In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion s...In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion source.Through the finite element analysis method,the electrostatic analyses of insulators and grid plates were carried out,the material and structure parameters of insulators were determined.The maximum electric field around each insulator is about 4 kV/mm,and the maximum electric field between grids is about 14 kV/mm,which can meet the 120 keV withstand voltage holding.The insulation system for the positive ion source accelerator with 120 keV is designed,and the connection and basic parameters of insulators and support flanges are analyzed and determined.展开更多
In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses...In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses and strong disturbances and construction conditions such as the application of high prestress.It is essential to study the support components performance under dynamic-static coupling conditions.Based on this,a multi-functional anchorage support dynamic-static coupling performance test system(MAC system)is developed,which can achieve 7 types of testing functions,including single component performance,anchored net performance,anchored rock performance and so on.The bolt and cable mechanical tests are conducted by MAC system under different prestress levels.The results showed that compared to the non-prestress condition,the impact resistance performance of prestressed bolts(cables)is significantly reduced.In the prestress range of 50–160 k N,the maximum reduction rate of impact energy resisted by different types of bolts is 53.9%–61.5%compared to non-prestress condition.In the prestress range of 150–300 k N,the impact energy resisted by high-strength cable is reduced by76.8%–84.6%compared to non-prestress condition.The MAC system achieves dynamic-static coupling performance test,which provide an effective means for the design of anchorage support system.展开更多
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat...This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.展开更多
In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, an...In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.展开更多
Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy b...Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy based on a support vector machine （SVM） with inverse identification was proposed and applied to research simulating coordinated control systems. This method combines SVM inverse control and fuzzy control, taking advantage of the merits of SVM inverse controls which can be designed easily and have high reliability, and those of fuzzy controls, which respond rapidly and have good anti-jamming capability and robustness. It ensures the controller can be controlled with near instantaneous adjustments to maintain a steady state, even if the SVM is not trained well. The simulation results show that the control quality of this fuzzy-SVM compound control algorithm is high, with good performance in dynamic response speed, static stability, restraint of overshoot, and robustness.展开更多
BACKGROUND:Rapid and accurate identification of high-risk patients in the emergency departments(EDs)is crucial for optimizing resource allocation and improving patient outcomes.This study aimed to develop an early pre...BACKGROUND:Rapid and accurate identification of high-risk patients in the emergency departments(EDs)is crucial for optimizing resource allocation and improving patient outcomes.This study aimed to develop an early prediction model for identifying high-risk patients in EDs using initial vital sign measurements.METHODS:This retrospective cohort study analyzed initial vital signs from the Chinese Emergency Triage,Assessment,and Treatment(CETAT)database,which was collected between January 1^(st),2020,and June 25^(th),2023.The primary outcome was the identification of high-risk patients needing immediate treatment.Various machine learning methods,including a deep-learningbased multilayer perceptron(MLP)classifier were evaluated.Model performance was assessed using the area under the receiver operating characteristic curve(AUC-ROC).AUC-ROC values were reported for three scenarios:a default case,a scenario requiring sensitivity greater than 0.8(Scenario I),and a scenario requiring specificity greater than 0.8(Scenario II).SHAP values were calculated to determine the importance of each predictor within the MLP model.RESULTS:A total of 38,797 patients were analyzed,of whom 18.2%were identified as high-risk.Comparative analysis of the predictive models for high-risk patients showed AUC-ROC values ranging from 0.717 to 0.738,with the MLP model outperforming logistic regression(LR),Gaussian Naive Bayes(GNB),and the National Early Warning Score(NEWS).SHAP value analysis identified coma state,peripheral capillary oxygen saturation(SpO_(2)),and systolic blood pressure as the top three predictive factors in the MLP model,with coma state exerting the most contribution.CONCLUSION:Compared with other methods,the MLP model with initial vital signs demonstrated optimal prediction accuracy,highlighting its potential to enhance clinical decision-making in triage in the EDs.展开更多
Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effe...Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.展开更多
A theoretical study of the influence of a quasi-electrostatic support on the amplification level of the slow space charge wave(SCW) in the amplification section of a superheterodyne free electron laser(FEL) was carrie...A theoretical study of the influence of a quasi-electrostatic support on the amplification level of the slow space charge wave(SCW) in the amplification section of a superheterodyne free electron laser(FEL) was carried out. One of the ways to significantly increase the saturation level of the slow SCW is maintaining the conditions of a three-wave parametric resonance between the slow, fast SCWs and the resulting pump electric field. This can be done by introducing the quasielectrostatic support in the superheterodyne FEL amplification section. Also, it was found that the generated pump electric field significantly influences the maintenance of parametric resonance conditions. As a result, this increases the saturation level of the slow SCW by 70%. Finally, the quasi-electrostatic support significantly reduces the maximum value of the electrostatic undulator pump field strength, which is necessary to achieve the maximum saturation level of the slow SCW.展开更多
Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusio...Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusion of a recursive feature elimination(RFE)algorithm and a bidirectional gated recurrent unit(BGRU).Particularly,the RFE algorithm is employed to select features from high-dimensional data to reduce weak correlations between features and remove redundant features in the numerical feature space.Then,a neural network that combines the BGRU and multilayer perceptron(MLP)is adopted to extract deep intrusion behavior features.Finally,a support vector machine(SVM)classifier is used to classify intrusion behaviors.The proposed model is verified by experiments on the NSL-KDD dataset.The results indicate that the proposed model achieves a 90.25%accuracy and a 97.51%detection rate in binary classification and outperforms other machine learning and deep learning models in intrusion classification.The proposed method can provide new insight into network intrusion detection.展开更多
Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a g...Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.展开更多
Selective hydrogenation of furfural to furfuryl alcohol is a great challenge in the hydrogenation field due to thermodynamic preference for hydrogenation of C=C over C=O.Herein,a novel Al_(2)O_(3)/C-u hybrid catalyst,...Selective hydrogenation of furfural to furfuryl alcohol is a great challenge in the hydrogenation field due to thermodynamic preference for hydrogenation of C=C over C=O.Herein,a novel Al_(2)O_(3)/C-u hybrid catalyst,composed of N-modified dendritic carbon networks supporting Al_(2)O_(3)nanoparticles,was successfully prepared via carbonizing the freeze-dried gel from spontaneous cross-linking of alginate,Al3+and urea.The obtained carbon-supported Al_(2)O_(3)hybrid catalyst has a high ratio (31%) of Al species in pentahedral-coordinated state.The introduction of urea enhances the surface N content,the ratio of pyrrolic N,and specific surface area of catalyst,leading to improved adsorption capacity of C=O and the accessibility of active sites.In the furfural hydrogenation reaction with isopropyl alcohol as hydrogen donor,Al_(2)O_(3)/C-u catalyst achieved a 90%conversion of furfural with 98.0% selectivity to furfuryl alcohol,outperforming that of commercial γ-Al_(2)O_(3).Moreover,Al_(2)O_(3)/C-u demonstrates excellent catalytic stability in the recycling tests attributed to the synergistic effect of abundant weak Lewis acid sites and the anchoring effect of the carbon network on Al_(2)O_(3)nanoparticles.This work provides an innovative and facile strategy for fabrication of carbon-supported Al_(2)O_(3)hybrid catalysts with rich AlVspecies,serving as a high selective hydrogenation catalyst through MPV reaction route.展开更多
目的分析癌症患者决策后悔研究领域的发文现状、研究热点及发展趋势。方法在Web of Science核心合集数据库中检索2003年1月1日—2023年7月31日发表的以癌症决策后悔为主题的文献。利用CiteSpace 6.2.R4软件对发文量、发文国家及机构、...目的分析癌症患者决策后悔研究领域的发文现状、研究热点及发展趋势。方法在Web of Science核心合集数据库中检索2003年1月1日—2023年7月31日发表的以癌症决策后悔为主题的文献。利用CiteSpace 6.2.R4软件对发文量、发文国家及机构、关键词、突现词等进行可视化分析。结果共纳入516篇文献,年发文量总体呈上升趋势;发文量最多的国家与机构为美国和哈佛大学,影响力较强的研究主要集中在美国、澳大利亚、英国等发达国家;研究人群主要为乳腺癌、前列腺癌患者及照顾者;研究热点与前沿主要集中在决策后悔的影响因素、决策辅助工具的开发与验证、共享决策及晚期癌症患者家属的姑息治疗决策方面。结论现有的癌症决策后悔领域研究数量呈上升趋势,未来国内学者应积极关注国际热点前沿,深入探讨不同癌症患者及其照顾者决策后悔水平及影响因素,开发适合我国国情的决策辅助工具,促进我国医护患共同做出高质量的医疗决策,减少决策后悔的发生。展开更多
