High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with com...High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality (CMAQ) model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model (GPV-MSM) data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.展开更多
In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HH...In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HHTME), which combines the testabi- lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
Snow cover over the Tibetan Plateau(TP)(TPSC)has garnered significant attention as a crucial indicator of climate change,along with its variations and related climate processes.However,due to the complex terrain of th...Snow cover over the Tibetan Plateau(TP)(TPSC)has garnered significant attention as a crucial indicator of climate change,along with its variations and related climate processes.However,due to the complex terrain of the TP,most numerical models exhibit notable uncertainty in simulating snow conditions in this area.This study evaluates historical snow simulations and related climate anomalies over the TP in numerical models from phase 6 of the Coupled Model Intercomparison Project(CMIP6).The CMIP6 model simulations are compared with two observation-based products across different seasons and temporal scales,and the results indicate that the CMIP6 multimodel ensemble(MME)mean reasonably captures the spatial distribution of the annual and seasonal climatological mean TP snow,albeit with weaker magnitudes compared to observations.The CMIP6 MME performs better over the western TP than the eastern regions,showing a higher reproducibility of the long-term warming trends and declining snow cover trends,partly due to the atmospheric circulation anomalies related to global warming.Additionally,some CMIP6 models successfully capture the interannual variability of TPSC and its relationship with associated climate factors.Our work emphasizes the importance of CMIP6 model selection and pays attention to data reliability in interpreting CMIP6 model results across different TP regions when studying snow cover variations and climate effects using numerical models.展开更多
This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3...This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.展开更多
With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based i...With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.展开更多
In the concurrent extraction of coal and gas,the quantitative assessment of evolving characteristics in mining-induced fracture networks and mining-enhanced permeability within coal seams serves as the cornerstone for...In the concurrent extraction of coal and gas,the quantitative assessment of evolving characteristics in mining-induced fracture networks and mining-enhanced permeability within coal seams serves as the cornerstone for effective gas extraction.However,representing mining-induced fracture networks from a three-dimensional(3D)sight and developing a comprehensive model to evaluate the anisotropic mining-enhanced permeability characteristics still pose significant challenges.In this investigation,a field experiment was undertaken to systematically monitor the evolution of borehole fractures in the coal mass ahead of the mining face at the Pingdingshan Coal Mining Group in China.Using the testing data of borehole fracture,the mining-induced fracture network at varying distances from the mining face was reconstructed through a statistical reconstruction method.Additionally,utilizing fractal theory,a model for the permeability enhancement rate(PER)induced by mining was established.This model was employed to quantitatively depict the anisotropic evolution patterns of PER as the mining face advanced.The research conclusions are as follows:(1)The progression of the mining-induced fracture network can be classified into the stage of rapid growth,the stage of stable growth,and the stage of weak impact;(2)The PER of mining-induced fracture network exhibited a typical progression that can be characterized with slow growth,rapid growth and significant decline;(3)The anisotropic mining-enhanced permeability of the reconstructed mining-induced fracture networks were significant.The peak PER in the vertical direction of the coal seam is 6.86 times and 4446.38 times greater than the direction perpendicular to the vertical thickness and the direction parallel to the advancement of the mining face,respectively.This investigatione provides a viable approach and methodology for quantitatively assessing the anisotropic PER of fracture networks induced during mining,in the concurrent exploitation of coal and gas.展开更多
Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in t...Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in the otolaryngology department of our hospital from June 2022 to October 2024 were included in the study and equally divided into two groups using a convenient sampling method.30 nurses who chose traditional Chinese medicine skill teaching management were included in the control group,and 30 nurses who chose the new empowerment teaching method based on Kirkpatrick’s evaluation model were included in the observation group.Relevant indicators such as clinical teaching environment perception,theoretical knowledge scores of Chinese medicine nursing,and excellent rate of practical operation assessment were compared.Results:The nurses in the observation group had higher scores for clinical teaching environment perception than the control group(P<0.05).However,the midterm and final exam scores for theoretical knowledge of Chinese medicine nursing were higher in the observation group than in the control group(P<0.05).Compared with the control group,the observation group had a higher excellent rate of practical operation assessment(93.33%>73.33%)and a higher Chinese medicine nursing ability score[(215.69±19.73)points>(184.87±15.66)points](P<0.05).Conclusion:Applying the new empowerment teaching method based on Kirkpatrick’s evaluation model to Chinese medicine nursing teaching in otolaryngology can help nurses understand the theoretical knowledge of Chinese medicine nursing and optimize the clinical teaching environment,thereby promoting their practical skills and Chinese medicine nursing abilities.展开更多
