A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment ...A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment effect and interim result.For hypotheses and reversed hypotheses under normal models,we obtain analytical expressions of the ROC curves of the CCP,find optimal ROC curves of the CCP,investigate the superiority of the ROC curves of the CCP,calculate critical values of the False Positive Rate(FPR),True Positive Rate(TPR),and cutoff of the optimal CCP,and give go/no go decisions at the interim of the optimal CCP.In addition,extensive numerical experiments are carried out to exemplify our theoretical results.Finally,a real data example is performed to illustrate the go/no go decisions of the optimal CCP.展开更多
This research extends the literature on the environmental Phillips curve(EPC)and environmental Kuznets curve(EKC)by focusing on the 38 member economies of the Organization for Economic Co-operation and Development(OEC...This research extends the literature on the environmental Phillips curve(EPC)and environmental Kuznets curve(EKC)by focusing on the 38 member economies of the Organization for Economic Co-operation and Development(OECD).Using panel data from 2000 to 2021,the study employs several econometric techniques,including fixed effects,feasible generalized least squares,two-stage least squares,and the generalized method of moments.Our primary findings reveal that unemployment has a significant negative impact on CO_(2)emissions,thereby supporting the validity of the EPC hypothesis within OECD countries.This suggests a trade-off between unemployment and reductions in CO_(2)emissions.Similarly,the results validate the EKC hypothesis,with further analysis indicating that the EKC exhibits an N-shaped curve-an important contribution to the literature on environmental dynamics in advanced economies.Additionally,the results show that both trade openness and renewable energy usage have significantly improved environmental quality in OECD economies.Finally,extensive causality testing identifies both one-way and two-way causal relationships among the key variables examined.These findings have important policy implications for the management of environmental quality and macroeconomic variables in the OECD context.展开更多
Prior to 2012,the integration of designed vertical or horizontal curves into microtunnel alignments was unheard of in Ontario.Straight and relatively short microtunnels,less than 200m long,were the local accepted indu...Prior to 2012,the integration of designed vertical or horizontal curves into microtunnel alignments was unheard of in Ontario.Straight and relatively short microtunnels,less than 200m long,were the local accepted industry standard.Following the release of a large number of infrastructure projects in the suburban Greater Toronto Area(GTA),clients and design consultants encouraged contractors to present value engineered alternatives to proposed project alignments and construction methods.Such an initiative has allowed contractors to develop cost effective solutions,which harnessed the application of state-of-the-art microtunnelling methods and equipment.As a result,several recent projects now feature pre-designed curved microtunnels as part of the tender documents.This paper discusses,in technical detail,three recent projects,whereby,long distance curved microtunnels were successfully constructed.Each of the projects had tunnel drives exceeding 300m in length,ranging in diameter from 1200mm ID to 1500mm ID,incorporating the use of Vertical,Horizontal,and Spatial Curves.Critical parameters such as pre-project planning and engineering are highlighted,while the importance of post-tunnelling assessments is also discussed.展开更多
This article examines the influence of annealing temperature on fracture toughness and forming limit curves of dissimilar aluminum/silver sheets.In the cold roll bonding process,after brushing and acid washing,the pre...This article examines the influence of annealing temperature on fracture toughness and forming limit curves of dissimilar aluminum/silver sheets.In the cold roll bonding process,after brushing and acid washing,the prepared surfaces are placed on top of each other and by rolling with reduction more than 50%,the bonding between layers is established.In this research,the roll bonding process was done at room temperature,without the use of lubricants and with a 70%thickness reduction.Then,the final thickness of the Ag/Al bilayer sheet reached 350μm by several stages of cold rolling.Before cold rolling,it should be noted that to decrease the hardness created due to plastic deformation,the roll-bonded samples were subjected to annealing heat treatment at 400℃for 90 min.Thus,the final samples were annealed at 200,300 and 400℃for 90 min and cooled in a furnace to examine the annealing temperature effects.The uniaxial tensile and microhardness tests measured mechanical properties.Also,to investigate the fracture mechanism,the fractography of the cross-section was examined by scanning electron microscope(SEM).To evaluate the formability of Ag/Al bilayer sheets,forming limit curves were obtained experimentally through the Nakazima test.The resistance of composites to failure due to cracking was also investigated by fracture toughness.The results showed that annealing increases the elongation and formability of the Ag/Al bilayer sheet while reduces the ultimate tensile strength and fracture toughness.However,the changing trend is not the same at different temperatures,and according to the results,the most significant effect is obtained at 300℃and aluminum layers.It was also determined that by increasing annealing temperature,the fracture mechanism from shear ductile with small and shallow dimples becomes ductile with deep cavities.展开更多
The deformation caused by tunnel excavation is quite important for safety,especially when it is adjacent to the existing tunnel.Nevertheless,the investigation of deformation characteristics in overlapped curved shield...The deformation caused by tunnel excavation is quite important for safety,especially when it is adjacent to the existing tunnel.Nevertheless,the investigation of deformation characteristics in overlapped curved shield tunneling remains inadequate.The analytical solution for calculating the deformation of the ground and existing tunnel induced by overlapped curved shield tunneling is derived by the Mirror theory,Mindlin solution and Euler-Bernoulli-Pasternak model,subsequently validated through both finite element simulation and field monitoring.It is determined that the overcutting plays a crucial role in the ground settlement resulting from curved shield tunneling compared to straight shield tunneling.The longitudinal settlement distribution can be categorized into five areas,with the area near the tunnel surface experiencing the most dramatic settlement changes.The deformation of the existing tunnel varies most significantly with turning radius compared to tunnel clearance and grouting pressure,especially when the turning radius is less than 30 times the tunnel diameter.The tunnel crown exhibits larger displacement than the tunnel bottom,resulting in a distinctive‘vertical egg'shape.Furthermore,an optimized overcutting mode is proposed,involving precise control of the extension speed and angular velocity of the overcutting cutter,which effectively mitigates ground deformation,ensuring the protection of the existing tunnel during the construction.展开更多
Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accura...Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.展开更多
On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1...On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1)Todasystems on X\{P_(1);…;P_(k)}are recognized by the associated toric curves in.We introduce character n-ensembles as-tuples of meromorphic one-forms with simple poles and purely imaginary periods,generating toric curves on minus finitelymany points.On X,we establish a correspondence between character-ensembles and toric solutions to the SU(n+1)system with finitely many cone singularities.Our approach not only broadens seminal solutions with two conesingularities on the Riemann sphere,as classified by Jost-Wang(Int.Math.Res.Not.,2002,(6):277-290)andLin-Wei-Ye(Invent.Math.,2012,190(1):169-207),but also advances beyond the limits of Lin-Yang-Zhong’s existencetheorems(J.Differential Geom.,2020,114(2):337-391)by introducing a new solution class.展开更多
In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natura...In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natural disaster risk area,requiring continuous research related to the stability of the area.To obtain the soil-water characteristic curve,undisturbed samples of residual and sedimentary soil were collected,followed by suction testing using the filter paper method.Considering the bimodal characteristic presented by the soil,LABFIT software was employed for curve fitting using the generic formulation“Harris+C”.The results of the tests indicated that the phenomenon of hysteresis had a greater influence in situations with higher suction levels.When comparing the residual moisture values of the macropores between residual soil and sedimentary soil,the former exhibited the lower value.This suggests that the residual soil has a coarser grain size and larger pores,which facilitates the release of water retained in the soil’s macropores.展开更多
For the purpose of carrying out the large deformation finite element analysis of spatial curved beams,the total Lagrangian（TL）and the updated Lagrangian（UL）incremental formulations for arbitrary spatial curved bea...For the purpose of carrying out the large deformation finite element analysis of spatial curved beams,the total Lagrangian（TL）and the updated Lagrangian（UL）incremental formulations for arbitrary spatial curved beam elements are established with displacement vector interpolation,which is improved from component interpolation of the straight beam displacement.A strategy of replacing the actual curve with the isoparametric curve is used to expand the applications of the UL formulation.The examples indicate that the process of establishing the curved beam element is correct,and the accuracy with the curved beam element is obviously higher than that with the straight beam element.Generally,the same level of computational accuracy can be achieved with 1/5 as many curved beam elements as otherwise with straight beam elements.展开更多
Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunatel...Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.展开更多
Pre-injection is a technique that involves injecting grout materials into the ground prior to excavation,with the aim of stabilizing the surrounding rock mass.This paper introduces an analytical closed-form model for ...Pre-injection is a technique that involves injecting grout materials into the ground prior to excavation,with the aim of stabilizing the surrounding rock mass.This paper introduces an analytical closed-form model for determining the ground reaction curve of tunnels in rock masses exhibiting elastic-brittleplastic behavior and adhering to the Mohr-Coulomb failure criterion.The model incorporates the reinforced region created by the pre-injection method.When the rock mass is reinforced through preinjection,plastic regions can form independently in both the natural and injected rock masses.This leads to six distinct modes of the problem.The analytical model presented in this paper considers three possible scenarios for the development of plastic regions.Each scenario comprises four stages,with each stage representing a different mode of the problem.While injecting the rock mass can enhance its strength and stiffness,it may also increase the brittleness of the injected rock mass and create stress concentrations within it,particularly when brittle grouts are used.As a result,this can elevate the risk of rockburst due to unstable failure.The results obtained from the model demonstrate that ductile grout performs exceptionally well in controlling tunnel convergence in rock masses,as it accommodates deformation without sudden failure,even in squeezing rock mass conditions.Conversely,the use of brittle grouts should be approached with caution,particularly in squeezing rock masses,due to their susceptibility to rockburst incidents.展开更多
The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always f...The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always focused on the mercury injection curves themselves, neglecting the important geologicalinformation conveyed by the mercury ejection curves. This paper quantitatively describes the fractalcharacteristics of ejection curves by using four fractal models, i.e.,. Menger model, Thermodynamicmodel, Sierpinski model, and multi- fractal model. In comparison with mercury injection curves, weexplore the fractal significance of mercury ejection curves and define the applicability of different fractalmodels in characterizing pore architectures. Investigated tight sandstone samples can be divided intofour types (Types A, B, C and D) based on porosity, permeability, and mercury removal efficiency. Type Dsamples are unique in that they have higher permeability (>0.6 mD) but lower mercury removal effi-ciency (<35%). Fractal studies of the mercury injection curve show that it mainly reflects the pore throatcharacteristics, while the mercury ejection curve serves to reveal the pore features, and porosity andpermeability correlate well with the fractal dimension of the injection curve, while mercury removalefficiency correlates only with the Ds' value of the ejection curve. The studies on the mercury ejectioncurves also reveal that the small pores and micropores of the Type C and Type D samples are moredeveloped, with varying pore architecture. The fractal dimension Ds' value of Type D samples is greaterthan that of Type C samples, and the dissolution of Type D samples is more intense than that of Type Csamples, which further indicates that the Type D samples are smaller in pore size, rougher in surface, andwith greater difficulty for the hydrocarbon to enter, resulting in their reservoir capacity probably lessthan that of Type C samples. In this regard, the important information characterized by the mercuryejection curve should be considered in evaluating the tight sandstone reservoirs. Finally, the Menger andThermodynamic models prove to be more suitable for describing the total pore architecture, while theSierpinski model is better for characterizing the variability of the interconnected pores.展开更多