In this paper, we propose a multidimensional version of recurrent least squares support vector machines （MDRLS- SVM） to solve the problem about the prediction of chaotic system. To acquire better prediction performa...In this paper, we propose a multidimensional version of recurrent least squares support vector machines （MDRLS- SVM） to solve the problem about the prediction of chaotic system. To acquire better prediction performance, the high-dimensional space, which provides more information on the system than the scalar time series, is first reconstructed utilizing Takens＇s embedding theorem. Then the MDRLS-SVM instead of traditional RLS-SVM is used in the high- dimensional space, and the prediction performance can be improved from the point of view of reconstructed embedding phase space. In addition, the MDRLS-SVM algorithm is analysed in the context of noise, and we also find that the MDRLS-SVM has lower sensitivity to noise than the RLS-SVM.展开更多
Extreme ground behaviour in high-stress rock masses such as rockburst prone and squeezing ground conditions are encountered in a range of underground projects both in civil and mining applications.The occurrence of su...Extreme ground behaviour in high-stress rock masses such as rockburst prone and squeezing ground conditions are encountered in a range of underground projects both in civil and mining applications.The occurrence of such ground behaviour types are difficult to predict and special design and construction measures must be taken to control them.Determining the most appropriate support system in such grounds is one of the major challenges for ground control engineers because there are many contributing factors to be considered,such as the rock mass parameters,the stress condition,the type and performance of the support systems,the condition of major geological structures and the size and geometry of the underground excavation.The main characteristics and support requirements of rockburst-prone and squeezing ground conditions are herein critically reviewed and characteristics of support functions are discussed.Different types of energy-absorbing rockbolts and other support elements applicable for ground support in burst-prone and squeezing grounds are introduced.Important differences in the choice and economics of ground support strategies in high-stress ground conditions between civil tunnels and mining excavations are discussed.Ground support benchmarking data and mitigation measures for mines and civil tunnels in burst-prone,squeezing and heavily swelling grounds conditions are briefly presented by some examples in practice.展开更多
Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natur...Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems(DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.展开更多
The submersible pumping unit is a new type of pumping system for lifting formation fluids from onshore oil wells, and the identification of its working condition has an important influence on oil production. In this p...The submersible pumping unit is a new type of pumping system for lifting formation fluids from onshore oil wells, and the identification of its working condition has an important influence on oil production. In this paper we proposed a diagnostic method for identifying the working condition of the submersible pumping system. Based on analyzing the working principle of the pumping unit and the pump structure, different characteristics in loading and unloading processes of the submersible linear motor were obtained at different working conditions. The characteristic quantities were extracted from operation data of the submersible linear motor. A diagnostic model based on the support vector machine （SVM） method was proposed for identifying the working condition of the submersible pumping unit, where the inputs of the SVM classifier were the characteristic quantities. The performance and the misjudgment rate of this method were analyzed and validated by the data acquired from an experimental simulation platform. The model proposed had an excellent performance in failure diagnosis of the submersible pumping system. The SVM classifier had higher diagnostic accuracy than the learning vector quantization （LVQ） classifier.展开更多
