As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency...As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.展开更多
Using a recognition model of atmospheric gravity waves(AGWs),we identified 519 AGW events from the OH airglow images observed at the Dandong and Lhasa stations from 2015 to 2017.The 317 AGW events detected at the Dand...Using a recognition model of atmospheric gravity waves(AGWs),we identified 519 AGW events from the OH airglow images observed at the Dandong and Lhasa stations from 2015 to 2017.The 317 AGW events detected at the Dandong station have wavelengths ranging from 30 to 60 km,periods from 14 to 20 min,horizontal speeds from 30 to 60 m/s,and relative intensities from 0.4%to 0.6%,respectively.The parameters of 202 events recorded at the Lhasa station mainly vary within 15-35 km in horizontal wavelength,4-6 min in period,40-100 m/s in horizontal velocity,and 0.1%-0.3%in relative intensity.The occurrence rate peaks in winter and summer at Dandong and the peak in summer are absent at Lhasa because of the lack of convective weather.The seasonal propagation directions of the waves are influenced by both the wind field-filtering effect and the distribution of wave sources.In spring,because of the southeastward background wind field,fewer southeastward events are observed at the Dandong station.The situation at the Lhasa station is similar.In summer,both the Lhasa and Dandong stations are dominated by northeastward AGWs,which can be attributed to the southwestward wind.In autumn,ray-tracing results show that the events at Dandong mainly originate from wind shear,whereas the events at the Lhasa station are triggered by convective weather.The location of the wave sources determines the trend of the propagation directions at the Dandong and Lhasa stations in autumn.In winter,because of the eastward wind,more events are propagating to the southwest at the Dandong station.展开更多
This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learnin...This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.展开更多
With constant deepening of the reform and opening-up,national economic system has changed from planned economy to market economy,and rural survey and statistics remain in a difficult transition period. In this period,...With constant deepening of the reform and opening-up,national economic system has changed from planned economy to market economy,and rural survey and statistics remain in a difficult transition period. In this period,China needs transforming original statistical mode according to market economic system. All levels of government should report and submit a lot and increasing statistical information. Besides,in this period,townships,villages and counties are faced with old and new conflicts. These conflicts perplex implementation of rural statistics and survey and development of rural statistical undertaking,and also cause researches and thinking of reform of rural statistical and survey methods.展开更多
To sustain the management of natural resources, land use and land cover （LULC） should be spatially mapped and temporally monitored using GIS. For large areas, conventional methods are laborious. Alternatively, remot...To sustain the management of natural resources, land use and land cover （LULC） should be spatially mapped and temporally monitored using GIS. For large areas, conventional methods are laborious. Alternatively, remote sensing can be used for LULC mapping and monitoring. Normalized differential vegetation index （NDVI） is the most used vegetation index for crop identification and phenology. For agricultural areas, crop statistics are estimated yearly at regional level following administrative units. However, these statistics are not informing about spatial extent of these crops within administrative units; such information is crucial for crop monitoring. The main objective of this research was to fill the gap, based on statistical methods and GIS, by adding spatial information to crop statistics by analyzing temporal NDVI profiles. The study area covers 1300 km2. Data consist of 147 decadal Spot Vegetation NDVI images. Crop statistics were compiled on seasonal basis and aggregated to different administrative levels. Images were processed using an unsupervised classification method. A series of classification runs corresponding to different numbers of clusters were used. Using stepwise multiple linear regression, cropped areas from agricultural statistics were related to areas of each NDVI profile cluster. Estimated regression coefficients were used to generate maps showing cropped fractions by map units. The optimal number of clusters was 18. Similar profiles were merged leading to eight clusters. The results show that, for example, rice was grown, in autumn, on 50% of the area of map-units represented by NDVI-profile group 4 and 75% of the area of group 7 while it was grown, in spring, on 2, 69 and 25% of areas of NDVI-profile groups 2, 61 and 7, respectively. Regression coefficients were used to generate map of crops. This research illustrates the benefit of integrating statistical methods, GIS, remote sensing and crop statistics to delineate NDVI profile clusters with their corresponding agricultural land cover map units and to link these statistics to geographical locations. These map units can be used as a reference for future monitoring of natural resources, in particular crop growth and development and for forecasting crop production and/or yield and stresses like drought.展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, includ...Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals （As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn） and other items （pH values and organic matter） have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong （广东） Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis （CA） and factor analysis （FA） show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as ＂industrial and traffic pollution sources＂. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.展开更多