Through the investigation of the species of street trees located along the main urban roads in Hefei City,a total of 22 species were selected,belonging to 16 families and 22 genera,with the Sapindaceae family being th...Through the investigation of the species of street trees located along the main urban roads in Hefei City,a total of 22 species were selected,belonging to 16 families and 22 genera,with the Sapindaceae family being the most prevalent.In this study,the Analytic Hierarchy Process(AHP)was employed to assess the comprehensive value of 22 species of street trees applied along the main urban roads in Hefei City.Fourteen evaluation criteria were selected from four categories:morphological indices,functional indices,resistance indices,and management indices,to develop a comprehensive evaluation model.Based on a composite score derived from 22 street trees,these trees were classified into three distinct grades.Grade I(L≥3.0)exhibited a high comprehensive application value in Hefei City and included 6 tree species,such asPlatanus.Grade II(2.5≤L<3.0)also demonstrated a high comprehensive application value,comprising 15 tree species,includingCatalpabungei.In contrast,grade III(L<2.5)indicated a general comprehensive application value,represented by a single species,Cedrusdeodara.The evaluation results can offer theoretical insights for the selection of urban street trees.展开更多
With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,...With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,in the current standardized training for some nurses,there are problems such as the simplification of nursing skill evaluation models and insufficient post competence of nurses.Therefore,optimizing the training model for nursing talents has become an inevitable measure.The problem-based learning(PBL)method and the Direct Observation of Procedural Skills(DOPS)evaluation model provide new directions and guidance for the development of training.Against this background,this paper explores effective approaches for standardized nurse training,starting from basic concepts and gradually delving into specific practical paths,aiming to improve the quality of talent cultivation and provide valuable references for other researchers.展开更多
This paper proposes a multivariate data fusion based quality evaluation model for software talent cultivation.The model constructs a comprehensive ability and quality evaluation index system for college students from ...This paper proposes a multivariate data fusion based quality evaluation model for software talent cultivation.The model constructs a comprehensive ability and quality evaluation index system for college students from a perspective of engineering course,especially of software engineering.As for evaluation method,relying on the behavioral data of students during their school years,we aim to construct the evaluation model as objective as possible,effectively weakening the negative impact of personal subjective assumptions on the evaluation results.展开更多
To improve China's residential environment evaluation system and enhance its guiding role, current research results are analyzed and summarized from three aspects including research scales, evaluation methods and app...To improve China's residential environment evaluation system and enhance its guiding role, current research results are analyzed and summarized from three aspects including research scales, evaluation methods and applied technology by means of comparison, induction and empirical application. The guiding role of the current macro-scale evaluation system of urban planning and construction is generally not obvious, whereas the guiding role of medium and micro-scale systems to the improvement of residential environments is improving. There are diversified methods for determining the threshold values and the weights of indices in China's evaluation system. For instance, the analytic hierarchy process(AHP) method is adopted to determine the weights of indices. The advantages and disadvantages of the method are analyzed on the basis of empirical calculation. In the course of comprehensive analyses, a nonlinear model can reflect interactions among indices more than a linear model; the evaluation model under the ARCGIS platform prevails since it combines space and attribute, and it has intuitive results. So far, the methodological system of China's residential environment evaluation has not been established; its subject coverage and research category should be expanded, and its guiding role should be enhanced.展开更多
[Objective] The aim was to study on RBF model about evaluation on carrying capacity of water resources based on standardized indices. [Method] The indices were transformed and the averages of standard values in differ...[Objective] The aim was to study on RBF model about evaluation on carrying capacity of water resources based on standardized indices. [Method] The indices were transformed and the averages of standard values in different levels were taken as the standardized values of components of central vectors for basic functions of RBF hidden nodes. Hence, the basic functions are suitable for most indices, simplifying expression and calculation of basic functions. [Result] RBF models concluded through Monkey-king Genetic Algorithm with weights optimization are used in evaluation on water carrying capacity in three districts in Changwu County in Shaanxi Province, which were in consistent with that through fuzzy evaluation. [Conclusion] RBF, simple and practical, is universal and popular.展开更多