The Fischer–Tropsch to olefins（FTO） process is a method for the direct conversion of synthesis gas to lower C–Colefins. Carbon-supported iron carbide nanoparticles are attractive catalysts for this reaction.The ca...The Fischer–Tropsch to olefins（FTO） process is a method for the direct conversion of synthesis gas to lower C–Colefins. Carbon-supported iron carbide nanoparticles are attractive catalysts for this reaction.The catalytic activity can be improved and undesired formation of alkanes can be suppressed by the addition of sodium and sulfur as promoters but the influence of their content and ratio remains poorly understood and the promoted catalysts often suffer from rapid deactivation due to particle growth. A series of carbon black-supported iron catalysts with similar iron content and nominal sodium/sulfur loadings of 1–30/0.5–5 wt% with respect to iron are prepared and characterized under FTO conditions at 1and 10 bar syngas pressure to illuminate the influence of the promoter level on the catalytic properties.Iron particles and promoters undergo significant reorganization during FTO operation under industrially relevant conditions. Low sodium content（1–3 wt%） leads to a delay in iron carbide formation. Sodium contents of 15–30 wt% lead to rapid loss of catalytic activity due to the covering of the iron surface with promoters during particle growth under FTO operation. Higher activity and slower loss of activity are observed at low promoter contents（1–3 wt% sodium and 0.5–1 wt% sulfur） but a minimum amount of alkali is required to effectively suppress methane and C–Cparaffin formation. A reference catalyst support（carbide-derived carbon aerogel） shows that the optimum promoter level depends on iron particle size and support pore structure.展开更多
An experimental study of an active body-weight support（BWS） system for improving treadmill-based locomotion training is performed.The dynamical foundation of the proposed system is developed based on a simplified ca...An experimental study of an active body-weight support（BWS） system for improving treadmill-based locomotion training is performed.The dynamical foundation of the proposed system is developed based on a simplified cable suspended mass-spring-damping system which is used to mimic the vertical gait of a walking human.A specifically designed cable pulley suspended cam-slider system is used to mimic the walking gait of a human in vertical direction.A load cell is installed to connect the slider and the cable which is driven by a winch based on the acceleration feedback.The contact force between the slider and the cam is measured to evaluate the walking load of the system.The experimental results demonstrate that the proposed active BWS system can simultaneously reduce both gravitational and inertial load of the walking body,which implies that the walking body suspended in such a BWS system will dynamically behave as if certain amount of body mass had been removed.展开更多
基金supported by National Natural Science Foundation of China(No.11975261)。
文摘In order to support the physical research on the EAST tokamak,a new positive ion source with designed beam energy of 120 keV was proposed to be developed.Accelerator structure is one of the key components of the ion source.Through the finite element analysis method,the electrostatic analyses of insulators and grid plates were carried out,the material and structure parameters of insulators were determined.The maximum electric field around each insulator is about 4 kV/mm,and the maximum electric field between grids is about 14 kV/mm,which can meet the 120 keV withstand voltage holding.The insulation system for the positive ion source accelerator with 120 keV is designed,and the connection and basic parameters of insulators and support flanges are analyzed and determined.
基金supported by the National Natural Science Foundation of China(Nos.51927807,52074164,42277174,42077267 and 42177130)the Natural Science Foundation of Shandong Province,China(No.ZR2020JQ23)China University of Mining and Technology(Beijing)Top Innovative Talent Cultivation Fund for Doctoral Students(No.BBJ2023048)。
文摘In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses and strong disturbances and construction conditions such as the application of high prestress.It is essential to study the support components performance under dynamic-static coupling conditions.Based on this,a multi-functional anchorage support dynamic-static coupling performance test system(MAC system)is developed,which can achieve 7 types of testing functions,including single component performance,anchored net performance,anchored rock performance and so on.The bolt and cable mechanical tests are conducted by MAC system under different prestress levels.The results showed that compared to the non-prestress condition,the impact resistance performance of prestressed bolts(cables)is significantly reduced.In the prestress range of 50–160 k N,the maximum reduction rate of impact energy resisted by different types of bolts is 53.9%–61.5%compared to non-prestress condition.In the prestress range of 150–300 k N,the impact energy resisted by high-strength cable is reduced by76.8%–84.6%compared to non-prestress condition.The MAC system achieves dynamic-static coupling performance test,which provide an effective means for the design of anchorage support system.
