This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can ...This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.展开更多
Synapse organizers are essential for the development,transmission,and plasticity of synapses.Acting as rare synapse suppressors,the MAM domain containing glycosylphosphatidylinositol anchor(MDGA)proteins contributes t...Synapse organizers are essential for the development,transmission,and plasticity of synapses.Acting as rare synapse suppressors,the MAM domain containing glycosylphosphatidylinositol anchor(MDGA)proteins contributes to synapse organization by inhibiting the formation of the synaptogenic neuroligin-neurexin complex.A previous analysis of MDGA2 mice lacking a single copy of Mdga2 revealed upregulated glutamatergic synapses and behaviors consistent with autism.However,MDGA2 is expressed in diverse cell types and is localized to both excitatory and inhibitory synapses.Differentiating the network versus cell-specific effects of MDGA2 loss-of-function requires a cell-type and brain region-selective strategy.To address this,we generated mice harboring a conditional knockout of Mdga2 restricted to CA1 pyramidal neurons.Here we report that MDGA2 suppresses the density and function of excitatory synapses selectively on pyramidal neurons in the mature hippocampus.Conditional deletion of Mdga2 in CA1 pyramidal neurons of adult mice upregulated miniature and spontaneous excitatory postsynaptic potentials,vesicular glutamate transporter 1 intensity,and neuronal excitability.These effects were limited to glutamatergic synapses as no changes were detected in miniature and spontaneous inhibitory postsynaptic potential properties or vesicular GABA transporter intensity.Functionally,evoked basal synaptic transmission and AMPAR receptor currents were enhanced at glutamatergic inputs.At a behavioral level,memory appeared to be compromised in Mdga2 cKO mice as both novel object recognition and contextual fear conditioning performance were impaired,consistent with deficits in long-term potentiation in the CA3-CA1 pathway.Social affiliation,a behavioral analog of social deficits in autism,was similarly compromised.These results demonstrate that MDGA2 confines the properties of excitatory synapses to CA1 neurons in mature hippocampal circuits,thereby optimizing this network for plasticity,cognition,and social behaviors.展开更多
Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P...Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N(P)availability and nutrient-limiting conditions.However,the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive.We conducted a metaanalysis of data about the concentrations and allocation proportions of leaf P fractions,specifically associated with individual and combined additions of N and P in evergreen forests,the dominant vegetation type in southern China where the primary productivity is usually considered limited by P.This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies.Nitrogen addition(exacerbating P limitation)reduced the concentrations of leaf total P and different leaf P fractions.Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions,while P addition showed opposite trends.The simultaneous additions of N and P showed an antagonistic(mutual suppression)effect on the concentrations of leaf P fractions,but an additive(summary)effect on the allocation proportions of leaf P fractions.These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability.Importantly,our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions,thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.展开更多
This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The inp...This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The input circuit of a conventional inverter consists of a thick-gate-oxide n-type MOSFET(NMOS).These conventional drivers can tolerate a total ionizing dose(TID)of up to 100 krad(Si).In contrast,the proposed comparator input circuit uses both a thick-gate-oxide p-type MOSFET(PMOS)and thin-gate-oxide NMOS to offer a high input voltage and higher TID tolerance.Because the thick-gate-oxide PMOS and thin-gate-oxide NMOS collectively provide better TID tolerance than the thick-gate-oxide NMOS,the circuit exhibits enhanced TID tolerance of>300 krad(Si).Simulations and experimental date indicate that the DSS structure reduces the probability of unwanted parasitic bipolar junction transistor activation,yielding a better single-event effect tolerance of over 81.8 MeVcm^(2)mg^(-1).The innovative strategy proposed in this study involves circuit and layout design optimization,and does not require any specialized process flow.Hence,the proposed circuit can be manufactured using common commercial 0.35μm BCD processes.展开更多
The overall objective of this work is to evaluate the energy potential of biogas inputs(chicken manure and pig poop)with a view to their value.The research determined the physicochemical composition,the amount of biog...The overall objective of this work is to evaluate the energy potential of biogas inputs(chicken manure and pig poop)with a view to their value.The research determined the physicochemical composition,the amount of biogas produced per day and the average.For hen dung,humidity(28.47%),DM(dry matter)(71.53%),OM(organic matter)(67%),density(270.77 kg/m^(3)),carbon content(39.7%),nitrogen content(2.55%)and C/N ratio(15.23)and pig pork,moisture(47.98%),DM(45.6%),OM(23.55%),mass volumic(693.12 kg/m^(3)),carbon(38.88%),nitrogen(1.82%)and C/N(11.26).These results compared to those of the literature revealed a very good coincidence.Two experiments on the methanation of these inputs were carried out,the anaerobic digestion lasted 24 days,in a temperature range of 24 to 30℃(mesophilic range).It was obtained for:hen dung 0.02526 m^(3) and pig poach 0.00841 m^(3) and on average the daily specific production of biogas of different substrates is:pork dung(0.00407 m^(3)/day)and the hen dung(0.00108 m^(3)/d)at an average temperature of 24℃.展开更多