In this study,geochemical anomaly separation was carried out with methods based on the distribution model,which includes probability diagram(MPD),fractal(concentration-area technique),and U-statistic methods.The main ...In this study,geochemical anomaly separation was carried out with methods based on the distribution model,which includes probability diagram(MPD),fractal(concentration-area technique),and U-statistic methods.The main objective is to evaluate the efficiency and accuracy of the methods in separation of anomalies on the shear zone gold mineralization.For this purpose,samples were taken from the secondary lithogeochemical environment(stream sediment samples)on the gold mineralization in Saqqez,NW of Iran.Interpretation of the histograms and diagrams showed that the MPD is capable of identifying two phases of mineralization.The fractal method could separate only one phase of change based on the fractal dimension with high concentration areas of the Au element.The spatial analysis showed two mixed subpopulations after U=0 and another subpopulation with very high U values.The MPD analysis followed spatial analysis,which shows the detail of the variations.Six mineralized zones detected from local geochemical exploration results were used for validating the methods mentioned above.The MPD method was able to identify the anomalous areas higher than 90%,whereas the two other methods identified 60%(maximum)of the anomalous areas.The raw data without any estimation for the concentration was used by the MPD method using aminimum of calculations to determine the threshold values.Therefore,the MPD method is more robust than the other methods.The spatial analysis identified the detail soft hegeological and mineralization events that were affected in the study area.MPD is recommended as the best,and the spatial U-analysis is the next reliable method to be used.The fractal method could show more detail of the events and variations in the area with asymmetrical grid net and a higher density of sampling or at the detailed exploration stage.展开更多
Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of...Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of death and damage to property. To better understand the landslide condition in the Nepal Himalaya, we carried out an investigation on the landslide distribution and susceptibility using the landslide inventory data and 12 different contributing factors in the Dailekh district, Western Nepal. Based on the evaluation of the frequency distribution of the landslide, the relationship between the landslide and the various contributing factors was determined.Then, the landslide susceptibility was calculated using logistic regression and statistical index methods along with different topographic(slope, aspect, relative relief, plan curvature, altitude, topographic wetness index) and non-topographic factors(distance from river, normalized difference vegetation index(NDVI), distance from road, precipitation, land use and land cover, and geology), and 470(70%) of total 658 landslides. The receiver operating characteristic(ROC) curve analysis using 198(30%) of total landslides showed that the prediction curve rates(area under the curve, AUC) values for two methods(logistic regression and statistical index) were 0.826, and 0.823with success rates of 0.793, and 0.811, respectively. The values of R-Index for the logistic regression and statistical index methods were83.66 and 88.54, respectively, consisting of high susceptible hazard classes. In general, this research concluded that the cohesive and coherent natural interplay of topographic and non-topographic factors strongly affects landslide occurrence, distribution, and susceptibility condition in the Nepal Himalaya region. Furthermore, the reliability of these two methods is verified for landslide susceptibility mapping in Nepal’s central mountain region.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
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 atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absenc...In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.展开更多