文摘This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.
文摘In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.
文摘Multivariables, strong coupling, nonlinearity, and large delays characterize the boiler-turbine coordinated control systems for ship power equipment. To better deal with these conditions, a compound control strategy based on a support vector machine （SVM） with inverse identification was proposed and applied to research simulating coordinated control systems. This method combines SVM inverse control and fuzzy control, taking advantage of the merits of SVM inverse controls which can be designed easily and have high reliability, and those of fuzzy controls, which respond rapidly and have good anti-jamming capability and robustness. It ensures the controller can be controlled with near instantaneous adjustments to maintain a steady state, even if the SVM is not trained well. The simulation results show that the control quality of this fuzzy-SVM compound control algorithm is high, with good performance in dynamic response speed, static stability, restraint of overshoot, and robustness.
基金Applicable Funding Source University of Science and Technology of China(to YLL)National Natural Science Foundation of China(12126604)(to MPZ)+1 种基金R&D project of Pazhou Lab(Huangpu)(2023K0609)(to MPZ)Anhui Provincial Natural Science(grant number 2208085MH235)(to KJ)。
文摘BACKGROUND:Rapid and accurate identification of high-risk patients in the emergency departments(EDs)is crucial for optimizing resource allocation and improving patient outcomes.This study aimed to develop an early prediction model for identifying high-risk patients in EDs using initial vital sign measurements.METHODS:This retrospective cohort study analyzed initial vital signs from the Chinese Emergency Triage,Assessment,and Treatment(CETAT)database,which was collected between January 1^(st),2020,and June 25^(th),2023.The primary outcome was the identification of high-risk patients needing immediate treatment.Various machine learning methods,including a deep-learningbased multilayer perceptron(MLP)classifier were evaluated.Model performance was assessed using the area under the receiver operating characteristic curve(AUC-ROC).AUC-ROC values were reported for three scenarios:a default case,a scenario requiring sensitivity greater than 0.8(Scenario I),and a scenario requiring specificity greater than 0.8(Scenario II).SHAP values were calculated to determine the importance of each predictor within the MLP model.RESULTS:A total of 38,797 patients were analyzed,of whom 18.2%were identified as high-risk.Comparative analysis of the predictive models for high-risk patients showed AUC-ROC values ranging from 0.717 to 0.738,with the MLP model outperforming logistic regression(LR),Gaussian Naive Bayes(GNB),and the National Early Warning Score(NEWS).SHAP value analysis identified coma state,peripheral capillary oxygen saturation(SpO_(2)),and systolic blood pressure as the top three predictive factors in the MLP model,with coma state exerting the most contribution.CONCLUSION:Compared with other methods,the MLP model with initial vital signs demonstrated optimal prediction accuracy,highlighting its potential to enhance clinical decision-making in triage in the EDs.
基金funded by the National Natural Science Foundation of China (No. 52304133)the National Key R&D Program of China (No. 2022YFC3004605)the Department of Science and Technology of Liaoning Province (No. 2023-BS-083)。
文摘Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.
文摘A theoretical study of the influence of a quasi-electrostatic support on the amplification level of the slow space charge wave(SCW) in the amplification section of a superheterodyne free electron laser(FEL) was carried out. One of the ways to significantly increase the saturation level of the slow SCW is maintaining the conditions of a three-wave parametric resonance between the slow, fast SCWs and the resulting pump electric field. This can be done by introducing the quasielectrostatic support in the superheterodyne FEL amplification section. Also, it was found that the generated pump electric field significantly influences the maintenance of parametric resonance conditions. As a result, this increases the saturation level of the slow SCW by 70%. Finally, the quasi-electrostatic support significantly reduces the maximum value of the electrostatic undulator pump field strength, which is necessary to achieve the maximum saturation level of the slow SCW.
