Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing r...Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing renewable-energy consumption and supporting sustainable-energy systems.User participation is central to demand response;however,many users are not inclined to engage actively;therefore,the full potential of demand response remains unrealized.User satisfaction must be prioritized in demand-response assessments.This study proposed a two-stage,capacity-optimization configuration method for user-level energy systems con-sidering thermal inertia and user satisfaction.This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual,total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction.Indoor heating is adjusted,for optimizing device output and load profiles,with a focus on typical,daily,economic,and environmental objectives.The studyfindings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction.This optimization mitigates environmental concerns and enhances clean-energy integration.展开更多
Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many f...Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.展开更多
Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil s...Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.展开更多
Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence...Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups,(i) training dataset and(ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages,distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.展开更多
Actual sea condition testing and inspection and evaluation method research are carried out for tidal energy devices to provide scientific and effective technical support for the ocean high-tech achievement transformat...Actual sea condition testing and inspection and evaluation method research are carried out for tidal energy devices to provide scientific and effective technical support for the ocean high-tech achievement transformation and marine renewable energy development. By analyzing three core indicators, including the power output characteristics of the tidal current device, the generating capacity, energy conversion efficiency, proposed the test contents and evaluation methods of indicators are proposed in this paper; and based on the research of wind farms, power quality testing and assessment methods of offshore tidal energy device are proposed; given the security access to the test contents of tidal current energy device, tidal current energy device running conditions in the testing ground are comprehensively assessed.展开更多
The morphing technology of hypersonic vehicle improved the flight performance by changing aerodynamic characteristics with shape deformations,but the design of guidance and control system with morphing laws remained t...The morphing technology of hypersonic vehicle improved the flight performance by changing aerodynamic characteristics with shape deformations,but the design of guidance and control system with morphing laws remained to be explored.An Integrated of Guidance,Control and Morphing(IGCM)method for Hypersonic Morphing Vehicle(HMV)was developed in this paper.The IGCM method contributed to an effective solution of morphing characteristic to improve flight performance and reject the disturbance for guidance and control system caused by the morphing system for HMV in gliding phase.The IGCM models were established based on the motion models and aerodynamic models of the variable span vehicle.Then the IGCM method was designed by adaptive block dynamic surface back-stepping method with stability proof.The parallel controlled simulations’results showed the effectiveness in accomplishing the flight mission of IGCM method in glide phase with smaller terminal errors.The velocity loss of HMV was reduced by 32.8%which inferred less flight time and larger terminal flight velocity than invariable span vehicle.Under the condition of large deviations of aerodynamic parameters and atmospheric density,the robustness of IGCM method with variable span was verified.展开更多
Objective: The integrated method was investigated to measure Vm/Km of mouse liver glutathione S-transfer-ase (GST) activity on GSH and 7-Cl-4-nitrobenzofurazozan. Methods: Presetting concentration of one substrate twe...Objective: The integrated method was investigated to measure Vm/Km of mouse liver glutathione S-transfer-ase (GST) activity on GSH and 7-Cl-4-nitrobenzofurazozan. Methods: Presetting concentration of one substrate twenty-fold above the other's and taking maximum product absorbance Am as parameter while Km as constant, Vm/Km was obtained by nonlinear fitting of GST reaction curve to the integrated Michaelis-Menten equation In [Am/(Am -Ai)] + Ai/ ( ξ× Km ) = ( Vm/Km )×ti (1). Results: Vm/Km for GST showed slight dependence on initial substrate concentration and data range, but it was resistant to background absorbance, error in reaction origin and small deviation in presetting Km. Vm/Km was proportional to the amount of GST with upper limit higher than that by initial rate. There was close correlation between Vm/Km and initial rate of the same GST. Consistent results were obtained by this integrated method and classical initial rate method for the measurement of mouse liver GST. Conclusion: With the concentration of one substrate twenty-fold above the other's, this integrated method was reliable to measure the activity of enzyme on two substrates , and substrate concentration of the lower one close to its apparent Km was able to be used.展开更多
