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
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
To the editor:Peer workers-people with personal experiences of using mental health services,trained to provide support to others currently using similar services--are increasingly integrated into the workforce of ment...To the editor:Peer workers-people with personal experiences of using mental health services,trained to provide support to others currently using similar services--are increasingly integrated into the workforce of mental health systems internationally.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
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
Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3...Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe oxide.It is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe oxide.Considering the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.展开更多
To obtain accurate forms and surfaces in free surface grinding, it is important to provide grinding conditions suitable for a curved surface. A grinding support system for the free surface （GSX-F） is proposed to hel...To obtain accurate forms and surfaces in free surface grinding, it is important to provide grinding conditions suitable for a curved surface. A grinding support system for the free surface （GSX-F） is proposed to help the operator grind a free surface with the high accuracy and the high productivity. To succeed in free surface grinding, the property of a ball type wheel must be known. Therefore, a basic study of free surface grinding with a ball type wheel is carried out based on the grinding center （GC）. Some working points for achieving sufficient accuracy in free surface grinding are discussed. GSX-F is constructed using the patch division method and is used to test grinding. Reasonable results are obtained.展开更多
The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct ...The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct virtual elements and stress servo control to approximately replace the hydraulic support problem,this paper establishes a new numerical model of hydraulic support with the same working characteristics as the actual hydraulic support by integrating numerical simulation software Rhino,Griddle and FLAC3D,which can realize the simulation of different working conditions.Based on this model,the influence mechanism of the supporting strength of hydraulic support on surrounding rock stress regulation and coal stability in front of the top coal caving face in extra thick coal seam were researched.Firstly,under different support intensity,the abutment pressure of the bearing coal and the coal in front of it presents the “three-stage”evolution characteristics.The influence range of support intensity is 15%–30%.Secondly,1.5 MPa is the upper limit of impact that the support strength can have on the front coal failure area.Thirdly,within a displacement range of 2.76 m from the coal wall,a support strength of1.5 MPa provides optimal control of the horizontal displacement of the coal.展开更多
Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile...Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile organic compounds(VOCs).In this work,we prepared the mesoporous chromia-supported bimetallic Co and Ni single-atom(Co_(1)Ni_(1)/meso-Cr_(2)O_(3))and bimetallic Co and Ni nanoparticle(Co_(NP)Ni_(NP)/mesoCr_(2)O_(3))catalysts adopting the one-pot polyvinyl pyrrolidone(PVP)-and polyvinyl alcohol(PVA)-protecting approaches,respectively.The results indicate that the Co_(1)Ni_(1)/meso-Cr_(2)O_(3)catalyst exhibited the best catalytic activity for n-hexane(C_(6)H_(14))combustion(T_(50%)and T_(90%)were 239 and 263℃ at a space velocity of 40,000 mL g^(-1)h^(-1);apparent activation energy and specific reaction rate at 260℃ were 54.7 kJ mol^(-1)and 4.3×10^(-7)mol g^(-1)_(cat)s^(-1),respectively),which was associated with its higher(Cr^(5+)+Cr^(6+))amount,large n-hexane adsorption capacity,and good lattice oxygen mobility that could enhance the deep oxidation of n-hexane,in which Ni_(1) was beneficial for the enhancements in surface lattice oxygen mobility and low-temperature reducibility,while Co_(1) preferred to generate higher contents of the high-valence states of chromium and surface oxygen species as well as adsorption and activation of n-hexane.n-Hexane combustion takes place via the Mars van Krevelen(MvK)mechanism,and its reaction pathways are as follows:n-hexane→olefins or 3-hexyl hydroperoxide→3-hexanone,2-hexanone or 2,5-dimethyltetrahydrofuran→2-methyloxirane or 2-ethyl-oxetane→acrylic acid→CO_x→CO_(2)and H_(2)O.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
Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for...Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.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
Aqueous-phase reforming(APR)is an attractive process to produce bio-based hydrogen from waste biomass streams,during which the catalyst stability is often challenged due to the harsh reaction conditions.In this work,t...Aqueous-phase reforming(APR)is an attractive process to produce bio-based hydrogen from waste biomass streams,during which the catalyst stability is often challenged due to the harsh reaction conditions.In this work,three Pt-based catalysts supported on C,AlO(OH),and ZrO_(2)were investigated for the APR of hydroxyacetone solution in afixed bed reactor at 225℃and 35 bar.Among them,the Pt/C catalyst showed the highest turnover frequency for H_(2)production(TOF of 8.9 molH_(2)molPt^(-1)min^(-1))and the longest catalyst stability.Over the AlO(OH)and ZrO_(2)supported Pt catalysts,the side reactions consuming H_(2),formation of coke,and Pt sintering result in a low H_(2)production and the fast catalyst deactivation.The proposed reaction pathways suggest that a promising APR catalyst should reform all oxygenates in the aqueous phase,minimize the hydrogenation of the oxygenates,maximize the WGS reaction,and inhibit the condensation and coking reactions for maximizing the hydrogen yield and a stable catalytic performance.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