基金supported in part by the National Natural Science Foundation of China(No.62001333)the Scientific Research Project of Education Department of Hubei Province(No.D20221702).
文摘Intrusion detection systems play a vital role in cyberspace security.In this study,a network intrusion detection method based on the feature selection algorithm(FSA)and a deep learning model is developed using a fusion of a recursive feature elimination(RFE)algorithm and a bidirectional gated recurrent unit(BGRU).Particularly,the RFE algorithm is employed to select features from high-dimensional data to reduce weak correlations between features and remove redundant features in the numerical feature space.Then,a neural network that combines the BGRU and multilayer perceptron(MLP)is adopted to extract deep intrusion behavior features.Finally,a support vector machine(SVM)classifier is used to classify intrusion behaviors.The proposed model is verified by experiments on the NSL-KDD dataset.The results indicate that the proposed model achieves a 90.25%accuracy and a 97.51%detection rate in binary classification and outperforms other machine learning and deep learning models in intrusion classification.The proposed method can provide new insight into network intrusion detection.
基金approved by our institutional Research Ethics Committee(HREC Approval Number H13554).
文摘Purpose:This study investigates key factors contributing to research impact and their interactions with the Research Impact Quintuple Helix Model by Arsalan et al.(2024).Design/methodology/approach:Using data from a global survey of 630 scientists across diverse disciplines,genders,regions,and experience levels,Structural Equation Modelling(SEM)was employed to assess the influence of 29 factors related to researcher characteristics,research attributes,publication strategies,institutional support,and national roles.Findings:The study validated the Quintuple Helix Model,uncovering complex interdependencies.Institutional support significantly affects research impact by covering leadership,resources,recognition,and funding.Researcher attributes,including academic experience and domain knowledge,also play a crucial role.National socioeconomic conditions indirectly influence research impact by supporting institutions,underscoring the importance of conducive national frameworks.Research limitations:While the study offers valuable insights,it has limitations.Although statistically sufficient,the response rate was below 10%,suggesting that the findings may not fully represent the entire global research community.The reliance on self-reported data may also introduce bias,as perceptions of impact can be subjective.Practical implications:The findings have a significant impact on researchers aiming to enhance their work’s societal,economic,and cultural significance,institutions seeking supportive environments,and policymakers interested in creating favourable national conditions for impactful research.The study advocates for a strategic alignment among national policies,institutional practices,and individual researcher efforts to maximise research impact and effectively address global challenges.Originality/value:By empirically validating the Research Impact Quintuple Helix Model,this study offers a holistic framework for understanding the synergy of factors that drive impactful research.
基金China Postdoctoral Science Foundation (2023M733451)Dalian Innovation Team in Key Areas(2020RT06)Engineering Research Center for Key Aromatic Compounds and LiaoNing Key Laboratory,Liaoning Provincial Natural Science Foundation (Doctoral Research Start-up Fund 2024-BSBA-37)。
文摘Selective hydrogenation of furfural to furfuryl alcohol is a great challenge in the hydrogenation field due to thermodynamic preference for hydrogenation of C=C over C=O.Herein,a novel Al_(2)O_(3)/C-u hybrid catalyst,composed of N-modified dendritic carbon networks supporting Al_(2)O_(3)nanoparticles,was successfully prepared via carbonizing the freeze-dried gel from spontaneous cross-linking of alginate,Al3+and urea.The obtained carbon-supported Al_(2)O_(3)hybrid catalyst has a high ratio (31%) of Al species in pentahedral-coordinated state.The introduction of urea enhances the surface N content,the ratio of pyrrolic N,and specific surface area of catalyst,leading to improved adsorption capacity of C=O and the accessibility of active sites.In the furfural hydrogenation reaction with isopropyl alcohol as hydrogen donor,Al_(2)O_(3)/C-u catalyst achieved a 90%conversion of furfural with 98.0% selectivity to furfuryl alcohol,outperforming that of commercial γ-Al_(2)O_(3).Moreover,Al_(2)O_(3)/C-u demonstrates excellent catalytic stability in the recycling tests attributed to the synergistic effect of abundant weak Lewis acid sites and the anchoring effect of the carbon network on Al_(2)O_(3)nanoparticles.This work provides an innovative and facile strategy for fabrication of carbon-supported Al_(2)O_(3)hybrid catalysts with rich AlVspecies,serving as a high selective hydrogenation catalyst through MPV reaction route.