The integrated energy systems,usually including electric energy,natural gas and thermal energy,play a pivotal role in the energy Internet project,which could improve the accommodation of renewable energy through multi...The integrated energy systems,usually including electric energy,natural gas and thermal energy,play a pivotal role in the energy Internet project,which could improve the accommodation of renewable energy through multienergy complementary ways.Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network,a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper.The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm,and thereby achieved a hierarchical and non-repeated sampling.Then,the improved RelieF algorithm is used to identify the feature vectors,calculate the feature weights,and select the preferred feature subset according to the initially set threshold.In addition,a correlation coefficient method is applied to reduce the feature subset,and further eliminate the redundant feature vectors to obtain the optimal feature subset.Finally,the softmax classifier is used to obtain the early warnings of the integrated energy system.Case studies are conducted on an integrated energy system in the south of China to demonstrate the accuracy of fault risk warning method proposed in this paper.展开更多
In this study,to develop a benefit-allocation model,in-depth analysis of a distributed photovoltaic-powergeneration carport and energy-storage charging-pile project was performed;the model was developed using Shapley ...In this study,to develop a benefit-allocation model,in-depth analysis of a distributed photovoltaic-powergeneration carport and energy-storage charging-pile project was performed;the model was developed using Shapley integrated-empowerment benefit-distribution method.First,through literature survey and expert interview to identify the risk factors at various stages of the project,a dynamic risk-factor indicator system is developed.Second,to obtain a more meaningful risk-calculation result,the subjective and objective weights are combined,the weights of the risk factors at each stage are determined by the expert scoring method and entropy weight method,and the interest distribution model based on multi-dimensional risk factors is established.Finally,an example is used to verify the rationality of the method for the benefit distribution of the charging-pile project.The results of the example indicate that the limitations of the Shapley method can be reasonably avoided,and the applicability of the model for the benefit distribution of the charging-pile project is verified.展开更多
Objective:The objective of this study is to establish a nursing standard of integrated traditional Chinese and Western medicine for patients with COVID‑19(mild and common)in Beijing,to provide reference for clinical n...Objective:The objective of this study is to establish a nursing standard of integrated traditional Chinese and Western medicine for patients with COVID‑19(mild and common)in Beijing,to provide reference for clinical nursing of patients with COVID‑19(mild and common).Methods:Through online communication meeting with nurses who are in the frontline of anti‑epidemic,clinical investigation,literature research,and expert demonstration meeting are carried out to prepare the draft of the standard,and the Delphi method is applied to determine the standard of integrated traditional Chinese and Western medicine care for patients with COVID‑19(mild and common)in Beijing.Results:The nursing standard of integrated traditional Chinese and Western medicine for patients with COVID‑19(mild and common)was established,which included 5 first‑level indicators,14 second-level indicators and 60 third‑level indicators.After two rounds of Delphi method,the positive coefficients of experts were 96%and 83%,the authoritative coefficients of experts were 0.89 and 0.91,and the Kendall’s coefficient of concordance(W)of experts were 0.12,0.09,0.10,0.13(P<0.05)and 0.44,0.43,0.37,0.39(P<0.05).Conclusion:The standard of integrated traditional Chinese and Western medicine nursing for patients with COVID‑19(mild and common)in Beijing constructed by the Delphi method is scientific and practical,which provides a reference for clinical application of integrated traditional Chinese and Western medicine nursing to fight against COVID‑19 infection.展开更多
When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes...When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.展开更多
Nitrogen oxides(NO_(x))and particulate matter(PM)present significant risks to both human health and environmental sustainability.The Integrated Dust Removal and Denitrification Technology(DRDt)offers a more efficient ...Nitrogen oxides(NO_(x))and particulate matter(PM)present significant risks to both human health and environmental sustainability.The Integrated Dust Removal and Denitrification Technology(DRDt)offers a more efficient and cost-effective solution for achieving ultralow industrial flue gas emissions;however,its effectiveness is undermined by low catalyst load rates and poor stability in filter materials.This study addresses these limitations by modifying conventional PTFE filter media(PTFE-Tim)through the incorporation of sodium alginate(SA)and dopamine(DA)as modifiers,resulting in two new filter materials:PTFE-SA-MOF and PTFE-DA-MOF.By optimizing the parameters of an orthogonal experimental design,we identified the ideal preparation conditions for these composite materials.The addition of SA and DA enhanced the bonding between the catalyst(Mn-Cu-MOF)crystal particles and the PTFE fibers through mechanisms such as ion exchange,hydrogen bonding,and adhesion.Consequently,the catalyst loading rate and stability of the DRDt filters were significantly improved.Specifically,the PTFE-SA-MOF and PTFE-DA-MOF filters achieved high catalyst loading rates of 15.97% and 15.86%,these values represent improvements of 2.53 and 2.51 times,while maintaining excellent stability,with mass retention rates of 98.64% and 98.27%,respectively,over the conventional PTFE-Tim filter.展开更多