The fundamental scientific and engineering knowledge concerning the solar power curve,which maps solar irradiance and other auxiliary meteorological variables to photovoltaic output power,has been gathered and put for...The fundamental scientific and engineering knowledge concerning the solar power curve,which maps solar irradiance and other auxiliary meteorological variables to photovoltaic output power,has been gathered and put forward in the preceding tutorial review.Despite the many pages of that review,it was incomplete in the sense that it did not elaborate on the applications of this very important tool of solar energy meteorology.Indeed,solar power curves are ubiquitously needed in a broad spectrum of solar forecasting and solar resource assessment tasks.Hence,this tutorial review should continue from where it left off and present examples concerning the usage of solar power curves.In a nutshell,this tutorial review,together with the preceding one,should elucidate how surface shortwave radiation data,be they ground-based,satelliteretrieved,or model-output,are bridged to various power system operations via solar power curves.展开更多
Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated opt...Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.Design/methodology/approach–Taking a small-radius curve of a high-speed railway as the research object,field measurements were conducted to obtain track parameters and wheel–rail profiles.A coupled vehicle-track dynamics model was established.Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.Findings–Key service parameters affecting wheel–rail creepage were identified,including the matching relationship between curve geometry and vehicle speed and rail profile parameters.The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis,leading to the establishment of parameter optimization criteria.Originality/value–This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves.A response surface-based parameter-creepage relationship model was established,and a multi-parameter coordinated optimization strategy was proposed.The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.展开更多
To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the p...To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the pre-trained large language model,the Gaia significantly improved its ability in extracting sequential patterns and spatial features from well-log curves.Leveraging the adapter method for fine-tuning,this model required training only about 1/70 of its original parameters,greatly improving training efficiency.Comparative experiments,ablation experiments,and generalization experiments were designed and conducted using well-log data from 250 wells.In the comparative experiment,the Gaia model was benchmarked against cutting-edge small deep learning models and conventional large language models,demonstrating that the Gaia model reduced the mean absolute error(MAE)by at least 20%.In the ablation experiments,the synergistic effect of the Gaia model's multiple components was validated,with its MAE being at least 30%lower than that of single-component models.In the generalization experiments,the superior performance of the Gaia model in blind-well predictions was further confirmed.Compared to traditional models,the Gaia model is significantly superior in accuracy and generalization for logging curve reconstruction,fully showcasing the potential of large language models in the field of well-logging.This provides a new approach for future intelligent logging data processing.展开更多
The water retention curve(WRC)has been widely used to quantify moisture transport characteristics of maritime snowpack.However,there is a notable deficiency in experimental studies focused on the WRC of dry-cold snowp...The water retention curve(WRC)has been widely used to quantify moisture transport characteristics of maritime snowpack.However,there is a notable deficiency in experimental studies focused on the WRC of dry-cold snowpack in continental climate conditions.This study selected dry-cold snowpack samples with five densities to measure the variations in volumetric water content using the pressure plate method.The Van Genuchten(VG)and Brooks-Corey(BC)models were then used to fit the snowpack WRCs,aiming to investigate their applicability to dry-cold snowpack and explore the relationship between the model parameters and snowpack characteristics.The results indicated that:(1)Compared to the particle size and the ratio of snowpack density to particle size,the snowpack density shows a higher correlation with the shape parameters of VG model and BC model;(2)There is a nonlinear relationship between the snowpack density and the shape parameters of VG model and BC model;(3)Both the BC and VG models provide a high level of accuracy in fitting the experimental data,with the BC model showing slightly better precision.However,after regression correction,the VG model outperforms the BC model.The findings provide support for in-depth studies of moisture movement characteristics in different types of snow,and have significantly practical value for improving the accuracy of early warning systems for hazards such as avalanches and floods.展开更多
This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environment...This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environments involving missile or bomb detonations,extreme overpressure conditions were generated using a shock tube.The influence of explosive charge mass on tire damage was quantitatively evaluated.Experimental results identified two critical failure thresholds:for loss of pressure,the threshold was 354 kPa peak overpressure and 3052 kPa·ms impulse;for rupture,the values were 485 kPa and 4237 kPa-ms,respectively.The same damage profile was reproduced through finite element analysis(FEA),verifying the reliability of the simulation.A Single Degree of Freedom(SDOF)model and Kingery-Bulmash(K-B)chart were employed to generate pressure-impulse data as a function of standoff distance.These data were applied to a finite element tire model using the BLAST ENHANCED keyword in LS-DYNA.The applied peak overpressures were identical to the experimental values with a 24%-27%difference in impulse.The simulation also captured recurring bead rim separation phenomenon,leading to internal pressure loss consistent with high-speed camera observations from the experiments.The resulting fragility curve clearly defines the threshold conditions for tire damage and provides a standardized damage assessment model applicable to various explosive charge masses and stand-off distances.The proposed model offers a quantitative basis for evaluating tire vulnerability,providing foundational reference data for defense applications.Specifically,the findings are expected to serve as a reliable source for weapon effects analysis and target vulnerability assessments involving wheeled military vehicles.展开更多