Drilling optimization requires accurate drill bit rate-of-penetration(ROP)predictions.ROP decreases drilling time and costs and increases rig productivity.This study employs random forest(RF),gradient boosting modelin...Drilling optimization requires accurate drill bit rate-of-penetration(ROP)predictions.ROP decreases drilling time and costs and increases rig productivity.This study employs random forest(RF),gradient boosting modeling(GBM),extreme gradient boosting(XGBoost),and adaptive boosting(Adaboost)models to generate ROP pre-dictions.The models use well data from a 3200-m segment across the stratigraphic column(Dibdibba to Zubair formations)of the large West Qurna oil field in Southern Iraq,penetrating 19 formations and four oil reservoirs.The reservoir sections are between 40 and 440 m thick and consist of both carbonate and clastic lithologies.The ROP predictive models were developed using 14 operational parameters:TVD,weight on bit(WOB),torque,effective circulating density(ECD),drilling rotation per minute(RPM),flow rate,standpipe pressure(SPP),bit size,total RPM,D exponent,gamma ray(GR),density,neutron,caliper,and discrete lithology distribution.Training and validation of the ROP models involves data compiled from three development wells.Applying Random subsampling,the compiled dataset was split into 85%for training and 15%for validation and testing.The test subgroup’s measured and predicted ROP mismatch was assessed using root mean square error(RMSE)and coefficient of correlation(R^(2)).The RF,GBM,and XGBoost models provide ROP predictions versus depth with low errors.Models with cross-validation that integrate data from three wells deliver more accurate ROP pre-dictions than datasets from single well.The input variables’influences on ROP optimization identify the optimal value ranges for 14 operating parameters that help to increase drilling speed and reduce cost.展开更多
In this study,a strategy is proposed to use the congestion index as a new input feature.This approach can reveal more deeply the complex effects of traffic conditions on variations in particulate matter(PM_(2.5))conce...In this study,a strategy is proposed to use the congestion index as a new input feature.This approach can reveal more deeply the complex effects of traffic conditions on variations in particulate matter(PM_(2.5))concentrations.To assess the effectiveness of this strategy,we conducted an ablation experiment on the congestion index and implemented a multi-scale input model.Compared with conventional models,the strategy reduces the root mean square error(RMSE)of all benchmark models by>6.07%on average,and the bestperforming model reduces it by 12.06%,demonstrating excellent performance improvement.In addition,evenwith high traffic emissions,the RMSE during peak hours is still below 9.83μg/m^(3),which proves the effectiveness of the strategy by effectively addressing pollution hotspots.This study provides new ideas for improving urban environmental quality and public health and anticipates inspiring further research in this domain.展开更多
Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input data...Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.展开更多
This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded cond...This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded condition,P91 steel welds primarily consist of untempered martensite,which transforms into tempered martensite during post-weld heat treatment(PWHT).Electron spectro-scopy analysis reveals the presence of M_(23)C_(6) and MX carbonitride precipitates at grain boundaries.Increasing the heat input leads to greater quantities of precipitates in the prior austenite grain boundaries,which can affect material properties.Weldment hardness profiles exhibit modest improvements,while ultimate tensile strength and toughness decrease with higher welding heat input,poten-tially due to the formation of a ferritic phase.Residual stress distributions are noticeably influenced by the welding heat input level.展开更多
This paper addresses the tracking control problem of a class of multiple-input–multiple-output nonlinear systems subject to actuator faults.Achieving a balance between input saturation and performance constraints,rat...This paper addresses the tracking control problem of a class of multiple-input–multiple-output nonlinear systems subject to actuator faults.Achieving a balance between input saturation and performance constraints,rather than conducting isolated analyses,especially in the presence of frequently encountered unknown actuator faults,becomes an interesting yet challenging problem.First,to enhance the tracking performance,Tunnel Prescribed Performance(TPP)is proposed to provide narrow tunnel-shape constraints instead of the common over-relaxed trumpet-shape performance constraints.A pair of non-negative signals produced by an auxiliary system is then integrated into TPP,resulting in Saturation-tolerant Prescribed Performance(SPP)with flexible performance boundaries that account for input saturation situations.Namely,SPP can appropriately relax TPP when needed and decrease the conservatism of control design.With the help of SPP,our developed Saturation-tolerant Prescribed Control(SPC)guarantees finite-time convergence while satisfying both input saturation and performance constraints,even under serious actuator faults.Simulations are conducted to illustrate the effectiveness of the proposed SPC.展开更多
To investigate the potential of KTIG-MIG coupling welding in improving welding efficiency and quality for medium-thickness Q235B low-carbon steel plates,this study specifically analyzes the microstructural characteris...To investigate the potential of KTIG-MIG coupling welding in improving welding efficiency and quality for medium-thickness Q235B low-carbon steel plates,this study specifically analyzes the microstructural characteristics of three distinct regions in butt joints-the base metal(BM),heat-affected zone(HAZ),and weld metal zone(WMZ)-while simultaneously conducting comprehensive mechanical property testing on the welded joints.The test results of mechanical properties are combined with the data of microstructure analysis.The relationship between mechanical properties and microstructure of the WMZ of the butt joint is found.The results show that the microstructure of weld zone does not change significantly with the increase of heat input,but the grain structure of fusion zone and heat affected zone increases gradually.The tensile properties of welded joints are better than those of base materials under different heat input conditions.展开更多