The research of carbon content along the casting direction of 82B cord steel billets is of great significance for improvingthe quality of cord products from subsequent processing.However,the traditional segregation an...The research of carbon content along the casting direction of 82B cord steel billets is of great significance for improvingthe quality of cord products from subsequent processing.However,the traditional segregation and billets quality evaluationmethods have certain limitations,such as sampling length and analysis area.which affect the accuracy of quality judgment.Thus.the statistics of extreme values(SEV)was introduced to predict the maximum value of carbon element contentalong the casting direction,which can quantitatively characterize the segregation degree.The size of the selected billet is150 mm×150 mm,and the sampling location is the centerline of the billet.The experiment was conducted by consideringthe effect of cooling intensity and casting speed on the maximum value of carbon element content.Firstly,the calculationresults show that the SEN method can predict the maximum value of carbon element content along the casting directionof 82B cord steel,and the SEV method is proved to be effective by analyzing the carbon distribution and fluctuation in billets.To some extent,the SEV method can break the limitations of the sampling length and analysis area by predicting themaximum value of carbon element on a larger range of continuous casting billets with few samples.During the continuouscasting process the increase in cooling intensity makes the surface shrinking rate increase,which can slow down the flowof solute-enriched liquid to the center,and the center segregation can be reduced.On the other hand,the function area ofthe final electromagnetic stirring can be expanded with the increase in the casting speed,which can reduce the concentration of carbon element in the center of the billets and reduce the maximum value of carbon element content.Ilt can providea new theoretical reference for the quantitative calculation of carbon content in continuous casting billets and the qualityevaluation of continuous casting billcts.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy ...In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy are presented.It is assumed that the controllable information is submitted as the text element images and it contains redundancy,caused by statistical relations and non-uniformity probability distribution of the transmitted data.The use of statistical redundancy allows to develop the adaptive rules of the authenticity control which take into account non-stationarity properties of image data while transferring the information.The structural redundancy peculiar to the container of image in a data transfer package is used for developing new rules to control the information authenticity on the basis of pattern recognition mechanisms.The techniques offered in this work are used to estimate the authenticity in structure of data transfer packages.The results of comparative analysis for developed methods and algorithms show that their parameters of efficiency are increased by criterion of probability of undetected mistakes,labour input and cost of realization.展开更多
Statistical analysis is critical in medical research.The objective of this article is to summarize the appropriate use and reporting of commonly used statistical methods in medical research,on the basis of existing st...Statistical analysis is critical in medical research.The objective of this article is to summarize the appropriate use and reporting of commonly used statistical methods in medical research,on the basis of existing statistical guidelines and the authors’experience in reviewing manuscripts,to provide recommendations for statistical applications and reporting.展开更多
A statistic method, statistics of extreme values （SEV）, was described in detail, which can esti mate the size of maximum inclusion in steel. The characteristic size of the maximum inclusion in a high clean bearing s...A statistic method, statistics of extreme values （SEV）, was described in detail, which can esti mate the size of maximum inclusion in steel. The characteristic size of the maximum inclusion in a high clean bearing steel （GCrl5） was evaluated by this method, and the morphology and corn position of large inclusions found were analyzed by scanning electron microscopy （SEM）. When standard inspection area （S0） is 280 mm2, the characteristic size of the biggest inclusion found in 30 standard inspection area is 23.93 μm, and it has a 99.9% probability of the characteristic size of maximum inclusion predicted being no larger than 36.85μm in the experimental steel. SEM result shows that large inclusions found are mainly composed of CaS, calcium-aluminate and MgO. Compositing widely exists in large inclusions in high clean bearing steel. Compared with traditional evaluation method, SEV method mainly focuses on inclusion size, and the esti- mation result is not affected by inclusion types. SEV method is suitable for the inclusion eval uation of high clean bearing steel.展开更多