In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evalu...In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evaluation index. As a result, 81 indices and the hierarchical structures of the index such as the object layer, the sub-object layer, the criterion layer and the index layer are determined. Then, based on the fuzzy characteristics of each index layer, the analytical hierarchy process(AHP)and the fuzzy comprehensive evaluation are applied to generate the weight and the satisfaction of the index and the criterion layers. When analyzing the relationship between the sub-object layer and the object layer, it is easy to find that the number of sub-objects is too large and sub-objects are significantly redundant. The partial least square (PLS) is proposed to solve the problems. Finally, an application example, whose result has already been accepted and employed as the indication of a new project in improving incident management, is introduced and the result verifies the feasibility and efficiency of the model.展开更多
A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded ...A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.展开更多
This paper presents a risk evaluation model of water and mud inrush for tunnel excavation in karst areas.The factors affecting the probabilities of water and mud inrush in karst tunnels are investigated to define the ...This paper presents a risk evaluation model of water and mud inrush for tunnel excavation in karst areas.The factors affecting the probabilities of water and mud inrush in karst tunnels are investigated to define the dangerousness of this geological disaster.The losses that are caused by water and mud inrush are taken into consideration to account for its harmfulness.Then a risk evaluation model based on the dangerousness-harmfulness evaluation indicator system is constructed,which is more convincing in comparison with the traditional methods.The catastrophe theory is used to evaluate the risk level of water and mud inrush and it has great advantage in handling problems involving discontinuous catastrophe processes.To validate the proposed approach,the Qiyueshan tunnel of Yichang-Wanzhou Railway is taken as an example in which four target segments are evaluated using the risk evaluation model.Finally,the evaluation results are compared with the excavation data,which shows that the risk levels predicted by the proposed approach are in good agreements with that observed in engineering.In conclusion,the catastrophe theory-based risk evaluation model is an efficient and effective approach for water and mud inrush in karst tunnels.展开更多
In this research, the residential environment index system and evaluation model were established by means of subjective and objective methods. The methodology for establishing the evaluation system for residential env...In this research, the residential environment index system and evaluation model were established by means of subjective and objective methods. The methodology for establishing the evaluation system for residential environment was first analyzed; then the subjective evaluation data-base was established by questionnaire survey; and at the same time, the objective evaluation data-base was constructed by Geographic Information System (GIS); and then the related equation system between subjective and objective system was developed by multiple regression analysis. This research could benefit evaluation of the residential environment quality for various purposes, and also provide important rudimentary data-base for the development and improvement of residential environment for officials. Furthermore, the index system and evaluation model established in this research could construct a strong relation between subjective evaluation and objective data; and thus could provide a comprehensive, efficient and effective methodology for the evaluation of residential environment.展开更多
This paper establishes an evaluation model of the customer satisfaction index for the wellhead blowout preventers of China's petroleum industry based on evaluation models of the customer satisfaction index at home an...This paper establishes an evaluation model of the customer satisfaction index for the wellhead blowout preventers of China's petroleum industry based on evaluation models of the customer satisfaction index at home and aboard, and by considering the consuming situation in China and the features of the China's petroleum industry. For the existence of: (1) multiple correlations among the factors in the model; (2) the variables need to be explained, but that are hard to observe; (3) the customer satisfaction degree of observation variables appears the shape of skewness or two or three peaks, the correlations between the satisfaction index and its factors cannot be described by common multiple regression. This paper uses a partial least squares (PLS) method based on principal components and typical correlative analysis to solve the problem. When PLS is used in the model of the customer satisfaction index of the wellhead blowout preventers, the latent variables and the explanation degree coefficient of the manifest variable to the corresponding latent variables are estimated by PLS path analysis, and the influencing coefficient among the latent variables in the model is estimated by PLS regression analysis. PLS is also be used to calculate and analyze the model and disclose the correlations among the structural variables as well as the correlation between structural variables and its corresponding observation variables, evaluating results of which provide useful information for petroleum industry to improve the product quality and to the enhancement of the customer satisfaction to the product.展开更多