文摘目的分析癌症患者决策后悔研究领域的发文现状、研究热点及发展趋势。方法在Web of Science核心合集数据库中检索2003年1月1日—2023年7月31日发表的以癌症决策后悔为主题的文献。利用CiteSpace 6.2.R4软件对发文量、发文国家及机构、关键词、突现词等进行可视化分析。结果共纳入516篇文献,年发文量总体呈上升趋势;发文量最多的国家与机构为美国和哈佛大学,影响力较强的研究主要集中在美国、澳大利亚、英国等发达国家;研究人群主要为乳腺癌、前列腺癌患者及照顾者;研究热点与前沿主要集中在决策后悔的影响因素、决策辅助工具的开发与验证、共享决策及晚期癌症患者家属的姑息治疗决策方面。结论现有的癌症决策后悔领域研究数量呈上升趋势,未来国内学者应积极关注国际热点前沿,深入探讨不同癌症患者及其照顾者决策后悔水平及影响因素,开发适合我国国情的决策辅助工具,促进我国医护患共同做出高质量的医疗决策,减少决策后悔的发生。
基金Project supported by the National Natural Science Foundation of China （Grant No 90207012）.
文摘In this paper, we propose a multidimensional version of recurrent least squares support vector machines （MDRLS- SVM） to solve the problem about the prediction of chaotic system. To acquire better prediction performance, the high-dimensional space, which provides more information on the system than the scalar time series, is first reconstructed utilizing Takens＇s embedding theorem. Then the MDRLS-SVM instead of traditional RLS-SVM is used in the high- dimensional space, and the prediction performance can be improved from the point of view of reconstructed embedding phase space. In addition, the MDRLS-SVM algorithm is analysed in the context of noise, and we also find that the MDRLS-SVM has lower sensitivity to noise than the RLS-SVM.
文摘Extreme ground behaviour in high-stress rock masses such as rockburst prone and squeezing ground conditions are encountered in a range of underground projects both in civil and mining applications.The occurrence of such ground behaviour types are difficult to predict and special design and construction measures must be taken to control them.Determining the most appropriate support system in such grounds is one of the major challenges for ground control engineers because there are many contributing factors to be considered,such as the rock mass parameters,the stress condition,the type and performance of the support systems,the condition of major geological structures and the size and geometry of the underground excavation.The main characteristics and support requirements of rockburst-prone and squeezing ground conditions are herein critically reviewed and characteristics of support functions are discussed.Different types of energy-absorbing rockbolts and other support elements applicable for ground support in burst-prone and squeezing grounds are introduced.Important differences in the choice and economics of ground support strategies in high-stress ground conditions between civil tunnels and mining excavations are discussed.Ground support benchmarking data and mitigation measures for mines and civil tunnels in burst-prone,squeezing and heavily swelling grounds conditions are briefly presented by some examples in practice.