In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization al...In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization algorithms used in dispersion curve inversion are highly dependent on the initial model and are prone to being trapped in local optima,while classical global optimization algorithms often suffer from slow convergence and low solution accuracy.To address these issues,this study introduces the Osprey Optimization Algorithm(OOA),known for its strong global search and local exploitation capabilities,into the inversion of dispersion curves to enhance inversion performance.In noiseless theoretical models,the OOA demonstrates excellent inversion accuracy and stability,accurately recovering model parameters.Even in noisy models,OOA maintains robust performance,achieving high inversion precision under high-noise conditions.In multimode dispersion curve tests,OOA effectively handles higher modes due to its efficient global and local search capabilities,and the inversion results show high consistency with theoretical values.Field data from the Wyoming region in the United States and a landfill site in Italy further verify the practical applicability of the OOA.Comprehensive test results indicate that the OOA outperforms the Particle Swarm Optimization(PSO)algorithm,providing a highly accurate and reliable inversion strategy for dispersion curve inversion.展开更多
Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causin...Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.展开更多
The unreasonable application of nitrogen fertilizer poses a threat to agricultural productivity and the environment protection in Northeast China.Therefore,accurately assessing crop nitrogen requirements and optimizin...The unreasonable application of nitrogen fertilizer poses a threat to agricultural productivity and the environment protection in Northeast China.Therefore,accurately assessing crop nitrogen requirements and optimizing fertilization are crucial for sustainable agricultural production.A three-year field experiment was conducted to evaluate the effects of planting density on the critical nitrogen concentration dilution curve(CNDC)for spring maize under drip irrigation and fertilization integration,incorporating two planting densities:D1(60,000 plants ha^(-1))and D2(90,000 plants ha^(-1))and six nitrogen levels:no nitrogen(N0),90(N90),180(N180),270(N270),360(N360),and 450(N450)kg ha^(-1).A Bayesian hierarchical model was used to develop CNDC models based on dry matter(DM)and leaf area index(LAI).The results revealed that the critical nitrogen concentration exhibited a power function relationship with both DM and LAI,while planting density had no significant impact on the CNDC parameters.Based on these findings,we propose unified CNDC equations for maize under drip irrigation and fertilization integration:Nc=4.505DM-0.384(based on DM)and Nc=3.793LAI-0.327(based on LAI).Additionally,the nitrogen nutrition index(NNI),derived from the CNDC,increased with higher nitrogen application rates.The nitrogen nutrition index(NNI)approached 1 with a nitrogen application rate of 180 kg ha^(-1)under the D1 planting density,while it reached 1 at 270 kg ha^(-1)under the D2 planting density.The relationship between NNI and relative yield(RY)followed a“linear+plateau”model,with maximum RY observed when the NNI approached 1.Thus,under the condition of drip irrigation and fertilization integration in Northeast China’s spring maize production,the optimal nitrogen application rates for achieving the highest yields were 180 kg ha^(-1)at a planting density of 60,000 plants ha^(-1),and 270 kg ha^(-1)at a density of 90,000 plants ha^(-1).The CNDC and NNI models developed in this study are valuable tools for diagnosing nitrogen nutrition and guiding precise fertilization practices in maize production under integrated drip irrigation and fertilization systems in Northeast China.展开更多
基金supported by the National Social Science Fund of China(Grand No.21XTJ001).
文摘A Receiver Operating Characteristic(ROC)analysis of a power is important and useful in clinical trials.A Classical Conditional Power(CCP)is a probability of a classical rejection region given values of true treatment effect and interim result.For hypotheses and reversed hypotheses under normal models,we obtain analytical expressions of the ROC curves of the CCP,find optimal ROC curves of the CCP,investigate the superiority of the ROC curves of the CCP,calculate critical values of the False Positive Rate(FPR),True Positive Rate(TPR),and cutoff of the optimal CCP,and give go/no go decisions at the interim of the optimal CCP.In addition,extensive numerical experiments are carried out to exemplify our theoretical results.Finally,a real data example is performed to illustrate the go/no go decisions of the optimal CCP.
文摘This research extends the literature on the environmental Phillips curve(EPC)and environmental Kuznets curve(EKC)by focusing on the 38 member economies of the Organization for Economic Co-operation and Development(OECD).Using panel data from 2000 to 2021,the study employs several econometric techniques,including fixed effects,feasible generalized least squares,two-stage least squares,and the generalized method of moments.Our primary findings reveal that unemployment has a significant negative impact on CO_(2)emissions,thereby supporting the validity of the EPC hypothesis within OECD countries.This suggests a trade-off between unemployment and reductions in CO_(2)emissions.Similarly,the results validate the EKC hypothesis,with further analysis indicating that the EKC exhibits an N-shaped curve-an important contribution to the literature on environmental dynamics in advanced economies.Additionally,the results show that both trade openness and renewable energy usage have significantly improved environmental quality in OECD economies.Finally,extensive causality testing identifies both one-way and two-way causal relationships among the key variables examined.These findings have important policy implications for the management of environmental quality and macroeconomic variables in the OECD context.
文摘Prior to 2012,the integration of designed vertical or horizontal curves into microtunnel alignments was unheard of in Ontario.Straight and relatively short microtunnels,less than 200m long,were the local accepted industry standard.Following the release of a large number of infrastructure projects in the suburban Greater Toronto Area(GTA),clients and design consultants encouraged contractors to present value engineered alternatives to proposed project alignments and construction methods.Such an initiative has allowed contractors to develop cost effective solutions,which harnessed the application of state-of-the-art microtunnelling methods and equipment.As a result,several recent projects now feature pre-designed curved microtunnels as part of the tender documents.This paper discusses,in technical detail,three recent projects,whereby,long distance curved microtunnels were successfully constructed.Each of the projects had tunnel drives exceeding 300m in length,ranging in diameter from 1200mm ID to 1500mm ID,incorporating the use of Vertical,Horizontal,and Spatial Curves.Critical parameters such as pre-project planning and engineering are highlighted,while the importance of post-tunnelling assessments is also discussed.