BACKGROUND Gestational diabetes mellitus(GDM)is a condition characterized by high blood sugar levels during pregnancy.The prevalence of GDM is on the rise globally,and this trend is particularly evident in China,which...BACKGROUND Gestational diabetes mellitus(GDM)is a condition characterized by high blood sugar levels during pregnancy.The prevalence of GDM is on the rise globally,and this trend is particularly evident in China,which has emerged as a significant issue impacting the well-being of expectant mothers and their fetuses.Identifying and addressing GDM in a timely manner is crucial for maintaining the health of both expectant mothers and their developing fetuses.Therefore,this study aims to establish a risk prediction model for GDM and explore the effects of serum ferritin,blood glucose,and body mass index(BMI)on the occurrence of GDM.AIM To develop a risk prediction model to analyze factors leading to GDM,and evaluate its efficiency for early prevention.METHODS The clinical data of 406 pregnant women who underwent routine prenatal examination in Fujian Maternity and Child Health Hospital from April 2020 to December 2022 were retrospectively analyzed.According to whether GDM occurred,they were divided into two groups to analyze the related factors affecting GDM.Then,according to the weight of the relevant risk factors,the training set and the verification set were divided at a ratio of 7:3.Subsequently,a risk prediction model was established using logistic regression and random forest models,and the model was evaluated and verified.RESULTS Pre-pregnancy BMI,previous history of GDM or macrosomia,hypertension,hemoglobin(Hb)level,triglyceride level,family history of diabetes,serum ferritin,and fasting blood glucose levels during early pregnancy were determined.These factors were found to have a significant impact on the development of GDM(P<0.05).According to the nomogram model’s prediction of GDM in pregnancy,the area under the curve(AUC)was determined to be 0.883[95%confidence interval(CI):0.846-0.921],and the sensitivity and specificity were 74.1%and 87.6%,respectively.The top five variables in the random forest model for predicting the occurrence of GDM were serum ferritin,fasting blood glucose in early pregnancy,pre-pregnancy BMI,Hb level and triglyceride level.The random forest model achieved an AUC of 0.950(95%CI:0.927-0.973),the sensitivity was 84.8%,and the specificity was 91.4%.The Delong test showed that the AUC value of the random forest model was higher than that of the decision tree model(P<0.05).CONCLUSION The random forest model is superior to the nomogram model in predicting the risk of GDM.This method is helpful for early diagnosis and appropriate intervention of GDM.展开更多
In order to take requirements for commercial operations or military missions into better consideration in new flight vehicle design, a tri-hierarchical task classification model of "design for operation" is proposed...In order to take requirements for commercial operations or military missions into better consideration in new flight vehicle design, a tri-hierarchical task classification model of "design for operation" is proposed, which takes basic man-object interaction task, complex collaborative operation and large-scale joint operation into account. The corresponding general architecture of evaluation criteria is also depicted. Then a virtual simulation-based approach to implement the evaluations at three hierarchy levels is mainly analyzed with a detailed example, which validates the feasibility and effectiveness of evaluation architecture. Finally, extending the virtual simulation architecture from design to operation training is discussed.展开更多
文摘High-resolution modeling approach is increasingly being considered as a necessary step for improving the monitoring and predictions of regional air quality. This is especially true for highly urbanized region with complex terrain and land-use. This study uses Community Multiscale Air Quality (CMAQ) model coupled with MM5 mesoscale model for a comprehensive analysis to assess the suitability of such high-resolution modeling system in predicting ozone air quality in the complex terrains of Osaka, Japan. The 1-km and 3-kin grid domains were nested inside a 9-km domain and the domain with 1-km grid covered the Osaka region. High-resolution Grid Point Value-Mesoscale Model (GPV-MSM) data were used after suitable validation. The simulated ozone concentrations were validated and evaluated using statistical metrics using performance criteria set for ozone. Daily maxima of ozone were found better simulated by the 1-krn grid domain than the coarser 9-km and 3-km domains, with the maximum improvement in the mean absolute gross error about 3 ppbv. In addition, 1-km grid results fared better than other grids at most of the observation stations that showed noticeable differences in gross error as well as correlation. These results amply justify the use of the integrated high-resolution MM5-CMAQ modeling system in the highly urbanized region, such as the Osaka region, which has complex terrain and land-use.
基金supported by the National Defense Pre-research Foundation of China(51327030104)
文摘In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method (HHTME), which combines the testabi- lity structure model (TSM) with the testability Bayesian networks model (TBNM), is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model (HHTM) is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.