基金co-financed by the European Union(European Social Fund-ESF)and Greek national funds through the Operational Program‘‘Education and Lifelong Learning’’of the National Strategic Reference Framework(NSRF)-Research Funding Program:Thales.Investing in knowledge society through the European Social Fund
文摘Forest ecosystems are our priceless natural resource and are a key component of the global carbon budget. Forest fires can be a hazard to the viability and sustainable management of forests with consequences for natural and cultural environments, economies, and the life quality of local and regional populations. Thus, the selection of strategies to manage forest fires, while considering both functional and economic efficiency, is of primary importance. The use of decision support systems(DSSs) by managers of forest fires has rapidly increased. This has strengthened capacity to prevent and suppress forest fires while protecting human lives and property. DSSs are a tool that can benefit incident management and decision making and policy, especially for emergencies such as natural disasters. In this study we reviewed state-of-the-art DSSs that use: database management systems and mathematical/economic algorithms for spatial optimization of firefighting forces; forest fire simulators and satellite technology for immediate detection and prediction of evolution of forest fires; GIS platforms that incorporate several tools to manipulate, process and analyze geographic data and develop strategic and operational plans.
文摘The submersible pumping unit is a new type of pumping system for lifting formation fluids from onshore oil wells, and the identification of its working condition has an important influence on oil production. In this paper we proposed a diagnostic method for identifying the working condition of the submersible pumping system. Based on analyzing the working principle of the pumping unit and the pump structure, different characteristics in loading and unloading processes of the submersible linear motor were obtained at different working conditions. The characteristic quantities were extracted from operation data of the submersible linear motor. A diagnostic model based on the support vector machine （SVM） method was proposed for identifying the working condition of the submersible pumping unit, where the inputs of the SVM classifier were the characteristic quantities. The performance and the misjudgment rate of this method were analyzed and validated by the data acquired from an experimental simulation platform. The model proposed had an excellent performance in failure diagnosis of the submersible pumping system. The SVM classifier had higher diagnostic accuracy than the learning vector quantization （LVQ） classifier.
基金supported by a Post Doc grant of the German Academic Exchange Service(Deutscher Akademischer Austauschdienst,DAAD grant no.91552012)by the European Research Council(EU FP7 ERC advanced grant no.338846)
文摘The Fischer–Tropsch to olefins（FTO） process is a method for the direct conversion of synthesis gas to lower C–Colefins. Carbon-supported iron carbide nanoparticles are attractive catalysts for this reaction.The catalytic activity can be improved and undesired formation of alkanes can be suppressed by the addition of sodium and sulfur as promoters but the influence of their content and ratio remains poorly understood and the promoted catalysts often suffer from rapid deactivation due to particle growth. A series of carbon black-supported iron catalysts with similar iron content and nominal sodium/sulfur loadings of 1–30/0.5–5 wt% with respect to iron are prepared and characterized under FTO conditions at 1and 10 bar syngas pressure to illuminate the influence of the promoter level on the catalytic properties.Iron particles and promoters undergo significant reorganization during FTO operation under industrially relevant conditions. Low sodium content（1–3 wt%） leads to a delay in iron carbide formation. Sodium contents of 15–30 wt% lead to rapid loss of catalytic activity due to the covering of the iron surface with promoters during particle growth under FTO operation. Higher activity and slower loss of activity are observed at low promoter contents（1–3 wt% sodium and 0.5–1 wt% sulfur） but a minimum amount of alkali is required to effectively suppress methane and C–Cparaffin formation. A reference catalyst support（carbide-derived carbon aerogel） shows that the optimum promoter level depends on iron particle size and support pore structure.
文摘An experimental study of an active body-weight support（BWS） system for improving treadmill-based locomotion training is performed.The dynamical foundation of the proposed system is developed based on a simplified cable suspended mass-spring-damping system which is used to mimic the vertical gait of a walking human.A specifically designed cable pulley suspended cam-slider system is used to mimic the walking gait of a human in vertical direction.A load cell is installed to connect the slider and the cable which is driven by a winch based on the acceleration feedback.The contact force between the slider and the cam is measured to evaluate the walking load of the system.The experimental results demonstrate that the proposed active BWS system can simultaneously reduce both gravitational and inertial load of the walking body,which implies that the walking body suspended in such a BWS system will dynamically behave as if certain amount of body mass had been removed.