In recent years there have been considerable new legislation and efforts by vehicle manufactures aimed at reducing pollutant emission to improve air quality in urban areas. Carbon monoxide is a major pollutant in urba...In recent years there have been considerable new legislation and efforts by vehicle manufactures aimed at reducing pollutant emission to improve air quality in urban areas. Carbon monoxide is a major pollutant in urban areas, and in this study we analyze monthly carbon monoxide (CO) data from Valencia City, a representative Mediterranean city in terms of its structure and climatology. Temporal and spatial trends in pollution were recorded from a monitoring net- work that consisted of five monitoring sites. A multiple linear model, incorporating meteorological parameters, annual cycles, and random error due to serial correlation, was used to estimate the temporal changes in pollution. An analysis performed on the meteorologically adjusted data reveals a significant decreasing trend in CO concentrations and an annual seasonal cycle. The model parameters are estimated by applying the least-squares method. The standard error of the parameters is determined while taking into account the serial correlation in the residuals. The decreasing trend im- plies to a certain extent an improvement in the air quality of the study area. The seasonal cycle shows variations that are mainly associated with traffic and meteorological patterns. Analysis of the stochastic spatial component shows that most of the intersite covariances can be analyzed using an exponential variogram model.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
Traffic flow statistics have become a particularly important part of intelligent transportation.To solve the problems of low real-time robustness and accuracy in traffic flow statistics.In the DeepSort tracking algori...Traffic flow statistics have become a particularly important part of intelligent transportation.To solve the problems of low real-time robustness and accuracy in traffic flow statistics.In the DeepSort tracking algorithm,the Kalman filter(KF),which is only suitable for linear problems,is replaced by the extended Kalman filter(EKF),which can effectively solve nonlinear problems and integrate the Histogram of Oriented Gradient(HOG)of the target.The multi-target tracking framework was constructed with YOLO V5 target detection algorithm.An efficient and longrunning Traffic Flow Statistical framework(TFSF)is established based on the tracking framework.Virtual lines are set up to record the movement direction of vehicles to more accurate and detailed statistics of traffic flow.In order to verify the robustness and accuracy of the traffic flow statistical framework,the traffic flow in different scenes of actual road conditions was collected for verification.The experimental validation shows that the accuracy of the traffic statistics framework reaches more than 93%,and the running speed under the detection data set in this paper is 32.7FPS,which can meet the real-time requirements and has a particular significance for the development of intelligent transportation.展开更多
基金support provided by the National Natural Science Foundation of China(No.22273043).
文摘As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFF0711402)the Specialized Research Fund for State Key Laboratories。
文摘Using a recognition model of atmospheric gravity waves(AGWs),we identified 519 AGW events from the OH airglow images observed at the Dandong and Lhasa stations from 2015 to 2017.The 317 AGW events detected at the Dandong station have wavelengths ranging from 30 to 60 km,periods from 14 to 20 min,horizontal speeds from 30 to 60 m/s,and relative intensities from 0.4%to 0.6%,respectively.The parameters of 202 events recorded at the Lhasa station mainly vary within 15-35 km in horizontal wavelength,4-6 min in period,40-100 m/s in horizontal velocity,and 0.1%-0.3%in relative intensity.The occurrence rate peaks in winter and summer at Dandong and the peak in summer are absent at Lhasa because of the lack of convective weather.The seasonal propagation directions of the waves are influenced by both the wind field-filtering effect and the distribution of wave sources.In spring,because of the southeastward background wind field,fewer southeastward events are observed at the Dandong station.The situation at the Lhasa station is similar.In summer,both the Lhasa and Dandong stations are dominated by northeastward AGWs,which can be attributed to the southwestward wind.In autumn,ray-tracing results show that the events at Dandong mainly originate from wind shear,whereas the events at the Lhasa station are triggered by convective weather.The location of the wave sources determines the trend of the propagation directions at the Dandong and Lhasa stations in autumn.In winter,because of the eastward wind,more events are propagating to the southwest at the Dandong station.
文摘This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.
基金Supported by Project of Business Management Cultivation Discipline in Commerce Department of Rongchang Campus,Southwest University
文摘With constant deepening of the reform and opening-up,national economic system has changed from planned economy to market economy,and rural survey and statistics remain in a difficult transition period. In this period,China needs transforming original statistical mode according to market economic system. All levels of government should report and submit a lot and increasing statistical information. Besides,in this period,townships,villages and counties are faced with old and new conflicts. These conflicts perplex implementation of rural statistics and survey and development of rural statistical undertaking,and also cause researches and thinking of reform of rural statistical and survey methods.