The main purpose of this paper is to use the Chelyshkov-collocation spectral method for solving nonlinear Quadratic integral equations of Volterra type.The method is based on the approximate solutions in terms of Chel...The main purpose of this paper is to use the Chelyshkov-collocation spectral method for solving nonlinear Quadratic integral equations of Volterra type.The method is based on the approximate solutions in terms of Chelyshkov polynomials with unknown coefficients.The Chelyshkov polynomials and their properties are employed to derive the operational matrices of integral and product.The application of these operational matrices for solving the mentioned problem is explained.The error analysis of the proposed method is investigated.Finally,some numerical examples are provided to demonstrate the efficiency of the method.展开更多
Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the random...Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.展开更多
This study pioneers the integrated fabrication of magnesium corrugated-core sandwich structures using wire-arc directed energy deposition(WA-DED).Two sandwich structures—V-type and X-type—were designed with optimize...This study pioneers the integrated fabrication of magnesium corrugated-core sandwich structures using wire-arc directed energy deposition(WA-DED).Two sandwich structures—V-type and X-type—were designed with optimized deposition paths to achieve comparable grain morphology while enhancing strength.The compression properties and failure modes of the two corrugated-core sandwich structures were examined through quasi-static compression tests.Results showed that the V-type structure exhibited a higher specific compressive strength(93 MPa∙cm^(3)/g)than the X-type structure(72 MPa∙cm^(3)/g).Both finite element analysis and experimental compression tests indicated that failure occurred at the midsection of the corrugated core.This work offers valuable insights for the efficient fabrication of high-strength corrugated-core sandwich structures.展开更多
As for the existing problems of boilers in integrated steelworks, the multi-boiler system could be quantitatively optimized with the decomposition and coordination method. Then, case studies were carried out based on ...As for the existing problems of boilers in integrated steelworks, the multi-boiler system could be quantitatively optimized with the decomposition and coordination method. Then, case studies were carried out based on the data of an integrated steelworks. Two groups of actual production records were contrastively analyzed, and the calculation results from the optimized program of these two groups indicated that for groups 1 and 2, the costs fall by 5.06% and 3.79%and the fuel consumptions decrease by 2.72% and 1.45%, respectively, compared with the actual data. To analyze the cost and fuel consumption change under the same condition of total load demand, assigned fuel consumption and water temperature, five sets of data were selected for further analysis. It was shown that the total cost and fuel consumption of the optimized program could fall by 3.5% and 1.6% respectively, compared with the actual production records. The optimal allocation significantly contributed to energy conservation and cost reduction. The effects of the system energy conservation cannot be realized by single equipment energy conservation. They were complementary to each other, and should be put on the same stage.展开更多
Objective To explore the application and the effect of the case based learning(CBL)method in clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.Methods The...Objective To explore the application and the effect of the case based learning(CBL)method in clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.Methods The CBL method was applied to the experimental group,and the traditional approach for the control group.After the lecture,a questionnaire survey was conducted to evaluate the teaching effect in the two groups.Results The CBL method efficiently increased the students’interest in learning and autonomous learning ability,enhanced their ability to solve clinical problems with basic theoretic knowledge and cultivated their clinical thinking ability.Conclusion The CBL method can improve the quality of clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.展开更多
Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving...Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.展开更多
基金supported by the science and technology foundation of Guizhou province[2022]general 013the science and technology foundation of Guizhou province[2022]general 014+1 种基金the science and technology foundation of Guizhou province GCC[2022]016-1the educational technology foundation of Guizhou province[2022]043.
文摘Integrated-energy systems(IESs)are key to advancing renewable-energy utilization and addressing environmental challenges.Key components of IESs include low-carbon,economic dispatch and demand response,for maximizing renewable-energy consumption and supporting sustainable-energy systems.User participation is central to demand response;however,many users are not inclined to engage actively;therefore,the full potential of demand response remains unrealized.User satisfaction must be prioritized in demand-response assessments.This study proposed a two-stage,capacity-optimization configuration method for user-level energy systems con-sidering thermal inertia and user satisfaction.This method addresses load coordination and complementary issues within the IES and seeks to minimize the annual,total cost for determining equipment capacity configurations while introducing models for system thermal inertia and user satisfaction.Indoor heating is adjusted,for optimizing device output and load profiles,with a focus on typical,daily,economic,and environmental objectives.The studyfindings indicate that the system thermal inertia optimizes energy-system scheduling considering user satisfaction.This optimization mitigates environmental concerns and enhances clean-energy integration.
