Research Institutes of China(No.2022 S01)the National Natural Science Foundation of China(Nos.42176191,42049902,and U22A2012)+5 种基金the Shandong Provincial Natural Science Foundation,China(No.ZR2022YQ40)the National Key R&D Program of China(No.2021YFF0501202)the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(No.SML2023 SP232)the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(No.241gqb006)Data acquisition and sample collections were supported by the National Natural Science Foundation of China Open Research Cruise(Cruise No.NORC2021-02+NORC2021301)funded by the Shiptime Sharing Project of the National Natural Science Foundation of China。
文摘Accurate acquisition and prediction of acoustic parameters of seabed sediments are crucial in marine sound propagation research.While the relationship between sound velocity and physical properties of sediment has been extensively studied,there is still no consensus on the correlation between acoustic attenuation coefficient and sediment physical properties.Predicting the acoustic attenuation coefficient remains a challenging issue in sedimentary acoustic research.In this study,we propose a prediction method for the acoustic attenuation coefficient using machine learning algorithms,specifically the random forest(RF),support vector machine(SVR),and convolutional neural network(CNN)algorithms.We utilized the acoustic attenuation coefficient and sediment particle size data from 52 stations as training parameters,with the particle size parameters as the input feature matrix,and measured acoustic attenuation as the training label to validate the attenuation prediction model.Our results indicate that the error of the attenuation prediction model is small.Among the three models,the RF model exhibited the lowest prediction error,with a mean squared error of 0.8232,mean absolute error of 0.6613,and root mean squared error of 0.9073.Additionally,when we applied the models to predict the data collected at different times in the same region,we found that the models developed in this study also demonstrated a certain level of reliability in real prediction scenarios.Our approach demonstrates that constructing a sediment acoustic characteristics model based on machine learning is feasible to a certain extent and offers a novel perspective for studying sediment acoustic properties.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.:81603182 and 81703607)the Fundamental Research Funds for the Central Universities,China(Grant Nos.:DUT21RC(3)057,DUT23YG226,DUT24MS018,and DUT23YG228)+1 种基金the Natural Science Foundation of Liaoning Province,China(Grant No.:2023-MSBA-018)the Open Funding of Cancer Hospital of Dalian University of Technology,China(Grant No.:2024-ZLKF-33).
文摘The focus of green analytical chemistry(GAC)is to minimize the negative impacts of analytical procedures on human safety,human health,and the environment.Several factors,such as the reagents used,sample collection,sample processing,instruments,energy consumed,and the quantities of hazardous materials and waste generated during analytical procedures,need to be considered in the evaluation of the greenness of analytical assays.In this study,we propose a greenness evaluation metric for analytical methods(GEMAM).The new greenness metric is simple,flexible,and comprehensive.The evaluation criteria are based on both the 12 principles of GAC(SIGNIFICANCE)and the 10 factors of sample preparation,and the results are presented on a 0–10 scale.The GEMAM calculation process is easy to perform,and its results are easy to interpret.The output of GEMAM is a pictogram that can provide both qualitative and quantitative information based on color and number.
文摘Erratum to:Research Methods Used for Developing Academic Wordlists:A Systematic Review of Studies Published Between 2000 and 2020,Chinese Journal of Applied Linguistics,Volume 48,Issue 3,2025,pp.425-450,doi:10.1515/CJAL-2025-0210.
基金supported by the Teaching Reform Research Project of Shaanxi University of Science&Technology(23Y083)the Project of National University Association for Mathematical Methods in Physics(JZW-23-SL-02)+3 种基金the Graduate Course Construction Project of Shaanxi University of Science&Technology(KC2024Y03)the 2024 National Higher Education University Physics Reform Research Project(2024PR064)the Teaching Reform Research Project of the International Office of Shaanxi University of Science&Technology(YB202410)Graduate Education and Teaching Reform Research Project of Shaanxi University of Science&Technology(JG2025Y18).
文摘With the development of educational digitalization,how to effectively apply digital animation technology to traditional classroom teaching has become an urgent problem to be solved.This study explores the application of Manim in the course of Mathematical Methods for Physics.Taking the visualization of Fourier series,complex numbers,and other content as examples,it improves students’understanding of complex and abstract mathematical physics concepts through dynamic and visual teaching methods.The teaching effect shows that Manim helps to enhance students’learning experience,improve teaching efficiency and effectiveness,and has a positive impact on students’active learning ability.The research in this paper can provide references and inspiration for the educational digitalization of higher education.