文摘To sustain the management of natural resources, land use and land cover （LULC） should be spatially mapped and temporally monitored using GIS. For large areas, conventional methods are laborious. Alternatively, remote sensing can be used for LULC mapping and monitoring. Normalized differential vegetation index （NDVI） is the most used vegetation index for crop identification and phenology. For agricultural areas, crop statistics are estimated yearly at regional level following administrative units. However, these statistics are not informing about spatial extent of these crops within administrative units; such information is crucial for crop monitoring. The main objective of this research was to fill the gap, based on statistical methods and GIS, by adding spatial information to crop statistics by analyzing temporal NDVI profiles. The study area covers 1300 km2. Data consist of 147 decadal Spot Vegetation NDVI images. Crop statistics were compiled on seasonal basis and aggregated to different administrative levels. Images were processed using an unsupervised classification method. A series of classification runs corresponding to different numbers of clusters were used. Using stepwise multiple linear regression, cropped areas from agricultural statistics were related to areas of each NDVI profile cluster. Estimated regression coefficients were used to generate maps showing cropped fractions by map units. The optimal number of clusters was 18. Similar profiles were merged leading to eight clusters. The results show that, for example, rice was grown, in autumn, on 50% of the area of map-units represented by NDVI-profile group 4 and 75% of the area of group 7 while it was grown, in spring, on 2, 69 and 25% of areas of NDVI-profile groups 2, 61 and 7, respectively. Regression coefficients were used to generate map of crops. This research illustrates the benefit of integrating statistical methods, GIS, remote sensing and crop statistics to delineate NDVI profile clusters with their corresponding agricultural land cover map units and to link these statistics to geographical locations. These map units can be used as a reference for future monitoring of natural resources, in particular crop growth and development and for forecasting crop production and/or yield and stresses like drought.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金supported by the Ministry of Land and Resources of China (No. [2005]011-16)State Environment Protection Administration of China (No. 2001-1-2)+2 种基金State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciencesthe Guangdong Provincial Office of SciencesTechnology via NSF Team Project and Key Project (Nos. 06202438, 2004A3030800)
文摘Dongguan （东莞） City, located in the Pearl River Delta, South China, is famous for its rapid industrialization in the past 30 years. A total of 90 topsoil samples have been collected from agricultural fields, including vegetable and orchard soils in the city, and eight heavy metals （As, Cu, Cd, Cr, Hg, Ni, Pb, and Zn） and other items （pH values and organic matter） have been analyzed, to evaluate the influence of anthropic activities on the environmental quality of agricultural soils and to identify the spatial distribution of trace elements and possible sources of trace elements. The elements Hg, Pb, and Cd have accumulated remarkably here, incomparison with the soil background content of elements in Guangdong （广东） Province. Pollution is more serious in the western plain and the central region, which are heavily distributed with industries and rivers. Multivariate and geostatistical methods have been applied to differentiate the influences of natural processes and human activities on the pollution of heavy metals in topsoils in the study area. The results of cluster analysis （CA） and factor analysis （FA） show that Ni, Cr, Cu, Zn, and As are grouped in factor F1, Pb in F2, and Cd and Hg in F3, respectively. The spatial pattern of the three factors may be well demonstrated by geostatistical analysis. It is shown that the first factor could be considered as a natural source controlled by parent rocks. The second factor could be referred to as ＂industrial and traffic pollution sources＂. The source of the third factor is mainly controlled by long-term anthropic activities, as a consequence of agricultural activities, fossil fuel consumption, and atmospheric deposition.
文摘In this study,geochemical anomaly separation was carried out with methods based on the distribution model,which includes probability diagram(MPD),fractal(concentration-area technique),and U-statistic methods.The main objective is to evaluate the efficiency and accuracy of the methods in separation of anomalies on the shear zone gold mineralization.For this purpose,samples were taken from the secondary lithogeochemical environment(stream sediment samples)on the gold mineralization in Saqqez,NW of Iran.Interpretation of the histograms and diagrams showed that the MPD is capable of identifying two phases of mineralization.The fractal method could separate only one phase of change based on the fractal dimension with high concentration areas of the Au element.The spatial analysis showed two mixed subpopulations after U=0 and another subpopulation with very high U values.The MPD analysis followed spatial analysis,which shows the detail of the variations.Six mineralized zones detected from local geochemical exploration results were used for validating the methods mentioned above.The MPD method was able to identify the anomalous areas higher than 90%,whereas the two other methods identified 60%(maximum)of the anomalous areas.The raw data without any estimation for the concentration was used by the MPD method using aminimum of calculations to determine the threshold values.Therefore,the MPD method is more robust than the other methods.The spatial analysis identified the detail soft hegeological and mineralization events that were affected in the study area.MPD is recommended as the best,and the spatial U-analysis is the next reliable method to be used.The fractal method could show more detail of the events and variations in the area with asymmetrical grid net and a higher density of sampling or at the detailed exploration stage.