Metal nanoaggregates can simultaneously enhance the activity and stability of Fe-N-C catalysts in proton-exchange-membrane fuel cells(PEMFC).Previous studies on the relevant mechanism have focused on the direct intera...Metal nanoaggregates can simultaneously enhance the activity and stability of Fe-N-C catalysts in proton-exchange-membrane fuel cells(PEMFC).Previous studies on the relevant mechanism have focused on the direct interaction between FeN_(4)active sites and metal nanoaggregates.However,the role of carbon support that hosts metal nanoaggregates and active sites has been overlooked.Here,a Fe-N-C catalyst encapsulating inactive gold nanoparticles is prepared as a model catalyst to investigate the electronic tuning of Au nanoparticles(NPs)towards the carbon support.Au NPs donate electrons to carbon support,making it rich inπelectrons,which reduces the work function and regulates the electronic configuration of the FeN_(4)sites for an enhanced ORR activity.Meanwhile,the electron-rich carbon support can mitigate the electron depletion of FeN_(4)sites caused by carbon support oxidation,thereby preserving its high activity.The yield and accumulation of H_(2)O_(2)are thus alleviated,which delays the oxidation of the catalyst and benefits the stability.Due to the electron-rich carbon support,the composite catalyst achieves a top-level peak power density of 0.74 W/cm^(2) in a 1.5 bar H_(2)-air PEMFC,as well as the improved stability.This work elucidates the key role of carbon support in the performance enhancement of the FeN-C/metal nanoaggregate composite catalysts for fuel cell application.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funded by National Institute for Health Research(NIHR)(RP-PG-1212-20019)。
文摘To the editor:Peer workers-people with personal experiences of using mental health services,trained to provide support to others currently using similar services--are increasingly integrated into the workforce of mental health systems internationally.
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Research Institute for Smart Energy(CDB2)the grant from the Research Institute for Advanced Manufacturing(CD8Z)+4 种基金the grant from the Carbon Neutrality Funding Scheme(WZ2R)at The Hong Kong Polytechnic Universitysupport from the Hong Kong Polytechnic University(CD9B,CDBZ and WZ4Q)the National Natural Science Foundation of China(22205187)Shenzhen Municipal Science and Technology Innovation Commission(JCYJ20230807140402006)Start-up Foundation for Introducing Talent of NUIST and Natural Science Foundation of Jiangsu Province of China(BK20230426).
文摘Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe oxide.It is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe oxide.Considering the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.
文摘To obtain accurate forms and surfaces in free surface grinding, it is important to provide grinding conditions suitable for a curved surface. A grinding support system for the free surface （GSX-F） is proposed to help the operator grind a free surface with the high accuracy and the high productivity. To succeed in free surface grinding, the property of a ball type wheel must be known. Therefore, a basic study of free surface grinding with a ball type wheel is carried out based on the grinding center （GC）. Some working points for achieving sufficient accuracy in free surface grinding are discussed. GSX-F is constructed using the patch division method and is used to test grinding. Reasonable results are obtained.
基金supported by Distinguished Youth Funds of National Natural Science Foundation of China (No.51925402)National Natural Science Foundation of China (Nos.51904203 and 52174125)+4 种基金the China Postdoctoral Science Foundation (No.2021M702049)the Tencent Foundation or XPLORER PRIZEShanxi Science and Technology Major Project Funds (No.20201102004)Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering (No.2021SX-TD001)Open Fund Research Project Supported by State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology (No.SICGM202209)。
文摘The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct virtual elements and stress servo control to approximately replace the hydraulic support problem,this paper establishes a new numerical model of hydraulic support with the same working characteristics as the actual hydraulic support by integrating numerical simulation software Rhino,Griddle and FLAC3D,which can realize the simulation of different working conditions.Based on this model,the influence mechanism of the supporting strength of hydraulic support on surrounding rock stress regulation and coal stability in front of the top coal caving face in extra thick coal seam were researched.Firstly,under different support intensity,the abutment pressure of the bearing coal and the coal in front of it presents the “three-stage”evolution characteristics.The influence range of support intensity is 15%–30%.Secondly,1.5 MPa is the upper limit of impact that the support strength can have on the front coal failure area.Thirdly,within a displacement range of 2.76 m from the coal wall,a support strength of1.5 MPa provides optimal control of the horizontal displacement of the coal.