As global trade networks deepen and trade patterns evolve,supply chain dynamics have emerged as a critical driver of high-quality development-particularly as reflected in firms’capacity to export higher-quality produ...As global trade networks deepen and trade patterns evolve,supply chain dynamics have emerged as a critical driver of high-quality development-particularly as reflected in firms’capacity to export higher-quality products.Drawing on new-new trade theory,this study incorporates supply chain behavior-specifically,the use of intermediate goods-into the analytical framework for determining export product quality.Theoretically,it posits that technical regulations on the supply chain influence export quality through two key channels:improvements in the quality of intermediate inputs and changes in their associated costs.Empirically,the study exploits China’s imposition of technical barriers to trade(TBT)on intermediate goods imports as a quasi-natural experiment,applying a difference-in-differences approach to firm-level export data from 2000 to 2014.The results show that supply chain technical regulations lead to significant improvements in the quality of exported final products.Mechanistically,the regulations raise the quality of imported intermediates,which in turn drive upgrades in final outputs,while leaving import costs largely unchanged-since compliance expenses are absorbed by foreign exporters rather than passed on to Chinese firms.Further analysis reveals substantial heterogeneity in these effects,depending on both the type of regulation and firm characteristics.These variations reflect differences in regulatory intensity and in firms’sensitivity to supply chain changes,adaptability,and capacity to convert input quality into product upgrades.Overall,the findings suggest that strengthening supply-side regulatory standards-when properly designed-represents a strategic lever for improving product quality and enhancing firms’international competitiveness,offering valuable insights for trade policy and global supply chain governance.展开更多
Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Insp...Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Inspired by the great success of artificial intelligence-based algorithms,especially deep learning-based methods in the field of biology,various computational methods have been introduced into antibody optimization to reduce costs and increase the success rate of lead candidate generation and optimization.Herein,we briefly review recent progress in deep learning-based antibody optimization,focusing on the available datasets and algorithm input data types that are crucial for constructing appropriate deep learning models.Furthermore,we discuss the current challenges and potential solutions for the future development of general-purpose deep learning algorithms in antibody optimization.展开更多
The effect of high welding heat inputs in the range of 50–200 kJ/cm on the microstructural evolution,MX(M=Ti,Nb and V;X=N and C)precipitation and mechanical properties was investigated in the coarse-grained heat-affe...The effect of high welding heat inputs in the range of 50–200 kJ/cm on the microstructural evolution,MX(M=Ti,Nb and V;X=N and C)precipitation and mechanical properties was investigated in the coarse-grained heat-affected zone(CGHAZ)of a high-Nb(0.10 wt.%)structural steel.The results showed that the primary microconstituents varied from lath bainite(LB)to intragranular acicular ferrite(IAF)+intragranular polygonal ferrite(IPF),and the most content of IAF was acquired at 100 kJ/cm.Moreover,the submicron Ti-and Nb-rich MX precipitates not only pinned prior austenite grain boundaries but also facilitated IAF and IPF nucleation with the Kurdjumov–Sachs orientation relationship of[011]_(MX)//[111]_(Ferrite);the nanoscale V-rich MX precipitates hindered dislocation movement and followed the Baker–Nutting orientation relationship of[001]_(MX)//[001]_(Ferrite)with ferrite matrix,synergistically strengthening and toughening the CGHAZ.In addition,the−20℃impact absorbed energy firstly elevated from 93±5.2 J at 50 kJ/cm to 131±5.4 J at 100 kJ/cm and finally decreased to 59±3.0 J at 200 kJ/cm,being related to the IAF content,while the microhardness decreased from 312±26.1 to 269±12.9 HV0.1,because of the coarsened microstructure and the decreased content of LB and martensite.Compared to the CGHAZ properties with 0.05 wt.%Nb,a higher Nb content produced better low-temperature toughness,as more solid dissolved Nb atoms and precipitated Nb-rich MX particles in austenite limited prior austenite grain growth and promoted IAF formation.Furthermore,the welding process at 100 kJ/cm was most applicable for the high-Nb steel.展开更多
Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate...Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate sensor readings.These faults may result in system instability or compromise safety.In this paper,we propose a fault compensation control system to mitigate the effects of sensor faults and ensure system safety.Specifically,we utilize the pressure sensor within the system to implement the control process and evaluate performance based on the piston position.First,we develop a mathematical model to identify optimal parameters for the fault estimation model based on the Lyapunov stability principle.Next,we design an unknown input observer that estimates the state vector and detects pressure sensor faults using a linear matrix inequality optimization algorithm.The estimated pressure faults are incorporated into the fault compensation control system to counteract their effects via a fault residual coefficient.The discrepancy between the feedback state and the estimated state determines this coefficient.We assess the piston position’s performance through pressure control to evaluate the proposed model’s effectiveness.Finally,the system simulation results are analyzed to validate the efficiency of the proposed model.When a pressure sensor fault occurs,the proposed approach effectively minimizes position control errors,enhancing overall system stability.When a pressure sensor fault occurs,the proposed model compensates for the fault to mitigate the impact of pressure problem,thereby enhancing the position control quality of the EHA system.The fault compensation method ensures over 90%system performance,with its effectiveness becoming more evident under pressure sensor faults.展开更多
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial...In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.展开更多
To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground moti...To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.展开更多
Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a locatio...Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
The effects of Ti/N ratio on the number densities of nano particles,the size of the prior austenite grain(PAG)and the toughness of the heat-affected zone(HAZ)of Mg-deoxidized steels were studied after high heat input ...The effects of Ti/N ratio on the number densities of nano particles,the size of the prior austenite grain(PAG)and the toughness of the heat-affected zone(HAZ)of Mg-deoxidized steels were studied after high heat input welding of 400 kJ/cm.With increasing the Ti/N ratio from 2.7 to 5.7,the cuboid nano-sized particles are formed,and their number density increases.The area fractions of ductile intragranular acicular ferrites(IAFs)have the highest value and the area fractions of brittle microstructures of ferrite side plates and upper bainites have the lowest value in TN30 steel.With the Ti/N ratio of about 3.0,the HAZ of steel plate has the best low-temperature toughness.With increasing the Ti/N ratio from 2.7 to 5.7,the PAG sizes after the high-temperature laser scanning confocal microscopy observation decrease linearly with increasing the number densities of nano-sized particles.The PAG size of TN30 steel is between 100 and 150μm,which is conducive to the nucleation of IAFs.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62376105,12101208,and 61906072)the Fundamental Research Funds for the Central Universities(Grant No.2662022XXQD001).
文摘This paper proposes a novel multivalued recurrent neural network model driven by external inputs,along with two innovative learning algorithms.By incorporating a multivalued activation function,the proposed model can achieve multivalued many-to-one associative memory,and the newly developed algorithms enable effective storage of many-to-one patterns in the coefficient matrix while maintaining the indispensability of inputs in many-to-one associative memory.The proposed learning algorithm addresses a critical limitation of existing models which fail to ensure completely erroneous outputs when facing partial input missing in many-to-one associative memory tasks.The methodology is rigorously derived through theoretical analysis,incorporating comprehensive verification of both the existence and global exponential stability of equilibrium points.Demonstrative examples are provided in the paper to show the effectiveness of the proposed theory.
基金supported by the National Natural Science Foundation of China(82001203,82173819,81871012,and 81571263)the Scientific Research Fund of Zhejiang Provincial Education Department(Y201839276)+3 种基金the Scientific Research Foundation of Zhejiang University City College(X-202103)the R&D Project of Zhejiang(2022C03034)the Natural Science Foundation of Zhejiang Province(LQ23C090001)a Canada Research Chair Award(P2018-0246).
文摘Synapse organizers are essential for the development,transmission,and plasticity of synapses.Acting as rare synapse suppressors,the MAM domain containing glycosylphosphatidylinositol anchor(MDGA)proteins contributes to synapse organization by inhibiting the formation of the synaptogenic neuroligin-neurexin complex.A previous analysis of MDGA2 mice lacking a single copy of Mdga2 revealed upregulated glutamatergic synapses and behaviors consistent with autism.However,MDGA2 is expressed in diverse cell types and is localized to both excitatory and inhibitory synapses.Differentiating the network versus cell-specific effects of MDGA2 loss-of-function requires a cell-type and brain region-selective strategy.To address this,we generated mice harboring a conditional knockout of Mdga2 restricted to CA1 pyramidal neurons.Here we report that MDGA2 suppresses the density and function of excitatory synapses selectively on pyramidal neurons in the mature hippocampus.Conditional deletion of Mdga2 in CA1 pyramidal neurons of adult mice upregulated miniature and spontaneous excitatory postsynaptic potentials,vesicular glutamate transporter 1 intensity,and neuronal excitability.These effects were limited to glutamatergic synapses as no changes were detected in miniature and spontaneous inhibitory postsynaptic potential properties or vesicular GABA transporter intensity.Functionally,evoked basal synaptic transmission and AMPAR receptor currents were enhanced at glutamatergic inputs.At a behavioral level,memory appeared to be compromised in Mdga2 cKO mice as both novel object recognition and contextual fear conditioning performance were impaired,consistent with deficits in long-term potentiation in the CA3-CA1 pathway.Social affiliation,a behavioral analog of social deficits in autism,was similarly compromised.These results demonstrate that MDGA2 confines the properties of excitatory synapses to CA1 neurons in mature hippocampal circuits,thereby optimizing this network for plasticity,cognition,and social behaviors.