基金funded by the Natural Science Foundation of China(Grant No.W2412145,42275031)the Natural Science Foundation of Yunnan Province(Grant No.202302AN360006)。
文摘Snow cover over the Tibetan Plateau(TP)(TPSC)has garnered significant attention as a crucial indicator of climate change,along with its variations and related climate processes.However,due to the complex terrain of the TP,most numerical models exhibit notable uncertainty in simulating snow conditions in this area.This study evaluates historical snow simulations and related climate anomalies over the TP in numerical models from phase 6 of the Coupled Model Intercomparison Project(CMIP6).The CMIP6 model simulations are compared with two observation-based products across different seasons and temporal scales,and the results indicate that the CMIP6 multimodel ensemble(MME)mean reasonably captures the spatial distribution of the annual and seasonal climatological mean TP snow,albeit with weaker magnitudes compared to observations.The CMIP6 MME performs better over the western TP than the eastern regions,showing a higher reproducibility of the long-term warming trends and declining snow cover trends,partly due to the atmospheric circulation anomalies related to global warming.Additionally,some CMIP6 models successfully capture the interannual variability of TPSC and its relationship with associated climate factors.Our work emphasizes the importance of CMIP6 model selection and pays attention to data reliability in interpreting CMIP6 model results across different TP regions when studying snow cover variations and climate effects using numerical models.
基金The National Key R&D Program of China under contract No.2021YFC3101503the Science and Technology Innovation Program of Hunan Province under contract No.2022RC3070+1 种基金the National Natural Science Foundation of China under contract Nos 42305176 and 42276205the Hunan Provincial Natural Science Foundation of China under contract No.2023JJ10053.
文摘This study evaluates the 1995-2020 global ocean-sea ice simulation using the unstructured-mesh model for prediction across scales(MPAS)-ocean/sea ice model within energy exascale earth system model(E3SM)version 2.1(E3SMv2-MPAS)at 60 km to 10 km resolution.Multi-source observational data are utilized to validate sea surface temperature/salinity,sea ice,three-dimensional thermal-saline structures,mixed layer depth,ocean heat content,and sea surface height.Key results show the following:(1)E3SMv2-MPAS captures seasonal-to-decadal variability in surface fields and sea ice,but shows systematic biases in sea surface temperature of western boundary currents(inadequate eddy parameterization)and Arctic sea surface salinity(misrepresented freshwater fluxes and mixing processes).(2)The model robustly represents three-dimensional climate variability,yet underestimates mixed layer depth in key regions(Antarctic Circumpolar Current and North Atlantic),revealing deficiencies in extreme mixing.(3)Ocean heat content distributions are well-simulated.(4)Sea surface height spatial patterns and interannual variability are accurately reproduced.This work identifies critical refinements for unstructured-mesh models:mesoscale eddy parameterization,polar ocean-sea ice coupling,and multi-scale energy processes,advancing high-resolution climate model development and laying the groundwork for improved ocean forecasting systems.
文摘With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.
基金supported by the National Natural Science Foundation of China (Grant No.42377143)Sichuan Natural Science Foundation (Grant No.2024NSFSC0097)the Open Fund of State Key Laboratory of Coal Mining and Clean Utilization,China (Grant No.2021-CMCU-KFZD001).
文摘In the concurrent extraction of coal and gas,the quantitative assessment of evolving characteristics in mining-induced fracture networks and mining-enhanced permeability within coal seams serves as the cornerstone for effective gas extraction.However,representing mining-induced fracture networks from a three-dimensional(3D)sight and developing a comprehensive model to evaluate the anisotropic mining-enhanced permeability characteristics still pose significant challenges.In this investigation,a field experiment was undertaken to systematically monitor the evolution of borehole fractures in the coal mass ahead of the mining face at the Pingdingshan Coal Mining Group in China.Using the testing data of borehole fracture,the mining-induced fracture network at varying distances from the mining face was reconstructed through a statistical reconstruction method.Additionally,utilizing fractal theory,a model for the permeability enhancement rate(PER)induced by mining was established.This model was employed to quantitatively depict the anisotropic evolution patterns of PER as the mining face advanced.The research conclusions are as follows:(1)The progression of the mining-induced fracture network can be classified into the stage of rapid growth,the stage of stable growth,and the stage of weak impact;(2)The PER of mining-induced fracture network exhibited a typical progression that can be characterized with slow growth,rapid growth and significant decline;(3)The anisotropic mining-enhanced permeability of the reconstructed mining-induced fracture networks were significant.The peak PER in the vertical direction of the coal seam is 6.86 times and 4446.38 times greater than the direction perpendicular to the vertical thickness and the direction parallel to the advancement of the mining face,respectively.This investigatione provides a viable approach and methodology for quantitatively assessing the anisotropic PER of fracture networks induced during mining,in the concurrent exploitation of coal and gas.