基金Supported by the Laoshan Laboratory(No.LSKJ202202402)the National Natural Science Foundation of China(No.42030410)+2 种基金the Startup Foundation for Introducing Talent of Nanjing University of Information Science&Technology,and Jiangsu Innovation Research Group(No.JSSCTD 202346)supported by the China National Postdoctoral Program for Innovative Talents(No.BX20240169)the China Postdoctoral Science Foundation(No.2141062400101)。
文摘Deep learning(DL)has become a crucial technique for predicting the El Niño-Southern Oscillation(ENSO)and evaluating its predictability.While various DL-based models have been developed for ENSO predictions,many fail to capture the coherent multivariate evolution within the coupled ocean-atmosphere system of the tropical Pacific.To address this three-dimensional(3D)limitation and represent ENSO-related ocean-atmosphere interactions more accurately,a novel this 3D multivariate prediction model was proposed based on a Transformer architecture,which incorporates a spatiotemporal self-attention mechanism.This model,named 3D-Geoformer,offers several advantages,enabling accurate ENSO predictions up to one and a half years in advance.Furthermore,an integrated gradient method was introduced into the model to identify the sources of predictability for sea surface temperature(SST)variability in the eastern equatorial Pacific.Results reveal that the 3D-Geoformer effectively captures ENSO-related precursors during the evolution of ENSO events,particularly the thermocline feedback processes and ocean temperature anomaly pathways on and off the equator.By extending DL-based ENSO predictions from one-dimensional Niño time series to 3D multivariate fields,the 3D-Geoformer represents a significant advancement in ENSO prediction.This study provides details in the model formulation,analysis procedures,sensitivity experiments,and illustrative examples,offering practical guidance for the application of the model in ENSO research.
基金supported financially by the National Natural Science Foundation of China (91325301, 41571212 and 41137224)the Project of "One-Three-Five" Strategic Planning & Frontier Sciences of the Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1622)the National Key Basic Research Special Foundation of China (2012FY112100)
文摘Environmental covariates are the basis of predictive soil mapping.Their selection determines the performance of soil mapping to a great extent,especially in cases where the number of soil samples is limited but soil spatial heterogeneity is high.In this study,we proposed an integrated method to select environmental covariates for predictive soil depth mapping.First,candidate variables that may influence the development of soil depth were selected based on pedogenetic knowledge.Second,three conventional methods(Pearson correlation analysis(PsCA),generalized additive models(GAMs),and Random Forest(RF))were used to generate optimal combinations of environmental covariates.Finally,three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate.We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China.A total of 129 soil sampling sites were collected using a representative sampling strategy,and RF and support vector machine(SVM)models were used to map soil depth.The results showed that compared to the set of environmental covariates selected by the three conventional selection methods,the set of environmental covariates selected by the proposed method achieved higher mapping accuracy.The combination from the proposed method obtained a root mean square error(RMSE)of 11.88 cm,which was 2.25–7.64 cm lower than the other methods,and an R^2 value of 0.76,which was 0.08–0.26 higher than the other methods.The results suggest that our method can be used as an alternative to the conventional methods for soil depth mapping and may also be effective for mapping other soil properties.
基金supported by the Project of the 12th Five-year National Sci-Tech Support Plan of China(2011BAK12B09)China Special Project of Basic Work of Science and Technology(2011FY110100-2)
文摘Bailongjiang watershed in southern Gansu province, China, is one of the most landslide-prone regions in China, characterized by very high frequency of landslide occurrence. In order to predict the landslide occurrence, a comprehensive map of landslide susceptibility is required which may be significantly helpful in reducing loss of property and human life. In this study, an integrated model of information value method and logistic regression is proposed by using their merits at maximum and overcoming their weaknesses, which may enhance precision and accuracy of landslide susceptibility assessment. A detailed and reliable landslide inventory with 1587 landslides was prepared and randomly divided into two groups,(i) training dataset and(ii) testing dataset. Eight distinct landslide conditioning factors including lithology, slope gradient, aspect, elevation, distance to drainages,distance to faults, distance to roads and vegetation coverage were selected for landslide susceptibility mapping. The produced landslide susceptibility maps were validated by the success rate and prediction rate curves. The validation results show that the success rate and the prediction rate of the integrated model are 81.7 % and 84.6 %, respectively, which indicate that the proposed integrated method is reliable to produce an accurate landslide susceptibility map and the results may be used for landslides management and mitigation.