基金supported by the National Natural Science Foundation of China(No.41473068)supported by China Postdoctoral Science Foundation(No.2022M722667)。
文摘Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N(P)availability and nutrient-limiting conditions.However,the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive.We conducted a metaanalysis of data about the concentrations and allocation proportions of leaf P fractions,specifically associated with individual and combined additions of N and P in evergreen forests,the dominant vegetation type in southern China where the primary productivity is usually considered limited by P.This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies.Nitrogen addition(exacerbating P limitation)reduced the concentrations of leaf total P and different leaf P fractions.Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions,while P addition showed opposite trends.The simultaneous additions of N and P showed an antagonistic(mutual suppression)effect on the concentrations of leaf P fractions,but an additive(summary)effect on the allocation proportions of leaf P fractions.These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability.Importantly,our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions,thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.
基金supported by the National Natural Science Foundation of China(U2241221).
文摘This article introduces a novel 20 V radiation-hardened high-voltage metal-oxide-semiconductor field-effect transistor(MOSFET)driver with an optimized input circuit and a drain-surrounding-source(DSS)structure.The input circuit of a conventional inverter consists of a thick-gate-oxide n-type MOSFET(NMOS).These conventional drivers can tolerate a total ionizing dose(TID)of up to 100 krad(Si).In contrast,the proposed comparator input circuit uses both a thick-gate-oxide p-type MOSFET(PMOS)and thin-gate-oxide NMOS to offer a high input voltage and higher TID tolerance.Because the thick-gate-oxide PMOS and thin-gate-oxide NMOS collectively provide better TID tolerance than the thick-gate-oxide NMOS,the circuit exhibits enhanced TID tolerance of>300 krad(Si).Simulations and experimental date indicate that the DSS structure reduces the probability of unwanted parasitic bipolar junction transistor activation,yielding a better single-event effect tolerance of over 81.8 MeVcm^(2)mg^(-1).The innovative strategy proposed in this study involves circuit and layout design optimization,and does not require any specialized process flow.Hence,the proposed circuit can be manufactured using common commercial 0.35μm BCD processes.
文摘The overall objective of this work is to evaluate the energy potential of biogas inputs(chicken manure and pig poop)with a view to their value.The research determined the physicochemical composition,the amount of biogas produced per day and the average.For hen dung,humidity(28.47%),DM(dry matter)(71.53%),OM(organic matter)(67%),density(270.77 kg/m^(3)),carbon content(39.7%),nitrogen content(2.55%)and C/N ratio(15.23)and pig pork,moisture(47.98%),DM(45.6%),OM(23.55%),mass volumic(693.12 kg/m^(3)),carbon(38.88%),nitrogen(1.82%)and C/N(11.26).These results compared to those of the literature revealed a very good coincidence.Two experiments on the methanation of these inputs were carried out,the anaerobic digestion lasted 24 days,in a temperature range of 24 to 30℃(mesophilic range).It was obtained for:hen dung 0.02526 m^(3) and pig poach 0.00841 m^(3) and on average the daily specific production of biogas of different substrates is:pork dung(0.00407 m^(3)/day)and the hen dung(0.00108 m^(3)/d)at an average temperature of 24℃.