文摘Objective:To explore the application value of a new empowerment teaching method based on Kirkpatrick’s evaluation model in teaching Chinese medicine nursing in otorhinolaryngology.Methods:60 nurses who practiced in the otolaryngology department of our hospital from June 2022 to October 2024 were included in the study and equally divided into two groups using a convenient sampling method.30 nurses who chose traditional Chinese medicine skill teaching management were included in the control group,and 30 nurses who chose the new empowerment teaching method based on Kirkpatrick’s evaluation model were included in the observation group.Relevant indicators such as clinical teaching environment perception,theoretical knowledge scores of Chinese medicine nursing,and excellent rate of practical operation assessment were compared.Results:The nurses in the observation group had higher scores for clinical teaching environment perception than the control group(P<0.05).However,the midterm and final exam scores for theoretical knowledge of Chinese medicine nursing were higher in the observation group than in the control group(P<0.05).Compared with the control group,the observation group had a higher excellent rate of practical operation assessment(93.33%>73.33%)and a higher Chinese medicine nursing ability score[(215.69±19.73)points>(184.87±15.66)points](P<0.05).Conclusion:Applying the new empowerment teaching method based on Kirkpatrick’s evaluation model to Chinese medicine nursing teaching in otolaryngology can help nurses understand the theoretical knowledge of Chinese medicine nursing and optimize the clinical teaching environment,thereby promoting their practical skills and Chinese medicine nursing abilities.
基金Sponsored by Provincial-level Undergraduate Innovation Training Program of Anhui Xinhua University(S202312216043)Natural Science Key Research Program for Colleges and Universities in Anhui Province(2023AH051816)Anhui General Teaching Research Project(2022jyxm665).
文摘Through the investigation of the species of street trees located along the main urban roads in Hefei City,a total of 22 species were selected,belonging to 16 families and 22 genera,with the Sapindaceae family being the most prevalent.In this study,the Analytic Hierarchy Process(AHP)was employed to assess the comprehensive value of 22 species of street trees applied along the main urban roads in Hefei City.Fourteen evaluation criteria were selected from four categories:morphological indices,functional indices,resistance indices,and management indices,to develop a comprehensive evaluation model.Based on a composite score derived from 22 street trees,these trees were classified into three distinct grades.Grade I(L≥3.0)exhibited a high comprehensive application value in Hefei City and included 6 tree species,such asPlatanus.Grade II(2.5≤L<3.0)also demonstrated a high comprehensive application value,comprising 15 tree species,includingCatalpabungei.In contrast,grade III(L<2.5)indicated a general comprehensive application value,represented by a single species,Cedrusdeodara.The evaluation results can offer theoretical insights for the selection of urban street trees.
文摘With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,in the current standardized training for some nurses,there are problems such as the simplification of nursing skill evaluation models and insufficient post competence of nurses.Therefore,optimizing the training model for nursing talents has become an inevitable measure.The problem-based learning(PBL)method and the Direct Observation of Procedural Skills(DOPS)evaluation model provide new directions and guidance for the development of training.Against this background,this paper explores effective approaches for standardized nurse training,starting from basic concepts and gradually delving into specific practical paths,aiming to improve the quality of talent cultivation and provide valuable references for other researchers.
基金supported in part by the Education Reform Key Projects of Heilongjiang Province(Grant No.SJGZ20220011,SJGZ20220012)the Excellent Project of Ministry of Education and China Higher Education Association on Digital Ideological and Political Education in Universities(Grant No.GXSZSZJPXM001)。
文摘This paper proposes a multivariate data fusion based quality evaluation model for software talent cultivation.The model constructs a comprehensive ability and quality evaluation index system for college students from a perspective of engineering course,especially of software engineering.As for evaluation method,relying on the behavioral data of students during their school years,we aim to construct the evaluation model as objective as possible,effectively weakening the negative impact of personal subjective assumptions on the evaluation results.