基金Project(4013311)supported by the National Science Foundation of Iran(INSF)。
文摘This article examines the influence of annealing temperature on fracture toughness and forming limit curves of dissimilar aluminum/silver sheets.In the cold roll bonding process,after brushing and acid washing,the prepared surfaces are placed on top of each other and by rolling with reduction more than 50%,the bonding between layers is established.In this research,the roll bonding process was done at room temperature,without the use of lubricants and with a 70%thickness reduction.Then,the final thickness of the Ag/Al bilayer sheet reached 350μm by several stages of cold rolling.Before cold rolling,it should be noted that to decrease the hardness created due to plastic deformation,the roll-bonded samples were subjected to annealing heat treatment at 400℃for 90 min.Thus,the final samples were annealed at 200,300 and 400℃for 90 min and cooled in a furnace to examine the annealing temperature effects.The uniaxial tensile and microhardness tests measured mechanical properties.Also,to investigate the fracture mechanism,the fractography of the cross-section was examined by scanning electron microscope(SEM).To evaluate the formability of Ag/Al bilayer sheets,forming limit curves were obtained experimentally through the Nakazima test.The resistance of composites to failure due to cracking was also investigated by fracture toughness.The results showed that annealing increases the elongation and formability of the Ag/Al bilayer sheet while reduces the ultimate tensile strength and fracture toughness.However,the changing trend is not the same at different temperatures,and according to the results,the most significant effect is obtained at 300℃and aluminum layers.It was also determined that by increasing annealing temperature,the fracture mechanism from shear ductile with small and shallow dimples becomes ductile with deep cavities.
基金financially supported by the National Natural Science Foundation of China(Grant No.52078334)the National Key Research and Development Program of China(Grant No.2017YFC0805402)the Tianjin Research Innovation Project for Postgraduate Students(Grant No.2021YJSB141).
文摘The deformation caused by tunnel excavation is quite important for safety,especially when it is adjacent to the existing tunnel.Nevertheless,the investigation of deformation characteristics in overlapped curved shield tunneling remains inadequate.The analytical solution for calculating the deformation of the ground and existing tunnel induced by overlapped curved shield tunneling is derived by the Mirror theory,Mindlin solution and Euler-Bernoulli-Pasternak model,subsequently validated through both finite element simulation and field monitoring.It is determined that the overcutting plays a crucial role in the ground settlement resulting from curved shield tunneling compared to straight shield tunneling.The longitudinal settlement distribution can be categorized into five areas,with the area near the tunnel surface experiencing the most dramatic settlement changes.The deformation of the existing tunnel varies most significantly with turning radius compared to tunnel clearance and grouting pressure,especially when the turning radius is less than 30 times the tunnel diameter.The tunnel crown exhibits larger displacement than the tunnel bottom,resulting in a distinctive‘vertical egg'shape.Furthermore,an optimized overcutting mode is proposed,involving precise control of the extension speed and angular velocity of the overcutting cutter,which effectively mitigates ground deformation,ensuring the protection of the existing tunnel during the construction.
文摘Objective Primary liver cancer,predominantly hepatocellular carcinoma(HCC),is a significant global health issue,ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality.Accurate and early diagnosis of HCC is crucial for effective treatment,as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma(ICC)exhibit different prognoses and treatment responses.Traditional diagnostic methods,including liver biopsy and contrast-enhanced ultrasound(CEUS),face limitations in applicability and objectivity.The primary objective of this study was to develop an advanced,lightweighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images.The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions.Methods This retrospective study encompassed a total of 161 patients,comprising 131 diagnosed with HCC and 30 with non-HCC malignancies.To achieve accurate tumor detection,the YOLOX network was employed to identify the region of interest(ROI)on both B-mode ultrasound and CEUS images.A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images.These curves provided critical data for the subsequent analysis and classification process.To analyze the extracted brightness change curves and classify the malignancies,we developed and compared several models.These included one-dimensional convolutional neural networks(1D-ResNet,1D-ConvNeXt,and 1D-CNN),as well as traditional machine-learning methods such as support vector machine(SVM),ensemble learning(EL),k-nearest neighbor(KNN),and decision tree(DT).The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics:area under the receiver operating characteristic(AUC),accuracy(ACC),sensitivity(SE),and specificity(SP).Results The evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM,0.56 for ensemble learning,0.63 for KNN,and 0.72 for the decision tree.These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves.In contrast,the deep learning models demonstrated significantly higher AUCs,with 1D-ResNet achieving an AUC of 0.72,1D-ConvNeXt reaching 0.82,and 1D-CNN obtaining the highest AUC of 0.84.Moreover,under the five-fold cross-validation scheme,the 1D-CNN model outperformed other models in both accuracy and specificity.Specifically,it achieved accuracy improvements of 3.8%to 10.0%and specificity enhancements of 6.6%to 43.3%over competing approaches.The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification.Conclusion The 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies,surpassing both traditional machine-learning methods and other deep learning models.This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’diagnostic capabilities.By improving the accuracy and efficiency of clinical decision-making,this tool has the potential to positively impact patient care and outcomes.Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.
基金supported by the National Natural Science Foundation of China(11931009,12271495,11971450,and 12071449)Anhui Initiative in Quantum Information Technologies(AHY150200)the Project of Stable Support for Youth Team in Basic Research Field,Chinese Academy of Sciences(YSBR-001).
文摘On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1)Todasystems on X\{P_(1);…;P_(k)}are recognized by the associated toric curves in.We introduce character n-ensembles as-tuples of meromorphic one-forms with simple poles and purely imaginary periods,generating toric curves on minus finitelymany points.On X,we establish a correspondence between character-ensembles and toric solutions to the SU(n+1)system with finitely many cone singularities.Our approach not only broadens seminal solutions with two conesingularities on the Riemann sphere,as classified by Jost-Wang(Int.Math.Res.Not.,2002,(6):277-290)andLin-Wei-Ye(Invent.Math.,2012,190(1):169-207),but also advances beyond the limits of Lin-Yang-Zhong’s existencetheorems(J.Differential Geom.,2020,114(2):337-391)by introducing a new solution class.