文摘Drilling optimization requires accurate drill bit rate-of-penetration(ROP)predictions.ROP decreases drilling time and costs and increases rig productivity.This study employs random forest(RF),gradient boosting modeling(GBM),extreme gradient boosting(XGBoost),and adaptive boosting(Adaboost)models to generate ROP pre-dictions.The models use well data from a 3200-m segment across the stratigraphic column(Dibdibba to Zubair formations)of the large West Qurna oil field in Southern Iraq,penetrating 19 formations and four oil reservoirs.The reservoir sections are between 40 and 440 m thick and consist of both carbonate and clastic lithologies.The ROP predictive models were developed using 14 operational parameters:TVD,weight on bit(WOB),torque,effective circulating density(ECD),drilling rotation per minute(RPM),flow rate,standpipe pressure(SPP),bit size,total RPM,D exponent,gamma ray(GR),density,neutron,caliper,and discrete lithology distribution.Training and validation of the ROP models involves data compiled from three development wells.Applying Random subsampling,the compiled dataset was split into 85%for training and 15%for validation and testing.The test subgroup’s measured and predicted ROP mismatch was assessed using root mean square error(RMSE)and coefficient of correlation(R^(2)).The RF,GBM,and XGBoost models provide ROP predictions versus depth with low errors.Models with cross-validation that integrate data from three wells deliver more accurate ROP pre-dictions than datasets from single well.The input variables’influences on ROP optimization identify the optimal value ranges for 14 operating parameters that help to increase drilling speed and reduce cost.
基金supported by the Enterprises Research Project(Nos.W2021JSKF0922 and W2023JSKF0116)the Key industrialization Projects of Intelligent Manufacturing Institute,Hefei University of Technology(No.IMICZ2019001).
文摘In this study,a strategy is proposed to use the congestion index as a new input feature.This approach can reveal more deeply the complex effects of traffic conditions on variations in particulate matter(PM_(2.5))concentrations.To assess the effectiveness of this strategy,we conducted an ablation experiment on the congestion index and implemented a multi-scale input model.Compared with conventional models,the strategy reduces the root mean square error(RMSE)of all benchmark models by>6.07%on average,and the bestperforming model reduces it by 12.06%,demonstrating excellent performance improvement.In addition,evenwith high traffic emissions,the RMSE during peak hours is still below 9.83μg/m^(3),which proves the effectiveness of the strategy by effectively addressing pollution hotspots.This study provides new ideas for improving urban environmental quality and public health and anticipates inspiring further research in this domain.
基金supported by the National Key Research and Development Program of China (2023YFD1902703)the National Natural Science Foundation of China (Key Program) (U23A20158)。
文摘Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.
文摘This study investigates the impact of welding heat input on weldments of modified 9Cr-1Mo(P91)steel,a high-strength material that requires high-energy welding processes like submerged arc welding.In the as-welded condition,P91 steel welds primarily consist of untempered martensite,which transforms into tempered martensite during post-weld heat treatment(PWHT).Electron spectro-scopy analysis reveals the presence of M_(23)C_(6) and MX carbonitride precipitates at grain boundaries.Increasing the heat input leads to greater quantities of precipitates in the prior austenite grain boundaries,which can affect material properties.Weldment hardness profiles exhibit modest improvements,while ultimate tensile strength and toughness decrease with higher welding heat input,poten-tially due to the formation of a ferritic phase.Residual stress distributions are noticeably influenced by the welding heat input level.
基金supported by the National Research Foundation Singapore under its AI Singapore Programme(Award Number:[AISG2-GC-2023-007]).
文摘This paper addresses the tracking control problem of a class of multiple-input–multiple-output nonlinear systems subject to actuator faults.Achieving a balance between input saturation and performance constraints,rather than conducting isolated analyses,especially in the presence of frequently encountered unknown actuator faults,becomes an interesting yet challenging problem.First,to enhance the tracking performance,Tunnel Prescribed Performance(TPP)is proposed to provide narrow tunnel-shape constraints instead of the common over-relaxed trumpet-shape performance constraints.A pair of non-negative signals produced by an auxiliary system is then integrated into TPP,resulting in Saturation-tolerant Prescribed Performance(SPP)with flexible performance boundaries that account for input saturation situations.Namely,SPP can appropriately relax TPP when needed and decrease the conservatism of control design.With the help of SPP,our developed Saturation-tolerant Prescribed Control(SPC)guarantees finite-time convergence while satisfying both input saturation and performance constraints,even under serious actuator faults.Simulations are conducted to illustrate the effectiveness of the proposed SPC.
基金supported by the National Natural Science Foundation of China(51605103)Key Projects of Science and Technology Research Plan of Hubei Provincial Department of Education(D20221306)Key Project of Hubei Provincial Science and Technology Department(2020BAB055).
文摘To investigate the potential of KTIG-MIG coupling welding in improving welding efficiency and quality for medium-thickness Q235B low-carbon steel plates,this study specifically analyzes the microstructural characteristics of three distinct regions in butt joints-the base metal(BM),heat-affected zone(HAZ),and weld metal zone(WMZ)-while simultaneously conducting comprehensive mechanical property testing on the welded joints.The test results of mechanical properties are combined with the data of microstructure analysis.The relationship between mechanical properties and microstructure of the WMZ of the butt joint is found.The results show that the microstructure of weld zone does not change significantly with the increase of heat input,but the grain structure of fusion zone and heat affected zone increases gradually.The tensile properties of welded joints are better than those of base materials under different heat input conditions.