基金The National Key Technology R&D Program during the 11th Five-Year Plan(No.2006BAJ11B04-2)the Soft Science Project of the Ministry of Construction of China(No.2008-R2-25)
文摘To improve China's residential environment evaluation system and enhance its guiding role, current research results are analyzed and summarized from three aspects including research scales, evaluation methods and applied technology by means of comparison, induction and empirical application. The guiding role of the current macro-scale evaluation system of urban planning and construction is generally not obvious, whereas the guiding role of medium and micro-scale systems to the improvement of residential environments is improving. There are diversified methods for determining the threshold values and the weights of indices in China's evaluation system. For instance, the analytic hierarchy process(AHP) method is adopted to determine the weights of indices. The advantages and disadvantages of the method are analyzed on the basis of empirical calculation. In the course of comprehensive analyses, a nonlinear model can reflect interactions among indices more than a linear model; the evaluation model under the ARCGIS platform prevails since it combines space and attribute, and it has intuitive results. So far, the methodological system of China's residential environment evaluation has not been established; its subject coverage and research category should be expanded, and its guiding role should be enhanced.
基金Supported by National Natural Science Foundation of China (51179110)~~
文摘[Objective] The aim was to study on RBF model about evaluation on carrying capacity of water resources based on standardized indices. [Method] The indices were transformed and the averages of standard values in different levels were taken as the standardized values of components of central vectors for basic functions of RBF hidden nodes. Hence, the basic functions are suitable for most indices, simplifying expression and calculation of basic functions. [Result] RBF models concluded through Monkey-king Genetic Algorithm with weights optimization are used in evaluation on water carrying capacity in three districts in Changwu County in Shaanxi Province, which were in consistent with that through fuzzy evaluation. [Conclusion] RBF, simple and practical, is universal and popular.
文摘In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evaluation index. As a result, 81 indices and the hierarchical structures of the index such as the object layer, the sub-object layer, the criterion layer and the index layer are determined. Then, based on the fuzzy characteristics of each index layer, the analytical hierarchy process(AHP)and the fuzzy comprehensive evaluation are applied to generate the weight and the satisfaction of the index and the criterion layers. When analyzing the relationship between the sub-object layer and the object layer, it is easy to find that the number of sub-objects is too large and sub-objects are significantly redundant. The partial least square (PLS) is proposed to solve the problems. Finally, an application example, whose result has already been accepted and employed as the indication of a new project in improving incident management, is introduced and the result verifies the feasibility and efficiency of the model.
基金Project supported by the China Postdoctoral Science Foundation,the Youth Foundation of Sichuan University(No.432028)and the National High-Tech Research and Development Program of China(863 Program)(No.2002AA2Z4251).
文摘A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.
基金Project(51378510)supported by National Natural Science Foundation of China。
文摘This paper presents a risk evaluation model of water and mud inrush for tunnel excavation in karst areas.The factors affecting the probabilities of water and mud inrush in karst tunnels are investigated to define the dangerousness of this geological disaster.The losses that are caused by water and mud inrush are taken into consideration to account for its harmfulness.Then a risk evaluation model based on the dangerousness-harmfulness evaluation indicator system is constructed,which is more convincing in comparison with the traditional methods.The catastrophe theory is used to evaluate the risk level of water and mud inrush and it has great advantage in handling problems involving discontinuous catastrophe processes.To validate the proposed approach,the Qiyueshan tunnel of Yichang-Wanzhou Railway is taken as an example in which four target segments are evaluated using the risk evaluation model.Finally,the evaluation results are compared with the excavation data,which shows that the risk levels predicted by the proposed approach are in good agreements with that observed in engineering.In conclusion,the catastrophe theory-based risk evaluation model is an efficient and effective approach for water and mud inrush in karst tunnels.