文摘In this paper,we present a modeling of the soil-water characteristic curve for residual and sedimentary soils of Bom Brinquedo Hill’s,located in Antonina,Brazil.This mountain range region is characterized as a natural disaster risk area,requiring continuous research related to the stability of the area.To obtain the soil-water characteristic curve,undisturbed samples of residual and sedimentary soil were collected,followed by suction testing using the filter paper method.Considering the bimodal characteristic presented by the soil,LABFIT software was employed for curve fitting using the generic formulation“Harris+C”.The results of the tests indicated that the phenomenon of hysteresis had a greater influence in situations with higher suction levels.When comparing the residual moisture values of the macropores between residual soil and sedimentary soil,the former exhibited the lower value.This suggests that the residual soil has a coarser grain size and larger pores,which facilitates the release of water retained in the soil’s macropores.
基金The Major Research Plan of the National Natural Science Foundation of China(No.90715021)
文摘For the purpose of carrying out the large deformation finite element analysis of spatial curved beams,the total Lagrangian（TL）and the updated Lagrangian（UL）incremental formulations for arbitrary spatial curved beam elements are established with displacement vector interpolation,which is improved from component interpolation of the straight beam displacement.A strategy of replacing the actual curve with the isoparametric curve is used to expand the applications of the UL formulation.The examples indicate that the process of establishing the curved beam element is correct,and the accuracy with the curved beam element is obviously higher than that with the straight beam element.Generally,the same level of computational accuracy can be achieved with 1/5 as many curved beam elements as otherwise with straight beam elements.
文摘Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.
文摘Pre-injection is a technique that involves injecting grout materials into the ground prior to excavation,with the aim of stabilizing the surrounding rock mass.This paper introduces an analytical closed-form model for determining the ground reaction curve of tunnels in rock masses exhibiting elastic-brittleplastic behavior and adhering to the Mohr-Coulomb failure criterion.The model incorporates the reinforced region created by the pre-injection method.When the rock mass is reinforced through preinjection,plastic regions can form independently in both the natural and injected rock masses.This leads to six distinct modes of the problem.The analytical model presented in this paper considers three possible scenarios for the development of plastic regions.Each scenario comprises four stages,with each stage representing a different mode of the problem.While injecting the rock mass can enhance its strength and stiffness,it may also increase the brittleness of the injected rock mass and create stress concentrations within it,particularly when brittle grouts are used.As a result,this can elevate the risk of rockburst due to unstable failure.The results obtained from the model demonstrate that ductile grout performs exceptionally well in controlling tunnel convergence in rock masses,as it accommodates deformation without sudden failure,even in squeezing rock mass conditions.Conversely,the use of brittle grouts should be approached with caution,particularly in squeezing rock masses,due to their susceptibility to rockburst incidents.
基金The research project was co-funded by the National Natural Science Foundation of China(No.42072172,No.41772120)Shandong Province Natural Science Fund for Distinguished Young Scholars(No.JQ201311)the Graduate Scientific and Technological Innovation Project Financially Supported by Shandong University of Science and Technology(No.SDKDYC190313).
文摘The high-pressure mercury intrusion (HPMI) experiment is widely used to assess the pore architecture oftight sandstone reservoirs. However, the conventional analysis of the high- pressure mercury intrusionhas always focused on the mercury injection curves themselves, neglecting the important geologicalinformation conveyed by the mercury ejection curves. This paper quantitatively describes the fractalcharacteristics of ejection curves by using four fractal models, i.e.,. Menger model, Thermodynamicmodel, Sierpinski model, and multi- fractal model. In comparison with mercury injection curves, weexplore the fractal significance of mercury ejection curves and define the applicability of different fractalmodels in characterizing pore architectures. Investigated tight sandstone samples can be divided intofour types (Types A, B, C and D) based on porosity, permeability, and mercury removal efficiency. Type Dsamples are unique in that they have higher permeability (>0.6 mD) but lower mercury removal effi-ciency (<35%). Fractal studies of the mercury injection curve show that it mainly reflects the pore throatcharacteristics, while the mercury ejection curve serves to reveal the pore features, and porosity andpermeability correlate well with the fractal dimension of the injection curve, while mercury removalefficiency correlates only with the Ds' value of the ejection curve. The studies on the mercury ejectioncurves also reveal that the small pores and micropores of the Type C and Type D samples are moredeveloped, with varying pore architecture. The fractal dimension Ds' value of Type D samples is greaterthan that of Type C samples, and the dissolution of Type D samples is more intense than that of Type Csamples, which further indicates that the Type D samples are smaller in pore size, rougher in surface, andwith greater difficulty for the hydrocarbon to enter, resulting in their reservoir capacity probably lessthan that of Type C samples. In this regard, the important information characterized by the mercuryejection curve should be considered in evaluating the tight sandstone reservoirs. Finally, the Menger andThermodynamic models prove to be more suitable for describing the total pore architecture, while theSierpinski model is better for characterizing the variability of the interconnected pores.