基金supported by the Implementation Programs for Marine Renewable Energy Special Funds (GHME2012ZC02)
文摘Actual sea condition testing and inspection and evaluation method research are carried out for tidal energy devices to provide scientific and effective technical support for the ocean high-tech achievement transformation and marine renewable energy development. By analyzing three core indicators, including the power output characteristics of the tidal current device, the generating capacity, energy conversion efficiency, proposed the test contents and evaluation methods of indicators are proposed in this paper; and based on the research of wind farms, power quality testing and assessment methods of offshore tidal energy device are proposed; given the security access to the test contents of tidal current energy device, tidal current energy device running conditions in the testing ground are comprehensively assessed.
文摘The morphing technology of hypersonic vehicle improved the flight performance by changing aerodynamic characteristics with shape deformations,but the design of guidance and control system with morphing laws remained to be explored.An Integrated of Guidance,Control and Morphing(IGCM)method for Hypersonic Morphing Vehicle(HMV)was developed in this paper.The IGCM method contributed to an effective solution of morphing characteristic to improve flight performance and reject the disturbance for guidance and control system caused by the morphing system for HMV in gliding phase.The IGCM models were established based on the motion models and aerodynamic models of the variable span vehicle.Then the IGCM method was designed by adaptive block dynamic surface back-stepping method with stability proof.The parallel controlled simulations’results showed the effectiveness in accomplishing the flight mission of IGCM method in glide phase with smaller terminal errors.The velocity loss of HMV was reduced by 32.8%which inferred less flight time and larger terminal flight velocity than invariable span vehicle.Under the condition of large deviations of aerodynamic parameters and atmospheric density,the robustness of IGCM method with variable span was verified.
基金National Natural Science Foundation of China (No.30200266)
文摘Objective: The integrated method was investigated to measure Vm/Km of mouse liver glutathione S-transfer-ase (GST) activity on GSH and 7-Cl-4-nitrobenzofurazozan. Methods: Presetting concentration of one substrate twenty-fold above the other's and taking maximum product absorbance Am as parameter while Km as constant, Vm/Km was obtained by nonlinear fitting of GST reaction curve to the integrated Michaelis-Menten equation In [Am/(Am -Ai)] + Ai/ ( ξ× Km ) = ( Vm/Km )×ti (1). Results: Vm/Km for GST showed slight dependence on initial substrate concentration and data range, but it was resistant to background absorbance, error in reaction origin and small deviation in presetting Km. Vm/Km was proportional to the amount of GST with upper limit higher than that by initial rate. There was close correlation between Vm/Km and initial rate of the same GST. Consistent results were obtained by this integrated method and classical initial rate method for the measurement of mouse liver GST. Conclusion: With the concentration of one substrate twenty-fold above the other's, this integrated method was reliable to measure the activity of enzyme on two substrates , and substrate concentration of the lower one close to its apparent Km was able to be used.
基金Supported by National Natural Science Foundation of China(No.51777193).
文摘The integrated energy systems,usually including electric energy,natural gas and thermal energy,play a pivotal role in the energy Internet project,which could improve the accommodation of renewable energy through multienergy complementary ways.Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network,a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper.The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm,and thereby achieved a hierarchical and non-repeated sampling.Then,the improved RelieF algorithm is used to identify the feature vectors,calculate the feature weights,and select the preferred feature subset according to the initially set threshold.In addition,a correlation coefficient method is applied to reduce the feature subset,and further eliminate the redundant feature vectors to obtain the optimal feature subset.Finally,the softmax classifier is used to obtain the early warnings of the integrated energy system.Case studies are conducted on an integrated energy system in the south of China to demonstrate the accuracy of fault risk warning method proposed in this paper.
基金Supported by Science and Technology Foundation of SGCC Research and development of key models for decision support of energy internet companies(NO.SGSDJY00GPJS1900057).