文摘In this research, the residential environment index system and evaluation model were established by means of subjective and objective methods. The methodology for establishing the evaluation system for residential environment was first analyzed; then the subjective evaluation data-base was established by questionnaire survey; and at the same time, the objective evaluation data-base was constructed by Geographic Information System (GIS); and then the related equation system between subjective and objective system was developed by multiple regression analysis. This research could benefit evaluation of the residential environment quality for various purposes, and also provide important rudimentary data-base for the development and improvement of residential environment for officials. Furthermore, the index system and evaluation model established in this research could construct a strong relation between subjective evaluation and objective data; and thus could provide a comprehensive, efficient and effective methodology for the evaluation of residential environment.
文摘This paper establishes an evaluation model of the customer satisfaction index for the wellhead blowout preventers of China's petroleum industry based on evaluation models of the customer satisfaction index at home and aboard, and by considering the consuming situation in China and the features of the China's petroleum industry. For the existence of: (1) multiple correlations among the factors in the model; (2) the variables need to be explained, but that are hard to observe; (3) the customer satisfaction degree of observation variables appears the shape of skewness or two or three peaks, the correlations between the satisfaction index and its factors cannot be described by common multiple regression. This paper uses a partial least squares (PLS) method based on principal components and typical correlative analysis to solve the problem. When PLS is used in the model of the customer satisfaction index of the wellhead blowout preventers, the latent variables and the explanation degree coefficient of the manifest variable to the corresponding latent variables are estimated by PLS path analysis, and the influencing coefficient among the latent variables in the model is estimated by PLS regression analysis. PLS is also be used to calculate and analyze the model and disclose the correlations among the structural variables as well as the correlation between structural variables and its corresponding observation variables, evaluating results of which provide useful information for petroleum industry to improve the product quality and to the enhancement of the customer satisfaction to the product.
文摘BACKGROUND Gestational diabetes mellitus(GDM)is a condition characterized by high blood sugar levels during pregnancy.The prevalence of GDM is on the rise globally,and this trend is particularly evident in China,which has emerged as a significant issue impacting the well-being of expectant mothers and their fetuses.Identifying and addressing GDM in a timely manner is crucial for maintaining the health of both expectant mothers and their developing fetuses.Therefore,this study aims to establish a risk prediction model for GDM and explore the effects of serum ferritin,blood glucose,and body mass index(BMI)on the occurrence of GDM.AIM To develop a risk prediction model to analyze factors leading to GDM,and evaluate its efficiency for early prevention.METHODS The clinical data of 406 pregnant women who underwent routine prenatal examination in Fujian Maternity and Child Health Hospital from April 2020 to December 2022 were retrospectively analyzed.According to whether GDM occurred,they were divided into two groups to analyze the related factors affecting GDM.Then,according to the weight of the relevant risk factors,the training set and the verification set were divided at a ratio of 7:3.Subsequently,a risk prediction model was established using logistic regression and random forest models,and the model was evaluated and verified.RESULTS Pre-pregnancy BMI,previous history of GDM or macrosomia,hypertension,hemoglobin(Hb)level,triglyceride level,family history of diabetes,serum ferritin,and fasting blood glucose levels during early pregnancy were determined.These factors were found to have a significant impact on the development of GDM(P<0.05).According to the nomogram model’s prediction of GDM in pregnancy,the area under the curve(AUC)was determined to be 0.883[95%confidence interval(CI):0.846-0.921],and the sensitivity and specificity were 74.1%and 87.6%,respectively.The top five variables in the random forest model for predicting the occurrence of GDM were serum ferritin,fasting blood glucose in early pregnancy,pre-pregnancy BMI,Hb level and triglyceride level.The random forest model achieved an AUC of 0.950(95%CI:0.927-0.973),the sensitivity was 84.8%,and the specificity was 91.4%.The Delong test showed that the AUC value of the random forest model was higher than that of the decision tree model(P<0.05).CONCLUSION The random forest model is superior to the nomogram model in predicting the risk of GDM.This method is helpful for early diagnosis and appropriate intervention of GDM.
文摘In order to take requirements for commercial operations or military missions into better consideration in new flight vehicle design, a tri-hierarchical task classification model of "design for operation" is proposed, which takes basic man-object interaction task, complex collaborative operation and large-scale joint operation into account. The corresponding general architecture of evaluation criteria is also depicted. Then a virtual simulation-based approach to implement the evaluations at three hierarchy levels is mainly analyzed with a detailed example, which validates the feasibility and effectiveness of evaluation architecture. Finally, extending the virtual simulation architecture from design to operation training is discussed.