基金supported by the National Natural Science Foundation of China(project no.42375192)supported by the National Natural Science Foundation of China(project no.42030608)+3 种基金China Meteorological Administration Climate Change Special Program(CMA-CCSPproject no.QBZ202315)supported by the National Research,Development and Innovation Fund,project no.OTKA-FK 142702the János Bolyai Research Scholarship。
文摘The fundamental scientific and engineering knowledge concerning the solar power curve,which maps solar irradiance and other auxiliary meteorological variables to photovoltaic output power,has been gathered and put forward in the preceding tutorial review.Despite the many pages of that review,it was incomplete in the sense that it did not elaborate on the applications of this very important tool of solar energy meteorology.Indeed,solar power curves are ubiquitously needed in a broad spectrum of solar forecasting and solar resource assessment tasks.Hence,this tutorial review should continue from where it left off and present examples concerning the usage of solar power curves.In a nutshell,this tutorial review,together with the preceding one,should elucidate how surface shortwave radiation data,be they ground-based,satelliteretrieved,or model-output,are bridged to various power system operations via solar power curves.
基金sponsored by the National Natural Science Foundation of China(Grant No.52405443)the Technology Research and Development Plan of China Railway(Grant No.N2023G063)the Fund of China Academy of Railway Sciences Corporation Limited(Grant No.2023YJ054).
文摘Purpose–To investigate the influence of vehicle operation speed,curve geometry parameters and rail profile parameters on wheel–rail creepage in high-speed railway curves and propose a multi-parameter coordinated optimization strategy to reduce wheel–rail contact fatigue damage.Design/methodology/approach–Taking a small-radius curve of a high-speed railway as the research object,field measurements were conducted to obtain track parameters and wheel–rail profiles.A coupled vehicle-track dynamics model was established.Multiple numerical experiments were designed using the Latin Hypercube Sampling method to extract wheel-rail creepage indicators and construct a parameter-creepage response surface model.Findings–Key service parameters affecting wheel–rail creepage were identified,including the matching relationship between curve geometry and vehicle speed and rail profile parameters.The influence patterns of various parameters on wheel–rail creepage were revealed through response surface analysis,leading to the establishment of parameter optimization criteria.Originality/value–This study presents the systematic investigation of wheel–rail creepage characteristics under multi-parameter coupling in high-speed railway curves.A response surface-based parameter-creepage relationship model was established,and a multi-parameter coordinated optimization strategy was proposed.The research findings provide theoretical guidance for controlling wheel–rail contact fatigue damage and optimizing wheel–rail profiles in high-speed railway curves.
基金Supported by the National Natural Science Foundation of China(52288101)National Key R&D Program of China(2024YFF1500600)。
文摘To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the pre-trained large language model,the Gaia significantly improved its ability in extracting sequential patterns and spatial features from well-log curves.Leveraging the adapter method for fine-tuning,this model required training only about 1/70 of its original parameters,greatly improving training efficiency.Comparative experiments,ablation experiments,and generalization experiments were designed and conducted using well-log data from 250 wells.In the comparative experiment,the Gaia model was benchmarked against cutting-edge small deep learning models and conventional large language models,demonstrating that the Gaia model reduced the mean absolute error(MAE)by at least 20%.In the ablation experiments,the synergistic effect of the Gaia model's multiple components was validated,with its MAE being at least 30%lower than that of single-component models.In the generalization experiments,the superior performance of the Gaia model in blind-well predictions was further confirmed.Compared to traditional models,the Gaia model is significantly superior in accuracy and generalization for logging curve reconstruction,fully showcasing the potential of large language models in the field of well-logging.This provides a new approach for future intelligent logging data processing.
基金supported by the Open Project of Key Laboratory,Xinjiang Uygur Autonomous Region(No.XJYS0907-2023-23)the National Natural Science Foundation of China(NSFC Grant 42371146,42401167)+3 种基金the Third Xinjiang Scientific Expedition Program(2022xjkk0602)the Youth Innovation Promotion Association,CAS(2022444)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0720203)The International Partnership Program of the Chinese Academy of Sciences(131965KYSB20210018)。
文摘The water retention curve(WRC)has been widely used to quantify moisture transport characteristics of maritime snowpack.However,there is a notable deficiency in experimental studies focused on the WRC of dry-cold snowpack in continental climate conditions.This study selected dry-cold snowpack samples with five densities to measure the variations in volumetric water content using the pressure plate method.The Van Genuchten(VG)and Brooks-Corey(BC)models were then used to fit the snowpack WRCs,aiming to investigate their applicability to dry-cold snowpack and explore the relationship between the model parameters and snowpack characteristics.The results indicated that:(1)Compared to the particle size and the ratio of snowpack density to particle size,the snowpack density shows a higher correlation with the shape parameters of VG model and BC model;(2)There is a nonlinear relationship between the snowpack density and the shape parameters of VG model and BC model;(3)Both the BC and VG models provide a high level of accuracy in fitting the experimental data,with the BC model showing slightly better precision.However,after regression correction,the VG model outperforms the BC model.The findings provide support for in-depth studies of moisture movement characteristics in different types of snow,and have significantly practical value for improving the accuracy of early warning systems for hazards such as avalanches and floods.
基金part of the Agency for Defense Development(ADD)research project on Weapon lethality/effectiveness analysis technology for material targets and grant funded by the korean goverment(511225-912A03301)。
文摘This study presents a fragility curve to assess explosively induced damage to military vehicle tires based on shock tube experiments.To replicate lateral damage scenarios that may occur in real battlefield environments involving missile or bomb detonations,extreme overpressure conditions were generated using a shock tube.The influence of explosive charge mass on tire damage was quantitatively evaluated.Experimental results identified two critical failure thresholds:for loss of pressure,the threshold was 354 kPa peak overpressure and 3052 kPa·ms impulse;for rupture,the values were 485 kPa and 4237 kPa-ms,respectively.The same damage profile was reproduced through finite element analysis(FEA),verifying the reliability of the simulation.A Single Degree of Freedom(SDOF)model and Kingery-Bulmash(K-B)chart were employed to generate pressure-impulse data as a function of standoff distance.These data were applied to a finite element tire model using the BLAST ENHANCED keyword in LS-DYNA.The applied peak overpressures were identical to the experimental values with a 24%-27%difference in impulse.The simulation also captured recurring bead rim separation phenomenon,leading to internal pressure loss consistent with high-speed camera observations from the experiments.The resulting fragility curve clearly defines the threshold conditions for tire damage and provides a standardized damage assessment model applicable to various explosive charge masses and stand-off distances.The proposed model offers a quantitative basis for evaluating tire vulnerability,providing foundational reference data for defense applications.Specifically,the findings are expected to serve as a reliable source for weapon effects analysis and target vulnerability assessments involving wheeled military vehicles.