文摘In this study,to develop a benefit-allocation model,in-depth analysis of a distributed photovoltaic-powergeneration carport and energy-storage charging-pile project was performed;the model was developed using Shapley integrated-empowerment benefit-distribution method.First,through literature survey and expert interview to identify the risk factors at various stages of the project,a dynamic risk-factor indicator system is developed.Second,to obtain a more meaningful risk-calculation result,the subjective and objective weights are combined,the weights of the risk factors at each stage are determined by the expert scoring method and entropy weight method,and the interest distribution model based on multi-dimensional risk factors is established.Finally,an example is used to verify the rationality of the method for the benefit distribution of the charging-pile project.The results of the example indicate that the limitations of the Shapley method can be reasonably avoided,and the applicability of the model for the benefit distribution of the charging-pile project is verified.
文摘Objective:The objective of this study is to establish a nursing standard of integrated traditional Chinese and Western medicine for patients with COVID‑19(mild and common)in Beijing,to provide reference for clinical nursing of patients with COVID‑19(mild and common).Methods:Through online communication meeting with nurses who are in the frontline of anti‑epidemic,clinical investigation,literature research,and expert demonstration meeting are carried out to prepare the draft of the standard,and the Delphi method is applied to determine the standard of integrated traditional Chinese and Western medicine care for patients with COVID‑19(mild and common)in Beijing.Results:The nursing standard of integrated traditional Chinese and Western medicine for patients with COVID‑19(mild and common)was established,which included 5 first‑level indicators,14 second-level indicators and 60 third‑level indicators.After two rounds of Delphi method,the positive coefficients of experts were 96%and 83%,the authoritative coefficients of experts were 0.89 and 0.91,and the Kendall’s coefficient of concordance(W)of experts were 0.12,0.09,0.10,0.13(P<0.05)and 0.44,0.43,0.37,0.39(P<0.05).Conclusion:The standard of integrated traditional Chinese and Western medicine nursing for patients with COVID‑19(mild and common)in Beijing constructed by the Delphi method is scientific and practical,which provides a reference for clinical application of integrated traditional Chinese and Western medicine nursing to fight against COVID‑19 infection.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2024JC-YBMS-026).
文摘When dealing with imbalanced datasets,the traditional support vectormachine(SVM)tends to produce a classification hyperplane that is biased towards the majority class,which exhibits poor robustness.This paper proposes a high-performance classification algorithm specifically designed for imbalanced datasets.The proposed method first uses a biased second-order cone programming support vectormachine(B-SOCP-SVM)to identify the support vectors(SVs)and non-support vectors(NSVs)in the imbalanced data.Then,it applies the synthetic minority over-sampling technique(SV-SMOTE)to oversample the support vectors of the minority class and uses the random under-sampling technique(NSV-RUS)multiple times to undersample the non-support vectors of the majority class.Combining the above-obtained minority class data set withmultiple majority class datasets can obtainmultiple new balanced data sets.Finally,SOCP-SVM is used to classify each data set,and the final result is obtained through the integrated algorithm.Experimental results demonstrate that the proposed method performs excellently on imbalanced datasets.
基金financially supported by Natural Science Foundation of Anhui Provincial Department of Education(2022AH050337)State Key Laboratory of Safety and Health for Metal Mines(2022-JSKSSYS-04)the Project of National Key Research and Development Program(2022YFC3901405).
文摘Nitrogen oxides(NO_(x))and particulate matter(PM)present significant risks to both human health and environmental sustainability.The Integrated Dust Removal and Denitrification Technology(DRDt)offers a more efficient and cost-effective solution for achieving ultralow industrial flue gas emissions;however,its effectiveness is undermined by low catalyst load rates and poor stability in filter materials.This study addresses these limitations by modifying conventional PTFE filter media(PTFE-Tim)through the incorporation of sodium alginate(SA)and dopamine(DA)as modifiers,resulting in two new filter materials:PTFE-SA-MOF and PTFE-DA-MOF.By optimizing the parameters of an orthogonal experimental design,we identified the ideal preparation conditions for these composite materials.The addition of SA and DA enhanced the bonding between the catalyst(Mn-Cu-MOF)crystal particles and the PTFE fibers through mechanisms such as ion exchange,hydrogen bonding,and adhesion.Consequently,the catalyst loading rate and stability of the DRDt filters were significantly improved.Specifically,the PTFE-SA-MOF and PTFE-DA-MOF filters achieved high catalyst loading rates of 15.97% and 15.86%,these values represent improvements of 2.53 and 2.51 times,while maintaining excellent stability,with mass retention rates of 98.64% and 98.27%,respectively,over the conventional PTFE-Tim filter.