基金Under the auspices of the CAS Overseas Institutions Platform Project (No. 131C11KYSB20200033)the National Natural Science Foundation of China (No. 42071349)the Sichuan Science and Technology Program (No. 2020JDJQ0003)。
文摘Landslide distribution and susceptibility mapping are the fundamental steps for landslide-related hazard and disaster risk management activities, especially in the Himalaya region which has resulted in a great deal of death and damage to property. To better understand the landslide condition in the Nepal Himalaya, we carried out an investigation on the landslide distribution and susceptibility using the landslide inventory data and 12 different contributing factors in the Dailekh district, Western Nepal. Based on the evaluation of the frequency distribution of the landslide, the relationship between the landslide and the various contributing factors was determined.Then, the landslide susceptibility was calculated using logistic regression and statistical index methods along with different topographic(slope, aspect, relative relief, plan curvature, altitude, topographic wetness index) and non-topographic factors(distance from river, normalized difference vegetation index(NDVI), distance from road, precipitation, land use and land cover, and geology), and 470(70%) of total 658 landslides. The receiver operating characteristic(ROC) curve analysis using 198(30%) of total landslides showed that the prediction curve rates(area under the curve, AUC) values for two methods(logistic regression and statistical index) were 0.826, and 0.823with success rates of 0.793, and 0.811, respectively. The values of R-Index for the logistic regression and statistical index methods were83.66 and 88.54, respectively, consisting of high susceptible hazard classes. In general, this research concluded that the cohesive and coherent natural interplay of topographic and non-topographic factors strongly affects landslide occurrence, distribution, and susceptibility condition in the Nepal Himalaya region. Furthermore, the reliability of these two methods is verified for landslide susceptibility mapping in Nepal’s central mountain region.
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 atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the paralneters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Pfiysical-space Statistical Analysis System （PSAS） height-wind forecast error covariance model. This method consists of two components： the first component computes the error statistics by using the National Meteorological Center （NMC） method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation （MLE） with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office （GMAO）, NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.
基金The authors are very grateful for support from United Funds between National Natural Science Foundation and Baowu Steel Group Corporation Limited from China(No.U1860101)Chongqing Fundamental Research and Cutting-Edge Technology Funds(No.cstc2017jcyjAX0019).
文摘The research of carbon content along the casting direction of 82B cord steel billets is of great significance for improvingthe quality of cord products from subsequent processing.However,the traditional segregation and billets quality evaluationmethods have certain limitations,such as sampling length and analysis area.which affect the accuracy of quality judgment.Thus.the statistics of extreme values(SEV)was introduced to predict the maximum value of carbon element contentalong the casting direction,which can quantitatively characterize the segregation degree.The size of the selected billet is150 mm×150 mm,and the sampling location is the centerline of the billet.The experiment was conducted by consideringthe effect of cooling intensity and casting speed on the maximum value of carbon element content.Firstly,the calculationresults show that the SEN method can predict the maximum value of carbon element content along the casting directionof 82B cord steel,and the SEV method is proved to be effective by analyzing the carbon distribution and fluctuation in billets.To some extent,the SEV method can break the limitations of the sampling length and analysis area by predicting themaximum value of carbon element on a larger range of continuous casting billets with few samples.During the continuouscasting process the increase in cooling intensity makes the surface shrinking rate increase,which can slow down the flowof solute-enriched liquid to the center,and the center segregation can be reduced.On the other hand,the function area ofthe final electromagnetic stirring can be expanded with the increase in the casting speed,which can reduce the concentration of carbon element in the center of the billets and reduce the maximum value of carbon element content.Ilt can providea new theoretical reference for the quantitative calculation of carbon content in continuous casting billets and the qualityevaluation of continuous casting billcts.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
文摘In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy are presented.It is assumed that the controllable information is submitted as the text element images and it contains redundancy,caused by statistical relations and non-uniformity probability distribution of the transmitted data.The use of statistical redundancy allows to develop the adaptive rules of the authenticity control which take into account non-stationarity properties of image data while transferring the information.The structural redundancy peculiar to the container of image in a data transfer package is used for developing new rules to control the information authenticity on the basis of pattern recognition mechanisms.The techniques offered in this work are used to estimate the authenticity in structure of data transfer packages.The results of comparative analysis for developed methods and algorithms show that their parameters of efficiency are increased by criterion of probability of undetected mistakes,labour input and cost of realization.