基金supported by the National Natural Science Committee of China-Liaoning Provincial People's Government Joint Fund(U1908204)National Natural Science Foundation of China(21876006,21976009,and 21961160743)+2 种基金Foundation on the Creative Research Team Construction Promotion Project of Beijing Municipal Institutions(IDHT20190503)Natural Science Foundation of Beijing Municipal Commission of Education(KM201710005004)Development Program for the Youth Outstanding-Notch Talent of Beijing Municipal Commission of Education(CIT&TCD201904019)。
文摘Developing the alternative supported noble metal catalysts with low cost,high catalytic efficiency,and good resistance toward carbon dioxide and water vapor is critically demanded for the oxidative removal of volatile organic compounds(VOCs).In this work,we prepared the mesoporous chromia-supported bimetallic Co and Ni single-atom(Co_(1)Ni_(1)/meso-Cr_(2)O_(3))and bimetallic Co and Ni nanoparticle(Co_(NP)Ni_(NP)/mesoCr_(2)O_(3))catalysts adopting the one-pot polyvinyl pyrrolidone(PVP)-and polyvinyl alcohol(PVA)-protecting approaches,respectively.The results indicate that the Co_(1)Ni_(1)/meso-Cr_(2)O_(3)catalyst exhibited the best catalytic activity for n-hexane(C_(6)H_(14))combustion(T_(50%)and T_(90%)were 239 and 263℃ at a space velocity of 40,000 mL g^(-1)h^(-1);apparent activation energy and specific reaction rate at 260℃ were 54.7 kJ mol^(-1)and 4.3×10^(-7)mol g^(-1)_(cat)s^(-1),respectively),which was associated with its higher(Cr^(5+)+Cr^(6+))amount,large n-hexane adsorption capacity,and good lattice oxygen mobility that could enhance the deep oxidation of n-hexane,in which Ni_(1) was beneficial for the enhancements in surface lattice oxygen mobility and low-temperature reducibility,while Co_(1) preferred to generate higher contents of the high-valence states of chromium and surface oxygen species as well as adsorption and activation of n-hexane.n-Hexane combustion takes place via the Mars van Krevelen(MvK)mechanism,and its reaction pathways are as follows:n-hexane→olefins or 3-hexyl hydroperoxide→3-hexanone,2-hexanone or 2,5-dimethyltetrahydrofuran→2-methyloxirane or 2-ethyl-oxetane→acrylic acid→CO_x→CO_(2)and H_(2)O.
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financially supported by the National Council for Scientific and Technological Development(CNPq,Brazil),Swedish-Brazilian Research and Innovation Centre(CISB),and Saab AB under Grant No.CNPq:200053/2022-1the National Council for Scientific and Technological Development(CNPq,Brazil)under Grants No.CNPq:312924/2017-8 and No.CNPq:314660/2020-8.
文摘Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.
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support from European Union Seventh Frame-work Programme(FP7/2007-2013 project SusFuelCat,grant No.310490)is acknowledged.
文摘Aqueous-phase reforming(APR)is an attractive process to produce bio-based hydrogen from waste biomass streams,during which the catalyst stability is often challenged due to the harsh reaction conditions.In this work,three Pt-based catalysts supported on C,AlO(OH),and ZrO_(2)were investigated for the APR of hydroxyacetone solution in afixed bed reactor at 225℃and 35 bar.Among them,the Pt/C catalyst showed the highest turnover frequency for H_(2)production(TOF of 8.9 molH_(2)molPt^(-1)min^(-1))and the longest catalyst stability.Over the AlO(OH)and ZrO_(2)supported Pt catalysts,the side reactions consuming H_(2),formation of coke,and Pt sintering result in a low H_(2)production and the fast catalyst deactivation.The proposed reaction pathways suggest that a promising APR catalyst should reform all oxygenates in the aqueous phase,minimize the hydrogenation of the oxygenates,maximize the WGS reaction,and inhibit the condensation and coking reactions for maximizing the hydrogen yield and a stable catalytic performance.
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.
基金supported by the Natural Science Foundation of Beijing Municipality (Z200012)the National Natural Science Foundation of China (U21A20328,22225903)the National Key Research and Development Program of China (2021YFB4000601)。
文摘Metal nanoaggregates can simultaneously enhance the activity and stability of Fe-N-C catalysts in proton-exchange-membrane fuel cells(PEMFC).Previous studies on the relevant mechanism have focused on the direct interaction between FeN_(4)active sites and metal nanoaggregates.However,the role of carbon support that hosts metal nanoaggregates and active sites has been overlooked.Here,a Fe-N-C catalyst encapsulating inactive gold nanoparticles is prepared as a model catalyst to investigate the electronic tuning of Au nanoparticles(NPs)towards the carbon support.Au NPs donate electrons to carbon support,making it rich inπelectrons,which reduces the work function and regulates the electronic configuration of the FeN_(4)sites for an enhanced ORR activity.Meanwhile,the electron-rich carbon support can mitigate the electron depletion of FeN_(4)sites caused by carbon support oxidation,thereby preserving its high activity.The yield and accumulation of H_(2)O_(2)are thus alleviated,which delays the oxidation of the catalyst and benefits the stability.Due to the electron-rich carbon support,the composite catalyst achieves a top-level peak power density of 0.74 W/cm^(2) in a 1.5 bar H_(2)-air PEMFC,as well as the improved stability.This work elucidates the key role of carbon support in the performance enhancement of the FeN-C/metal nanoaggregate composite catalysts for fuel cell application.