基金sponsored by China Geological Survey Project(DD20243193 and DD20230206508).
文摘In Rayleigh wave exploration,the inversion of dispersion curves is a crucial step for obtaining subsurface stratigraphic information,characterized by its multi-parameter and multi-extremum nature.Local optimization algorithms used in dispersion curve inversion are highly dependent on the initial model and are prone to being trapped in local optima,while classical global optimization algorithms often suffer from slow convergence and low solution accuracy.To address these issues,this study introduces the Osprey Optimization Algorithm(OOA),known for its strong global search and local exploitation capabilities,into the inversion of dispersion curves to enhance inversion performance.In noiseless theoretical models,the OOA demonstrates excellent inversion accuracy and stability,accurately recovering model parameters.Even in noisy models,OOA maintains robust performance,achieving high inversion precision under high-noise conditions.In multimode dispersion curve tests,OOA effectively handles higher modes due to its efficient global and local search capabilities,and the inversion results show high consistency with theoretical values.Field data from the Wyoming region in the United States and a landfill site in Italy further verify the practical applicability of the OOA.Comprehensive test results indicate that the OOA outperforms the Particle Swarm Optimization(PSO)algorithm,providing a highly accurate and reliable inversion strategy for dispersion curve inversion.
基金partially supported by the National Key R&D Program of China (2022YFE0133700)the National Natural Science Foundation of China(12273007)+4 种基金the Guizhou Provincial Excellent Young Science and Technology Talent Program (YQK[2023]006)the National SKA Program of China (2020SKA0110300)the National Natural Science Foundation of China(11963003)the Guizhou Provincial Basic Research Program (Natural Science)(ZK[2022]143)the Cultivation project of Guizhou University ([2020]76).
文摘Solar flares are violent solar outbursts which have a great influence on the space environment surrounding Earth,potentially causing disruption of the ionosphere and interference with the geomagnetic field,thus causing magnetic storms.Consequently,it is very important to accurately predict the time period of solar flares.This paper proposes a flare prediction model,based on physical images of active solar regions.We employ X-ray flux curves recorded directly by the Geostationary Operational Environmental Satellite,used as input data for the model,allowing us to largely avoid the influence of accidental errors,effectively improving the model prediction efficiency.A model based on the X-ray flux curve can predict whether there will be a flare event within 24 hours.The reverse can also be verified by the peak of the X-ray flux curve to see if a flare has occurred within the past 24 hours.The True Positive Rate and False Positive Rate of the prediction model,based on physical images of active regions are 0.6070 and 0.2410 respectively,and the accuracy and True Skill Statistics are 0.7590 and 0.5556.Our model can effectively improve prediction efficiency compared with models based on the physical parameters of active regions or magnetic field records,providing a simple method for solar flare prediction.
基金supported by the grants from National Key Research and Development Program of China(2023YFD2303300)China Agriculture Research System(CARS-02-15)the Agricultural Science and Technology Innovation Program(CAAS-ZDRW202004).
文摘The unreasonable application of nitrogen fertilizer poses a threat to agricultural productivity and the environment protection in Northeast China.Therefore,accurately assessing crop nitrogen requirements and optimizing fertilization are crucial for sustainable agricultural production.A three-year field experiment was conducted to evaluate the effects of planting density on the critical nitrogen concentration dilution curve(CNDC)for spring maize under drip irrigation and fertilization integration,incorporating two planting densities:D1(60,000 plants ha^(-1))and D2(90,000 plants ha^(-1))and six nitrogen levels:no nitrogen(N0),90(N90),180(N180),270(N270),360(N360),and 450(N450)kg ha^(-1).A Bayesian hierarchical model was used to develop CNDC models based on dry matter(DM)and leaf area index(LAI).The results revealed that the critical nitrogen concentration exhibited a power function relationship with both DM and LAI,while planting density had no significant impact on the CNDC parameters.Based on these findings,we propose unified CNDC equations for maize under drip irrigation and fertilization integration:Nc=4.505DM-0.384(based on DM)and Nc=3.793LAI-0.327(based on LAI).Additionally,the nitrogen nutrition index(NNI),derived from the CNDC,increased with higher nitrogen application rates.The nitrogen nutrition index(NNI)approached 1 with a nitrogen application rate of 180 kg ha^(-1)under the D1 planting density,while it reached 1 at 270 kg ha^(-1)under the D2 planting density.The relationship between NNI and relative yield(RY)followed a“linear+plateau”model,with maximum RY observed when the NNI approached 1.Thus,under the condition of drip irrigation and fertilization integration in Northeast China’s spring maize production,the optimal nitrogen application rates for achieving the highest yields were 180 kg ha^(-1)at a planting density of 60,000 plants ha^(-1),and 270 kg ha^(-1)at a density of 90,000 plants ha^(-1).The CNDC and NNI models developed in this study are valuable tools for diagnosing nitrogen nutrition and guiding precise fertilization practices in maize production under integrated drip irrigation and fertilization systems in Northeast China.