文摘The main purpose of this paper is to use the Chelyshkov-collocation spectral method for solving nonlinear Quadratic integral equations of Volterra type.The method is based on the approximate solutions in terms of Chelyshkov polynomials with unknown coefficients.The Chelyshkov polynomials and their properties are employed to derive the operational matrices of integral and product.The application of these operational matrices for solving the mentioned problem is explained.The error analysis of the proposed method is investigated.Finally,some numerical examples are provided to demonstrate the efficiency of the method.
基金supports of the National Natural Science Foundation of China(Nos.12032008,12102080)the Fundamental Research Funds for the Central Universities,China(No.DUT23RC(3)038)are much appreciated。
文摘Fatigue analysis of engine turbine blade is an essential issue.Due to various uncertainties during the manufacture and operation,the fatigue damage and life of turbine blade present randomness.In this study,the randomness of structural parameters,working condition and vibration environment are considered for fatigue life predication and reliability assessment.First,the lowcycle fatigue problem is modelled as stochastic static system with random parameters,while the high-cycle fatigue problem is considered as stochastic dynamic system under random excitations.Then,to deal with the two failure modes,the novel Direct Probability Integral Method(DPIM)is proposed,which is efficient and accurate for solving stochastic static and dynamic systems.The probability density functions of accumulated damage and fatigue life of turbine blade for low-cycle and high-cycle fatigue problems are achieved,respectively.Furthermore,the time–frequency hybrid method is advanced to enhance the computational efficiency for governing equation of system.Finally,the results of typical examples demonstrate high accuracy and efficiency of the proposed method by comparison with Monte Carlo simulation and other methods.It is indicated that the DPIM is a unified method for predication of random fatigue life for low-cycle and highcycle fatigue problems.The rotational speed,density,fatigue strength coefficient,and fatigue plasticity index have a high sensitivity to fatigue reliability of engine turbine blade.
基金supported by JCKY Project(Grant No.JCKY2023602B012).
文摘This study pioneers the integrated fabrication of magnesium corrugated-core sandwich structures using wire-arc directed energy deposition(WA-DED).Two sandwich structures—V-type and X-type—were designed with optimized deposition paths to achieve comparable grain morphology while enhancing strength.The compression properties and failure modes of the two corrugated-core sandwich structures were examined through quasi-static compression tests.Results showed that the V-type structure exhibited a higher specific compressive strength(93 MPa∙cm^(3)/g)than the X-type structure(72 MPa∙cm^(3)/g).Both finite element analysis and experimental compression tests indicated that failure occurred at the midsection of the corrugated core.This work offers valuable insights for the efficient fabrication of high-strength corrugated-core sandwich structures.
基金Item Sponsored by the Fundamental Research Funds for the Central University of China(N140203002)
文摘As for the existing problems of boilers in integrated steelworks, the multi-boiler system could be quantitatively optimized with the decomposition and coordination method. Then, case studies were carried out based on the data of an integrated steelworks. Two groups of actual production records were contrastively analyzed, and the calculation results from the optimized program of these two groups indicated that for groups 1 and 2, the costs fall by 5.06% and 3.79%and the fuel consumptions decrease by 2.72% and 1.45%, respectively, compared with the actual data. To analyze the cost and fuel consumption change under the same condition of total load demand, assigned fuel consumption and water temperature, five sets of data were selected for further analysis. It was shown that the total cost and fuel consumption of the optimized program could fall by 3.5% and 1.6% respectively, compared with the actual production records. The optimal allocation significantly contributed to energy conservation and cost reduction. The effects of the system energy conservation cannot be realized by single equipment energy conservation. They were complementary to each other, and should be put on the same stage.
文摘Objective To explore the application and the effect of the case based learning(CBL)method in clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.Methods The CBL method was applied to the experimental group,and the traditional approach for the control group.After the lecture,a questionnaire survey was conducted to evaluate the teaching effect in the two groups.Results The CBL method efficiently increased the students’interest in learning and autonomous learning ability,enhanced their ability to solve clinical problems with basic theoretic knowledge and cultivated their clinical thinking ability.Conclusion The CBL method can improve the quality of clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.
基金financially supported by the Fundamental Research Funds for the Central Universities Nos.DL12EB01-03the planning subject of "the Twelfth Five-Year-Plan" in National Science and Technology Nos.2012AA102003-2Heilongjiang Natural Science Fund in China Nos.F201116
文摘Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.