文摘Statistical analysis is critical in medical research.The objective of this article is to summarize the appropriate use and reporting of commonly used statistical methods in medical research,on the basis of existing statistical guidelines and the authors’experience in reviewing manuscripts,to provide recommendations for statistical applications and reporting.
基金funded by National Natural Science Foundation of China(51474076)International S&T Cooperation Program(ISTCP)of China(2015DFG51950)
文摘A statistic method, statistics of extreme values （SEV）, was described in detail, which can esti mate the size of maximum inclusion in steel. The characteristic size of the maximum inclusion in a high clean bearing steel （GCrl5） was evaluated by this method, and the morphology and corn position of large inclusions found were analyzed by scanning electron microscopy （SEM）. When standard inspection area （S0） is 280 mm2, the characteristic size of the biggest inclusion found in 30 standard inspection area is 23.93 μm, and it has a 99.9% probability of the characteristic size of maximum inclusion predicted being no larger than 36.85μm in the experimental steel. SEM result shows that large inclusions found are mainly composed of CaS, calcium-aluminate and MgO. Compositing widely exists in large inclusions in high clean bearing steel. Compared with traditional evaluation method, SEV method mainly focuses on inclusion size, and the esti- mation result is not affected by inclusion types. SEV method is suitable for the inclusion eval uation of high clean bearing steel.
文摘In recent years there have been considerable new legislation and efforts by vehicle manufactures aimed at reducing pollutant emission to improve air quality in urban areas. Carbon monoxide is a major pollutant in urban areas, and in this study we analyze monthly carbon monoxide (CO) data from Valencia City, a representative Mediterranean city in terms of its structure and climatology. Temporal and spatial trends in pollution were recorded from a monitoring net- work that consisted of five monitoring sites. A multiple linear model, incorporating meteorological parameters, annual cycles, and random error due to serial correlation, was used to estimate the temporal changes in pollution. An analysis performed on the meteorologically adjusted data reveals a significant decreasing trend in CO concentrations and an annual seasonal cycle. The model parameters are estimated by applying the least-squares method. The standard error of the parameters is determined while taking into account the serial correlation in the residuals. The decreasing trend im- plies to a certain extent an improvement in the air quality of the study area. The seasonal cycle shows variations that are mainly associated with traffic and meteorological patterns. Analysis of the stochastic spatial component shows that most of the intersite covariances can be analyzed using an exponential variogram model.
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.
基金This work is supported by the Qingdao People’s Livelihood Science and Technology Plan(Grant 19-6-1-88-nsh).
文摘Traffic flow statistics have become a particularly important part of intelligent transportation.To solve the problems of low real-time robustness and accuracy in traffic flow statistics.In the DeepSort tracking algorithm,the Kalman filter(KF),which is only suitable for linear problems,is replaced by the extended Kalman filter(EKF),which can effectively solve nonlinear problems and integrate the Histogram of Oriented Gradient(HOG)of the target.The multi-target tracking framework was constructed with YOLO V5 target detection algorithm.An efficient and longrunning Traffic Flow Statistical framework(TFSF)is established based on the tracking framework.Virtual lines are set up to record the movement direction of vehicles to more accurate and detailed statistics of traffic flow.In order to verify the robustness and accuracy of the traffic flow statistical framework,the traffic flow in different scenes of actual road conditions was collected for verification.The experimental validation shows that the accuracy of the traffic statistics framework reaches more than 93%,and the running speed under the detection data set in this paper is 32.7FPS,which can meet the real-time requirements and has a particular significance for the development of intelligent transportation.