基金supported by a major project from the Key Research Base of Humanities and Social Sciences of the Ministry of Education,“Research on Open Development and High-Quality Integrated Development of the Yangtze River Delta Region”(Grant No.22JJD790035).
文摘As global trade networks deepen and trade patterns evolve,supply chain dynamics have emerged as a critical driver of high-quality development-particularly as reflected in firms’capacity to export higher-quality products.Drawing on new-new trade theory,this study incorporates supply chain behavior-specifically,the use of intermediate goods-into the analytical framework for determining export product quality.Theoretically,it posits that technical regulations on the supply chain influence export quality through two key channels:improvements in the quality of intermediate inputs and changes in their associated costs.Empirically,the study exploits China’s imposition of technical barriers to trade(TBT)on intermediate goods imports as a quasi-natural experiment,applying a difference-in-differences approach to firm-level export data from 2000 to 2014.The results show that supply chain technical regulations lead to significant improvements in the quality of exported final products.Mechanistically,the regulations raise the quality of imported intermediates,which in turn drive upgrades in final outputs,while leaving import costs largely unchanged-since compliance expenses are absorbed by foreign exporters rather than passed on to Chinese firms.Further analysis reveals substantial heterogeneity in these effects,depending on both the type of regulation and firm characteristics.These variations reflect differences in regulatory intensity and in firms’sensitivity to supply chain changes,adaptability,and capacity to convert input quality into product upgrades.Overall,the findings suggest that strengthening supply-side regulatory standards-when properly designed-represents a strategic lever for improving product quality and enhancing firms’international competitiveness,offering valuable insights for trade policy and global supply chain governance.
基金supported by the National Natural Science Foundation of China(No.12104396)the National Key R&D Program of China(Nos.2021YFF1200404 and 2021YFA1201200)+2 种基金the National Independent Innovation Demonstration Zone Shanghai Zhangjiang Major Projects(No.ZJZX2020014)the Starry Night Science Fund at Shanghai Institute for Advanced Study of Zhejiang University(No.SN-ZJU-SIAS-003)the Shanghai Artificial Intelligence Lab(No.P22KN00272),China.
文摘Antibodies currently comprise the predominant treatment modality for a variety of diseases;therefore,optimizing their properties rapidly and efficiently is an indispensable step in antibody-based drug development.Inspired by the great success of artificial intelligence-based algorithms,especially deep learning-based methods in the field of biology,various computational methods have been introduced into antibody optimization to reduce costs and increase the success rate of lead candidate generation and optimization.Herein,we briefly review recent progress in deep learning-based antibody optimization,focusing on the available datasets and algorithm input data types that are crucial for constructing appropriate deep learning models.Furthermore,we discuss the current challenges and potential solutions for the future development of general-purpose deep learning algorithms in antibody optimization.
基金financially supported by the National Natural Science Foundation of China(Grant No.52104333)the Natural Science Foundation of Inner Mongolia(Grant No.2024MS05029)+1 种基金the Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Grant No.NJYT24070)the Research Project of Carbon Peak and Carbon Neutrality in Universities of Inner Mongolia Autonomous Region(Grant No.STZX202316).
文摘The effect of high welding heat inputs in the range of 50–200 kJ/cm on the microstructural evolution,MX(M=Ti,Nb and V;X=N and C)precipitation and mechanical properties was investigated in the coarse-grained heat-affected zone(CGHAZ)of a high-Nb(0.10 wt.%)structural steel.The results showed that the primary microconstituents varied from lath bainite(LB)to intragranular acicular ferrite(IAF)+intragranular polygonal ferrite(IPF),and the most content of IAF was acquired at 100 kJ/cm.Moreover,the submicron Ti-and Nb-rich MX precipitates not only pinned prior austenite grain boundaries but also facilitated IAF and IPF nucleation with the Kurdjumov–Sachs orientation relationship of[011]_(MX)//[111]_(Ferrite);the nanoscale V-rich MX precipitates hindered dislocation movement and followed the Baker–Nutting orientation relationship of[001]_(MX)//[001]_(Ferrite)with ferrite matrix,synergistically strengthening and toughening the CGHAZ.In addition,the−20℃impact absorbed energy firstly elevated from 93±5.2 J at 50 kJ/cm to 131±5.4 J at 100 kJ/cm and finally decreased to 59±3.0 J at 200 kJ/cm,being related to the IAF content,while the microhardness decreased from 312±26.1 to 269±12.9 HV0.1,because of the coarsened microstructure and the decreased content of LB and martensite.Compared to the CGHAZ properties with 0.05 wt.%Nb,a higher Nb content produced better low-temperature toughness,as more solid dissolved Nb atoms and precipitated Nb-rich MX particles in austenite limited prior austenite grain growth and promoted IAF formation.Furthermore,the welding process at 100 kJ/cm was most applicable for the high-Nb steel.
基金supported by Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam,provided with the facilities required to carry out this work.
文摘Hydraulic-electric systems are widely utilized in various applications.However,over time,these systems may encounter random faults such as loose cables,ambient environmental noise,or sensor aging,leading to inaccurate sensor readings.These faults may result in system instability or compromise safety.In this paper,we propose a fault compensation control system to mitigate the effects of sensor faults and ensure system safety.Specifically,we utilize the pressure sensor within the system to implement the control process and evaluate performance based on the piston position.First,we develop a mathematical model to identify optimal parameters for the fault estimation model based on the Lyapunov stability principle.Next,we design an unknown input observer that estimates the state vector and detects pressure sensor faults using a linear matrix inequality optimization algorithm.The estimated pressure faults are incorporated into the fault compensation control system to counteract their effects via a fault residual coefficient.The discrepancy between the feedback state and the estimated state determines this coefficient.We assess the piston position’s performance through pressure control to evaluate the proposed model’s effectiveness.Finally,the system simulation results are analyzed to validate the efficiency of the proposed model.When a pressure sensor fault occurs,the proposed approach effectively minimizes position control errors,enhancing overall system stability.When a pressure sensor fault occurs,the proposed model compensates for the fault to mitigate the impact of pressure problem,thereby enhancing the position control quality of the EHA system.The fault compensation method ensures over 90%system performance,with its effectiveness becoming more evident under pressure sensor faults.
文摘In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.
基金National Natural Science Foundation of China under Grant No.52478568National Key R&D Program of China under Grant Nos.2021YFC3100701 and 2022YFC3003503the Nature Science Foundation of Hubei Province under Grant No.2023AFA030。
文摘To analyze the correlation between the input energy parameters(V_(E))and typical intensity measures(IMs)of offshore ground motions,based on 273 earthquake events recorded by the K-NET in Japan,892 offshore ground motion records with moment magnitudes from 4.0 to 7.0 were used in this study.Residuals obtained through a ground motion model were calculated and analyzed for the correlation between V_(E) and amplitude,duration,frequency content and cumulative IMs.The results indicate that PGV and PGD have strong correlation with the V_(E)(T>0.2 s and T>0.4 s),the duration IMs have weakly negative correlation with the V_(E),Sd_(1) has a strong correlation with the V_(E) in the periods of T>0.4 s,T_(g) has a weak correlation with V_(E) and the cumulative IMs have strong correlation with the V_(E).The parametric predictive equations between typical IMs and V_(E) was proposed,and the differences between the prediction equations from the onshore ground motion records were compared.The differences in parametric predicted equations between offshore and onshore ground motions were confirmed in this study.Proposed correlation equations can be applied to offshore probabilistic seismic hazard analysis and the selection of ground motion records by generalized conditional intensity measures.
基金supported by the National Natural Science Foundation of China(61901341).
文摘Using the existing positioning technology can easily obtain high-precision positioning information,which can save resources and reduce complexity when used in the communication field.In this paper,we propose a location-based user scheduling and beamforming scheme for the downlink of a massive multi-user input-output system.Specifically,we combine an analog outer beamformer with a digital inner beamformer.An outer beamformer can be selected from a codebook formed by antenna steering vectors,and then a reduced-complexity inner beamformer based on iterative orthogonal matrices and right triangular matrices(QR)decomposition is applied to cancel interuser interference.Then,we propose a low-complexity user selection algorithm using location information in this paper.We first derive the geometric angle between channel matrices,which represent the correlation between users.Furthermore,we derive the asymptotic signal to interference-plus-noise ratio(SINR)of the system in the context of two-stage beamforming using random matrix theory(RMT),taking into account inter-channel correlations and energies.Simulation results show that the algorithm can achieve higher system and speed while reducing computational complexity.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
基金financially supported by the National Natural Science Foundation of China(52474361).
文摘The effects of Ti/N ratio on the number densities of nano particles,the size of the prior austenite grain(PAG)and the toughness of the heat-affected zone(HAZ)of Mg-deoxidized steels were studied after high heat input welding of 400 kJ/cm.With increasing the Ti/N ratio from 2.7 to 5.7,the cuboid nano-sized particles are formed,and their number density increases.The area fractions of ductile intragranular acicular ferrites(IAFs)have the highest value and the area fractions of brittle microstructures of ferrite side plates and upper bainites have the lowest value in TN30 steel.With the Ti/N ratio of about 3.0,the HAZ of steel plate has the best low-temperature toughness.With increasing the Ti/N ratio from 2.7 to 5.7,the PAG sizes after the high-temperature laser scanning confocal microscopy observation decrease linearly with increasing the number densities of nano-sized particles.The PAG size of TN30 steel is between 100 and 150μm,which is conducive to the nucleation of IAFs.
